• Journal of Korea Multimedia Society
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• v.14 no.11
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• pp.1365-1372
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• 2011

This paper proposes a cognitive contrast enhancement algorithm based on the non-linear masking to advance low cognitive contrast in dark regions of images. In order to improve brightness in dark regions of an image, we propose a new contrast enhancement algorithm based on the non-linear masking using regional adaptive parameters of an image. For performance evaluation of the proposed method, chromaticity and saturation comparison as a quantitative assessment and z-score comparison as a qualitative assessment were executed between test images and their simulated images by SSR, MSR, a conventional non-linear masking and the proposed method, respectively. As a result, the proposed method showed low chromaticity and saturation difference and improved cognitive contrast for the three methods.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.4
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• pp.346-354
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• 2020

Nowadays, it is required to apply low observable technology to weapon systems in operation or under development. Radar Cross Section(RCS) is a measure of the scattered power in an given direction when a target is illuminated by an incident wave and used as a parameter to estimate the low observable performance of weapon system. RCS of a target can be calculated by various numerical methods. However, measurement is also needed to estimate RCS of a complex target because it is difficult to estimate theoretically. To acquire reliable measurement results, an analysis of measurement uncertainty is essential. In this paper, error components and uncertainties of near-field RCS measurement system which was constructed in ASTEC(Aerospace System Test & Evaluation Center) were analyzed based on the IEEE recommended practice for radar cross-section test procedures(IEEE Std. 1502-2007) which describes the uncertainty of RCS measurement and unique error components of this near-field measurement system were also identified.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5978-5999
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• 2018

Pedestrian detection is a challenging area in the intelligent vehicles domain. During the last years, many works have been proposed to efficiently detect motion in images. However, the problem becomes more complex when it comes to detecting moving areas while the vehicle is also moving. This paper presents a variational optical flow-based method for motion estimation in vehicular traffic scenarios. We introduce a framework for detecting motion areas with small and large displacements by computing optical flow using a multilevel architecture. The flow field is estimated at the shortest level and then successively computed until the largest level. We include a filtering parameter and a warping process using bicubic interpolation to combine the intermediate flow fields computed at each level during optimization to gain better performance. Furthermore, we find that by including a penalization function, our system is able to effectively reduce the presence of outliers and deal with all expected circumstances in real scenes. Experimental results are performed on various image sequences from Daimler Pedestrian Dataset that includes urban traffic scenarios. Our evaluation demonstrates that despite the complexity of the evaluated scenes, the motion areas with both moving and static camera can be effectively identified.

• IE interfaces
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• v.17 no.1
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• pp.1-12
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• 2004

In a modern semiconductor device manufacturing industry, statistical bin limits on wafer level test bin data are used for minimizing value added to defective product as well as protecting end customers from potential quality and reliability excursion. Most wafer level test bin data show skewed distributions. By Monte Carlo simulation, this paper evaluates methods and sample size effect regarding determination of statistical bin limits. In the simulation, it is assumed that wafer level test bin data follow the Poisson distribution. Hence, typical shapes of the data distribution can be specified in terms of the distribution's parameter. This study examines three different methods; 1) percentile based methodology; 2) data transformation; and 3) Poisson model fitting. The mean square error is adopted as a performance measure for each simulation scenario. Then, a case study is presented. Results show that the percentile and transformation based methods give more stable statistical bin limits associated with the real dataset. However, with highly skewed distributions, the transformation based method should be used with caution in determining statistical bin limits. When the data are well fitted to a certain probability distribution, the model fitting approach can be used in the determination. As for the sample size effect, the mean square error seems to reduce exponentially according to the sample size.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.2
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• pp.188-194
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• 2010

In this paper, the typical Synthetic Aperture Radar (SAR) image quality parameters and analysis method are defined, and the SAR image analysis tool is presented for SAR image evaluation. The structure of the developed SAR image analysis tool consists of four key modules; point target analysis (PTA) module, distributed target analysis (DTA) module, ambiguity analysis (AMA) module, and NESZ analysis (NESZA) module. The developed tool is able to extract the various SAR system parameters from standard SAR product format files. Based on these extracted system parameters, typical SAR image quality parameters are derived from SAR image data.

• Journal of the Earthquake Engineering Society of Korea
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• v.22 no.2
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• pp.95-101
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• 2018

Diagonally reinforced concrete coupling beams (DRCB) play an important role in coupled shear wall systems since these elements dissipate most of seismic input energy under earthquake loading. For reliable seismic performance evaluation using nonlinear response history analysis, it is important to use an accurate analytical model for DRCBs. In this study, the Pinching4 model is used as a base model to simulate the cyclic behavior of DRCBs. For simulating the cyclic behavior of DRCBs using the Pinching4 model, the analytical parameters for backbone curve, pinching and cyclic deterioration in strength and stiffness should be computed. To determine the proper values of the constituent analytical parameters efficiently and accurately, this study proposes the empirical equations for the analytical parameters using regression analyses. It is shown that the hysteretic behavior of coupling beams can be simulated efficiently and accurately using the proposed numerical model with the proposed empirical equations of model parameters.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.1
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• pp.37-41
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• 2018

In this paper, we evaluate the power consumption of IEEE802.15.4e TSCH which uses the specific link scheduling scheme proposed in reference[1]. And we also compares it with the power consumption of conventional single channel IEEE802.15.4. The power consumption of IEEE802.15.4e TSCH is smaller than the conventional one under the any conditions of traffic. The reasons can be explained as the followings. Firstly, TSCH does not have backoff time because of using the collision free link scheduling. Secondly, there is the timing difference of MAC offset parameter between TSCH and conventional IEEE802.15.4 Lastly, the devices in TSCH mode sleep during the time slots which are not assigned to itself.

• Journal of the Korean Magnetics Society
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• v.3 no.2
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• pp.115-120
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• 1993

The relationship between magnetic parameter and microwave absorbing performance evaluation factor of electomagnetic wave absorber such as matching frequency, matching thickness were investigated for Ni-Zn ferrite composites. It was identified that the maximum value of ${\mu}_{r}$" is shift to low frequency with decrese Ni/Zn ratio and the value of ${\mu}_{r}$" is maximum in the case of Ni/Zn=1. All Ni-Zn ferrite composites in this study have two matching frequencies in 1-12 GHz frequency. It can be suggested that $f_{m1}$ is proportional to resonance frequency and $f_{m2}$ is proportional to the saturation magnetization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.1
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• pp.85-100
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• 1991

In the discussion of digital mobile communication systems the speech coder based on the high quality low bit rate is an essential part of topics to overcome the limited availability of radio spectrum, which will enhance the communication services. In this paper we present the implementation and performance evaluation of 13kbps RPE LTP speech coder. An implementation of a real time full duplex coder with 75% of DSP loading rate using a single DSP chip has been shown, and also the fixed point simulations for H/W implementation has been performed. Finally, analysis result for relative bit importance of each transmitting parameter has been shown for channel coding.

• Journal of Platform Technology
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• v.11 no.4
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• pp.80-88
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• 2023

To construct a learning model in the field of artificial intelligence, a dataset should be collected and be delivered to the central server where the learning model is constructed. Federated learning is a machine learning method building a global learning model without transmitting data located in a client side in a collaborative manner. It can be used to protect privacy, and after constructing a local trained model on individual clients, the parameters of the local model are aggregated centrally to update the global model. In this paper, we reuse the existing learning parameter to improve federated learning, describe incremental federated learning. For this work, we do experiments using the federated learning framework named Flower, and evaluate the experiment results with regard to elapsed time and precision when executing optimization algorithms.