• Journal of Communications and Networks
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• v.18 no.5
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• pp.837-845
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• 2016

Providing a customer with tailored location-based services (LBSs) is a fundamental problem. For location-estimation techniques with radio-based measurements, LBS applications are widely available for mobile devices (MDs), such as smartphones, enabling users to run multi-task applications. LBS information not only enables obtaining the current location of an MD but also provides real-time push-pull communication service. For indoor environments, localization technologies based on radio frequency (RF) pattern-matching approaches are accurate and commonly used. However, to survey radio information for pattern-matching approaches, a considerable amount of time and work is spent in indoor environments. Consequently, in order to reduce the system-deployment cost and computing complexity, this article proposes an indoor positioning approach, which involves using Asus Xtion to facilitate capturing RF signals during an offline site survey. The depth information obtained using Asus Xtion is utilized to estimate the locations and predict the received signal strength (RF information) at uncertain locations. The proposed approach effectively reduces not only the time and work costs but also the computing complexity involved in determining the orientation and RF during the online positioning phase by estimating the user's location by using a smartphone. The experimental results demonstrated that more than 78% of time was saved, and the number of samples acquired using the proposed method during the offline phase was twice as much as that acquired using the conventional method. For the online phase, the location estimates have error distances of less than 2.67 m. Therefore, the proposed approach is beneficial for use in various LBS applications.

• The Journal of the Convergence on Culture Technology
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• v.5 no.4
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• pp.451-456
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• 2019

Recently, various bioinformation technologies have been proposed, and research and development on the collection and analysis of the human body related bioinformation have been continuously conducted to support the human life environment and healthcare. These biomedical research and development processes add to the redundancy and complexity of the R&D elements and put a heavy burden on the follow-up research developers. Therefore, this study utilizes an open bioinformation platform that effectively supports the collection and analysis of bioinformation to improve the redundancy and complexity of bioinformatics R&D based on the bioinformatics platform. In addition, I propose an open interface that supports acquisition, processing, analysis, and application of bio-signals. In particular, we propose a biometric information normalization pattern model through data analysis modeling of brain wave information based on an open interface.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.215-218
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• 2009

In this paper, we analyze the performance of interpolation in demosaicing techniques for single sensor digital camera. We choose BI(bilinear interpolation), ACPI(adaptive color plane interpolation), ECI(effective color interpolation), Ideal ACPI, and EECI(Enhanced effective color interpolation) in the literature of demosacing techniques since they provide low-complexity and substantial image quality. We survey the algorithms and simulate them. To evaluate the methods in terms of objective image quality and complexity, 24 Kodak images will be used in this experiment. Experimental results show that the ECI method is better than others in terms of image quality versus complexity.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.863-870
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• 2019

In the GSM method for OWC-MIMO System, it is important to select an activation pattern set(: APS) for the performance optimization in the environment where mutual interference is high depending on the location of the transmitter and receiver. However, due to the high computational complexity, a high cost is paid in selecting the transmission APS. In this paper, we propose a method to reduce the candidate APS by pre-determining basic APS when generating candidate APS. The simulation results show that the proposed method has the same BER performance and reduce the computational complexity by 90% compared to the general GSM method in the high interfering environment.

• Archives of design research
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• v.16 no.2
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• pp.141-150
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• 2003

In estimating designed architectural buildings, many factors in various design domains such as function, structure, form, environment may be considered and then a building design might be selected or modified as final design. This paper proposed a method to obtain complexity values from two dimensional drawings which are floor plans or elevations. The method has been developed based on information theory, shape pattern representation and cognitive theory. Results of measuring complexity value can make the computer evaluate and select final results produced from automatic design processes by the computer That is to say, aesthetic values based on order and chaos can be measured using complexity values and then some results having superior values can be selected as final result.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.2
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• pp.160-171
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• 2008

MU's mobility patterns can be found from a movement history data. The prediction accuracy and model complexity depend on the degree of application of history data. The more data we use, the more accurate the prediction is. As a result, the location management cost is reduced, but complexity of the model increases. In this paper, we classify MU's mobility patterns into four types. For each type, we find the respective optimal number of application of history data, and predictive location area by using the simulation. The optimal numbers of four types are shown to be different. When we use more than three application of history data, the simulation time and data storage are shown to increase very steeply.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.304-306
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• 2007

Methods of Object recognition from camera image are to compare features of color. edge or pattern with model in a general way. SIFT(scale-invariant feature transform) has good performance but that has high complexity of computation. Using simple color histogram has low complexity. but low performance. In this paper we represent a model as a color cooccurrence histogram. and we improve performance using pyramid matching. The color cooccurrence histogram keeps track of the number of pairs of certain colored pixels that occur at certain separation distances in image space. The color cooccurrence histogram adds geometric information to the normal color histogram. We suggest object recognition by pyramid matching of color cooccurrence histogram.

• Korean System Dynamics Review
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• v.1 no.1
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• pp.133-157
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• 2000

This paper deals with the social system from the point of system thinking consisting the fundamental construct of system dynamics. The Bertalanffy's general system theory, having been criticized because of its ambiguity, and the complex science theory, emerging system theory, are integrated by using the system thinking which is characterized with three concepts, 'feedback thinking', 'dynamic thinking', 'operational thinking'. In the integration, system thinking suggests the dynamic pattern of the social system have not only an equilibrium status but also complex status. The science of complexity gives an implication to system dynamics the important of the uncertainty and complexity if we interpret the social system as an open system. To show more concrete description, I simulate the cooperation model based on the iterated prisoner dilemma. The simulation results show the diverse patterns of cooperation and betrayal. Especially the sensitivity of initial payoff will cause the chaotic strategic landscapes as the game gose on. These results mean that we should not give the hasty prescription to control social system artificially. Because social system retains the self-organizing force in itself.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.27-30
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• 2003

The recent technology developments introduce new difficulties into the test process by the increased complexity of the chip. Most widely used method for testing high complexity and embedded systems is built-in self-test(BIST). In this paper, we describe 5-stage pipeline system as circuit under testing(CUT) and proposed a BIST scheme for the hazard detection unit of the pipeline system. The proposed BIST scheme can generate sequential instruction sets by pseudo-random pattern generator that can detect all hazard issues and compare the expected hazard signals with those of the pipelined system. Although BIST schemes require additional area in the system, it proves to provide a low-cost test solution and significantly reduce the test time.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.4
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• pp.534-540
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• 2014

In this paper, we propose a fuzzy combined Polynomial Neural Network(PNN) for pattern classification. The fuzzy combined PNN comes from the generic TSK fuzzy model with several linear polynomial as the consequent part and is the expanded version of the fuzzy model. The proposed pattern classifier has the polynomial neural networks as the consequent part, instead of the general linear polynomial. PNNs are implemented by stacking the simple polynomials dynamically. To implement one layer of PNNs, the various types of simple polynomials are used so that PNNs have flexibility and versatility. Although the structural complexity of the implemented PNNs is high, the PNNs become a high order-multi input polynomial finally. To estimate the coefficients of a polynomial neuron, The weighted linear discriminant analysis. The output of fuzzy rule system with PNNs as the consequent part is the linear combination of the output of several PNNs. To evaluate the classification ability of the proposed pattern classifier, we make some experiments with several machine learning data sets.