• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.5
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• pp.600-608
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• 2020

Machine learning constructs an objective function from learning data, and predicts the result of the data generated by checking the objective function through test data. In machine learning, input data is subjected to a normalisation process through a preprocessing. In the case of numerical data, normalization is standardized by using the average and standard deviation of the input data. In the case of nominal data, which is non-numerical data, it is converted into a one-hot code form. However, this preprocessing alone cannot solve the problem. For this reason, we propose a method that uses ontology to normalize input data in this paper. The test data for this uses the received signal strength indicator (RSSI) value of the Wi-Fi device collected from the mobile device. These data are solved through ontology because they includes noise and heterogeneous problems.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.823-826
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• 2004

In this paper, A tracking of the moving objects using normalized hue distribution in HSI color model was proposed. Moving objects are detected by using difference image method and integral projection method to background image and objects image only with hue area. Hue information of the detected moving area are normalized by 24 levels from $0^{\circ}$ to $3600^{\circ}A$ distance in between normalized levels with a hue distribution chart of the normalized moving objects is used for the identity distinction feature parameters of the moving objects. To examine proposed method in this paper, image of moving cars are obtained by setting up three cameras at different places every 1 km on outer motorway. The simulation results of identity distinction show that it is possible to distinct the identity a distance in between normalization levels of a hue distribution chart without background.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.2
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• pp.763-774
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• 2015

Hand posture recognition has been a wide region of applications in Human Computer Interaction and Computer Vision for many years. The problem arises mainly due to the high dexterity of hand and self-occlusions created in the limited view of the camera or illumination variations. To remedy these problems, a hand posture recognition method using 3-D point cloud is proposed to explicitly utilize 3-D information from depth maps in this paper. Firstly, hand region is segmented by a set of depth threshold. Next, hand image normalization will be performed to ensure that the extracted feature descriptors are scale and rotation invariant. By robustly coding and pooling 3-D facets, the proposed descriptor can effectively represent the various hand postures. After that, SVM with Gaussian kernel function is used to address the issue of posture recognition. Experimental results based on posture dataset captured by Kinect sensor (from 1 to 10) demonstrate the effectiveness of the proposed approach and the average recognition rate of our method is over 96%.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.71-74
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• 2003

The signal processing algorithm for a PSD(Position Sensitive Detector) using amplitude modulation/demodulation is addressed in this paper. Dark currents and external noises such as daylight and fluorescent lights are eliminated by using amplitude modulation/demodulation and a low pass filter. The proposed amplitude modulation/demodulation method for a PSD sensor is compared with pulse amplitude modulation method. The proposed amplitude modulation is proved to be more accurate and robust than PAM method by analysis and experiments. Multiple measurements using one PSD sensor by amplitude modulation/demodulation is also addressed. The Power variation of light source is compensated by normalization process using a divider.

• Journal of the Korean Institute of Navigation
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• v.19 no.3
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• pp.29-34
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• 1995

IEC and CISPR have continuously endeavored the measurement method of Immunity Test as international unification, but not established yet. The main reason is that the measurement method and the normalization of threshold to obtain the complicated parameters for Immunity Test are difficult. Thus, the Immunity Test Setups are used differently according to the measured electromagnetic environments. This study developed an Immunity Test System and Algorithm for measurement software suitable for IEC801-3 Regulatons using ready-made amplifier, signal generator, and developes interconnecting interface board interacting with other appratus i.e., RF Switch, Power Meter, Field Sensor and Pre-amp. We are to develope an automated software using Top/Down and OOP(Object Oriented Programming) method.

• Journal of Power Electronics
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• v.16 no.4
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• pp.1415-1425
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• 2016

This paper presents a new approach for fault diagnosis in three-level neutral point clamped inverters. The proposed method is based on the average values of the positive and negative parts of normalized output currents. This method is capable of detecting and locating multiple open-circuit faults in the controlled power switches of converters in half of a fundamental period of those currents. The implementation of this diagnostic approach only requires two output currents of the inverter. Therefore, no additional sensors are needed other than the ones already used by the control system of a drive based on this type of converter. Moreover, through the normalization of currents, the diagnosis is independent of the load level of the converter. The performance and effectiveness of the proposed diagnostic technique are validated by experimental results obtained under steady-state and transient conditions.

• Journal of Satellite, Information and Communications
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• v.8 no.4
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• pp.26-29
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• 2013

In order to estimate people crowdedness in public area, the texture based method or motion based method can be used. In this paper we have proposed a mixed method. By designating the region of interest, we made the degree of crowdedness more accurate. The feature normalization also reduced the image distortion which results from difference of camera angle. The proposed system was optimized to real time embedded hardware system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.5A
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• pp.426-432
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• 2007

The MAP algorithm is designed and implemented through the sliding window method for turbo decoding. First, the implementation issues, which are the length of the sliding window and the normalization method of state metrics are reviewed, and their optimal values are obtained by the simulation. All component schemes of the decoder including the branch metric evaluator are also presented. The proposed MAP architecture can be easily redesigned according to the size of sliding window, that is, sub-frame length because of its simplicity on buffer control.

• Proceedings of the KIEE Conference
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• 1999.07f
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• pp.2742-2744
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• 1999

In this paper, an auto-tuning method for fuzzy logic controller based on the genetic algorithm is presented. In the proposed method, normalization parameters and membership function parameters of fuzzy controller are translated into binary bit-strings, which are processed by the genetic algorithm in order to be optimized for the well-chosen objective function (i.e. fitness function). To examine the validity of the proposed method. a genetic algorithm based fuzzy controller for an indirect vector control of induction motors is simulated and experiment is carried out. The simulation and experimental results show a significant enhancement in shortening development time and improving system performance over a traditional manually tuned fuzzy logic controller.

• Journal of the Korean Institute of Telematics and Electronics
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• v.15 no.4
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• pp.14-19
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• 1978

Here a method is shown to extract features from two multi-variable classes by using the coordinate systems transformed by one-class and mixture normalization algorithms. Some properties and implemented results of this technique are described. Also, comparision of these features with factor analysis results is performed. This method is thought to be more powerful one, in feature extraction sense, than factor analysis.