• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.602-604
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• 2011

Due to wide usage of smartphones and mobile internet, mobile devices are used in various fields such as sending SMS, participating SNS, retrieving information and the number of users taking advantage of them are growing. The keypads of a mobile device are relatively smaller than those of desktop computers. Thus, the user has a difficulty in input sentences quickly and correctly. In this study, we introduce some string recommendation and modification techniques which can be used for helping a user input in mobile devices quickly and correctly. We describe a TRIE dictionary and n-gram language model which are the main technologies of the keyword recommendation applied to the online search engines.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2C
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• pp.175-180
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• 2009

When we apply the LDPC code for high density optical storage channel, it is necessary to make an algorithm that the modulation code decoder must feed the LDPC decoder soft-valued information because LDPC decoder exploits soft values using the soft input. Therefore, we propose the soft-input soft-output run-length limited 17PP decoding algorithm and compare performance of LDPC codes. Consequently, we found that the proposed soft-input soft-output decoding algorithm using 17PP is 0.8dB better than the soft-input soft-output decoding algorithm using (1, 7) RLL.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.41-45
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• 2014

In this paper, a high-efficiency power amplifier is implemented by using a drain bias control circuit operated at low input power for WPT(Wireless Power Transfer). Adaptive bias control circuit was added to high-efficiency class-E amplifier. It was possible to obtain the overall improvement in efficiency by adjusting the drain bias at low input power. The proposed adaptive class-E amplifier is implemented by using the input and output matching network and serial resonant circuit for improvement in efficiency. Drain bias control circuit consists of a directional coupler, power detector, and operational amplifier for adjusting the drain bias according to the input power. The measured results show that output powers of 41.83 dBm were obtained at 13.56 MHz. At this frequency, we have obtained the power added efficiency(PAE) of 85.67 %. It was confirmed increase of PAE of an average of 8 % than the fixed bias from the low input power level of 0 dBm ~ 6 dBm.

• KIEAE Journal
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• v.7 no.4
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• pp.147-152
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• 2007

Numerous non-destructive tests(NDT) to assess the safety of real structures have been developed. System identification(SI) techniques using dynamic responses and behaviors of structural systems become an outstanding issue of researchers. However the conventional SI techniques are identified to be non-practical to the complex and tall buildings, due to limitation of the availability of an accurate data that is magnitude or location of external loads. In most SI approaches, the information on input loading and output responses must be known. In many cases, measuring the input information may take most of the resources, and it is very difficult to accurately measure the input information during actual vibrations of practical importance, e.g., earthquakes, winds, micro seismic tremors, and mechanical vibration. However, the desirability and application potential of SI to real structures could be highly improved if an algorithm is available that can estimate structural parameters based on the response data alone without the input information. Thus a technique to estimate structural properties of building without input measurement data and using limited response is essential in structural health monitoring. In this study, shaking table tests on three-story plane frame steel structures were performed. Out-put only model analysis on the measured data was performed, and the dynamic properties were inverse analyzed using least square method in time domain. In results damage detection was performed in each member level, which was performed at story level in conventional SI techniques of frequency domain.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.2
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• pp.436-444
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• 2010

In this study, we introduce and discuss a concept of a granular-oriented radial basis function neural networks (GRBF NNs). In contrast to the typical architectures encountered in radial basis function neural networks(RBF NNs), our main objective is to develop a design strategy of GRBF NNs as follows : (a) The architecture of the network is fully reflective of the structure encountered in the training data which are granulated with the aid of clustering techniques. More specifically, the output space is granulated with use of K-Means clustering while the information granules in the multidimensional input space are formed by using a so-called context-based Fuzzy C-Means which takes into account the structure being already formed in the output space, (b) The innovative development facet of the network involves a dynamic reduction of dimensionality of the input space in which the information granules are formed in the subspace of the overall input space which is formed by selecting a suitable subset of input variables so that the this subspace retains the structure of the entire space. As this search is of combinatorial character, we use the technique of genetic optimization to determine the optimal input subspaces. A series of numeric studies exploiting some nonlinear process data and a dataset coming from the machine learning repository provide a detailed insight into the nature of the algorithm and its parameters as well as offer some comparative analysis.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.4
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• pp.47-60
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• 2011

With the increase in the use of mobile banking service, mobile banking has become an attractive target to attackers. Even though many security measures are applied to the current mobile banking service, some threats such as physical theft or penetration to a mobile device from remote side are still remained as unsolved. With aiming to fill this void, we propose a novel approach to prevent e-financial incidents by analyzing mobile device user's input patterns. This approach helps us to distinguish between original user's usage and attacker's usage through analyzing personal input patterns such as input time-interval, finger pressure level on the touch screen. Our proposed method shows high accuracy, and is effective to prevent the e-finance incidents proactively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.6C
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• pp.490-496
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• 2005

In this paper, we propose a self-constructed clustering algorithm based on inference information of the fuzzy model. This method makes it possible to automatically detect and optimize the number of cluster and parameters by using input-output data. The propose method improves the performance of clustering by extended supervised learning technique. This technique uses the output information as well as input characteristics. For effect the similarity measure in clustering, we use the TSK fuzzy model to sent the information of output. In the conceptually, we design a learning method that use to feedback the information of output to the clustering since proposed algorithm perform to separate each classes in input data space. We show effectiveness of proposed method using simulation than previous ones

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.172-178
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• 2006

This paper presents a development of court auction information system using time series forecasting. The system forecast a highest bid price for claim analysis, and it is designed to offer an quota information by the bid price. For this realization, we implemented input interface of object data and web interface of information support. Input interface can be input, update and delete function and web interface is support some information of court auction object. We propose a forecasting method of a highest bid price for auto-claim analysis with real time information support and the results are verified the feasibility of the proposed method by experiment.

• The Journal of the Acoustical Society of Korea
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• v.17 no.2E
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• pp.38-46
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• 1998

In this paper, we propose a remote speech input device, a new method of user-friendly speech input in spontaneous speech recognition system. We focus the user friendliness on hands-free and microphone independence in speech recognition applications. Our method adopts two algorithms, the automatic speech detection and the microphone array delay-and-sum beamforming (DSBF)-based speech enhancement. The automatic speech detection algorithm is composed of two stages; the detection of speech and nonspeech using the pitch information for the detected speech portion candidate. The DSBF algorithm adopts the time domain cross-correlation method as its time delay estimation. In the performance evaluation, the speech detection algorithm shows within-200 ms start point accuracy of 93%, 99% under 15dB, 20dB, and 25dB signal-to-noise ratio (SNR) environments, respectively and those for the end point are 72%, 89%, and 93% for the corresponding environments, respectively. The classification of speech and nonspeech for the start point detected region of input signal is performed by the pitch information-base method. The percentages of correct classification for speech and nonspeech input are 99% and 90%, respectively. The eight microphone array-based speech enhancement using the DSBF algorithm shows the maximum SNR gaing of 6dB over a single microphone and the error reductin of more than 15% in the spontaneous speech recognition domain.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.2
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• pp.113-120
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• 2015

Under the penetration of smartphones equipped with a variety of features grows globally, the efficient using of a variety of functions of smartphones has been increased. In accordance with this trend, a lot of researches on the remote control method using the smart phone for consumer products in home networks. Input methods of the current smpartphoes are typically button-based inputs through touching. The button input methods are inconvenient for people who are not familiar touch. Therefore, the researches on the different input schemes to replace the touch methods are required. In this paper, we propose a gesture based input method to replace the touch-sensitive input that of the existing smartphone applications, and a way to apply it to home networks. The proposed method uses three-axis acceleration sensor which is built into smatphones, and it also defines six kinds of gestures patterns that may be applied to home network systems by measuring the recognition rates.