• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.1
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• pp.46-55
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• 2007

The Newton-Raphson's algorithm for finding a floating point reciprocal and inverse square root calculates the result by performing a fixed number of multiplications. In this paper, an improved Newton-Raphson's algorithm is proposed, that performs multiplications a variable number. Since the number of multiplications performed by the proposed algorithm is dependent on the input values, the average number of multiplications per an operation is derived from many reciprocal and inverse square tables with varying sizes. The superiority of this algorithm is proved by comparing this average number with the fixed number of multiplications of the conventional algorithm. Since the proposed algorithm only performs the multiplications until the error gets smaller than a given value, it can be used to improve the performance of a reciprocal and inverse square root unit. Also, it can be used to construct optimized approximate tables. The results of this paper can be applied to many areas that utilize floating point numbers, such as digital signal processing, computer graphics, multimedia, scientific computing, etc.

• Journal of the Korea Society of Computer and Information
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• v.14 no.7
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• pp.33-40
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• 2009

Edge detection is very significant in low level image processing. However, majority edge detection methods are not only effective enough cause of the noise points' influence, even not flexible enough to different input images. In order to sort these problems, in this paper an algorithm is presented that has an extra noise reduction stage at first, and then automatically selects the both thresholds depending on gradient amplitude histogram and intra class minimum variance. Using this algorithm, can fade out almost all of the sensitive noise points, and calculate the propose thresholds for different images without setting up the practical parameters artificially, and then choose edge pixels by fuzzy algorithm. In finally, get the better result than the former Canny algorithm.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.1-16
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• 2011

The real-time ubiquitous environment is required to be able to process a series of sensor data within limited time. The whole sensor data processing consists of several phases : getting data out of sensor, acquiring context and responding to users. The ubiquitous computing middleware is aware of the context using the input sensor data and a series of data from database or knowledge-base, makes a decision suitable for the context and shows a response according to the decision. When the real-time ubiquitous environment gets a set of sensor data as its input, it needs to be able to estimate the delay-time of the sensor data considering the available resource and the priority of it for scheduling a series of sensor data. Also the sensor data of higher priority can stop the processing of proceeding sensor data. The research field for such a decision making is not yet vibrant. In this paper, we propose a queuing time computation algorithm for sensor data processing in real-time ubiquitous environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.10
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• pp.2121-2128
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• 2012

This paper proposed the real time face area detection using Wavelet transform and the strong detection algorithm that satisfies the efficiency of computation and detection performance at the same time was proposed. The detected face image recognizes the face by configuring the low-dimensional face symbol through the principal component analysis. The proposed method is well suited for real-time system construction because it doesn't require a lot of computation compared to the existing geometric feature-based method or appearance-based method and it can maintain high recognition rate using the minimum amount of information. In addition, in order to reduce the wrong recognition or recognition error occurred during face recognition, the input symbol of Hidden Markov Model is used by configuring the feature values projected to the unique space as a certain symbol through clustering algorithm. By doing so, any input face will be recognized as a face model that has the highest probability. As a result of experiment, when comparing the existing method Euclidean and Mahananobis, the proposed method showed superior recognition performance in incorrect matching or matching error.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.1
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• pp.48-59
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• 2002

TSK(Takagi-Sugeno-Kang) fuzzy models with linear equations consequents, which represent complex nonlinear systems very well with a few rules, can be easily identified systematically by using input-output data. Many algorithms designing TSK fuzzy controllers based on TSK fuzzy models, which guarantees the stability of the closed system, have been suggested. On the contrary, singleton fuzzy models with singleton consequents can be easily understood and adjusted. In this paper, in order to utilize the merits of TSK fuzzy systems and singleton fuzzy systems, an algorithm transforming a TSK fuzzy model into a singleton fuzzy model having the same input-output relation is suggested. The suggested algorithm is applied to a fuzzy modelling example and a fuzzy controller design example.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.9
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• pp.744-749
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• 2013

We propose soft user data input on LDPC codes with parity encoded by the (1, 7) run length limited (RLL) code for perpendicular magnetic recording channel. The user data are encoded by maximum transition run (MTR) (3;11) code. In order to minimize the loss of code rate, the (1, 7) RLL code only encode the parity of LDPC. Also, to increase performance, we propose only user data part applied soft output Viterbi algorithm (SOVA). The performance using the SOVA showed good performance lower than 26 dB. In contrast, it showed worse performance high than 26 dB. This is because of incorrect soft information by high jitter noise and two different input types for LDPC decoder.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.3
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• pp.159-168
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• 1996

In this paper, the natural language dialogue understanding sytem, based on discourse information and plan recognition, is designed and implemented. The system needs to analyze the user's input utterance and acquire the discoruse information to perform plan recognition and facilitate cooperative response. This paper proposes the mehtod of controlling a dialogue, based on the algorithm for extracting the discourse information. When the discourse information for dialogue understanding is extracted, the information-based value in feature structure that is obtained form korean parser is used. And the system makes use of the structure. Thus it can offer the response that the user wants to take, and let the dialogue to study in utterance level and enhance the efficiency of dialogue understanding. In this paper, we apply the system to the hotel reservation domain and show the mehtod of using the discoruse information to control the dialogue.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.211-227
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• 2011

Content Based Image Retrieval (CBIR) is an approach for retrieving similar images from an image database based on automatically-derived image features. The quality of a retrieval system depends on the features used to describe image content. In this paper, we propose an image clustering system that takes a database of images as input and clusters them using k-means clustering algorithm taking into consideration color, texture and shape features. Experimental results show that the combination of the three features brings about higher values of accuracy and precision.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.12 no.2
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• pp.69-76
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• 1998

This paper presents a novel algorithm for determining the optimal operation of a cogeneration plant with back-pressure and extraction-condensing turbine/generators. The proposed algorithm determines the optimum load of boilers and turbine/generators, using only one parameter, the steam mass flow rate, which can be obtained directly from on-line measurement during plant operation. The proposed algorithm consists of the non -linear operating cost function, and its correlated constraints. Furthermore, it has been successfully applied to an actual industrial cogeneration plant, with satisfactory results. Comparison of these results with actual operating data has revealed that using the proposed algorithm results in at least 1.2~4.5[%] operating cost saving, depending on the process steam load. Furthermore the proposed algorithm can be easily installed in a process control computer because the required input data can be easily obtained from information available on-line.n-line.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.1959-1975
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• 2011

Adaptive Bit Loading (ABL) in Multiple-Input Multiple-Output Orthogonal Frequency-Division Multiplexing (MIMO-OFDM) is often used to achieve the desired Bit Error Rate (BER) performance in wireless systems. In this paper, we discuss some of the bit loading algorithms, compare them in terms of the BER performance, and present an effective and concise Adaptive Grouped Loading (AGL) algorithm. Furthermore, we propose a "weight factor" for loading algorithm to converge rapidly to the final solution for various data rate with variable Signal to Noise Ratio (SNR) gaps. In particular, we consider the bit loading in near optimal Singular Value Decomposition (SVD) based MIMO-OFDM system. While using SVD based system, the system requires perfect Channel State Information (CSI) of channel transfer function at the transmitter. This scenario of SVD based system is taken as an ideal case for the comparison of loading algorithms and to show the actual enhancement achievable by our AGL algorithm. Irrespective of the CSI requirement imposed by the mode of the system itself, ABL demands high level of feedback. Grouped Loading (GL) would reduce the feedback requirement depending upon the group size. However, this also leads to considerable degradation in BER performance. In our AGL algorithm, groups are formed with a number of consecutive sub-channels belonging to the same transmit antenna, with individual gains satisfying predefined criteria. Simulation results show that the proposed "weight factor" leads a loading algorithm to rapid convergence for various data rates with variable SNR gap values and AGL requires much lesser CSI compared to GL for the same BER performance.