• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.6C
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• pp.487-497
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• 2008

This paper proposes a new adaptive QRD-M algorithm for MIMO systems. The proposed scheme controls the number of survivor paths,0 based on the channel condition at each layer. The original QRD-M algorithm used fixed M at each layer and it needs large M to achieve near-MLD (maximum-likelihood detection) performance. However, using the large M increases the computation complexity. In this paper, we further effectively control M by employing the channel indicator which includes not only the channel gain, but also instantaneous noise information without necessity of SNR measurement. We found that the ratio of the minimum path metric to the second minimum is good reliability indicator for the channel condition. By adaptively changing M based on this ratio, the proposed scheme effectively achieves near MLD performance and computation complexity of the proposed scheme is significantly smaller than the conventional QRD-M algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.5
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• pp.924-930
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• 2015

In this paper, we propose a novel approach of low computational complexity to improve the speech quality of the small acoustic equipment in noisy environment. The conventional gain control algorithm suppresses the noise of input signal, and then the part of wide dynamic range compression (WDRC) amplifies the undesired signal. The proposed algorithm controls the gain of hearing aids according to speech present probability by using the output of a voice activity detection (VAD). The performance of the proposed scheme is evaluated under various noise conditions by using objective measurement and yields superior results compared with the conventional algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.7
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• pp.1462-1470
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• 2003

According to the necessity about information security as well as the advance of IT system and the spread of the Internet, a variety of cryptography algorithms are being developed and put to practical use. In addition the technique about cryptography attack also is advanced, and the algorithms which are strong against its attack are being studied. If the linear transformation matrix in the block cipher algorithm such as Substitution Permutation Networks(SPN) produces the Maximum Distance Separable(MDS) code, it has strong characteristics against the differential attack and linear attack. In this paper, we propose a new algorithm which cm estimate that the linear transformation matrix produces the MDS code. The elements of input code of linear transformation matrix over GF$({2_n})$ can be interpreted as variables. One of variables is transformed as an algebraic formula with the other variables, with applying the formula to the matrix the variables are eliminated one by one. If the number of variables is 1 and the all of coefficient of variable is non zero, then the linear transformation matrix produces the MDS code. The proposed algorithm reduces the calculation time greatly by diminishing the number of multiply and reciprocal operation compared with the conventional algorithm which is designed to know whether the every square submatrix is nonsingular.

• Journal of Intelligence and Information Systems
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• v.13 no.1
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• pp.81-90
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• 2007

This paper shows an intelligent disease diagnosis system for public. Our system deals with 30 diseases and their typical symptoms selected based on the report from Ministry of Health and Welfare, Korea. Technically, the system uses a modified FCM algorithm for clustering diseases and the input vector consists of the result of user-selected questionnaires. The modified FCM algorithm improves the quality of clusters by applying symmetrically measure based on the fuzzy theory so that the clusters are relatively sensitive to the shape of the pattern distribution. Furthermore, we extract the highest 5 diseases only related to the user-selected questionnaires based on the fuzzy membership function between questionnaires and diseases in order to avoid diagnosing unrelated disease.

• Nuclear Engineering and Technology
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• v.53 no.10
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• pp.3327-3334
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• 2021

Present electric grids are advanced to integrate smart grids, distributed resources, high-speed sensing and control, and other advanced metering technologies. Cybersecurity is one of the challenges of the smart grid and nuclear plant digital system. It affects the advanced metering infrastructure (AMI), for grid data communication and controls the information in real-time. The research article is emphasized solving the nuclear and smart grid hardware security issues with the integration of field programmable gate array (FPGA), and implementing the latest Time Authenticated Cryptographic Identity Transmission (TACIT) cryptographic algorithm in the chip. The cryptographic-based encryption and decryption approach can be used for a smart grid distribution system embedding with FPGA hardware. The chip design is carried in Xilinx ISE 14.7 and synthesized on Virtex-5 FPGA hardware. The state of the art of work is that the algorithm is implemented on FPGA hardware that provides the scalable design with different key sizes, and its integration enhances the grid hardware security and switching. It has been reported by similar state-of-the-art approaches, that the algorithm was limited in software, not implemented in a hardware chip. The main finding of the research work is that the design predicts the utilization of hardware parameters such as slices, LUTs, flip-flops, memory, input/output blocks, and timing information for Virtex-5 FPGA synthesis before the chip fabrication. The information is extracted for 8-bit to 128-bit key and grid data with initial parameters. TACIT security chip supports 400 MHz frequency for 128-bit key. The research work is an effort to provide the solution for the industries working towards embedded hardware security for the smart grid, power plants, and nuclear applications.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.51-66
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• 2023

In this paper, we propose a new type of process discovery framework, which is named as control-path-driven process group discovery framework, to be used for process mining and process reengineering in supporting life-cycle management of business process models. In addition, we develop a process mining system based on the proposed framework and perform experimental verification through it. The process execution event logs applied to the experimental effectiveness and verification are specially defined as Process BIG-Logs, and we use it as the input datasets for the proposed discovery framework. As an eventual goal of this paper, we design and implement a control path-driven process group discovery algorithm and framework that is improved from the ρ-algorithm, and we try to verify the functional correctness of the proposed algorithm and framework by using the implemented system with a BIG-Log dataset. Note that all the process mining algorithm, framework, and system developed in this paper are based on the structural information control net process modeling methodology.

• The Transactions of the Korea Information Processing Society
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• v.5 no.9
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• pp.2294-2301
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• 1998

The aim of this paper is to extract features from each news scenes for example, symbol icon which can be distinct each broadcasting corp, icon and caption which are has feature and important information for the scene in respectively, In this paper, we propose extraction methods of caption that has important prohlem of news videos and it can be classified in three steps, First of al!, we converted that input images from video frame to YIQ color vector in first stage. And then, we divide input image into regions in clear hy using equalized color histogram of input image, In last, we extracts caption using edge histogram based on vertical and horizontal line, We also propose the method which can extract news icon in selected key frames by the difference of inter-histogram and can divide each scene by the extracted icon. In this paper, we used comparison method of edge histogram instead of complex methcxls based on color histogram or wavelet or moving objects, so we shorten computation through using simpler algorithm. and we shown good result of feature's extraction.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.161-169
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• 2012

In general, Euclidean minimum spanning tree is a tree connecting input nodes with minimum connecting cost. But the tree may not be optimal when applied to real world problems of three dimension. In this paper, three dimension Euclidean minimum spanning tree is proposed, connecting all input nodes of 3-dimensional space with minimum cost. In experiments for 30,000 input nodes with 100% space ratio, the tree produced by the proposed method can reduce 90.0% connection cost tree, compared with the tree by two dimension Prim's minimum spanning tree. In two dimension plane, the proposed tree increases 251.2% connecting cost, which is pointless in 3-dimensional real world. Therefore, the proposed method can work well for many connecting problems in real world space of three dimensions.

• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.353-360
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• 2006

This paper presents a robust algorithm for segmenting a vehicle license plate area from a road image. We consider the features of license plates in three aspects : 1) edges due to the characters in the plate, 2) colors in the plate, and 3) geometric properties of the plate. In the preprocessing step, we compute the thresholds based on each feature to decide whether a pixel is inside a plate or not. A statistical approach is applied to the sample images to compute the thresholds. For a given road image, our algorithm binarizes it by using the thresholds. Then, we select three candidate regions to be a plate by searching the binary image with a moving window. The plate area is selected among the candidates with simple heuristics. This algorithm robustly detects the plate against the transformation or the difference of color intensity of the plate in the input image. Moreover, the preprocessing step requires only a small number of sample images for the statistical processing. The experimental results show that the algorithm has 97.8% of successful segmentation of the plate from 228 input images. Our prototype implementation shows average processing time of 0.676 seconds per image for a set of $1280{\times}960$ images, executed on a 3GHz Pentium4 PC with 512M byte memory.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12A
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• pp.2109-2119
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• 2001

In this paper, a fast information extraction algorithm for object-based MPEG-4 application from MPEG-2 bit-steam is proposed. For object-based MPEG-4 conversion, we need to extract such information as object-image, shape-image, macro-block motion vector, and header information from MPEG-2 bit-stream. If we use the extracted information, fast conversion for object-based MPEG-4 is possible. The proposed object extraction algorithm has two important steps, namely the motion vectors extraction from MPEG-2 bit-stream and the watershed algorithm. The algorithm extracts objects using user\`s assistance in the intra frame and tracks then in the following inter frames. If we have an unsatisfactory result for a fast moving object, the user can intervene to correct the segmentation. The proposed algorithm consist of two steps, which are intra frame object extracts processing and inter frame tracking processing. Object extracting process is the step in which user extracts a semantic object directly by using the block classification and watersheds. Object tacking process is the step of the following the object in the subsequent frames. It is based on the boundary fitting method using motion vector, object-mask, and modified watersheds. Experimental results show that the proposed method can achieve a fast conversion from the MPEG-2 bit-stream to the object-based MPEG-4 input.