• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.6A
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• pp.519-536
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• 2007

In this paper, we combine the Hybrid-Automatic Repeat reQuest (HARQ) algorithm with joint Tx and Rx antenna selection based on the reliability of the individual antennas links. The cyclic redundancy check (CRC) is applied on the data before being encoded using the Turbo encoder. In the receiver the CRC is used to detect errors of each antenna stream and to decide whether a retransmission is required or not. The receiver feeds back the transmitter with the Tx antennas ordering and the acknowledgement of each antenna (ACK or NACK). If the number of ACK antennas is higher than the NACK antennas, then the retransmission takes place from the ACK antennas using the Chase Combining (CC). If the number of the NACK antennas is higher than the ACK antennas then the ACK antennas are used to retransmit the data streams using the CC algorithm and additional NACK antennas are used to retransmit the remaining streams using Incremental Redundancy (IR, i.e. the encoder rate is reduced). Furthermore, the HARQ is used with the I-BLAST (Iterative-BLAST) which grantees a high transmission rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.10
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• pp.859-869
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• 2012

In this paper, a new method to efficiently generate the 3-D(three-dimensional) video holograms for 3-D moving scenes, which is called here the TSR-N-LUT method, is proposed by the combined use of temporal-spatial redundancy(TSR) of 3-D video images and novel look-up table(N-LUT) technique. That is, in the proposed scheme, with the differential pulse code modulation (DPCM) algorithm, temporally redundancy redundant data in the inter-frame of a 3-D video images are removed between the frames, and then inter-line redundant data in the inter-frame of 3-D video images are also removed by using the DPCM method between the lines. Experimental results show that the proposed method could reduced the number of calculated object points and the calculation time of one object point by 23.72% and 19.55%, respectively on the average compared to the conventional method. Good experimental results with 3-D test moving pictures finally confirmed the feasibility of the proposed method to the fast generation of CGH patterns of the 3-D video images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.574-575
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• 2018

The generation of redundant data according to the spatial-temporal correlation in a wireless sensor network that reduces the network lifetime by consuming unnecessary energy. In this paper, data collection experiment through the particulate matter sensor is carried out to confirm the spatial-temporal data redundancy and we propose permitted limit setting method for data transmission to solve this problem. In the proposed method, the data transmission permitted limit is set by using the integrated average value in the cluster. The set permitted limit reduces the redundant data of the member node and it is shows that redundant data reduction is possible even in a variable environment of collected data by resetting the permitted limit in the cluster head.

• Journal of Internet Computing and Services
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• v.11 no.6
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• pp.123-133
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• 2010

XML has been become the new standard for publishing and exchanging data on the Web. However, most business data is still stored and maintained in relational database management systems. As such, there is an increasing need to efficiently publish relational data as XML data for Internet-based applications. The most important issue in the transformation is to reflect structural and semantic relations of RDB to XML schema exactly. Most transformation approaches have been done to resolve the issue, but those methods have several problems. In this paper, we discuss algorithm in transforming a relational database schema into corresponding XML schema in XML Schema. We aim to achieve not only explicit/implicit referential integrity relation information but also high level of nested structure while introducing no data redundancy for the transformed XML schema. To achieve these goals, we propose a transformation model which is redundancy free and then we improve the XML Schema structure by exploring more nested structure.

• Journal of Information Processing Systems
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• v.14 no.5
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• pp.1167-1175
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• 2018

Microarray data plays an essential role in diagnosing and detecting cancer. Microarray analysis allows the examination of levels of gene expression in specific cell samples, where thousands of genes can be analyzed simultaneously. However, microarray data have very little sample data and high data dimensionality. Therefore, to classify microarray data, a dimensional reduction process is required. Dimensional reduction can eliminate redundancy of data; thus, features used in classification are features that only have a high correlation with their class. There are two types of dimensional reduction, namely feature selection and feature extraction. In this paper, we used k-means algorithm as the clustering approach for feature selection. The proposed approach can be used to categorize features that have the same characteristics in one cluster, so that redundancy in microarray data is removed. The result of clustering is ranked using the Relief algorithm such that the best scoring element for each cluster is obtained. All best elements of each cluster are selected and used as features in the classification process. Next, the Random Forest algorithm is used. Based on the simulation, the accuracy of the proposed approach for each dataset, namely Colon, Lung Cancer, and Prostate Tumor, achieved 85.87%, 98.9%, and 89% accuracy, respectively. The accuracy of the proposed approach is therefore higher than the approach using Random Forest without clustering.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.882-885
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• 2010

In view of the severe energy constraint in sensor networks, it is important to use the error control scheme of the energy efficiently. In this paper, we presented FEC (Forward Error Correcting) codes in terms of their power consumption. One method of FEC is RS (Reed-Solomon) coding, which uses block codes. RS codes work by adding extra redundancy to the data. The encoded data can be stored or transmitted. It could have errors introduced, when the encoded data is recovered. The added redundancy allows a decoder to detect which parts of the received data is corrupted, and corrects them. The number of errors which are able to be corrected by RS code can determine by added redundancy. We could predict the lifetime of RS codes which transmitted at 32 byte a 1 minutes. RS(15, 13), RS(31, 27), RS(63, 57), RS(127,115), and RS(255,239) can keep the days of 138, 132, 126, 111, and 103 respectively.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.8
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• pp.42-49
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• 1996

In this paper, we propose a satellite multispectral image data compression method using classified vector quantization. This method classifies each pixel vector considering band characteristics of multispectral images. For each class, we perform both intraband and interband vector quantization to romove spatial and spectral redundancy, respectively. And residual vector quantization for error images is performed to reduce error of interband vector quantization. Thus, this method improves compression efficiency because of removing both intraband(spatial) and interband (spectral) redundancy in multispectral images, effectively. Experiments on landsat TM multispectral image show that compression efficiency of proposed method is better than that of conventional method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.8
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• pp.1722-1732
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• 1997

In this paper, we propose a coding method of remotely sensed satellite image data using region classification and interband correlation. This method classifies each pixel vector consider spectral characteristics. Then we perform the classified intraband VQ to remove spatial (intraband redundancy for a reference band image. To remove interband redundancy effectively, we perform the classified interband prediction for the band images that the high correlation spectrally and perform the classified interband VQ for the remaining band images. Experiments on LANDSAT TM image show that the coding efficiency of the proposed method is better than that of the conventional Gupta's method. Especially, this method removes redundancies effectively for satellite iamge including various geographical objects and for and images that have low interband correlation.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.238-241
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• 2002

With the popularity of utilization of the Internet among people, the amount of data in the network rapidly increased. So that, the fall of response time from WWW server, which is caused by the network traffic and the burden on m server, has become more of an issue. This problem is encouraged the rearch by redundancy of requesting the same pages by many people, even though they browse the same the ones. To reduce these redundancy, WWW cache server is used commonly in order to store m page data and reuse them. However, the technical uses of WWW cache that different from CPU and Disk cache, is known for its difficulty of improving the cache hit rate. Consecuently, it is difficult to choose effective WWW data to be stored from all data flowing through the WWW cache server. On the other hand, there are room for improvement in commonly used cache replacement algorithms by WWW cache server. In our study, we try to realize a WWW cache server that stresses on the improvement of the stresses of response time. To this end, we propose the new cache replacement algorithm by focusing on the utilizable information of network distance from the WWW cache server to WWW server that possessing the page data of the user requesting.

• Journal of Korea Multimedia Society
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• v.24 no.3
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• pp.382-395
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• 2021

In this study, character recognition using deep learning is performed among the various defects in the PCB, the purpose of which is to check whether the printed characters are printed correctly on top of components, or the incorrect parts are attached. Generally, character recognition may be perceived as not a difficult problem when considering MNIST, but the printed letters on the PCB component data are difficult to collect, and have very high redundancy. So if a deep learning model is trained with original data without any preprocessing, it can lead to over fitting problems. Therefore, this study aims to reduce the redundancy to the smallest dataset that can represent large amounts of data collected in limited production sites, and to create datasets through data enhancement to train a flexible deep learning model can be used in various production sites. Moreover, ResNet model verifies to determine which combination of datasets is the most effective. This study discusses how to reduce and augment data that is constantly occurring in real PCB production lines, and discusses how to select coresets to learn and apply deep learning models in real sites.