• Proceedings of the Korea Information Assurance Society Conference
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• 2004.05a
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• pp.103-108
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• 2004

A Home Location Register(HLR) database system manages each subscriber's location information, which continuously changes in a cellular network. For this purpose, the HLR database system provides table management, index management, and backup management facilities. In this thesis, I propose using a two-level index method for the mobile directory number(MDN) as a suitable method and a chained bucket hashing method for the electronic serial number(ESN). Both the MDN and the ESN are used as keys in the HLR database system. I also propose an efficient backup method that takes into account the characteristics of HLR database transactions. The retrieval speed and the memory usage of the two-level index method are better than those of the T-tree index method. The insertion and deletion overhead of the chained bucket hashing method is less than that of the modified linear hashing method. In the proposed backup method, I use two kinds of dirty flags in order to solvethe performance degradation problem caused by frequent registration-location operations. I also propose using additional attributes in the HLR database scheme for location information secrecy as a suitable security method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.201-207
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• 2012

A RAM-based neural network is a weightless neural network based on binary neural network(BNN) which is efficient neural network with a one-shot learning. RAM-based neural network has multiful information bits and store counts of training in BNN. Supervised learning based on the RAM-based neural network has the excellent performance in pattern recognition but in pattern categorization with unsupervised learning as unsuitable. In this paper, we propose a unsupervised learning algorithm in the RAM-based neural network to perform pattern categorization. By the proposed unsupervised learning algorithm, RAM-based neural network create categories depending on the input pattern by itself. Therefore, RAM-based neural network for supervised learning and unsupervised learning should proof of all possible complex models. The training data for experiments provided by the MNIST offline handwritten digits which is consist of 0 to 9 multi-pattern.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.405-413
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• 2012

Low misclassification performance is significant with high classification accuracy for a reliable diagnosis of ECG signals, and diagnosing abnormal state as normal state can especially raises a deadly problem to a person in ECG test. In this paper, we propose detection and classification method of abnormal rhythm by rule-based rhythm classification reflecting clinical criteria for disease. Rule-based classification classifies rhythm types using rule-base for feature of rhythm section, and rule-base deduces decision results corresponding to professional materials of clinical and internal fields. Experimental results for the MIT-BIH arrhythmia database show that the applicability of proposed method is confirmed to classify rhythm types for normal sinus, paced, and various abnormal rhythms, especially without misclassification in detection aspect of abnormal rhythm.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.5
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• pp.125-133
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• 2016

Data processing capacity and speed are rapidly increasing due to the development of hardware and software in recent time. As a result, data usage is geometrically increasing and the amount of data which computers have to process has already exceeded five-thousand transaction per second. That is, the importance of Big Data is due to its 'real-time' and this makes it possible to analyze all the data in order to obtain accurate data at right time under any circumstances. Moreover, there are many researches about this as construction of smart factory with the application of Big Data is expected to have reduction in development, production, and quality management cost. In this paper, system using In-Memory Data Grid for high speed processing is implemented in semiconductor process which numerous data occur and improved performance is proven with experiments. Implemented system is expected to be possible to apply on not only the semiconductor but also any fields using Big Data and further researches will be made for possible application on other fields.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.109-116
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• 2019

This study proposed a robust detection algorithm. It detects face more stably with respect to changes in light and rotation for the identification of a face shape. Also it satisfies both efficiency of calculation and the function of detection. The algorithm proposed segmented the face area through pre-processing using a face shape as input information in an environment with a single camera and then identified the shape using a Self Organized Feature Map(SOFM). However, as it is not easy to exactly recognize a face area which is sensitive to light, it has a large degree of freedom, and there is a large error bound, to enhance the identification rate, rotation information on the face shape was made into a database and then a principal component analysis was conducted. Also, as there were fewer calculations due to the fewer dimensions, the time for real-time identification could be decreased.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.17-28
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• 2017

Recently, a study on data has been actively conducted because the value of the data has become more useful. Web crawler that is program of data collection recently spotlighted because it can take advantage of the various fields. Web crawler can be defined as a tool to analyze the web pages and collects the URL by traversing the web server in an automated manner. For the treatment of Big-data, distributed Web crawler is widely used which is based on the Hadoop MapReduce. But, it is difficult to use and has constraints on the performance. Apache spark that is the In-memory computing platform is an alternative to MapReduce. The search engine which is one of the main purposes of web crawler displays the information you search by keyword gathered by web crawler. If search engines implement a spark-based web crawler instead of traditional MapReduce-based web crawler, it would be a more rapid data collection.

• Journal of the Korean Data and Information Science Society
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• v.22 no.3
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• pp.389-400
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• 2011

This study was carried out to analysis factors related to in-hospital mortality of community-acquired peumonia using administrative database. The subjects were 5,353 community-acquired pneumonia inpatients of the Korean National Hospital Discharge Injury Survey 2004-2006 data. The data were analyzed using chi-squared test and decision tree model in the data mining technique. Among the decision tree model, C4.5 had the best performance. The critical factors on in-hospital mortality of communityacquired pneumonia are admission route, respiratory failure, congenital heart failure including age, comorbidity, and bed size. This study was carried out using the administrative database including patients' characteristics and comorbidity. However further study should be extensively including hospital characteristics, regional medical resources, and patient management practice behavior.

• Journal of the Korea Concrete Institute
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• v.28 no.4
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• pp.427-434
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• 2016

The purpose of this study is to propose a mixture proportioning approach based on the replacement level of natural sand for reducing $CO_2$ emissions from artificial lightweight aggregate concrete(LWAC) production. To assess the effect of natural sand on the reduction of $CO_2$ emissions and compressive strength of LWAC, a total of 379 specimens compiled from different sources were analyzed. Based on the non-linear regression analysis using the database and the previous mixture proportioning method proposed by Yang et al., simple equations were derived to determine the concrete mixture proportioning and the replacement level of natural sand for achieving the targeted performances(compressive strength, initial slump, air content, and $CO_2$ reduction ratio) of concrete. Furthermore, the proposed equations are practically applicable to straightforward determination of the $CO_2$ emissions from the provided mixture proportions of LWAC.

• Journal of the Korea Convergence Society
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• v.9 no.6
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• pp.1-7
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• 2018

As IT technology develops recently, medical equipment used in hospitals is demanding high performance. However, since the user visits different hospitals depending on the user's situation, the medical information treated at the hospital is distributed among the hospitals. In this paper, we propose a model to efficiently integrate the health care information of the users stored in the hospital in order to collect the healthcare information of the users who visited the different hospitals. The proposed model synchronizes users' healthcare information collected from personal wearable devices to collect user - centered healthcare information. In addition, the proposed model performs integrity and validity check related to user's healthcare information in a database existing in a cloud environment in order to smoothly share data with the healthcare service center. In particular, the proposed model enables tree - based data processing to smoothly manage healthcare information collected from mobile platforms.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.4
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• pp.19-26
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• 2008

Gene set enrichment analysis (GSEA) is a computational method to identify statistically significant gene sets showing significant differences between two groups of microarray expression profiles and simultaneously uncover their biological meanings in an elegant way by employing gene annotation databases, such as Cytogenetic Band, KEGG pathways, gene ontology, and etc. For the gone set enrichment analysis, all the genes in a given dataset are first ordered by the signal-to-noise ratio between the groups and then further analyses are proceeded. Despite of its impressive results in several previous studies, however, gene ranking by the signal-to-noise ratio makes it difficult to consider highly up-regulated genes and highly down-regulated genes at the same time as the candidates of significant genes, which possibly reflect certain situations incurred in metabolic and signaling pathways. To deal with this problem, in this article, we investigate the gene set enrichment analysis method with Fisher criterion for gene ranking and also evaluate its effects in Leukemia related pathway analyses.