• Journal of rehabilitation welfare engineering & assistive technology
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• v.2 no.1
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• pp.51-56
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• 2009

This study was tried to analyze the diagnosis of patients with cerebral infarction by sequence modeling that was one of data mining analysis method and find out previous disease or complication of patients with cerebral infarction. Mass data that the diagnosis code of cerebral infarction was 163 in 2000 to 2007 were extracted from A hospital's database and then the data mart was constructed for analysis. Total 2,267 patients illnesses were diagnosed as cerebral infarction and 32,692 cases related diagnosis were extracted. Sequence modeling in Clementine 12.0 program was used to analyze diagnosis of patients with cerebral infarction and 8 meaningful rules were found in this paper. This result could be used as a basic data to make secondary cerebral infarction prevention program and to prevent complication of cerebral infarction.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.11-19
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• 2002

In this paper, the problem of estimating a p-variate $(p\geq4)$ normal mean vector in a decision-theoretic setup is considered. Using a technique of Guo and Pal (1992), a sequence of estimators dominating the Lindley type estimator is derived and each improved estimator is better than the previous one.

• Journal of the Korean Data and Information Science Society
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• v.6 no.2
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• pp.9-15
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• 1995

In discriminant analysis the procedures commonly used to estimate the dimensionality involve testing a sequence of dimensionality hypotheses. There is a problem with the size of the test since dimensionality hypotheses are tested sequentially and thus they are actually conditional tests. The focus of this paper is "How is the size of the test affected by viewing this sequence of tests as conditional tests?".

• ETRI Journal
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• v.28 no.2
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• pp.250-252
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• 2006

In this letter, a discrete state, discrete time chaotic pseudo random number generator (CPRNG) is presented for stream ciphering of text, audio, or image data. The CPRNG is treated as a finite state machine, and its state is modulated according to the input bit sequence of the signal to be encrypted. The modulated state sequence obtained can be transmitted as a spread spectrum or encrypted data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.8B
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• pp.1333-1340
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• 2000

This paper shows that the Kronecker sequence, the rapid acquisition spreading code, can be used in packet wireless data communication systems. The general properties of the Kronecker sequence such as construction and correlation characteristics are described, and it is shown that the Kronecker sequence can use a partial-period correlation for a faster acquisition. Based on above Properties, it can be expected that the Kronecker sequence can be used in packet communication systems because the probability of false alarm for the Kronecker sequence is lower and flatter(that is, less sensitive to Ec/No variations) than that for the PN sequence under the assumption that both sequences have the same acquisition time.

• Journal of Advanced Navigation Technology
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• v.8 no.2
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• pp.163-168
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• 2004

In this paper, we propose a frequency synchronization algorithm using characteristic of CAZAC sequence for HDR-WPAN and analyze the performance by signal constellation and EVM(error vector magnitude). The proposed frequency offset technique estimated each sample phase error of two sequences among 12 CAZAC sequences which have excellent autocorrelated characteristic. Estimated phase error is multiplied to each sample of next sequence for compensating the frequency offset. The remaining frequency offset after compensating it with two sequences has maximum 0.002 offsest ranges at each sample. The computer simulation proved that the permission of EVM value had satisfied in the case of DQPSK at 20[dB].

• Korean Journal of Applied Biomechanics
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• v.33 no.4
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• pp.137-146
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• 2023

Objective: The horizontal bar of gymnastics is fundamentally based on rotational movements. This study aimed to determine the effect of kinematics variables and sequence during horizontal bar performance (Kovacs, Tkatchev Stretched & Kolman) in gymnastic. Method: Four gymnastics athletes of the national team were participated in this study. All subjects were asked to perform the three types of horizontal bar skill. Simi marker-less cameras were used to collect the raw data (120 Hz). Kinematic variables (total time, interval, center of mass, height, angular velocity etc.) and sequence variables were calculated to examine the differences. Results: As a result, horizontal bar performance in gymnastic has special sequence that making the peak angular velocity from distal joint to proximal joint (knee-hip-shoulder). It is rare sequence that typical sport does not have. Conclusion: In field, gymnastic coaches and players should know the result that there is special sequence in horizontal bar performance. It could be very useful to teach and enhance their performance.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.6
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• pp.59-72
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• 2012

Since a protein displays its specific functions when disorder region of protein sequence transits to order region with provoking a biological reaction, the separation of disorder region and order region from the sequence data is urgently necessary for predicting three dimensional structure and characteristics of the protein. To classify the disorder and order region efficiently, this paper proposes a classification/prediction method using sequence data while acquiring a non-biased result on a specific characteristics of protein and improving the classification speed. The emerging patterns based EPs-TFP methods utilizes only the essential emerging pattern in which the redundant emerging patterns are removed. This classification method finds the sequence patterns of disorder region, such sequence patterns are frequently shown in disorder region but relatively not frequently in the order region. We expand P-tree and T-tree conceptualized TFP method into a classification/prediction method in order to improve the performance of the proposed algorithm. We used Disprot 4.9 and CASP 7 data to evaluate EPs-TFP technique, the results of order/disorder classification show sensitivity 73.6, specificity 69.51 and accuracy 74.2.

• The KIPS Transactions:PartD
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• v.8D no.5
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• pp.553-560
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• 2001

Bioinformatics is a discipline to support biological experiment projects by storing, managing data arising from genome research. In can also lead the experimental design for genome function prediction and regulation. Among various approaches of the genome research, the proteomics have been drawing increasing attention since it deals with the final product of genomes, i.e., proteins, directly. This paper proposes a data mining technique to predict the structural characteristics of a given protein group, one of dominant factors of the functions of them. After explains associations among amino acid subsequences in the primary structures of proteins, which can provide important clues for determining secondary or tertiary structures of them, it defines a sequence association rule to represent the inter-subsequences. It also provides support and confidence measures, newly designed to evaluate the usefulness of sequence association rules, After is proposes a method to discover useful sequence association rules from a given protein group, it evaluates the performance of the proposed method with protein sequence data from the SWISS-PROT protein database.

• Journal of KIISE:Databases
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• v.32 no.1
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• pp.24-42
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• 2005

Characteristics of biological data including genome sequences are heterogeneous and various. Although the need of management systems for genome sequencing which should reflect biological characteristics has been raised, most current biological databases provide restricted function as repositories for biological data. Therefore, this paper describes a management system of nucleotide sequences at the level of biological laboratories. It includes format transformation, editing, storing and retrieval for collected nucleotide sequences from public databases, and handles sequence produced by experiments. It uses BSML based on XML as a common format in order to extract data fields and transfer heterogeneous sequence formats. To manage sequences and their changes, version management system for originated DNA is required so as to detect transformed new sequencing appearance and trigger database update. Our experimental results show that applying active trigger rules to manage changes of sequences can automatically store changes of sequences into databases.