• Genomics & Informatics
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• v.2 no.3
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• pp.121-125
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• 2004

The purpose of this study was to investigate the use of decision tree for the classification of antimicrobial peptides. The classification was based on the activities of known antimicrobial peptides against common microbes including Escherichia coli and Staphylococcus aureus. A feature selection was employed to select an effective subset of features from available attribute sets. Sequential applications of decision tree with 17 nodes with 9 leaves and 13 nodes with 7 leaves provided the classification rates of $76.74\%$ and $74.66\%$ against E. coli and S. aureus, respectively. Angle subtended by positively charged face and the positive charge commonly gave higher accuracies in both E. coli and S. aureusdatasets. In this study, we describe a successful application of decision tree that provides the understanding of the effects of physicochemical characteristics of peptides on bacterial membrane.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6C
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• pp.588-592
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• 2009

In this paper, we propose a novel method to improve the performance of the global soft decision which is based on the second-order conditional maximum a posteriori (CMAP). Conventional global soft decision scheme has an disadvantage in that the speech absence probability adjusted by a fixed-parameter was sensitive to the various noise environments. In proposed approach using the second-order CMAP, speech absence probability value is more flexible which exploit not only the current observation but also the speech activity decisions in the previous two frames. Experimental results show that the proposed improved global soft decision method based on second-order conditional MAP yields better results compared to the conventional global soft decision technique with the performance criteria of the ITU-T P. 862 perceptual evaluation of speech quality (PESQ).

• Journal of Fisheries and Marine Sciences Education
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• v.26 no.2
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• pp.335-344
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• 2014

The purpose of this study is to investigate the effects of self-efficacy and social support on career decision level for fisheries and merchant marine high school students. And it will help improving the Fisheries and Merchant Marine High School students' career decision level. To achieve the purpose of this research, the study carried out a survey targeting 456 fisheries and merchant marine high school students. Analysis methods includes Frequency Analysis, One way ANOVA, t-test, and Regression Analysis and data was analyzed by PASW Statistics 18. The results are as follows: First, fisheries and merchant marine high school students' self-efficacy and social support were generally positive. Second, The effects of the grade, the major and the school of students on self-efficacy showed statistically significant difference. Third, the higher self-efficacy and social support of students were, the higher career decision level was. Lastly, The effects of self-efficacy and social support on career decision level were valued positive.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.2
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• pp.92-99
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• 2014

This paper proposes the method of facial expression recognition based on decision tree structure. In the image of facial expression, ASM(Active Shape Model) and LBP(Local Binary Pattern) make the local features of a facial expressions extracted. The discriminant features gotten from local features make the two facial expressions of all combination classified. Through the sum of true related to classification, the combination of facial expression and local region are decided. The integration of branch classifications generates decision tree. The facial expression recognition based on decision tree shows better recognition performance than the method which doesn't use that.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.409-419
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• 2021

The study examines the effects of digital accounting on financial reporting quality, accounting information usefulness, and strategic decision effectiveness of listed firms in Thailand through digital transformation as the moderating variable. A total of 313 listed firms in Thailand were selected as the sample for the study. Structural equation model and multiple regression analysis are applied to test the research relationships. The results of the study show that digital accounting has a significant effect on financial reporting quality, accounting information usefulness, and strategic decision effectiveness. Financial reporting quality significantly affects both accounting information usefulness and strategic decision effectiveness while accounting information usefulness has a significant effect on strategic decision effectiveness. Both financial reporting quality and accounting information usefulness mediate the digital accounting-strategic decision effectiveness relationship. In addition, digital transformation moderates the digital accounting-financial reporting quality relationship and the digital accounting-accounting information usefulness relationship, but it does not moderate other relationships. Accordingly, digital accounting plays a significant role in determining and explaining firms' goal achievement. Executives are suggested to learn, invest and utilize the digital accounting system in the organization to ensure goal achievement and enhance organizational sustainability.

• Journal of Korean Society of Rural Planning
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• v.28 no.4
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• pp.1-9
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• 2022

Rural decline due to the decrease of the local population is an inevitable phenomenon, and a vicious cycle has been formed between a lack of basic living services and a population decrease in rural areas. Therefore, the study aims to derive the migration decision-making characteristics based on basic living service infrastructure data in rural areas. To do this, the population change over the past 20 years was categorized into six types, and the relationship between the classified population change types and the number of basic living service infrastructures was analyzed using decision tree analysis. Of the total 3,501 regions, 801 regions were the continuous decline type, of which 740 were rural areas. On the other hand, among 569 regions that were the continuous increase type, 401 regions were urban areas, confirming the population imbalance between rural and urban areas. As a result of the decision tree analysis on the relationship between population change types and the distribution of basic living service infrastructure, the number of daycare centers was derived as an important variable to classify the continuous increase type. Hospitals, parks, and public transportation were also found to be major basic living services affecting the classification of population change types.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10C
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• pp.778-786
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• 2008

The H.264/AVC video coding standard shows superior coding efficiency by adopting many new techniques. However, the encoding complexity increases greatly to achieve higher coding efficiency. Especially, the rate distortion optimization technique, which is used to decide the intra-prediction mode, increases the encoding complexity. In this paper, we propose an efficient intra-prediction mode decision method. By using the variance of pixel values and the edge direction, the computational complexity of the intra-prediction mode decision is greatly reduced.

• Speech Sciences
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• v.7 no.4
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• pp.41-47
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• 2000

This paper concerns an effective text-prompted speaker verification method to increase the performance of speaker verification. While various speaker verification methods have already been developed, their effectiveness has not yet been formally proven in terms of achieving an acceptable performance level. It is also noted that the traditional methods were focused primarily on single, prompted utterance for verification. This paper, instead, proposes sequential decision method using variable threshold focused at handling two utterances for text-prompted speaker verification. Experimental results show that the proposed speaker verification method outperforms that of the speaker verification scheme without using the sequential decision by a factor of up to 3 times. From these results, we show that the proposed method is highly effective and achieves a reliable performance suitable for practical applications.

• Speech Sciences
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• v.10 no.1
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• pp.71-84
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• 2003

In the acoustic modeling for large vocabulary speech recognition, a sparse data problem caused by a huge number of context-dependent (CD) models usually leads the estimated models to being unreliable. In this paper, we develop a new clustering method based on the C45 decision-tree learning algorithm that effectively encapsulates the CD modeling. The proposed scheme essentially constructs a supervised decision rule and applies over the pre-clustered triphones using the C45 algorithm, which is known to effectively search through the attributes of the training instances and extract the attribute that best separates the given examples. In particular, the data driven method is used as a clustering algorithm while its result is used as the learning target of the C45 algorithm. This scheme has been shown to be effective particularly over the database of low unknown-context ratio in terms of recognition performance. For speaker-independent, task-independent continuous speech recognition task, the proposed method reduced the percent accuracy WER by 3.93% compared to the existing rule-based methods.

• Industrial Engineering and Management Systems
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• v.15 no.3
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• pp.215-223
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• 2016

Design of personnel teams has been studied from diverse perspectives; the most common are the people and systems requirements perspectives. All these point of view are linked, which is the reason why it is necessary to study them simultaneously. Considering this gap, a decision making model is developed based on factors, models, and requirements mentioned in the literature. The model is applied to a real case. The findings indicate that the Personnel Behavior Based Lean model (PBBL) can be converted into a decision making model for the selection of team members. The study is focused not only on the individual candidates' knowledge, skills, and aptitudes, but also on how the model considers the company requirements, conflicts, and the importance of each person to the project.