• Journal of Microbiology and Biotechnology
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• 제15권5호
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• pp.1022-1027
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• 2005

Based on plasmid display technology by the complexes of fusion protein and the encoding plasmid DNA, an in vitro selection method for high affinity DNA-binding protein was developed and experimentally demonstrated. The GAL4 DNA-binding domain (GAL4 DBD) was selected as a model DNA-binding protein, and enhanced green fluorescent protein (EGFP) was used as an expression reporter for the selection of target proteins. Error prone PCR was conducted to construct a mutant library of the model. Based on the affinity decrease with increased salt concentration, mutants of GAL4 DBD having high affinity were selected from the mutant protein library of protein-encoding plasmid complex by this method. Two mutants of (Lys33Glu, Arg123Lys, Ile127Lys) and (Ser47Pro, Ser85Pro) having high affinity were obtained from the first generation mutants. This method can be used for rapid in vitro selection of high affinity DNA-binding proteins, and has high potential for the screening of high affinity DNA-binding proteins in a sequence-specific manner.

• Journal of Microbiology and Biotechnology
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• 제17권6호
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• pp.993-1001
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• 2007

The technique of serological analysis of antigens by recombinant cDNA expression library (SEREX) uses autologous patient sera as a screening probe to isolate tumor-associated antigens for various tumor types. Isolation of tumor-associated antigens that are specifically reactive with patient sera, but not with normal sera, is important to avoid false-positive and autoimmunogenic antigens for the cancer immunotherapy. Here, we describe a selection methodology to isolate patient sera-specific antigens from a yeast surface-expressed cDNA library constructed from 15 patient lung tissues with non-small cell lung cancer (NSCLC). Several rounds of positive selection using patient sera alone as a screening probe isolated clones exhibiting comparable reactivity with both patient and normal sera. However, the combination of negative selection with allogeneic normal sera to remove antigens reactive with normal sera and subsequent positive selection with patient sera efficiently enriched patient sera-specific antigens. Using the selection methodology described here, we isolated 3 known and 5 unknown proteins, which have not been isolated previously, but and potentially associated with NSCLC.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2006년도 춘계학술대회
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• pp.167-175
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• 2006

Building accurate corporate bankruptcy prediction models has been one of the most important research issues in finance. Recently, support vector machines (SVMs) are popularly applied to bankruptcy prediction because of its many strong points. However, in order to use SVM, a modeler should determine several factors by heuristics, which hinders from obtaining accurate prediction results by using SVM. As a result, some researchers have tried to optimize these factors, especially the feature subset and kernel parameters of SVM But, there have been no studies that have attempted to determine appropriate instance subset of SVM, although it may improve the performance by eliminating distorted cases. Thus in the study, we propose the simultaneous optimization of the instance selection as well as the parameters of a kernel function of SVM by using genetic algorithms (GAs). Experimental results show that our model outperforms not only conventional SVM, but also prior approaches for optimizing SVM.

• 한국의류학회지
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• 제8권1호
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• pp.75-84
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• 1984

The main purpose of the study were to investigate a selection motive of clothing and the feeling of wearing of Korean high school students. The results were as follows ; 1. For underwear, the body appearance and the hygienical aspect were shown as important factors in a selection motive of clothing. And the property of matter and hygienical aspect were shown as important factors in the feeling of wearing. 2. For outwear, a functionality and the psychological aspect were shown as important factors in a selective motive of clothing. And a exeroise and the psychological aspect were shown as important factors in the feeling of wearing. 3. For skirt, the psychological aspect was shown as an important factor in a selection motive of clothing and the feeling of wearing. For pants, a functionality was shown as an important factor in a selection motive of clothing. 4. A exercise was shown as an important factor in the feeling of wearing with the silhouette of outwear. 5. The hygienical aspect was shown as an important factor in the demand of selection motive of clothing for comfort.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권6호
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• pp.1540-1561
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• 2024

This research proposes a novel approach for Tamil Handwritten Character Recognition (THCR) that combines feature selection and ensemble learning techniques. The Tamil script is complex and highly variable, requiring a robust and accurate recognition system. Feature selection is used to reduce dimensionality while preserving discriminative features, improving classification performance and reducing computational complexity. Several feature selection methods are compared, and individual classifiers (support vector machines, neural networks, and decision trees) are evaluated through extensive experiments. Ensemble learning techniques such as bagging, and boosting are employed to leverage the strengths of multiple classifiers and enhance recognition accuracy. The proposed approach is evaluated on the HP Labs Dataset, achieving an impressive 95.56% accuracy using an ensemble learning framework based on support vector machines. The dataset consists of 82,928 samples with 247 distinct classes, contributed by 500 participants from Tamil Nadu. It includes 40,000 characters with 500 user variations. The results surpass or rival existing methods, demonstrating the effectiveness of the approach. The research also offers insights for developing advanced recognition systems for other complex scripts. Future investigations could explore the integration of deep learning techniques and the extension of the proposed approach to other Indic scripts and languages, advancing the field of handwritten character recognition.

• 한국식생활문화학회지
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• 제37권5호
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• pp.429-437
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• 2022

This study evaluated the quality of school milk programs and analyzed the relative importance of school milk program selection attributes using conjoint analysis. The survey was conducted on students from middle and high schools in metropolitan cities that provide school milk programs. Responses were received from 414 students and the data was subjected to frequency analysis, t-test, and conjoint analysis using the SPSS Statistics Package. While evaluating white milk in the school milk program, middle school students rated 'packaging condition' (4.23) the highest, high school students rated 'nutrition' (4.64) the highest, and their evaluation of all the quality attributes was significantly different from that of middle school students (p<0.001). Overall satisfaction scores too, showed a significant difference between high school (4.46) and middle school students (4.01) (p<0.001). Processed milk & dairy products had the highest satisfaction score in the attribute of 'serving time' (4.57). The relative importance of the choice attributes of the school milk program was in the order of 'number per item' (62.260%), 'temperature' (25.708%), and 'serving method' (12.032%) for all students. The school milk program most preferred by all students and middle school students was to provide milk at a refrigerated temperature, select white milk three times a week, processed milk, fermented milk, and cheese twice a week, and provide it at the desired time.

• International Journal of Internet, Broadcasting and Communication
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• 제9권4호
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• pp.51-58
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• 2017

This paper deals with the improvement of cluster head selection method in L-SEP for heterogeneous nodes among hierarchical routing protocols of wireless sensor network. Wireless sensor networks are classified into homogeneous and heterogeneous network. In heterogeneous network, SEP, L-SEP are mainly used because cluster head selection probability is different depending on node type. But, since protocol based on SEP has different cluster head selection probabilities depending on the node type, clusters that transmit data inefficiently can be formed. to improve this, it is necessary to select the cluster head that minimizes the transmission distance of member node and the cluster head. Therefore, we propose a protocol that improve the cluster head selection method.

• Industrial Engineering and Management Systems
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• 제8권1호
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• pp.47-53
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• 2009

We define product line (or mix) selection problem as selecting a subset of potential product variants that can simultaneously minimize product proliferation and maintain market coverage. Selecting the most efficient product mix is a complex problem, which requires analyses of multiple criteria. This paper proposes a method based on Data Envelopment Analysis (DEA) for product line selection. Data Envelopment Analysis (DEA) is a linear programming based technique commonly used for measuring the relative performance of a group of decision making units with multiple inputs and outputs. Although DEA has been proved to be an effective evaluation tool in many fields, it has not been applied to solve the product line selection problem. In this study, we construct a five-step method that systematically adopts DEA to solve a product line selection problem. We then apply the proposed method to an existing line of staplers to provide quantitative evidence for managers to generate desirable decisions to maximize the company profits while also fulfilling market demands.

• 한국콘텐츠학회논문지
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• 제21권2호
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• pp.374-385
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• 2021

본 연구의 목적은 학생부종합전형의 평가 요소와 기준에 대한 고등학교 교사와 학부모의 인식을 살펴보고 이를 통해 학생 역량을 보다 공정하고 정확하게 측정할 수 있는 대입 전형 개발의 기초 자료를 제공하는 것이다. 이를 위해 전국의 고등학교 교사 102명과 고등학생 자녀를 갖고 있는 68명의 학부모를 대상으로 온라인 설문을 실시하였다. 온라인 설문지는 J대학의 학생종합전형 기준을 바탕으로 제작되었으며, 크게 '서류평가', '면접평가', '기초설문'의 3영역으로 구성하였다. 이를 통해 얻은 결과는 다음과 같다. 첫째, 교사와 학부모 모두 학생생활기록부 중심의 학생부종합전형이 2015 개정 교육과정 운영의 활성화에 기여할 수 있는 대입전형이라고 응답하였다. 둘째, 교사와 학부모 모두 인성, 적성, 잠재력 모두 서류 평가와 면접 평가에서 중요한 요소라고 응답하였다. 셋째, 2015 개정 교육과정 활성화를 위해 학생부종합전형이 계속 유지되어야 하나 해당 전형의 공정성 확보가 선행되어야 함을 지적하였다. 마지막으로 연구 결과를 토대로 대입 전형 개선을 위한 제언을 제시하였다.

• 보건의료산업학회지
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• 제6권1호
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• pp.105-116
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• 2012

Some radiology majors at three-year colleges in Daegu and Gyeongsangbuk-Do Province were selected for the research. The survey was conducted by explaining its objectives and distributing the self-administered questionnaires from March 7 to 30, 2011; then, the final analysis was carried out on 122 copies, drawing the following conclusions : 1) 31.1% of the radiology majors were motivated to enter their department by good employment after graduation, and 37.7% were getting information from their parents or relatives in selecting their major. 2) The majority of the respondents wanted to get a job in a big city after graduation on the basis of good pay. 3) Department selection was significantly affected by transportation, department and school image, and school facilities, and the effects were higher among females. 4) Department satisfaction was significantly affected by professor satisfaction, prospects for the department, and support for employment activities, and the effects were higher among females. 5) School satisfaction was significantly affected by satisfaction with school selection decision, good selection, and school environment, and the effects were higher among females. 6) Females were found to have higher professional consciousness as a radiologist, showing statistically significant differences: "the occupation as a radiologist will continue to be developed" at $3.97{\pm}.837$ for males and at $4.55{\pm}.663$ for females and "the occupation as a radiologist is stable and will be help get a life-long job" at $3.82{\pm}.9.08$ for males and at $4.41{\pm}.787$ for females.