• Asian-Australasian Journal of Animal Sciences
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• v.30 no.9
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• pp.1215-1224
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• 2017

Objective: To assess the differences in ovarian transcriptomes in Shan Ma ducks between their peak and late stages of egg production, and to obtain new transcriptomic data of these egg-producing ducks. Methods: The Illumina HiSeq 2000 system was used for high throughput sequencing of ovarian transcriptomes from Shan Ma ducks at their peak or late stages of egg production. Results: Greater than 93% of the sequencing data had a base quality score (Q score) that was not less than 20 (Q20). From ducks at their peak stage of egg production, 42,782,676 reads were obtained, with 4,307,499,083 bp sequenced. From ducks at their late stage of egg production, 45,316,166 reads were obtained, with 4,562,063,363 bp sequenced. A comparison of the two datasets identified 2,002 differentially expressed genes, with 790 upregulated and 1,212 downregulated. Further analysis showed that 1,645 of the 2,002 differentially expressed genes were annotated in the non-redundant (NR) database, with 646 upregulated and 999 downregulated. Among the differentially expressed genes with annotations in the NR database, 696 genes were functionally annotated in the clusters of orthologous groups of proteins database, involving 25 functional categories. One thousand two hundred four of the differentially expressed genes with annotations in the NR database were functionally annotated in the gene ontology (GO) database, and could be divided into three domains and 56 categories. The three domains were cellular component, molecular function, and biological process. Among the genes identified in the GO database, 451 are involved in development and reproduction. Analysis of the differentially expressed genes with annotations in the NR database against the Kyoto encyclopedia of genes and genomes database revealed that 446 of the genes could be assigned to 175 metabolic pathways, of which the peroxisome proliferator-activated receptor signaling pathway, insulin signaling pathway, fructose and mannose metabolic pathways, gonadotropin releasing hormone signaling pathway and transforming growth factor beta signaling pathway were significantly enriched. Conclusion: The differences in ovarian transcriptomes in Shan Ma ducks between their peak and late stages of egg production were elucidated, which greatly enriched the ovarian transcriptomic information of egg-producing ducks.

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.357-367
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• 2012

This paper presents a two-stage methodology for anomaly detection from hyperspectral imagery that consists of transform-based feature extraction and selection, and computation of a local spatial auto-correlation statistic. First, principal component transform and 3D wavelet transform are applied to reduce redundant spectral information from hyperspectral imagery. Then feature selection based on global skewness and the portion of highly skewed sub-areas is followed to find optimal features for anomaly detection. Finally, a local indicator of spatial association (LISA) statistic is computed to account for both spectral and spatial information unlike traditional anomaly detection methodology based only on spectral information. An experiment using airborne CASI imagery is carried out to illustrate the applicability of the proposed anomaly detection methodology. From the experiments, anomaly detection based on the LISA statistic linked with the selection of optimal features outperformed both the traditional RX detector which uses only spectral information, and the case using major principal components with large eigen-values. The combination of low- and high-frequency components by 3D wavelet transform showed the best detection capability, compared with the case using optimal features selected from principal components.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.145-155
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• 2013

In this paper, we proposed a $4{\times}4$ block parallel architecture of interpolation for high-performance H.264/AVC Fractional Motion Estimation in 8K UHD($7680{\times}4320$) video real time processing. To improve throughput, we design $4{\times}4$ block parallel interpolation. For supplying the $10{\times}10$ reference data for interpolation, we design 2D cache buffer which consists of the $10{\times}10$ memory arrays. We minimize redundant storage of the reference pixel by applying the Search Area Stripe Reuse scheme(SASR), and implement high-speed plane interpolator with 3-stage pipeline(Horizontal Vertical 1/2 interpolation, Diagonal 1/2 interpolation, 1/4 interpolation). The proposed architecture was simulated in 0.13um standard cell library. The gate count is 436.5Kgates. The proposed H.264/AVC Fractional Motion Estimation can support 8K UHD at 30 frames per second by running at 187MHz.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.102-111
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• 2013

In this paper, we proposed a $4{\times}4$ block parallel architecture of interpolation for high-performance H.264/AVC Motion Compensation in 4K UHD($3840{\times}2160$) video real time processing. To improve throughput, we design $4{\times}4$ block parallel interpolation. For supplying the $9{\times}9$ reference data for interpolation, we design 2D cache buffer which consists of the $9{\times}9$ memory arrays. We minimize redundant storage of the reference pixel by applying the Search Area Stripe Reuse scheme(SASR), and implement high-speed plane interpolator with 3-stage pipeline(Horizontal Vertical 1/2 interpolation, Diagonal 1/2 interpolation, 1/4 interpolation). The proposed architecture was simulated in 0.13um standard cell library. The maximum operation frequency is 150MHz. The gate count is 161Kgates. The proposed H.264/AVC Motion Compensation can support 4K UHD at 72 frames per second by running at 150MHz.

• Horticultural Science & Technology
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• v.31 no.5
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• pp.598-606
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• 2013

Anther is the major organ of flower in responsible to reproduction and outward appearance. From anther-specific cDNA library of Lilium Oriental Hybrid 'Acapulco', 2000 expressed sequence tags were selected randomly. Differential slot blot analysis with cDNA probes from the anther and leaf was used to get anther-expressed clone and 570 non-redundant ESTs were obtained and sequenced. Compared to the GenBank database using BLASTX algorithm, 191 clones showed significant similarity but others (66.5%) did not measured to known sequence. Functional categories according to gene ontology (GO) annotation included sequence representing a significant portion of protein in cell and cell part respectively. A transcriptional analysis at 7 different organs and developmental stage was performed using northern blot with thirty ESTs as putative anther specific gene. This report suggest that selection of anther expressed clone using differential slot blot was considered as very effective tool and our current study can provide fundamental information on the lily anther including pollen furthermore.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.57-70
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• 2023

The investigation delved into 457 pieces of scholarly work, encompassing articles, published theses, and dissertations from the National Research Foundation of Korea, spanning the period of the 1997 IMF financial crisis up to 2022. The materials were sourced using terms such as 'angel investment', 'angel investor', and 'angel investment attraction'. The initial phase involved filtering out redundant entries from the preliminary collection of 267 works, leaving aside pieces that didn't pertain directly to angel investment as indicated in their abstracts. The next stage of the analysis involved a more rigorous selection process. Out of 43 papers earmarked in the preceding cut, only 32 were chosen. The criteria for this focused on the exclusion of conference presentations, articles that were either not submitted or inconclusive, and those that duplicated content under different titles. The final selection of 32 papers underwent a thorough systematic literature review. These documents, all pertinent to angel investment in South Korea, were scrutinized under five distinct categories: 1) publication year, 2) themes of research, 3) strategies employed in the studies, 4) participants involved in the research, and 5) methods of research utilized. This meticulous process illuminated the existing landscape of angel investment studies within Korea. Moreover, this study pinpointed gaps in the current body of research, offering guidance on future scholarly directions and proposing social scientific theories to further enrich the field of angel investment studies and analysis also seeks to pinpoint which areas require additional exploration to energize the field of angel investment moving forward. Through a comprehensive review of literature, this research intends to validate the establishment of future research trajectories and pinpoint areas that are currently and relatively underexplored in Korea's angel investment research stream. This study revealed that current research on domestic angel investment is concentrated on several areas: 1) the traits of angel investors, 2) the motivations behind angel investing, 3) startup ventures, 4) relevant institutions and policies, and 5) the various forms of angel investments. It was determined that there is a need to broaden the scope of research to aid in enhancing and stimulating the scale of domestic angel investing. This includes research into performance analysis of angel investments and detailed case studies in the field. Furthermore, the study emphasizes the importance of diversifying research efforts. Instead of solely focusing on specific factors like investment types, startups, accelerators, venture capital, and regulatory frameworks, there is a call for research that explores a variety of associated variables. These include aspects related to crowdfunding and return on investment in the context of angel investing, ensuring a more holistic approach to research in this domain. Specifically, there's a clear need for more detailed studies focusing on the relationships with variables that serve as dependent variables influencing the outcomes of angel investments. Moreover, it's essential to invigorate both qualitative and quantitative research that delves into the theoretical framework from multiple perspectives. This involves analyzing the structure of variables that have an impact on angel investments and the decisions surrounding these investments, thereby enriching the theoretical foundation of this field. Finally, we presented the direction of development for future research by confirming that the effect on the completeness of the business plan is high or low depending on the satisfaction of the entrepreneurs in addition to the components.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.67-88
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• 2018

Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.