• STI Policy Review
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• 제7권1호
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• pp.1-16
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• 2016

Technology supply has been the main thrust of the Korean government's science & technology policy, focusing on the development and acquisition of new technology in line with the catching-up strategy of economic growth and industrial development. However, new social or societal problems have become major government policy issues, heralding new innovation policy aimed to address them. Such new policy initiatives for social problem-solving present a niche where the existing system of government innovation policy process is challenged, including such processes as goal-setting, planning, implementation, project management, and evaluation. The rigidity of the existing institution of government innovation policy, however, still shapes the content and progression of innovation policy for social problem-solving. This study reviews Korean innovation policy for social problem-solving as a policy niche, and aims to clarify its challenges and opportunities. It uses a system transition framework to explain the emergence and evolution of the innovation policy niche in Korea. The main research question is to what extent and in what aspect the existing innovation policy regime shaped innovation policy for social problem-solving. The study examines the inertia of the current paradigm of innovation policies and R&D programs, and sheds light on the search for a distinctive identity for innovation policies that tackles social problems.

• Mycobiology
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• 제42권2호
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• pp.100-108
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• 2014

Twelve plant species were collected from the east coast of Korea to identify culturable endophytes present in their roots. The fungal internal transcribe spacer (ITS) region (ITS1-5.8SrRNA-ITS2) was used as a DNA barcode for identification of fungi. A total of 194 fungal strains were identified and categorized into 31 genera. The genus Penicillium accounted for the largest number of strains, followed by the genus Aspergillus. Furthermore, using 5 statistical methods, the diversity indices of the fungi were calculated at the genus level. After comprehensive evaluation, the endophytic fungal group from Phragmites australis ranked highest in diversity analyses. Several strains responsible for plant growth and survival (Penicillium citrinum, P. funiculosum, P. janthinellum, P. restrictum, and P. simplicissimum), were also identified. This study provides basic data on the sheds light on the symbiotic relationship between coastal plants and fungi.

• Asian Journal of Innovation and Policy
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• 제9권1호
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• pp.12-35
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• 2020

Quality performance information has been regarded as a significant step toward managing public performance. Although a correlation between the quality of information and its actual usage among managers in high-accountability policy areas has been found, quality performance information has not been properly provided to practitioners. This study takes an Institutional Analysis and Development approach to assess an appropriate institutional framework that facilitates state agencies and academics to coproduce this information. Based on a conceptual framework, we analyze a public information system of the Workforce Data Quality Initiative in Ohio and carry out a content analysis with NVIVO. It is found that arrangements that can manage the incentive dynamic in this process may help to align heterogeneous stakeholders in a mutually supportive fashion. Also, the research agenda and information resulted from being coproduced for management and academic purposes, simultaneously. This use of administrative data sheds light on how quality performance information can be coproduced under an appropriate institutional arrangement between administration and research communities. It is suggested that accessibility to the information system among various stakeholders should be improved.

• 미술이론과 현장
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• 제10호
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• pp.85-103
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• 2010

Mona Hatoum and community make unlikely bedfellows. From her beginnings as a teenage exile to her maturity as an internationally celebrated artistic nomad, Hatoum defies classification within any single geographical or cultural community. Attempting, however, to locate specific points of contact between her and certain communities in terms of artist-in-residence projects in which she participated might be a particularly fruitful way of circumventing her notorious critical resistance to identity and her refusal of homogeneity. This paper starts with Miwon Kwon's critique of contemporary practices in community-based art, which locate an essentialising force that isolates a single point of commonality and overlooks authentic differences. It then turns to Jean-Luc Nancy's reconceptualization of community as 'unworked' and 'being-in-common' to provide analytical tools for avoiding the dangers of essentialism. By examining the three residencies that Hatoum accepted in the mid-1990s in the light of Nancy's observations and theories, and by bringing the idea of artistic nomadism and that of community into juxtaposition, we hope to show that Hatoum succeeds in finding an equilibrium between art and community, and that this sheds new light on the issues raised in recent discussions on such relationship.

• 한국정보시스템학회지:정보시스템연구
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• 제27권3호
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• pp.63-80
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• 2018

Purpose The purpose of this study is to build a machine learning-based customer classification model to promote customer expansion effect of the free sample promotion. Specifically, the proposed model classifies potential target customers who are expected to purchase the products included in the free sample promotion after receiving the free samples. Design/methodology/approach This study proposes to build a customer classification model for determining customers suitable for providing free samples by using various machine learning techniques such as logistic regression, multiple discriminant analysis, case-based reasoning, decision tree, artificial neural network, and support vector machine. To validate the usefulness of the proposed model, we apply it to a real-world free sample-based target marketing case of a Korean major cosmetic retail company. Findings Experimental results show that a machine learning-based customer classification model presents satisfactory accuracy ranging from 70% to 75%. In particular, support vector machine is found to be the most effective machine learning technique for free sample-based target marketing model. Our study sheds a light on customer relationship management strategies using free sample promotions.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2003년도 International Meeting on Information Display
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• pp.21-24
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• 2003

The understanding of the mechanism of device degradation has been accomplished recently, for devices using $AlQ_3$ electron transport and emitter molecule. In this presentation the experimental evidence for the degradation mechanism of $AlQ_3$ based devices will be reviewed, showing that the hypothesis of an unstable $AlQ_3^+$ cation explains a large amount of experimental data. This hypothesis, however, explains not only the room temperature device degradation in time but also sheds light on temperature stability of OLEDs. Dependence of half-life of a series of devices with an emitter layer composed of a mixture of $AlQ_3$ and different hole transport molecules (mixed emitter layer) will be discussed when they are operated at elevated temperatures. These results can also be explained in the framework of an unstable $AlQ_3^+$ species. An OLED structure containing a doped mixed emitter layer will be described, which shows extraordinary stability, half-life of 1200 hours at operating temperature of 70 C and initial luminance of 1650 $cd/m^2$. We will also discuss a novel Black $Cathode^{TM}$ OLED with reduced optical reflectivity, which is also stable at elevated temperatures. The new cathode utilizes a conductive light-absorbing layer made of a mixture of metals and organic materials.

• BMB Reports
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• 제48권8호
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• pp.473-478
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• 2015

The NEK6 (NIMA-related kinases 6) is reported to play po-tential roles in tumorigenesis. Although it is suggested to function in several cellular pathways, the underlying mechanism in tumorigenesis is still largely unknown. In the present study, we discovered interaction of NEK6 with Smad4, a key member of transforming growth factor beta (TGFβ) pathway. Over-expression of NEK6 in hepatocellular carcinoma (HCC) cell lines suppresses TGFβ-mediated transcription activity in a kinase activity-dependent manner. In addition, NEK6 suppresses the cell growth arrest induced by TGFβ. Mechanically, NEK6 blocks nuclear translocation of Smad4, which is essential for TGFβ function. Moreover, we identified that NEK6 could be regulated by TGFβ and hypoxia. Our study sheds new light on the roles of NEK6 in canonical TGFβ/Smad pathway and tum-origenesis. [BMB Reports 2015; 48(8): 473-478]

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2003년도 The Fifth Asian Computational Fluid Dynamics Conference
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• pp.294-298
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• 2003

The complex, unsteady, self-sustained pressure oscillations induced by supersonic flow past a rectangular cavity is investigated using numerical simulations. The present numerical study is performed using a parallel, multiblock solver for the two-dimensional, compressible Navier­Stokes equations. Open cavities with length-to-depth (L / D) ratio in the range 0.5 - 3.3 are considered. This paper sheds light on the cavity physics, cavity oscillatory mechanism, and the organisation of vortical structures inside the cavity. The vortex shedding phenomenon, the shear layer impingement event at the aft wall and the movement of the acoustic/compression wave within the cavity are well predicted. The vortical structures· and the source of the acoustic disturbances are found to be located near the aft wall of the cavity. With the increase in the cavity length, strong recompression of the flow near the aft wall leading to a sudden jump in the cavity form drag is observed. The estimated cavity tones are in good agreement with the available semi­empirical relation. Multiple peaks are noticed in deep and long cavities. For the present free­stream Mach number 1.71, it is observed that around L/D=2.0, the cavity oscillatory mechanism changes from the transverse to longitudinal oscillatory mode. The effects of this transition on various fluid dynamics and acoustic properties are also discussed.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2008년도 춘계학술대회논문집
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• pp.476-479
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• 2008

Understanding the dynamics of proteins is essential to gain insight into biological functions of proteins. The protein dynamics is delineated by conformational fluctuation (i.e. thermal vibration), and thus, thermal vibration of proteins has to be understood. In this paper, a simple mechanical model was considered for understanding protein's dynamics. Specifically, a mechanical vibration model was developed for understanding the large protein dynamics related to biological functions. The mechanical model for large proteins was constructed based on simple elastic model (i.e. Tirion's elastic model) and model reduction methods (dynamic model condensation). The large protein structure was described by minimal degrees of freedom on the basis of model reduction method that allows one to transform the refined structure into the coarse-grained structure. In this model, it is shown that a simple reduced model is able to reproduce the thermal fluctuation behavior of proteins qualitatively comparable to original molecular model. Moreover, the protein's dynamic behavior such as collective dynamics is well depicted by a simple reduced mechanical model. This sheds light on that the model reduction may provide the information about large protein dynamics, and consequently, the biological functions of large proteins.

• 제어로봇시스템학회논문지
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• 제6권3호
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• pp.273-283
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• 2000

In this paper we suggest an optimal design method of Fuzzy-Neural Networks(FNN) model for complex and nonlinear systems. The FNNs use the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. And we use a HCM(Hard C-Means) Clustering Algorithm to find initial parameters of the membership function. The parameters such as parameters of membership functions learning rates and momentum weighted value is proposed to achieve a sound balance between approximation and generalization abilities of the model. According to selection and adjustment of a weighting factor of an aggregate objective function which depends on the number of data and a certain degree of nonlinearity (distribution of I/O data we show that it is available and effective to design and optimal FNN model structure with a mutual balance and dependency between approximation and generalization abilities. This methodology sheds light on the role and impact of different parameters of the model on its performance (especially the mapping and predicting capabilities of the rule based computing). To evaluate the performance of the proposed model we use the time series data for gas furnace the data of sewage treatment process and traffic route choice process.