• Knowledge Management Research
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• v.6 no.2
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• pp.1-22
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• 2005

Knowledge is recognized as the most important asset among enterprises. Therefore, the necessity of knowledge management is ever on the increase nowadays. While many people have endeavored to develop knowledge storage, sharing and usage, knowledge creation is not sufficiently investigated for practical application, because knowledge creation is largely related to creativity and difficult to establish a systematic methodology. In order to overcome such problems, the creative knowledge creation model is proposed by using the whole brain theory and creative thinking tools. First of all, the creative knowledge creation model is based on the Nonaka's knowledge creation model integrated with the whole brain theory. The whole brain theory is then used as a standard to organize a whole brain team that is composed of members who have diverse thinking patterns. For creative thinking tools, the mandal-art and the contradiction matrix of TRIZ are used for a knowledge conversion. Each process of the creative knowledge creation model is sequentially suggested and several terms are defined. In order to verify the effectiveness of the creative knowledge creation model, the proposed model is applied to the development of a dishwasher with a new concept. According to the order of the proposed method, the model is applied twice in the cycle of spiral evolution. Three kinds of dish-washing methods have been developed using the proposed model. The results of the application are then analyzed and presented.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2193-2196
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• 1998

Cellular automata are dynamical systems in which space and time are discrete, where each cell has a finite number of states and updates its states by interactive rules among the cell-neighborhood. From the characteristics of self-reproduction and self- organization, it is possible to create a neural network which has the specific patterns or structures dynamically. CAM-Brain is a kind of such neural network system which evolves its structure by adopting evolutionary computations like genetic algorithms (GA). In this paper, we suggest the evolution strategies for the structure of neural networks based on cellular automata.

• Investigative Magnetic Resonance Imaging
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• v.17 no.4
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• pp.267-274
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• 2013

Purpose : To re-evaluate additional clinical significance of the apparent diffusion coefficient (ADC) map in the inference of infarction stage, authors studied the evolution patterns of the DWI and the ADC map of the brain infarction. Materials and Methods: In 127 patients with cerebral infarctions, including follow-up checks, 199 studies were performed. They were classified as hourly (117 studies)-, daily (108 studies)-, weekly (62 studies)-based groups. The signal intensity (SI) was measured at the core of the infarction and contralateral area with ROI of 0.3 $cm^2$ or more on the images of the DWI and the ADC map, and calculated the ratios of SI and ADC value of the infarction area / contralateral normal area, and compared the patterns of the change according to the evolution. Results: Infarction was detected as early as 1 hour after the attack, and the ratio of SI in the DWI became over than 2 after 12 hours, which showed a plateau until the 6th day. Thereafter, it decreased slowly to 1 on the 30th day, and changed to lower SI than the surrounding brain. The ratio in the ADC map became 0.46 in 24 hours after the attack, and increased slowly to 1 in the 15th day. Thereafter, it became a higher value than the surrounding brain. Overall, the ratio in the ADC map changed earlier than in the DWI, and the ratio curves showed inverse pattern each other according to the evolution of the infarction. Conclusion: The evolution patterns of infarction on the ADC map showed an inverse curve of DWI curve, which means that the ADC value is accurately predictable from DWI, and the ADC map joined with the DWI seems helpful in the determination of subacute infarction between 15 to 30 days.

• Asian Journal of Innovation and Policy
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• v.5 no.3
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• pp.330-342
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• 2016

This is an interview with Professor Kwang-Hyung Lee, founding Dean of KAIST Moon Soul Graduates School of Future Strategy and founder of the Department of Bio and Brain Engineering of the same university casting two questions about academics. The first question is what pattern is desirable in the evolution of research topics of an academics. While traditional researchers in science and engineering tend to focus on one subject in ever greater depth over time, Professor Lee's research agenda has spanned several new topics by gradually changing the content of the study: from artificial intelligence to bio and brain research, and to creativity development method, further to future study. The second question is about researchers' social responsibility. He has devoted to contributes to industry fields and the nation through academic activities as well as educating several successful business people, founding a new academic department and graduate school of future studies.

• Journal of Korean Philosophical Society
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• v.131
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• pp.131-163
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• 2014

This Paper aims to elaborate on the origin of thinking mind. And this is a cooperative project between philosophy and neuroscience and brain science. I have written this paper in admiration for the achievements of twentieth century neuroscience and brain science, and out of desire to assist the subject in future. Much of the history of modern philosophy, from Descartes and Kant forward, consists of failed models of brain. As Edward O. Wilson precisely said, the shortcoming is not the fault of the philosophers, who have doggedly pushed their methods to the limit, but a straightforward consequence of the biological evolution of the brain. Guiding that investigation down pathways that will illuminate brain research is a task of neuroscience and brain science. Investigating logical relations among concepts is a philosophical task. If we are to understand the neural structures and dynamics that make perception, thought, intentional behaviour possible, clarity about these concepts and categories and their relations is essential. Hence our joint venture of philosophy and science. Sure, it is human beings that perceives, not parts of its brain. And it is human beings that who think and reason, not their brain. But the brain and its activities make it possible for human beings-not for it-to perceive and think, to feel emotions, and to form and pursue projects. Thus We try to investigate and reveal the origin of thinking mind as follow: 1) The difference between chimpanzee and human beings 2) brain and mind 3) the origin of thinking 4) the wisdom of nature.

• STI Policy Review
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• v.1 no.2
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• pp.1-18
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• 2010

The development and maintenance of human capacity in economies is critical to long term competitiveness, but also for the overall health and environment of regions. Yet, human science and technology-based capacity is multidimensional and has interrelated characteristics which present certain policy challenges. This paper addresses a range of issues specific to a discussion on human capacity in S&T. First, the paper emphasizes the importance of acknowledging the complexity of human capacity issues and how they evolve along the STEM (science, technology, engineering, and mathematics) pipeline. The pipeline is an often used reference to describe the training and development in STEM disciplines, from early childhood education, to more advanced training, and finally to professional collaboration and interaction and serves as a useful organizing framework for the discussion of capacity along the career evolution process. Second, the paper offers an organizing framework for discussion of policy mechanisms that have been developed to address issues and gaps that occur along this STEM pipeline. Specifically, it contrasts the traditional mechanisms of building human capacity in STEM areas with newer "gap filling" and integrated approached to addressed human capacity disparities and priorities. Third, the paper addresses core challenges in human capacity in STEM, including the education and training, participation of women and underrepresented groups, brain drain/brain circulation issues, and the globalization of science. The paper concludes with a discussion of policy implication for the development of human capacity.

• Molecules and Cells
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• v.25 no.3
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• pp.323-331
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• 2008

Plants are continually exposed to a variety of potentially pathogenic microbes, and the interactions between plants and pathogenic invaders determine the outcome, disease or disease resistance. To defend themselves, plants have developed a sophisticated immune system. Unlike animals, however, they do not have specialized immune cells and, thus all plant cells appear to have the innate ability to recognize pathogens and turn on an appropriate defense response. Using genetic, genomic and biochemical methods, tremendous advances have been made in understanding how plants recognize pathogens and mount effective defenses. The primary immune response is induced by microbe-associated molecular patterns (MAMPs). MAMP receptors recognize the presence of probable pathogens and evoke defense. In the co-evolution of plant-microbe interactions, pathogens gained the ability to make and deliver effector proteins to suppress MAMP-induced defense responses. In response to effector proteins, plants acquired R-proteins to directly or indirectly monitor the presence of effector proteins and activate an effective defense response. In this review we will describe and discuss the plant immune responses induced by two types of elicitors, PAMPs and effector proteins.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.707-712
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• 1998

This paper presents several softcomputing techniques such as neural networks, fuzzy logic and genetic algorithms : Neural networks as brain metaphor provide fundamental structure, fuzzy logic gives a possibility to utilize top-down knowledge from designer, and genetic algorithms as evolution metaphor determine several system parameters with the process of bottom up development. With these techniques, we develop a pattern recognizer which consists of multiple neural networks aggregated by fuzzy integral in which genetic algorithms determine the fuzzy density values. The experimental results with the problem of recognizing totally unconstrained handwritten numeral show that the performance of the proposed method is superior to that of conventional methods.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.11_12
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• pp.682-691
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• 2005

We present a two-step evolution system that produces controllable virtual creatures in physically simulated 3D environment. Previous evolutionary methods for virtual creatures did not allow any user intervention during evolution process, because they generated a creature's shape, locomotion, and high-level behaviors such as target-following and obstacle avoidance simultaneously by one-time evolution process. In this work, we divide a single system into manageable two sub-systems, and this more likely allowsuser interaction. In the first stage, a body structure and low-level motor controllers of a creature for straight movement are generated by an evolutionary algorithm. Next, a high-level control to follow a given path is achieved by a neural network. The connection weights of the neural network are optimized by a genetic algorithm. The evolved controller could follow any given path fairly well. Moreover, users can choose or abort creatures according to their taste before the entire evolution process is finished. This paper also presents a new sinusoidal controller and a simplified hydrodynamics model for a capped-cylinder, which is the basic body primitive of a creature.

• Journal of Korean Neurosurgical Society
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• v.58 no.4
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• pp.379-384
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• 2015

Objective : To investigate the risks and pattern of evolution of peritumoral brain edema (PTE) after stereotactic radiosurgery (SRS) for asymptomatic intracranial meningiomas. Methods : A retrospective study was conducted on 320 patients (median age 56 years, range 24-87 years) who underwent primary Gamma Knife radiosurgery for asymptomatic meningiomas between 1998 and 2012. The median tumor volume was 2.7 cc (range 0.2-10.5 cc) and the median follow-up was 48 months (range 24-168 months). Volumetric data sets for tumors and PTE on serial MRIs were analyzed. The edema index (EI) was defined as the ratio of the volume of PTE including tumor to the tumor volume, and the relative edema indices (rEIs) were calculated from serial EIs normalized against the baseline EI. Risk factors for PTE were analyzed using logistic regression. Results : Newly developed or increased PTE was noted in 49 patients (15.3%), among whom it was symptomatic in 28 patients (8.8%). Tumor volume larger than 4.2 cc (p<0.001), hemispheric tumor location (p=0.005), and pre-treatment PTE (p<0.001) were associated with an increased risk of PTE. rEI reached its maximum value at 11 months after SRS and decreased thereafter, and symptoms resolved within 24 months in most patients (85.7%). Conclusion : Caution should be exercised in decision-making on SRS for asymptomatic meningiomas of large volume (>4.2 cc), of hemispheric location, or with pre-treatment PTE. PTE usually develops within months, reaches its maximum degree until a year, and resolves within 2 years after SRS.