• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2296-2298
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• 1998

In this paper, an on-chip learning pulse-mode digital neural network with a massively parallel yet compact and flexible network architecture is suggested. Algebraic neural operations are replaced by stochastic processes using pseudo-random sequences and simple logic gates are used as basic computing elements. Using Back-propagation algorithm both feed-forward and learning phases are efficiently implemented with simple logical gates. RNG architecture using LFSR and barrel shifter are adopted to avoid some correlation between pulse trains. Suggested network is designed in digital circuit and its performance is verified by computer simulation.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.357-366
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• 2022

Artificial intelligence (AI) is the replication of human intelligence by computer systems and machines using tools like machine learning, deep learning, expert systems, and natural language processing. AI can be applied in administrative settings to automate repetitive processes, analyze and forecast data, foster social communication skills among staff, reduce costs, and boost overall operational effectiveness. In order to understand how AI is being used for administrative duties in various organizations, this paper gives a critical dialogue on the topic and proposed a framework for using artificial intelligence in organizations. Additionally, it offers a list of specifications, attributes, and requirements that organizations planning to use AI should consider.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.29-29
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• 2023

To mitigate the damaging impacts of floods, accurate prediction of runoff, streamflow and flood inundation is needed. Conventional approach of simulating hydrology and hydraulics using loosely coupled models cannot capture the complex dynamics of surface and sub-surface processes. Additionally, the scarcity of data in ungauged basins and quality of data in gauged basins add uncertainty to model predictions, which need to be quantified. In this presentation, first the role of integrated modeling on creating accurate flood simulations and inundation maps will be presented with specific focus on urban environments. Next, the use of machine learning in producing streamflow predictions will be presented with specific focus on incorporating covariate shift and the application of theory guided machine learning. Finally, a framework to quantify the uncertainty in flood models using Hierarchical Bayesian Modeling Averaging will be presented. Overall, this presentation will highlight that creating accurate information on flood magnitude and extent requires innovation and advancement in different aspects related to hydrologic predictions.

• Educational Technology International
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• v.10 no.2
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• pp.29-61
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• 2009

The purpose of this study was to design an inquiry supporting tool on wiki based collaborative learning and to investigate the effect of the inquiry supporting tool. Eight design principles were selected and more specified design strategies were made from the literatures. The first system with the first-round design principles was developed and implemented in an actual classroom. After the first field study, researcher found a few drawbacks of the system. The second system was implemented in the classroom again. Finally developed wiki-based inquiry supporting tool system is unique in that it allows instructors to design their own CSCL inquiry activities, and it has intuitive menu tabs showing inquiry learning processes.

• Journal of the Semiconductor & Display Technology
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• v.23 no.2
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• pp.135-142
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• 2024

Cu-Cu bonding, one of the key technologies in advanced packaging, enhances semiconductor chip performance, miniaturization, and energy efficiency by facilitating rapid data transfer and low power consumption. However, the quality of the interface bonding can significantly impact overall bond quality, necessitating strategies to quickly detect and classify in-process defects. This study presents a methodology for detecting defects in wafer junction areas from Scanning Acoustic Microscopy images using a ResNet-50 based deep learning model. Additionally, the use of the defect map is proposed to rapidly inspect and categorize defects occurring during the Cu-Cu bonding process, thereby improving yield and productivity in semiconductor manufacturing.

• Journal of The Korean Association For Science Education
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• v.20 no.1
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• pp.174-182
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• 2000

In this study, the effects of grouping by communication apprehension level in cooperative learning strategy applied to general science class and the difference between high and low communication apprehension levels were investigated. Three classes (N=112) were randomly assigned to two cooperative and one traditional learning groups. Students in two cooperative learning classes were grouped into homogeneous and heterogeneous groups with respect to their communication apprehension levels based on the test score of students' communication apprehension. After the instructions concerning the matter for 11 class hours, achievement, self-esteem, motivation to learn science. and student's perception to lack about communication ability and expectation about receiving help in cooperative learning processes were examined. Two-way ANOVA results revealed that there were no main and interactive effects in the scores of the achievement test. However, significant main effect of the treatment was found in the scores of the relevance and the satisfaction among four motivation sub-categories. In post-hoc comparison, the scores of the heterogeneous group were found to be significantly higher than those of the control group. For expectation about receiving help in cooperative learning processes, the scores of the heterogeneous group were significantly higher than those of the homogeneous group. Students in high communication apprehension level had significantly lower self-esteem and more perception to lack about communication ability than students in low level.

• The Mathematical Education
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• v.44 no.2 s.109
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• pp.159-167
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• 2005

As the 7th mathematics curriculum reform in Korea was implemented with its goal based on Freudenthal's perspectives on mathematization theory, the research on the effect of mathematization has been become more significant. The purpose of this thesis is not only to find whether this foreign theory would be also applied effectively into our educational practice in Korea, but also to investigate how much important role teachers should play in their teaching students, in order that students accomplish the process of mathematization more effectively. Two case studies were carried out with two groups of middle-school students using qualitative-research method with the research instrument designed by the researcher. It was found that we could get the possibility of being able to apply effectively this theory even to our educational practice since the students engaged in their mathematization using the horizontal mathematization and the vertical mathematization in geometry. Also, it was mentioned that teachers' role was so important in guiding students' processes of mathematization, although mathematization is the teaching-learning theory, stimulating students' activities. Since the Freudenthal's mathematization applied in the thesis is so meaningful in our educational practice, we need more various research about this theory that helps students develope their mathematical thinking.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.57-60
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• 1999

An optimal control technique designed for simultaneous tracking and quality control for batch processes. The proposed technique is designed by transforming quadratic-criterion based iterative learning control(Q-ILC) into linear quadratic control problem. For real-time quality inferential control, the quality is modeled by linear combination of control input around target qualify and then the relationship between quality and control input can be transformed into time-varying linear state space model. With this state space model, the real-time quality inferential control can be incorporated to LQ control Problem. As a consequence, both the quality variable as well as other controlled variables can progressively reduce their control error as the batch number increases while rejecting real-time disturbances, and finally reach the best achievable states dictated by a quadratic criterion even in case that there is significant model error Also the computational burden is much reduced since the most computation is calculated in off-line. The Proposed control technique is applied to a semi-batch reactor model where series-parallelreactions take place.

• Proceedings of the Technology Innovation Conference
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• 1998.06a
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• pp.57-90
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• 1998

This study attempts to explore the evolution paths of Korean SMEs'strategies and their technological teaming processes. Several different evolution paths are identified based on a dynamic strategic group analysis of 115 SMEs'strategy in the Korean electronic component industry for the period of 1990-1995. Further, inadept case analyses on technological learning processes in 5 firms are undertaken. Major findings of this study can be summarized as follows : 1) There are three dominant evolution paths in SMEs'strategy. First path indicates the evolution from a subcontractor or petty imitator group(a strategic group with the narrow product/market domain and the low level of accumulated resource/capabilities) into an innovator group(a strategic group with the narrow domain but high level of technological capability) by accumulating technological capabilities. Second, some firms move from a subcontractor group into a generalizer group(a strategic group with broad product/market domain but relatively low level of technological capability) by simply adding product lines. Third path involves firms which evolve from a subcontractor group into a production focus group(a strategic group with high level of production capability) by investing in production capabilities. 2) An in-depth case analysis shows those who succeeded in technological learning are managed by CEOs, who have technological expertise and strategic vision, and have made an effort to establish management practices to support innovation, such employee educational program, performance-based reward system, etc. The successful firms also aggressively pursue diverse external linkages with outside technology sources to learn product and process technologies. Fiendly, this study discusses several implications of the findings for the theoretical development and strategic management of small firms in Korea.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.4
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• pp.666-683
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• 2023

This research aims to develop based clothing design process tailored to the industry-university collaborative setting and apply it in a fashion design class. into three distinct phases: designing and organizing our fashion design class, conducting our class at a university, and gathering student feedback. First, we conducted a literature review on employing new technologies in traditional clothing design processes. We consulted with industry professionals from the Samsung C&T Fashion Group to develop an AI-based clothing design process. We then developed in-class learning activities that leveraged fashion brand product databases, a supervised learning AI model, and operating an AI-based Creativity Support Tool (CST). Next, we setup an industry-university fashion design class at a university in South Korea. Finally, we obtained feedback from undergraduate students who participated in the class. The survey results showed a satisfaction level of 4.7 out of 5. The evaluations confirmed that the instructional methods, communication, faculty, and student interactions within the class were both adequate and appropriate. These research findings highlighted that our AI-based clothing design process applied within the fashion design class led to valuable data-driven convergent thinking and technical experience beyond that of traditional clothing design processes.