• Journal of Electrochemical Science and Technology
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• v.10 no.3
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• pp.329-334
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• 2019

Sn-Cu alloy powders were prepared via a simple chemical reduction method for the negative electrode materials in lithiumion batteries. The addition of Cu can suppress the growth of Sn particles during synthetic process. Furthermore, the Cu also acts as a matrix phase against the volume change during cycling. With increasing amount of the Cu, a stable $Cu_6Sn_5$ phase formed in the Sn-Cu alloy and its cycle performance greatly enhanced depending on the Cu content. To promote the generation of the $Cu_6Sn_5$ phase, the synthesis temperature is raised to $60-100^{\circ}C$ from the ambient temperature. The Sn-Cu alloy powders prepared at elevated temperatures showed remarkable cycle performances. The Sn-Cu alloy powder obtained at $60^{\circ}C$ exhibited a significantly high volumetric capacity of over 2,000 mAh/cc at the 50th cycle.

• Safety and Health at Work
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• v.12 no.1
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• pp.1-9
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• 2021

This review article addresses the role of safety professionals in the diffusion strategies for predictive analytics for safety performance. The article explores the models, definitions, roles, and relationships of safety professionals in knowledge application, access, management, and leadership in safety analytics. The article addresses challenges safety professionals face when integrating safety analytics in organizational settings in four operations areas: application, technology, management, and strategy. A review of existing conventional safety data sources (safety data, internal data, external data, and context data) is briefly summarized as a baseline. For each of these data sources, the article points out how emerging analytic data sources (such as Industry 4.0 and the Internet of Things) broaden and challenge the scope of work and operational roles throughout an organization. In doing so, the article defines four perspectives on the integration of predictive analytics into organizational safety practice: the programmatic perspective, the technological perspective, the sociocultural perspective, and knowledge-organization perspective. The article posits a four-level, organizational knowledge-skills-abilities matrix for analytics integration, indicating key organizational capacities needed for each area. The work shows the benefits of organizational alignment, clear stakeholder categorization, and the ability to predict future safety performance.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.505-509
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• 2020

Twitter is a useful medium to grasp various damage situations that have occurred in society. However, it is a laborious task to spot damage-related topics according to time in the environment where information is constantly produced. This paper proposes a methodology of constructing a knowledge structure by combining the BERT-based classifier and the community detection techniques to discover the topics underlain in the damage information. The methodology consists of two steps. In the first step, the tweets are classified into the classes that are related to human damage, infrastructure damage, and industrial activity damage by a BERT-based transfer learning approach. In the second step, networks of the words that appear in the damage-related tweets are constructed based on the co-occurrence matrix. The derived networks are partitioned by maximizing the modularity to reveal the hidden topics. Five keywords with high values of degree centrality are selected to interpret the topics. The proposed methodology is validated with the Hurricane Harvey test data.

• Clinical and Experimental Pediatrics
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• v.53 no.7
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• pp.735-740
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• 2010

Renal fibrosis, characterized by tubulointerstitial fibrosis and glomerulosclerosis, is the final manifestation of chronic kidney disease. Renal fibrosis is characterized by an excessive accumulation and deposition of extracellular matrix components. This pathologic result usually originates from both underlying complicated cellular activities such as epithelial-to-mesenchymal transition, fibroblast activation, monocyte/macrophage infiltration, and cellular apoptosis and the activation of signaling molecules such as transforming growth factor beta and angiotensin II. However, because the pathogenesis of renal fibrosis is extremely complicated and our knowledge regarding this condition is still limited, further studies are needed.

• Honam Mathematical Journal
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• v.30 no.2
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• pp.311-321
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• 2008

Mathematical paradoxes may arise when computations give unexpected results. We use three paradoxes to illustrate how they work in the basic probability theory. In the process of resolving the paradoxes, we expect that student-teachers can pedagogically gain valuable experience in regards to sharpening their mathematical knowledge and critical reasoning.

• Biotechnology and Bioprocess Engineering:BBE
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• v.10 no.5
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• pp.400-407
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• 2005

Reverse engineering is defined as the process where the internal structures and dynamics of a given system are inferred and analyzed from external observations and relevant knowledge. The first part of this paper surveys existing techniques for biosystem reverse engineering. Network structure inference techniques such as Correlation Matrix Construction (CMC), Boolean network and Bayesian network-based methods are explained. After the numeric and logical simulation techniques are briefly described, several representative working software tools were introduced. The second part presents our component-based software architecture for biosystem reverse engineering. After three design principles are established, a loosely coupled federation architecture consisting of 11 autonomous components is proposed along with their respective functions.

• 한국경영정보학회:학술대회논문집
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• 2007.06a
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• pp.571-575
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• 2007

For better predictions and classifications in customer recommendation, this study proposes an integrative model that efficiently combines the currently-in-use statistical and artificial intelligence models. In particular, by integrating the models such as Association Rule, Connection Frequency Matrix, and Rule Induction, this study suggests an integrative prediction model.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.3
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• pp.316-325
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• 1991

This paper presents the design of a new sliding mode controller to improve the rate of convergence by Lyapunov's stability analysis. The proposed controller shows that the elimination of the steady state position errors can be achieved by replacing the desired trajectory by the virtual reference trajectory. The proposed control scheme which consists of the upper bounded and estimated values of eac term of the manipulator dynamic equation does not require good knowledge of the parameters and the computation of matrix inversion. The performance of proposed controller is evaluated by the simulation for a two-link manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.127-130
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• 1990

The fuzzy logic controller which can be applied to various industrial processes is quite often dependent on the heuristics of the experienced operator. The operator's knowledge is often uncertain. Therefore an incorrect control rule on the basis of the operator's information is a cause of bad performance of the system. This paper proposes a new self-learning fuzzy control method by the fuzzy system identification using the data pairs of input and output and arbitrary initial relation matrix. The position control of a DC servo motor model is simulated to verify the effectiveness of the proposed algorithm.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1076-1078
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• 1996

In this paper, we design the robust controller for MIMO system using multiple fuzzy logic controller. Based on the knowledge of system input/output data, we introduce the simple adaptation laws to approximate the decoupling matrix from input channel to output channel. The proposed control algorithm is applied numerical example.