• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.2
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• pp.306-316
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• 2016

In this paper, an NMOS-diode eFuse OTP (One-Time Programmable) memory cell is proposed using a parasitic junction diode formed between a PW (P-Well), a body of an isolated NMOS (N-channel MOSFET) transistor with the small channel width, and an n+ diffusion, a source node, in a DNW (Deep N-Well) instead of an NMOS transistor with the big channel width as a program select device. Blowing of the proposed cell is done through the parasitic junction formed in the NMOS transistor in the program mode. Sensing failures of '0' data are removed because of removed contact voltage drop of a diode since a NMOS transistor is used instead of the junction diode in the read mode. In addition, a problem of being blown for a non-blown eFuse from a read current through the corresponding eFuse OTP cell is solved by limiting the read current to less than $100{\mu}A$ since a voltage is transferred to BL by using an NMOS transistor with the small channel width in the read mode.

• Proceedings of KOSOMES biannual meeting
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• 2005.05a
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• pp.141-146
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• 2005

Ship have cutout inner bottom and girder and floor etc. Ship's structure is used much, and structure strength must be situated, but establish new concept when high stress interacts sometimes fatally the area. There is no big problem usually by aim of weight reduction, a person and change of freight, piping etc. Because cutout's existence grow up in this place, and, elastic buckling strength by load causes large effect in ultimate strength. Therefore, stiffened perforated plate considering buckling strength and ultimate strength is one of important design criteria which must examine when decide structural concept at initial design. Therefore, and, reasonable buckling strength about perforated stiffened plate need to ultimate strength limited design . Calculated ultimate strength varied several web height and cutout's dimension, and thickness in this investigated data. Used program(ANSYS) applied F.E.A code based on finite element method.

• Journal of Korean society of Dental Hygiene
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• v.17 no.5
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• pp.921-930
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• 2017

Objectives: The purposes of this study were to analyze the trade newspapers related to 'recognition of the dental hygienist as the healthcare professional' using R program and to identify opinions of groups concerned with dental hygienists. Methods: This study was designed with contents analysis and cross-sectional. The subjects of the study were the articles for the last three years in medical and dental newspapers about the recognition of the dental hygienist as the healthcare professional. The collected articles were categorized and classified for each group's opinions about the issue. The key words were extracted according to the priorities of the opinions of agreement and disagreement. They were visualized after frequency analysis using R, a big data analysis program. Results: A total of 237 newspaper articles were extracted among 270 ones containing opinions. 245 were positive opinions and 25 were negatives. The main key words of the agreement were 'Amendment of Medical Law', 'Medical Practice', and 'Legal Guarantee of the Practice'. Advocates addressed that the issues should be resolved with the amendment of the law, as dental hygienists are not guaranteed to work based on the current law although they are actually doing the medical practices. Main key words of disagreement were 'Legal Guarantee of the Practice', 'Revision of Medical Technician Law', and 'Review of Job Type'. They described that the problem can be resolved by revising medical technicians act, and it needs to consider as job types of all healthcare professional. Conclusions: In the group who showed the positive opinions, it is possible to utilize measures such as promoting the cooperation of dental hygienists and developing public consensus through publicity.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.1
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• pp.120-130
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• 2012

As long span and complex bridges are constructed often recently, safety estimation became a big issue. Various types of measuring instruments are installed in case of long span bridge. New wireless technologies for long span bridges such as sending information through a gateway at the field or sending it through cables by signal processing the sensing data are applied these days. However, The case of occurred accidents related to bridge in the world have been reported that serious accidents occur due to lack of real-time proactive, intelligent action based on recognition accidents. To solve this problem in this study, the idea of "communication among things", which is the basic method of RFID/USN technology, is applied to the bridge monitoring system. A sensor node module for USN based intelligent bridge system in which sensor are utilized on the bridge and communicates interactively to prevent accidents when it captures the alert signals and urgent events, sends RF wireless signal to the nearest traffic signal to block the traffic and prevent massive accidents, is designed and tested by performing TinyOS based middleware design and sensor test free Space trans-receiving distance.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.722-728
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• 2012

Urban sewer systems has a limitation of capacity of rainwater storage and problem of occurrence of untreated sewage, so adopting a storage facility for sewer flooding prevention and urban non-point pollution reduction has a big attention. The Korea Ministry of Environment has recently introduced a new concept of "multi-functional storage facility", which is crucial not only in preventive stormwater management but also in dealing with combined sewer overflow and sanitary sewer discharge, and also has been promoting its adoption. However, reserving a space for a single large-scale storage facility might be difficult especially in urban areas. Thus, decentralized construction of small- and midium-sized storage facilities and its operation have been introduced as an alternative way. In this paper, we propose a model predictive control scheme for an optimized operation of distributed storage facilities and sewer networks. To this aim, we first describe the mathematical model of each component of networks system which enables us to analyze its detailed dynamic behavior. Second, overflow locations and volumes will be predicted based on the developed network model with data on the external inflow occurred at specific locations of the network. MPC scheme based on the introduced particle swarm optimization technique then produces the optimized the gate setting for sewer network flow control, which minimizes sewer flooding and maximizes the potential storage capacity. Finally, the operational efficacy of the proposed control scheme is demonstrated by simulation study with virtual rainstorm event.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.297-304
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• 2021

This study aims not only to access the visual thought-oriented approach that has been implemented in established art therapy and education but also to integrate language education and therapeutic approach to support the development of school-age children. Thus, text mining technique was applied to search for areas where different areas of language and art can be integrated. This research was conducted in accordance with the procedure of basic research, preliminary DB construction, text screening, DB pre-processing and confirmation, stop-words removing, text mining analysis and the deduction about the convergent areas. These results demonstrated that this study draws convergence areas related to regional, communication, and learning functions, areas related to problem solving and sensory organs, areas related to art and intelligence, areas related to information and communication, areas related to home and disability, topics, conceptualization, peer-related areas, integration, reorganization, attitudes. In conclusion, this study is meaningful in that it established a framework for designing an activity-centered convergence program of art and language in the future and attempted a holistic approach to support child development.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.307-332
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• 2022

One of the most intensively conducted research areas in business application study is a bankruptcy prediction model, a representative classification problem related to loan lending, investment decision making, and profitability to financial institutions. Many research demonstrated outstanding performance for bankruptcy prediction models using artificial intelligence techniques. However, since most machine learning algorithms are "black-box," AI has been identified as a prominent research topic for providing users with an explanation. Although there are many different approaches for explanations, this study focuses on explaining a bankruptcy prediction model using a counterfactual example. Users can obtain desired output from the model by using a counterfactual-based explanation, which provides an alternative case. This study introduces a counterfactual generation technique based on a genetic algorithm (GA) that leverages both domain knowledge (i.e., causal feasibility) and feature importance from a black-box model along with other critical counterfactual variables, including proximity, distribution, and sparsity. The proposed method was evaluated quantitatively and qualitatively to measure the quality and the validity.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.217-226
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• 2022

In the view of the application of high-precision spatial information production, UAV (Umanned Aerial Vehicle)-Photogrammetry has a problem in that it lacks specific procedures and detailed regulations for quantitative quality verification methods or certification of captured images. In addition, test tools for UAV image quality assessment use only the GSD (Ground Sample Distance), not MTF (Modulation Transfer Function), which reflects image resolution and contrast at the same time. This fact makes often the quality of UAV image inferior to that of manned aerial image. We performed MTF and GSD analysis simultaneously using a siemens star to confirm the necessity of MTF analysis in UAV image quality assessment. The analyzing results of UAV images taken with different payload and sensors show that there is a big difference in σ_MTF values, representing image resolution and the degree of contrast, but slightly different in GSD. It concluded that the MTF analysis is a more objective and reliable analysis method than just the GSD analysis method, and high-quality drone images can only be obtained when the operator make images after judging the proper selection the sensor performance, image overlaps, and payload type. However, the results of this study are derived from analyzing only images acquired by limited sensors and imaging conditions. It is therefore expected that more objective and reliable results will be obtained if continuous research is conducted by accumulating various experimental data in related fields in the future.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.6
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• pp.266-274
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• 2022

In this study, a smoothing method was applied to improve the accuracy of peak wave period estimation using the water surface elevation observed from the Oceanographic and Meteorological Observation Tower located on the west coast of the Korean Peninsula. Validation of the application of the smoothing method was per- formed using variance of the surface elevation and total amount wave energy, and then the effect on the application of smoothing was analyzed. As a result of the analysis, the correlation coefficient between variance of the surface elevation and total amount wave energy was 0.9994, confirming that there was no problem in applying the method. Thereafter, as a result of reviewing the effect of smoothing, it was found to be reduced by about 4 times compared to the confidence interval of the existing estimated spectrum, confirming that the accuracy of the estimated peak wave period was improved. It was found that there was a statistically significant difference in proba- bility density between 4 and 6 seconds due to the smoothing application. In addition, for optimal smoothing, the appropriate number of smoothings according to the significant wave height range was calculated using a statistical technique, and the number of smoothings was found to increase due to the unstable spectral shape as the significant wave height decreased.

• Information Systems Review
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• v.24 no.1
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• pp.105-123
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• 2022

Thanks to the remarkable success of Artificial Intelligence (A.I.) techniques, a new possibility for its application on the real-world problem has begun. One of the prominent applications is the bankruptcy prediction model as it is often used as a basic knowledge base for credit scoring models in the financial industry. As a result, there has been extensive research on how to improve the prediction accuracy of the model. However, despite its impressive performance, it is difficult to implement machine learning (ML)-based models due to its intrinsic trait of obscurity, especially when the field requires or values an explanation about the result obtained by the model. The financial domain is one of the areas where explanation matters to stakeholders such as domain experts and customers. In this paper, we propose a novel approach to incorporate financial domain knowledge into local rule generation to provide explanations for the bankruptcy prediction model at instance level. The result shows the proposed method successfully selects and classifies the extracted rules based on the feasibility and information they convey to the users.