• The KIPS Transactions:PartB
• /
• v.15B no.1
• /
• pp.45-52
• /
• 2008

As the recent development of the IT services, there is a urgent need of effective diagnosis system to present appropriate solution for the complicated problems of breakdown control, a cause analysis of breakdown and others. So we propose an intelligent diagnosis system that integrates the case-based reasoning and the artificial neural network to improve the system performance and to achieve optimal diagnosis. The case-based reasoning is a reasoning method that resolves the problems presented in current time through the past cases (experience). And it enables to make efficient reasoning by means of less complicated knowledge acquisition process, especially in the domain where it is difficult to extract formal rules. However, reasoning by using the case-based reasoning alone in diagnosis problem domain causes a problem of suggesting multiple causes on a given symptom. Since the suggested multiple causes of given symptom has the same weight, the unnecessary causes are also examined as well. In order to resolve such problems, the back-propagation learning algorithm of the artificial neural network is used to train the pairs of the causes and associated symptoms and find out the cause with the highest weight for occurrence to make more clarified and reliable diagnosis.

• Journal of The Korean Association of Information Education
• /
• v.23 no.5
• /
• pp.469-480
• /
• 2019

One of the goals of the new 2015 revised curriculum is to cultivate the creativity of students who will live in the era of the Fourth Industrial Revolution to create new things through diverse ideas and challenges based on basic learning skills. Accordingly, in order to solve the given problems rationally, the convergence problem solving ability that can process and utilize various areas of knowledge and information is becoming important. Therefore, in this study, we designed the integrative education using a 3D printer based on Tinkercad modeling and applied it to the class to investigate the effect on the improvement of computing thinking ability of elementary school students. To verify the contents of the study, two classes of 25 sixth-grade elementary school students were divided into an experimental group and a controlled group. For the experimental group, 12 classes of convergence education programs using a 3D printer were applied for about three months, and the same amount of general curriculum was conducted for the control group. After that, the t-tests were carried out using the pre-post test to measure the effectiveness of the computational thinking ability. After the application of the program, the experimental group showed statistically significant improvement in computational thinking ability, but the controlled group showed no statistically significant difference. The results show that convergence education using the Tinkercad modeling-based 3D printer has a positive effect on the improvement of computing thinking ability of elementary school students.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.4
• /
• pp.165-172
• /
• 2020

In this paper we propose an uses on-device-based edge computing technology and big data analysis methods through the use of on-device-based edge computing technology and analysis of big data, which are distributed computing paradigms that introduce computations and storage devices where necessary to solve problems such as transmission delays that occur when data is transmitted to central centers and processed in current general smart factories. However, even if edge computing-based technology is applied in practice, the increase in devices on the network edge will result in large amounts of data being transferred to the data center, resulting in the network band reaching its limits, which, despite the improvement of network technology, does not guarantee acceptable transfer speeds and response times, which are critical requirements for many applications. It provides the basis for developing into an AI-based facility prediction conservation analysis tool that can apply deep learning suitable for big data in the future by supporting intelligent facility management that can support productivity growth through research that can be applied to the field of facility preservation and smart factory industry with integrated hardware technology that can accommodate these requirements and factory management and control technology.

• The Korean Journal of Food And Nutrition
• /
• v.34 no.5
• /
• pp.477-486
• /
• 2021

To utilize Malus pruniforia Borkh. as a functional material, cold-water (CW), hot-water (HW), and 70% ethanol (EtOH) extracts were prepared, and their antioxidant and anti-inflammatory activities were compared. The antioxidant activity of the HW extract evaluated by ABTS and DPPH radical scavenging and FRAP activity was significantly effective. The total polyphenol content of the HW extract was also higher by 15.5±0.7 mg GAE/g extract compared to other extracts. The EtOH extract showed significantly decreased TNF-α (39.8%), IL-6 (65.5%), and NO (34.9%) levels in RAW 264.7 cells compared to the LPS-induced control group. The levels of IL-6 (21.1%) and IL-8 (19.3%) were significantly decreased by treatment of EtOH extract in HaCaT keratinocytes induced with TNF-α and IFN-γ. The UHPLC-MS results indicated that the EtOH extract might have chlorogenic acid and phlorizin as the major compounds. This was validated using HPLC-DAD, which showed that the EtOH extract had higher levels of chlorogenic acid and phlorizin (1,185±58 and 470±10 ㎍/g extract, respectively). In conclusion, the present study suggested that the anti-inflammatory activity of the EtOH extract was more effective than the CW and HW extracts, and chlorogenic acid and phlorizin could be used as indicator compounds and functional substances.

• Journal of the Korean School Mathematics Society
• /
• v.24 no.1
• /
• pp.83-105
• /
• 2021

In this paper, we analyzed the misconceptions and errors incurred during factorization learning. We also examined whether online individualization classes had a positive effect on students' mathematical achievement. The experiment was conducted for 4 weeks (16 times in total) on middle school juniors in rural areas of Gyeonggi Province, where the influence of private extra education was small. In the class, the 'Google Classroom' was used as a LMS, the video lecture was uploaded to YouTube, and the teacher interacted with the students through "Zoom" and "Facetalk". In the online class situation, students' assignments and test answers were checked in real time through 'Google Classroom', and immediate feedback was provided to the experimental class group's students. However, for the control group students, feedback was provided only to those who desired. A total of 7 achievement evaluations were conducted in the order of pre-test, formative evaluation (5 times), and post-test to confirm the change in students' ability improvement and achievement. Through the formative evaluation analysis, it was possible to grasp the types of errors and misconceptions that occured during the factorization process. Students' errors were divided into four types: theorem or definition distortion error, functional errors such as calculation, operation, and manipulation, errors that do not verify the solution, and no response. As a result of ANCOVA, the two groups did not show any difference from the 1st to 4th formative assessment. However, the 5th formative assessment and post-test showed statistically significant differences, confirming that online individualization classes contributed to improvemed achievement.

• Journal of Korea Water Resources Association
• /
• v.54 no.12
• /
• pp.1233-1242
• /
• 2021

In this study, a model was developed to determine whether flooding occurred using image data, which is unstructured data. CNN-based VGG16 and VGG19 were used to develop the flood classification model. In order to develop a model, images of flooded and non-flooded images were collected using web crawling method. Since the data collected using the web crawling method contains noise data, data irrelevant to this study was primarily deleted, and secondly, the image size was changed to 224×224 for model application. In addition, image augmentation was performed by changing the angle of the image for diversity of image. Finally, learning was performed using 2,500 images of flooding and 2,500 images of non-flooding. As a result of model evaluation, the average classification performance of the model was found to be 97%. In the future, if the model developed through the results of this study is mounted on the CCTV control center system, it is judged that the respons against flood damage can be done quickly.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.5
• /
• pp.241-251
• /
• 2019

In the present study, we investigated the effect of microcurrent against cognitive impairment in Alzheimer's disease (AD) mice model. The cognitive impairment was induced by intracerebroventricularly injection of amyloid beta ($A{\beta}$) to ICR mouse brain, and four kinds of micorocurrent wave were applied to AD mice. We observed the improved cognitive ability in microcurrent-applied AD mice through novel object recognition test and Morris water maze test, compared to $A{\beta}$-injected control group. The contents of malondialdehyde generated by $A{\beta}$ in the brain were also reduced by microcurrent application. These effects of microcurrent were related to the modulation of $A{\beta}$ producing and brain-derived neurotrophic factor (BDNF). Microcurrent down-regulated ${\beta}$-secretase, presenilin 1, and presenilin 2 which were related amyloidogenic pathway, and up-regulated human brain-derived neurotrophic factor in the mice brain, especially Wave4 group [STEP FORM wave form (0, 1.5, 3, 5V), wave superposition]. These results suggest that microcurrent application could provide help for improvement learning and memory ability, at least partly.

• International Journal of Computer Science & Network Security
• /
• v.21 no.8
• /
• pp.71-78
• /
• 2021

The relevance of research provides the necessity to identify the basic problems in the public governance sphere and information technology relations, forasmuch as understanding such interconnections can indicate the consequences of the development and spreading information technologies. The purpose of the research is to outline the issues of applying information technologies in public governance sphere. 500 civil servants took part in the survey (Ukraine). A two-stage study was conducted in order to obtain practical results of the research. The first stage involved collecting and analyzing the responses of civil servants on the Mentimeter online platform. In the second stage, the administrator used the SWOT-analysis system. The tendencies in using information technologies have been determined as follows: the institutional support development; creation of analytical portals for ensuring public control; level of accountability, transparency, activity of civil servants; implementation of e-government projects; changing the philosophy of electronic services development. Considering the threats and risks to the public governance system in the context of applying information technologies, the following aspects generated by societal requirements have been identified, namely: creation of the digital bureaucracy system; preservation of information and digital inequality; insufficient level of knowledge and skills in the field of digital technologies, reducing the publicity of the state and municipal governance system. Weaknesses of modern public governance in the context of IT implementation have been highlighted, namely: "digitization for digitalization"; lack of necessary legal regulation; inefficiency of electronic document management (issues caused by the imperfection of the interface of reporting interactive forms, frequent changes in the composition of indicators in reporting forms, the desire of higher authorities to solve the problem of their introduction); lack of data analysis infrastructure (due to imperfections in the organization of interaction between departments and poor capacity of information resources; lack of analytical databases), lack of necessary digital competencies for civil servants. Based on the results of SWOT-analysis, the strengths have been identified as follows: (possibility of continuous communication; constant self-learning); weaknesses (age restrictions for civil servants; insufficient acquisition of knowledge); threats (system errors in the provision of services through automation); opportunities for the introduction of IT in the public governance system (broad global trends; facilitation of the document management system). The practical significance of the research lies in providing recommendations for eliminating the problems of IT implementation in the public governance sphere outlined by civil servants..

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.49 no.2
• /
• pp.95-106
• /
• 2021

Side-jets enable the immediate maneuver of a missile compared to control surfaces; however, they may cause adverse effects on aerodynamic coefficients, for they interfere with freestream. To find out the impact of side-jets on aerodynamic coefficients, we simulate side-jets as air gas and utilize multi-fidelity models to evaluate differences between aerodynamic coefficients obtained with and without side-jets. We computed differences in aerodynamic coefficients to investigate side-jet effects for the changes of a Mach number, a bank angle, and an angle of attack. As a result, asymmetrically developed side-jets affect the longitudinal force and moment coefficients, and the lateral force and moment coefficients drastically change in-between -30 and 30 degrees of bank angles. In contrast, side-jets hardly influence the axial force coefficients. As for the axial moment coefficient, we could not determine the side-jet effect due to a lack of aerodynamic coefficient samples in the Mach number. All in all, we confirm that side-jets lead to the change of a missile attitude as they considerably vary the longitudinal and lateral aerodynamic coefficients.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.9 no.4
• /
• pp.11-22
• /
• 1999

Least-mean-square(LMS) adaptive filters have proven to be extremely useful in a number of signal processing tasks. However LMS adaptive filter suffer from a slow rate of convergence for a given steady-state mean square error as compared to the behavior of recursive least squares adaptive filter. In this paper an efficient signal interference control technique is introduced to improve the convergence speed of LMS algorithm with tap weighted vectors updating which were controled by reusing data which was abandoned data in the Adaptive transversal filter in the scheme with data recycling buffers. The computer simulation show that the character of convergence and the value of MSE of proposed algorithm are faster and lower than the existing LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is the number of recycled data buffer without complexity of computation. Adaptive transversal filter with proposed data recycling buffer algorithm could efficiently reject ISI of channel and increase speed of convergence in avoidance burden of computational complexity in reality when it was experimented having the same condition of LMS algorithm.