• Communications of Mathematical Education
• /
• v.37 no.2
• /
• pp.277-297
• /
• 2023

In mathematics, the concept of convolution is widely used. The convolution operation is required for understanding computer vision and deep learning in artificial intelligence. Therefore, it is vital for this concept to be explained in college mathematics education. In this paper, we present our new teaching and learning materials on convolution available for engineering mathematics. We provide the knowledge and applications on convolution with Python-based code, and introduce Convolutional Neural Network (CNN) used for image classification as an example. These materials can be utilized in class for the teaching of convolution and help students have a good understanding of the related knowledge in artificial intelligence.

• Proceedings of the Korean Information Science Society Conference
• /
• 2007.10a
• /
• pp.161-162
• /
• 2007

• Journal of Digital Convergence
• /
• v.16 no.6
• /
• pp.187-195
• /
• 2018

Recently, the 4th industrial revolution has emerged as the core for enhancing national competitiveness, the development of a technology roadmap to efficiently develop related technologies to realize super intelligence as a main feature of the 4th Industrial Revolution is a major task has been highlighted. The objective of this study is to analyze the domestic and foreign technology level in the artificial intelligence field which is the core technology of the 4th Industrial Revolution era and to present the direction of development based on this. The keyword network analysis and the blank technical analysis based on the IPC classification were performed on the data derived from the keyword search of 'AI (Artificial Intelligence)' among domestic and foreign patent data. As a result, the number of domestic artificial intelligence related technology development was 1.2% compared with developed countries such as USA and Europe. In the major development fields, data recognition technology and digital information transmission technology were relatively insufficient. Through this study, we obtained the blank technology as a result of comparative analysis of domestic artificial intelligence related technologies compared to advanced countries and suggested the direction of domestic artificial intelligence technology development in future.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.12B
• /
• pp.1509-1521
• /
• 2011

WfMC, which is one of the international standardization organizations leading the business process and workflow technologies, has been officially released the BPAF1.0 that is a standard format to record process instances' event logs according as the business process intelligence mining technologies have recently issued in the business process and workflow literature. The business process mining technologies consist of two groups of algorithms and their analysis techniques; one is to rediscover flow-oriented process-intelligence, such as control-flow, data-flow, role-flow, and actor-flow intelligence, from process instances' event logs, and the other has something to do with rediscovering relation-oriented process-intelligence like process-driven social networks and process-driven affiliation networks from the event logs. The current standardized format of BPAF1.0 aims at only supporting the control-flow oriented process-intelligence mining techniques, and so it is unable to properly support the relation-oriented process-intelligence mining techniques. Therefore, this paper tries to extend the BPAF1.0 so as to reasonably support the relation-oriented process-intelligence mining techniques, and the extended BPAF is termed BPAF2.0. Particularly, we have a plan to standardize the extended BPAF2.0 as not only the national standard specifications through the e-Business project group of TTA, but also the international standard specifications of WfMC.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.6
• /
• pp.834-841
• /
• 2022

Recently, applying artificial intelligence technologies in various fields of production has drawn an upsurge of research interest due to the increase for smart factory and artificial intelligence technologies. A great deal of effort is being made to introduce artificial intelligence algorithms into the defect detection task. Particularly, detection of defects on the surface of metal has a higher level of research interest compared to other materials (wood, plastics, fibers, etc.). In this paper, we compare and analyze the speed and performance of defect classification by combining machine learning techniques (Support Vector Machine, Softmax Regression, Decision Tree) with dimensionality reduction algorithms (Principal Component Analysis, AutoEncoders) and two convolutional neural networks (proposed method, ResNet). To validate and compare the performance and speed of the algorithms, we have adopted two datasets ((i) public dataset, (ii) actual dataset), and on the basis of the results, the most efficient algorithm is determined.

• 한국정보교육학회:학술대회논문집
• /
• 2021.08a
• /
• pp.385-391
• /
• 2021

In this paper, a case of deep learning artificial neural network education was studied for artificial intelligence literacy education for preservice teachers and incumbent teachers. In addition, through the proposed educational case, we tried to explore the contents of artificial neural network principle education that elementary, middle and high school students can experience. To this end, first, an example of training on the principle of operation of an artificial neural network that recognizes two types of images is presented. And as an artificial neural network extension application education case, an artificial neural network education case for recognizing three types of images was presented. The number of output layers was changed according to the number of images to be recognized by the artificial neural network, and the cases implemented in a spreadsheet were divided and explained. In addition, in order to experience the operation results of the artificial neural network, we presented the educational contents to directly write the learning data necessary for the artificial neural network of the supervised learning method. In this paper, the implementation of the artificial neural network and the recognition test results are visually presented using a spreadsheet.

• Korean Security Journal
• /
• no.61
• /
• pp.59-85
• /
• 2019

In the reality that the boundary between the real world and the virtual world disappears with the 4th Industrial Revolution, cyber crimes that occur beyond time and space have clear limitations in fulfilling their duties only with the police force of government organizations established under the real law system. The research method of this thesis is based on the literature research and the experience of security work. The purpose of this paper is to establish a social system where collective intelligence of each social field can participate voluntarily to respond to cyber crimes occurring beyond the time and space before the law and institutionalization. In addition, the social system in which collective intelligence in each social sector can participate voluntarily was established to define crime types in cyberspace in real time and to prevent crimes defined by the people themselves and the counter-measures had been proposed in order to form social consensus. First, it is necessary to establish a collective intelligent network-type cyberpolice volunteer system. The organization consists of professors of security and security related departments at universities nationwide, retired public officials from the National Intelligence Service, the National Police Agency, and the National Emergency Management Agency, security companies and the organizations, civilian investigators, security & guard, firefighting, police, transportation, intelligence, security, national security, and research experts. Second, private sector regulation should be established newly under the Security Business Act. Third, the safety guard of the collective intelligent cyberpolice volunteer system for the stability of the people's lives should strengthen volunteer work. Fourth, research lessons and legal countermeasures against cybercrime in advanced countries should be introduced. Fifth, the Act on the Protection of Personal Information, the Act on Promotion of Information and Communication Network Utilization and Information Protection, the Act on the Utilization and Protection of Credit Information, and the Special Act on the Materials and Parts Industry should be amended. Sixth, police officers should develop cybercrime awareness skills for proactive prevention activities.

• Journal of Digital Convergence
• /
• v.11 no.5
• /
• pp.145-158
• /
• 2013

I estimate stock prices of listed companies using financial information and Ohlson model, which is used for the evaluation of company value. Furthermore, I use the artificial neural network, one of artificial intelligence systems, which are not based on linear relationship between variables, to estimate stock prices of listed companies. By reapplying this in estimating stock prices of newly listed companies, I evaluate the appropriateness in stock valuation with such methods. The result of practical analysis of this study is as follows. On the top of that, the multiplier for the actual stock price is accounted by generating the estimated stock prices based on the artificial neural network model. As a result of the comparison of two multipliers, the estimated stock prices by the artificial neural network model does not show statistically difference with the actual stock prices. Given that, the estimated stock price with artificial neural network is close to the actual stock prices rather than the estimated stock prices with Ohlson model.

• Journal of the Korea Convergence Society
• /
• v.11 no.9
• /
• pp.21-29
• /
• 2020

The Topic Modeling research, the methodology for deduction keyword within literature, has become active with the explosion of data from digital society transition. The research objective is to investigate research trends in D.N.A.(Data, Network, Artificial Intelligence) field using DTM(Dynamic Topic Model). DTM model was applied to the 1,519 of research projects with SW·A.I technology classifications among ICT(Information and Communication Technology) field projects between 6 years(2015~2020). As a result, technology keyword for D.N.A. field; Big data, Cloud, Artificial Intelligence, extended keyword; Unstructured, Edge Computing, Learning, Recognition was appeared every year, and accordingly that the above technology is being researched inclusively from other projects can be inferred. Finally, it is expected that the result from this paper become useful for future policy·R&D planning and corporation's technology·marketing strategy.

• Journal of Internet Computing and Services
• /
• v.11 no.1
• /
• pp.1-13
• /
• 2010

It is not easy to set RED(Random Early Detection) parameter according to environment in managing Network Device. Especially, it is more difficult to set parameter in the case of maintaining the constant service rate according to the change of environment. In this paper, we hypothesize the router that has Multi-core CPU in output queue and propose AI RED(Artificial Intelligence RED), which directly induces Genetic Algorithm of Artificial Intelligence in the output queue that is appropriate to the optimization of parameter according to RED environment, which is automatically adaptive to workload. As a result, AI RED Is simpler and finer than FuRED(Fuzzy-Logic-based RED), and RED parameter that AI RED searches through simulations is more adaptive to environment than standard RED parameter, providing the effective service. Consequently, the automation of management of RED parameter can provide a manager with the enhancement of efficiency in Network management.