• Journal of Digital Convergence
• /
• v.20 no.2
• /
• pp.269-275
• /
• 2022

As artificial intelligence services targeting humans increase, social demands are increasing that artificial intelligence should also be made on an ethical basis. Following this trend, the government and businesses are preparing policies and norms related to artificial intelligence ethics. In order to establish reasonable policies and norms, the first step is to understand the public's perceptions. In this paper, social data and news comments were collected and analyzed to understand the public's perception related to artificial intelligence and ethics. Interest analysis, emotional analysis, and discourse analysis were performed and visualized on the collected datasets. As a result of the analysis, interest in "artificial intelligence ethics" and "artificial intelligence" favorability showed an inversely proportional correlation. As a result of discourse analysis, the biggest issue was "personal information leakage," and it also showed a discourse on contamination and deflection of learning data and whether computer-made artificial intelligence should be given a legal personality. This study can be used as data to grasp the public's perception when preparing artificial intelligence ethical norms and policies.

• Review of KIISC
• /
• v.26 no.1
• /
• pp.92-98
• /
• 2016

IT기술이 발달함에 따라서 데이터는 대량화, 다양화 되었다. 그에 따라서 이를 침해하려는 다양한 공격기술들이 등장하고 있다. 특히, 지능형 타깃 지속 공격이라는 APT(Advanced Persistent Threat) 공격은 날로 발전하고 있다. APT공격 중에서도 특히 은닉형 악성코드를 이용한 공격들이 많이 등장하고 있다. 은닉형 악성코드는 사용자가 인식하지 못하도록 보안시스템을 우회하고, 중요 데이터의 수집 및 유출을 위하여 교묘하게 시스템에 숨어들어 악의적인 행위를 하는 형태의 악성코드를 말한다. 이러한 고도화된 악의적인 행위를 하는 악성코드를 탐지하고, 대응하기 위한 기술들은 아직까지 부족한 것이 현실이다. 본 논문에서 대표적인 은닉형 악성코드와 공격사례를 분석하여 이를 대응할 수 있는 방안을 고찰해본다. 또한 이를 통하여 고도화된 공격기술들에 대해 예방하고 대응하는 자료로 활용 가능하다.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.12
• /
• pp.11-19
• /
• 2014

In this paper, we design an intelligent agent system with the data mining module and information fusion module as the core components of the system and investigate the possibility for the medical expert system. In the data mining module, fuzzy neural network, OFUN-NET analyzes multi-view data and produces fuzzy cluster knowledge base. In the information fusion module and application module, they serve the diagnosis result with possibility degree and useful information for diagnosis, such as uncertainty decision status or detection of asymmetry. We also present the experiment results on the BI-RADS-based feature data set selected form DDSM benchmark database. They show higher classification accuracy than conventional methods and the feasibility of the system as a computer aided diagnosis system.

• Journal of Christian Education in Korea
• /
• v.66
• /
• pp.309-341
• /
• 2021

The purpose of this study is to develop an intelligent learning platform model for faith education in preparation for the post-corona era. This study reviewed artificial intelligence algorithms, research on learning platform development, and prior research related to faith education. The draft of the intelligent learning platform design model was developed by synthesizing previous studies. The developed draft model was validated by a Delphi survey targeting 5 experts. The content validity of the developed draft model was all 1. This is the validation of the draft model. Three revised opinions of experts were presented on the model. And the model was revised to reflect the opinions of experts. The modified final model consisted of three areas: learning materials, learning activities, learning data, and artificial intelligence. Each area is composed of 9 elements of curriculum, learning content additional learning resources, learner type, learning behavior, evaluation behavior, learner characteristic data, learning activity data, artificial intelligence data, and learning analysis. Each component has 29 sub-elements. In addition, 14 learning floors were formed. The biggest implication of this study is the first development of a basic model of an intelligent learning platform for faith education.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2001.12a
• /
• pp.31-36
• /
• 2001

We design the intelligent diagnosis system for deciding on operation state of TMS Analyzer in this paper. We propose the method to model the neno-fuzzy model for diagnosing the operation state of analyzer by using input and output signals of TMS to measure NOx and SOx. By using experiment data, neuro-fuzzy model is investigated. Validity of the proposed system is asserted by numerical simulation.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.11 no.8
• /
• pp.695-700
• /
• 2001

We design the intelligent diagnosis system for deciding on operation of TMS Analysis in this paper. We propose the method to model the neuro-fuzzy model for diagnosing the operation state of analyzer by using input and output signals of TMS and Expert's experiment data. Validity of the proposed system is asserted by numerical simulation.

• Journal of Christian Education in Korea
• /
• v.77
• /
• pp.225-249
• /
• 2024

Research Purpose : Based on artificial intelligence, this study considers learners' characteristics, learning content, and individual learning, and analyzes the collected learning data to develop a model that supports customized learning for individual learners. Research content and method : In order to achieve the research purpose, the literature was analyzed to investigate the structure of customized learning support, learning data analysis, and learning activities, and based on the investigated data, the area and detailed components of the customized learning support model were derived. did. A draft model was constructed through literature analysis, and the first expert Delphi survey was conducted on the draft model with five experts. The model was revised by reflecting the results of the first Delphi, and the validity of the revised model was verified through the second expert Delphi. The model was elaborated through expert Delphi, and the final model was constructed through this. Conclusion and Recommendation : Through research, customized learning support area, class management system area, and learning analysis data area were formed, and detailed elements were derived for each area. The results of this study provide basic data that can be used as a reference for constructing a customized learning support system based on artificial intelligence, taking into account the university's class environment.

• Journal of Intelligence and Information Systems
• /
• v.29 no.2
• /
• pp.219-240
• /
• 2023

Conversational AI which allows users to interact with satisfaction is a long-standing research topic. To develop conversational AI, it is necessary to build training data that reflects real conversations between people, but current Korean datasets are not in question-answer format or use honorifics, making it difficult for users to feel closeness. In this paper, we propose a conversation dataset (KOMUChat) consisting of 30,767 question-answer sentence pairs collected from online communities. The question-answer pairs were collected from post titles and first comments of love and relationship counsel boards used by men and women. In addition, we removed abuse records through automatic and manual cleansing to build high quality dataset. To verify the validity of KOMUChat, we compared and analyzed the result of generative language model learning KOMUChat and benchmark dataset. The results showed that our dataset outperformed the benchmark dataset in terms of answer appropriateness, user satisfaction, and fulfillment of conversational AI goals. The dataset is the largest open-source single turn text data presented so far and it has the significance of building a more friendly Korean dataset by reflecting the text styles of the online community.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2022.06a
• /
• pp.319-320
• /
• 2022

본 논문에서는 '지능형 해상교통정보 서비스'로 축적된 선박 위치데이터를 가공하여 선박의 조우상황 데이터를 추출하고 분석하였다. 선박의 위치, 침로, 속력을 통해 TCPA, DCPA와 선박간 거리를 계산함으로써 선박의 충돌위험 인지 후 회피 상황에서 보이는 데이터의 형태와 분포를 분석하였다. 추후 상대방위와 SOG가 TCPA 변화량에 미치는 영향에 대한 연구가 진행되면, 실제 사용자의 충돌위험 판단과 근접한 충돌위험도 분석 모델로 활용할 수 있을 것으로 보인다.

• Journal of Intelligence and Information Systems
• /
• v.22 no.4
• /
• pp.139-155
• /
• 2016

The purpose of this study is to find the research identity of the Korea Intelligent Information Systems Society through the profiling methods and co-word analysis in the most recent three-year('2014~'2016) study to collect keyword. In order to understand the research identity for intelligence information system, we need that the relative position of the study will be to compare identity by collecting keyword and research methodology of The korea Society of Management Information Systems and Korea Association of Information Systems, as well as Korea Intelligent Information Systems Society for the similar. Also, Korea Intelligent Information Systems Society is focusing on the four research areas such as artificial intelligence/data mining, Intelligent Internet, knowledge management and optimization techniques. So, we analyze research trends with a representative journals for the focusing on the four research areas. A journal of the data-related will be investigated with the keyword and research methodology in Korean Society for Big Data Service and the Korean Journal of Big Data. Through this research, we will find to research trends with research keyword in recent years and compare against the study methodology and analysis tools. Finally, it is possible to know the position and orientation of the current research trends in Korea Intelligent Information Systems Society. As a result, this study revealed a study area that Korea Intelligent Information Systems Society only be pursued through a unique reveal its legitimacy and identity. So, this research can suggest future research areas to intelligent information systems specifically. Furthermore, we will predict convergence possibility of the similar research areas and Korea Intelligent Information Systems Society in overall ecosystem perspectives.