• The Transactions of the Korea Information Processing Society
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• v.6 no.2
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• pp.335-346
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• 1999

The process of program debugging is essentially an intelligence intensive process. It is thought viable to develop a knowledge-based tool to help programmer perform this process. This paper presents the design of such a system. Unlike other knowledge-based debugging tools which are mostly based on formal program specification and automatic program understanding, this tool is based on debugging heuristic. This tool is a debugging assistant which only suggests the programmer in program debugging what and where to examine using the debugging heuristic stored in the knowledge base. In this paper, a umber of useful heuristic debugging knowledge are explained and their usage in debugging process are described. The, a scheme to organize the knowledge in the knowledge base and an intelligent program debugging assistant using the knowledge are proposed and discussed.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.65-70
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• 2023

The "information roadway" will give us an impact of new PC based assignments and administrations, yet the unusualness of this new condition will ask for another style of human-PC association, where the PC transforms into a sharp, dynamic and customized partner. Interface administrators are PC programs that use Artificial Intelligence frameworks to give dynamic help to a customer with PC based errands. Operators drastically change the present client encounter, through the similitude that a specialist can go about as an individual collaborator. The operator procures its capability by gaining from the client and from specialists helping different clients. A couple of model administrators have been gathered using this methodology, including authorities that give customized help with meeting planning, electronic mail taking care of, Smart Personal Assistant and choice of diversion. Operators help clients in a scope of various ways: they perform assignments for the client's sake; they can prepare or educate the client, they enable diverse clients to work together and they screen occasions and methods.

• Journal of KIISE
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• v.42 no.2
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• pp.190-202
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• 2015

Much research has been conducted on location-based intelligent personal assistants that can understand a user's intention by learning the user's route model and then inferring the user's destinations and routes using data of GPS and other sensors in a smartphone. The intelligence of the location-based personal assistant is contingent on the accuracy and efficiency of the real-time predictions of the user's intended destinations and routes by processing movement information based on uncertain sensor data. We propose a robust particle filter based on Dynamic Bayesian Network model to infer the user's routes. The proposed robust particle filter includes a particle generator to supplement the incorrect and incomplete sensor information, an efficient switching function and an weight function to reduce the computation complexity as well as a resampler to enhance the accuracy of the particles. The proposed method improves the accuracy and efficiency of determining a user's routes and destinations.

• The Journal of the Korea Contents Association
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• v.9 no.10
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• pp.482-491
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• 2009

The purpose of this research is to design and develop teacher assistant contents 'My Class' for an intelligent robot iRobiQ, using in early childhood educational setting. After observing daily activities and correspondence role of teachers in educational settings, we selected the robots' target contents as 6 main functions (Attendance, Activity, Gallery, Learning, Role Calling, and Timer). We designed the contents according to the PLU (Player-Learner-User) model which suggests importance of entertainment, education, and enabling features to meet player, learner, and user requirements. We also considered 'emotional' features to satisfy 'companion' requirements. The developed contents in this study was deployed in kindergarten classrooms consisting of five-years-old for 4 weeks to see how they response and use the contents. We found that both teachers and children were likely to show positive responses to the contents. Especially, young children responded to the entertainment and emotional features more actively than to the other features. And they continually explored for something new inside the contents. Finally, this paper discusses what should be considered to develop more useful teacher assistant contents for iRobiQ.

• Journal of Science and Technology Studies
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• v.19 no.2
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• pp.169-206
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• 2019

This article seeks to explore new relationships and ethics of human and technology by analyzing a cultural imaginary produced by artificial intelligence. Drawing on theoretical reflections of the Feminist Scientific and Technological Studies which understand science and technology as the matter of care(Puig de la Bellacas, 2011), this paper focuses on the fact that artificial intelligence and robots materialize cultural imaginary such as autonomy. This autonomy, defined as the capacity to adapt to a new environment through self-learning, is accepted as a way to conceptualize an authentic human or an ideal subject. However, this article argues that artificial intelligence is mediated by and dependent on invisible human labor and complex material devices, suggesting that such autonomy is close to fiction. The recent growth of the so-called 'assistant technology' shows that it is differentially visualizing the care work of both machines and humans. Technology and its cultural imaginary hide the care work of human workers and actively visualize the one of the machine. And they make autonomy and agency ideal humanness, leaving disabled bodies and dependency as unworthy. Artificial intelligence and its cultural imaginary negate the value of disabled bodies while idealizing abled-bodies, and result in eliminating the real relationship between man and technology as mutually dependent beings. In conclusion, the author argues that the technology we need is not the one to exclude the non-typical bodies and care work of others, but the one to include them as they are. This technology responsibly empathizes marginalized beings and encourages solidarity between fragile beings. Inspired by an art performance of artist Sue Austin, the author finally comes up with and suggests 'artificial intelligence in wheelchair' as an alternative figuration for the currently dominant 'autonomous artificial intelligence'.

• Korean Journal of Radiology
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• v.25 no.3
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• pp.224-242
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• 2024

The emergence of Chat Generative Pre-trained Transformer (ChatGPT), a chatbot developed by OpenAI, has garnered interest in the application of generative artificial intelligence (AI) models in the medical field. This review summarizes different generative AI models and their potential applications in the field of medicine and explores the evolving landscape of Generative Adversarial Networks and diffusion models since the introduction of generative AI models. These models have made valuable contributions to the field of radiology. Furthermore, this review also explores the significance of synthetic data in addressing privacy concerns and augmenting data diversity and quality within the medical domain, in addition to emphasizing the role of inversion in the investigation of generative models and outlining an approach to replicate this process. We provide an overview of Large Language Models, such as GPTs and bidirectional encoder representations (BERTs), that focus on prominent representatives and discuss recent initiatives involving language-vision models in radiology, including innovative large language and vision assistant for biomedicine (LLaVa-Med), to illustrate their practical application. This comprehensive review offers insights into the wide-ranging applications of generative AI models in clinical research and emphasizes their transformative potential.

• Journal of The Korean Association of Information Education
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• v.23 no.6
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• pp.675-687
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• 2019

As interest in artificial intelligence increases, each university has been establishing a special graduate school with artificial intelligence major, and recently, the Korea government has established various support policies for artificial intelligence education. However, each university has a lot of difficulties because it has little experience in operating graduate education with the latest field of artificial intelligence and it is not easy to find experts. In this study, the response of graduate school students majoring in artificial intelligence was analyzed using IPA technique, and the direction of education of graduate school artificial intelligence major was searched. Among the 40 items surveyed by IPA, 12 items such as systematization of artificial intelligence curriculum, progress of class considering learning level, improvement of academic relations with guidance professors were extracted as items to be improved first. On the other hand, 8 items such as assistant capacity, and relationship with colleagues were overloaded, and twelve items such as instructor's lecture competency, appropriateness of educational contents, learner's artificial intelligence skills and knowledge, and attitude acquisition were to be maintained. In addition, eight items such as convergence education curriculum and diversity of education methods were all low in importance and performance. It is suggested that AI graduate school should be divided into two tracks(technical specialization, convergence expansion) by educational goal, and each track should be conducted by level-specific educational contents and methods suitable for student level. The curriculum should be elaborate and systematic to acquire AI knowledge, skills, and attitudes, and should have an individualized guidance system centered on excellent faculty members.

• International journal of advanced smart convergence
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• v.10 no.2
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• pp.79-85
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• 2021

Speech recognition technology refers to a technology in which a computer interprets the speech language spoken by a person and converts the contents into text data. This technology has recently been combined with artificial intelligence and has been used in various fields such as smartphones, set-top boxes, and smart TVs. Examples include Google Assistant, Google Home, Samsung's Bixby, Apple's Siri and SK's NUGU. Google and Daum Kakao offer free open APIs for speech recognition technologies. This paper selects three APIs that are free to use by ordinary users, and compares each recognition rate according to the three types. First, the recognition rate of "numbers" and secondly, the recognition rate of "Ga Na Da Hangul" are conducted, and finally, the experiment is conducted with the complete sentence that the author uses the most. All experiments use real voice as input through a computer microphone. Through the three experiments and results, we hope that the general public will be able to identify differences in recognition rates according to the applications currently available, helping to select APIs suitable for specific application purposes.

• Korean Journal of Artificial Intelligence
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• v.11 no.1
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• pp.1-7
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• 2023

In this paper, a study was conducted to compare the prediction model of cardiovascular disease occurrence. It is the No.1 disease that accounts for 1/3 of the world's causes of death, and it is also the No. 2 cause of death in Korea. Primary prevention is the most important factor in preventing cardiovascular diseases before they occur. Early diagnosis and treatment are also more important, as they play a role in reducing mortality and morbidity. The Results of an experiment using Azure ML, Logistic Regression showed 88.6% accuracy, Decision Tree showed 86.4% accuracy, and Support Vector Machine (SVM) showed 83.7% accuracy. In addition to the accuracy of the ROC curve, AUC is 94.5%, 93%, and 92.4%, indicating that the performance of the machine learning algorithm model is suitable, and among them, the results of applying the logistic regression algorithm model are the most accurate. Through this paper, visualization by comparing the algorithms can serve as an objective assistant for diagnosis and guide the direction of diagnosis made by doctors in the actual medical field.

• The Journal of Society for e-Business Studies
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• v.9 no.3
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• pp.155-167
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• 2004

At this time, the two main techniques for achieving web personalization assistant systems generally concern direct manipulation and software agents. While both direct manipulation and software agents are intended for permitting user to complete tasks rapidly, efficiently, and easily, their methodologies are different. The central debate involving these web personalization techniques originates from the amount of control that each allows to, or holds back from, the users. Direct manipulation can provide users with comprehensibel, predictable and controllable user interfaces that give them a feeling of accomplishnent and responsibility. On the other hand, the intelligent software components, the agents, can assist users with artificial intelligence by monitoring or retrieving personal histories or behaviors. In this empirical study, two web personalization assistant systems are evaluated. One of them, WebPersonalizer, is an agent based user personalization tool; the other, AntWorld, is a collaborative recommendation tool which provides direct manipulation interfaces. Through this empirical study, we have focused on two different paradigms as web personalization assistant systems : direct manipulation and software agents. Each approach has its own advantages and disadvantages. We also provide the experimental result that is worth referring for developers of electronic commerce system and suggest the methodologies for conveniently retrieving necessary information based on their personal needs.