• Korean Journal of Artificial Intelligence
• /
• v.12 no.1
• /
• pp.7-16
• /
• 2024

This study aims to explore driving factors of Artificial Intelligence application for city marketing strategy with perspectives of millennials and generation Z. This study proposed the following research questions: i) how perceived place branding factor, public service factor, affective factor, immersive experience factor, cognitive factor, cost benefit factor, social networking factor, and promotional value factor affect attitude toward AI application for city marketing; and ii) how attitude affect satisfaction and prospect toward AI application for city marketing? This study conducted an online survey with the assistance of a well-known research agency and applied factor and regression analysis to test hypotheses. The results found that effects of place branding, cognitive, social networking, and promotional value affect attitude significantly in the case of millennials, while effects of public service, affective, cost benefit, social networking, and promotional value affect attitude significantly in the case of generation Z. The results found that effects of attitude on satisfaction and prospect of AI showed significance. The results provide implications and different aspects for AI application of city marketing strategy with perspectives by generations, while millennials and generation Z perceived effects of promotional value as the most significant factor for AI application of city marketing strategy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.174-176
• /
• 2022

In this paper, we present a mobile application for 'personalized customized learning' for children with articulation disorders using an artificial intelligence (AI) algorithm. A dataset (Data Set) to analyze, judge, and predict the learner's articulation situation and degree. In particular, we designed a prototype model by looking at how AI can be improved and advanced compared to existing applications from the UX/UI (GUI) aspect. So far, the focus has been on visual experience, but now it is an important time to process data and provide a UX/UI (GUI) experience to users. The UX/UI (GUI) of the proposed mobile application was to be provided according to the learner's articulation level and situation by using CRNN (Convolution Recurrent Neural Network) of DeepLearning and Auto Encoder GPT-3 (Generative Pretrained Transformer). The use of artificial intelligence algorithms will provide a learning environment with a high degree of perfection to children with articulation disorders, thereby enhancing the learning effect. I hope that you do not have any fear or discomfort in conversation by improving the perfection of articulation with 'personalized and customized learning'.

• 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.

• Dementia and Neurocognitive Disorders
• /
• v.17 no.3
• /
• pp.83-89
• /
• 2018

Machine learning is where a machine (i.e., computer) determines for itself how input data is processed and predicts outcomes when provided with new data. An artificial neural network is a machine learning algorithm based on the concept of a human neuron. The purpose of this review is to explain the fundamental concepts of artificial neural networks.

• Journal of Korean Society of Archives and Records Management
• /
• v.19 no.4
• /
• pp.221-230
• /
• 2019

This paper aims to introduce the case of operating electronic document system and record management system as one system called i-Works at Korea Midland Power Company. i-Works combines intelligent services, such as artificial intelligence and a chatbot, as a supplementary tool for record management. As such, the preparation process and progress direction for the development of the record management system is introduced, an in-depth review of real-time transfer and utilization of the functional classification system to enhance the utilization of the current records is presented, and new technologies, such as artificial intelligence for an efficient management of the increasing number of electronic records, are established.

• Journal of Korea Entertainment Industry Association
• /
• v.15 no.4
• /
• pp.15-29
• /
• 2021

Many countries and companies are pursuing and developing Artificial intelligence as it is the core technology of the 4th industrial revolution. Global IT companies such as Apple, Microsoft, Amazon, Google and Samsung have all released their own AI assistant hardware products, hoping to increase customer loyalty and capture market share. Competition within the industry for AI agent is intense. AI assistant products that command the biggest market shares and customer loyalty have a higher chance of becoming the industry standard. This study analyzed the current status of major overseas and domestic IT companies in the field of artificial intelligence, and suggested future strategic directions for voice UI technology development and user satisfaction. In terms of B2B technology, it is recommended that IT companies use cloud computing to store big data, innovative artificial intelligence technologies and natural language technologies. Offering voice recognition technologies on the cloud enables smaller companies to take advantage of such technologies at considerably less expense. Companies also consider using GPT-3(Generative Pre-trained Transformer 3) an open source artificial intelligence language processing software that can generate very natural human-like interactions and high levels of user satisfaction. There is a need to increase usefulness and usability to enhance user satisfaction. This study has practical and theoretical implications for industry and academia.

• Journal of Science and Technology Studies
• /
• v.1 no.2 s.2
• /
• pp.399-422
• /
• 2001

Models for human cognition currently discussed in cognitive science cannot be appropriate ones. The symbolic model of the traditional artificial intelligence works for reasoning and problem-solving tasks, but doesn't fit for pattern recognition such as letter/sound cognition. Connectionism shows the contrary phenomena to those of the traditional artificial intelligence. Connectionist systems has been shown to be very strong in the tasks of pattern recognition but weak in most of logical tasks. Brooks' situated action theory denies the. notion of representation which is presupposed in both the traditional artificial intelligence and connectionism and suggests a subsumption model which is based on perceptions coming from real world. However, situated action theory hasn't also been well applied to human cognition so far. In emphasizing those characteristics of models I refer those models 'left-brain model', 'right-brain model', and 'robot model' respectively. After I examine those models in terms of substantial items of cognitions- mental state, mental procedure, basic element of cognition, rule of cognition, appropriate level of analysis, architecture of cognition, I draw three arguments of embodiment. I suggest a way of unifying those existing models by examining their theoretical compatability which is found in those arguments.

• Journal of the Korean Geosynthetics Society
• /
• v.18 no.4
• /
• pp.39-52
• /
• 2019

In this paper the development and implementation of an artificial intelligence (AI)-based Tunnelling Impact prediction and assessment program (SKKU-iTunnel) is presented. Program predicts tunnelling induced surface settlement and groundwater drawdown by utilizing well trained ANNs and uses these predicted values to perform the damage assessment likely to occur in nearby structures and pipelines/utilities for a given tunnel problem. Generalised artificial neural networks (ANNs) were trained, to predict the induced parameters, through databases generated by combining real field data and numerical analysis for cases that represented real field conditions. It is shown that program equipped with carefully trained ANN can predict tunnel impact assessments and perform damage assessments quiet efficiently and comparable accuracy to that of numerical analysis. This paper describes the idea and implementation details of the SKKU-iTunnel with an example for demonstration.

• Journal of the Korea Computer Graphics Society
• /
• v.29 no.3
• /
• pp.85-92
• /
• 2023

Recently, interest in artificial intelligence has increased due to the development of artificial intelligence fields such as ChatGPT and self-driving cars. However, there are still many unknown elements in training process of artificial intelligence, so that optimizing the model requires more time and effort than it needs. Therefore, there is a need for a tool or methodology that can analyze the weight changes during the training process of artificial intelligence and help out understatnding those changes. In this research, I propose a visualization system which helps people to understand the accumulated weight changes. The system calculates the weights for each training period to accumulates weight changes and stores accumulated weight changes to plot them in 3D space. This research will allow us to explore different aspect of artificial intelligence learning process, such as understanding how the model get trained and providing us an indicator on which hyperparameters should be changed for better performance. These attempts are expected to explore better in artificial intelligence learning process that is still considered as unknown and contribute to the development and application of artificial intelligence models.

• Korean Institute of Interior Design Journal
• /
• no.7
• /
• pp.70-78
• /
• 1996

Artificial Intelligence is generally concerned with tasks whose execution appears to involve some intelligence if done by humans, and knowledge-based system ( in other word, expert system) is the research about the specific domain. This concept also can be applied to interior design field. So the purpose of this study is in reconstructing the accomplishment of artificial Intelligence and knowledge engineering, searching basic theories and cased to knowledge engineering , searching basic theories and cases to formulate knowledge -based design system, and testing the posibilities how the design information can be dealt in computer system. Given that recognition , two major problems must be solved before knowledge-based CAD systems could be come practical : Firstly , identification of the interior of designers use .Secondly , representing this knowledge in a computationally effective manner. I had discussed the basic concepts on which to base a knowledge- based design model, knowledge representation schemes, and problem solving, I could find the possibility which the knowledge-based system can be applied to the interior design according to this study. But there are non-deductive, often irrational and now easily computerized design process in interior design. Those are problems which are relevant to the machine learning and the creativity in design. So there should be a lot of research about the machine learning and the creatively in design in order to construct successfully intelligent knowledge-based design system.