• Nutrition Research and Practice
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• v.16 no.6
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• pp.801-812
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• 2022

BACKGROUND/OBJECTIVES: Diet planning in childcare centers is difficult because of the required knowledge of nutrition and development as well as the high design complexity associated with large numbers of food items. Artificial intelligence (AI) is expected to provide diet-planning solutions via automatic and effective application of professional knowledge, addressing the complexity of optimal diet design. This study presents the results of the evaluation of the utility of AI-generated diets for children and provides related implications. MATERIALS/METHODS: We developed 2 AI solutions for children aged 3-5 yrs using a generative adversarial network (GAN) model and a reinforcement learning (RL) framework. After training these solutions to produce daily diet plans, experts evaluated the human- and AI-generated diets in 2 steps. RESULTS: In the evaluation of adequacy of nutrition, where experts were provided only with nutrient information and no food names, the proportion of strong positive responses to RL-generated diets was higher than that of the human- and GAN-generated diets (P < 0.001). In contrast, in terms of diet composition, the experts' responses to human-designed diets were more positive when experts were provided with food name information (i.e., composition information). CONCLUSIONS: To the best of our knowledge, this is the first study to demonstrate the development and evaluation of AI to support dietary planning for children. This study demonstrates the possibility of developing AI-assisted diet planning methods for children and highlights the importance of composition compliance in diet planning. Further integrative cooperation in the fields of nutrition, engineering, and medicine is needed to improve the suitability of our proposed AI solutions and benefit children's well-being by providing high-quality diet planning in terms of both compositional and nutritional criteria.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1516-1529
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• 2023

In this paper, a motor gearbox fault-detection system based on a hierarchical flow-based model is proposed. The proposed system is used for the anomaly detection of a motion sound-based actuator module. The proposed flow-based model, which is a generative model, learns by directly modeling a data distribution function. As the objective function is the maximum likelihood value of the input data, the training is stable and simple to use for anomaly detection. The operation sound of a car's side-view mirror motor is converted into a Mel-spectrogram image, consisting of a folding signal and an unfolding signal, and used as training data in this experiment. The proposed system is composed of an encoder and a decoder. The data extracted from the layer of the pretrained feature extractor are used as the decoder input data in the encoder. This information is used in the decoder by performing an interlayer cross-scale convolution operation. The experimental results indicate that the context information of various dimensions extracted from the interlayer hierarchical data improves the defect detection accuracy. This paper is notable because it uses acoustic data and a normalizing flow model to detect outliers based on the features of experimental data.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.21-30
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• 2024

This research aims to design a system capable of generating real web pages based on deep learning and big data, in three stages. First, a classification system was established based on the industry type and functionality of e-commerce websites. Second, the types of components of web pages were systematically categorized. Third, the entire web page auto-generation system, applicable for deep learning, was designed. By re-engineering the deep learning model, which was trained with actual industrial data, to analyze and automatically generate existing websites, a directly usable solution for the field was proposed. This research is expected to contribute technically and policy-wise to the field of generative AI-based complete website creation and industrial sectors.

• The Journal of the Convergence on Culture Technology
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• v.10 no.5
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• pp.673-679
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• 2024

Recently, various contents set in the Josun Dynasty have emerged. However, there is a growing number of hanboks that do not preserve the basic original form of hanbok, such as hanboks that deviate significantly from the form of hanboks. Therefore, in this study, a system was created and implemented in the game to express various colors and patterns of hanbok using the DALL-E API in this game by examining the basic hanbok form of hanbok through literature review. However, despite the fact that the results are inconsistent depending on the quality of the Generative AI service and the limitations of not passing through the historical evidence of traditional hanbok experts, it is meaningful to present a system that uses the creativity of users to create a design that can enhance the aesthetics of traditional hanbok. In future research, we want to investigate users' preferences and develop a system that can create an image that fits them when clicking the interface.

• Archives of design research
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• v.15 no.2
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• pp.253-266
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• 2002

Web Based Instruction has its theoretical background in constructivism paradigm of education. According to social changes called information era and thanks to the sophisticated internet mechanism the constructivism in education has been dominant paradigm. In this paradigm information and knowledge are not merely given by a instructor facing the loaners. This system of instruction has n almost every field of discipline introduced. This article aims to examine how far WBI and constructivism are applicable for design education. Richard Branchia predicted that the learner oriented instruction method would become the dominant education system. He stressed an interactivity of the teacher and students. Upon this can the applicability of WBI for design education be affirmed. Furthermore, there is a dozen of successful cases like www.cyberartcenter.com) (www.digitalyeil.co.kr)', http://www.schooleweb.co.kr/, htp://www.startstudy.co.kr/among many others. This article suggests several ways to solve the problems web based design education faces, including the lesson should inevitably combine the outline and of online study.

• Journal of Christian Education in Korea
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• v.78
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• pp.57-85
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• 2024

Purpose of the study: In order to utilize artificial intelligence-generated AI in educational ministry, this study analyzes the concept of artificial intelligence and generative AI and the educational theological aspects of educational ministry to find ways to efficiently utilize artificial intelligence ChatGPT in educational ministry. Contents and methods of the study: The contents of this study are. First, the contents of this study were analyzed by dividing the concepts of artificial intelligence and generative AI into the concept of artificial intelligence, types of artificial intelligence, and generative language model AI ChatGPT. Second, the educational theological analysis of educational ministry was divided into the concept of educational ministry, the goals of educational ministry, the content of educational ministry, and the direction of educational ministry in the era of artificial intelligence. Third, the plan to use artificial intelligence ChatGPT in educational ministry is to provide tools for writing sermon manuscripts, preparation tools for worship and prayer, and church education, focusing on the five functions of the early church community. It was analyzed by dividing it into tools for teaching, tools for teaching materials for believers, and tools for serving and volunteering. Conclusion and Recommendation: The conclusion of this study is that, first, when writing sermon manuscripts through artificial intelligence ChatGPT, high-quality sermon manuscripts can be written through the preacher's spirituality, faith, and insight. Second, through artificial intelligence ChatGPT, you can efficiently design and plan worship services and prepare services that serve the congregation objectively through various scenarios. Third, by using artificial intelligence ChatGPT in church education, it can be used while maintaining a complementary relationship with teachers through collaboration with human and artificial intelligence teachers. Fourth, through artificial intelligence ChatGPT, we provide a program that allows members of the church community to share spiritual fellowship, a plan to meet the needs of church members and strengthen interdependence, and an attitude of actively welcoming new people and respecting diversity. It provides useful materials that can play an important role in giving, loving, serving, and growing together in the love of Christ. Lastly, through artificial intelligence ChatGPT, we are seeking ways to provide various information about volunteer activities, learning support for children and youth in the community, mentoring-related programs, and playing a leading role in forming a village community in the local community.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.11
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• pp.88-95
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• 1998

This paper is the result of constructing information processing system such as living creatures' brain based on artificial life techniques. The living things are best information processing system in themselves. One individual is developed from a generative cell. And a species of this individual has adapted itself to the environment through evolution. In this paper, we propose a new method of designing neural networks using biological inspired developmental and evolutionary concept. Ontogeny of organism is embodied in cellular automata(CA) and phylogeny of species is realized by evolutionary algorithms(EAs). We call 'Evolving Cellular Automata Neural Systems' as ECANSI. The connection among cells is determined by the rule of cellular automata. In order to obtain the best neural networks in given environment, we evolve the arragemetn of initial cells. The cell, that is a neuron of neural networks, is modeled on chaotic neuron with firing or rest state like biological neuron. A final output of network is measured by frequency of firing state. The effectiveness of the proposed scheme is verified by applying it to Exclusive-OR and parity problem.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.3
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• pp.127-133
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• 2009

In this study, dimensionless-cumulative rainfall curves were generated by multivariate Monte Carlo method. For generation of rainfall curve rainfall storms were divided and made into dimensionless type since it was required to remove the spatial and temporal variances as well as differences in rainfall data. The dimensionless rainfall curves were divided into 4 types, and log-ratio method was introduced to overcome the limitations that elements of dimensionless-cumulative rainfall curve should always be more than zero and the sum total should be one. Orthogonal transformation by Johnson system and the constrained non-normal multivariate Monte Carlo simulation were introduced to analyse the rainfall characteristics. The generative technique in stochastic rainfall variation using multivariate Monte Carlo method will contribute to the design and evaluation of hydrosystems and can use the establishment of the flood disaster prevention system.

• Journal of Internet Computing and Services
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• v.6 no.4
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• pp.21-35
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• 2005

Software product-lines is the software development paradigm to attain the rapid development of quality applications by customizing the reconfigurable components and composing them based on predefined software architectures. Recently various methodologies for the component-based product lines are proposed, but these don't provide the specific implementation techniques of the components in terms of variability resolution mechanism. In other hand, the several approaches to implement the component supporting the variabilities resolution are developed, but these don't define the systematic analysis and design method considering the variabilities from the initial phase. This paper proposes the integration of PLUS, the one of product line methodologies extending UML modeling, and component code generation technique in order to increase the efficiency of producing the specific product in the software product lines. In this paper, the component has the hierarchical architecture consisting of the implementation elements, and each implementation elements are implemented as XSLT scripts. The codes of the components are generated from the feature selection. Using the microwave oven product lines as case study, the development process for the reconfigurable components supporting the automatic variability resolution is described.

• Proceedings of the KAIS Fall Conference
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• 2009.05a
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• pp.565-570
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• 2009

국내의 비정형 건축물은 현재 도입기로, 동대문디자인파크, 전곡선사박물관, 부산국제영화센터 등이 건설 계획 되어지고 있지만 대부분이 실시설계 또는 착공단계에 머물고 있고, 아직까지 구체적인 시공단계에 이른 건축물이 없는 실정으로 비정형외장재의 이중곡률 (Non-Uniform Rational B-Spines)을 반영한 프로토타이핑(Prototyping), 패널화(Panelizing), 현장조립 시 기하학 통제기법, 시공오차 측정기법, As-Planned 도면과 As-Built 도면의 비교를 통한 준공도면의 작성기법 등에 대한 준비가 절실히 필요한 상황이다. 그러나 현재 비정형 건축물의 설계는 초기계획(Concept Design) 단계에서 건축가와 구조기술자의 협업 중요성만 강조되고 있고, 건축물이 비정형화됨에 따라 기하학적으로 설계 및 시공되어야 하는 건축물의 외장재에 대한 설계방법과 시공단계에서 시공품질 확보방안, 시공 하자를 유발시키는 다양한 변수에 대한 대응방안 등은 아직까지도 그 중요성을 인식하지 못하고 있는 실정이다. 따라서 본 연구에서는 비정형 건축물의 설계에 사용되는 Architectural Geometry Control 도구 중 그 활용성이 부각되어 지고 있는 Bentley 사의 Generative Components를 활용하여 비정형 건축물의 이중곡률 곡면외장재의 부재생산을 위한 패널화, 제작도면 추출에 관한 연구를 수행하고자 한다.