• Journal of the Korean Society of Clothing and Textiles
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• v.41 no.5
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• pp.825-839
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• 2017

Generative Art (also called as the art of the algorithm) creates unexpected results, moving autonomously according to rules or algorithms. The evolution of digital media in art, which tries to seek novelty, increases the possibility of new artistic fields; subsequently, this study establishes the basis for new design approaches by analyzing visual cases of Generative Art that have emerged since the 20th century and characteristics expressed on fashion. For the methodology, the study analyzes fashion designs that have emerged since 2000, based on theoretical research that includes literature and research papers relating to Generative Art. According to the study, expression characteristics shown in fashion, based on visual properties of Generative Art, are as follows. First, abstract randomness is expressed with unexpected coincidental forms using movements of a creator and properties of materials as variables in accordance to rules or algorithms. Second, endlessly repeated pattern imitation expresses an emergent shape by endless repetition created by a modular system using rules or 3D printing using a computer algorithm. Third, the systematic variability expresses constantly changing images with a combination of system and digital media by a wearing method. It is expected that design by algorithm becomes a significant method in producing other creative ideas and expressions in modern fashion.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.327-329
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• 1998

Up-Propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden variables using top-down connections. The inversion process is iterative, utilizing a negative feedback loop that depends on an error signal propagated by bottom-up connections. The error signal is also used to learn the generative model from examples. the algorithm is benchmarked against principal component analysis in experiments on images of handwritten digits.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.186-191
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• 2023

This study would investigate the generative AIs currently in service in the era of hyperscale AIs and explore measures for the use of generative AIs, focusing on 'ChatGPT,' which has received attention as a leader of generative AIs. Among the various generative AIs, this study selected ChatGPT, which has rich application cases to conduct research, investigation, and use. This study investigated the concept, learning principle, and features of ChatGPT, identified the algorithm of conversational AI as one of the specific cases and checked how it is used. In addition, by comparing various cases of the application of conversational AIs such as Google's Bard and MS's NewBing, this study sought efficient ways to utilize them through the collected cases and conducted research on the limitations of conversational AI and precautions for its use. If connected to city-related databases, it can provide information on city infrastructure, transportation systems, and public services, so residents can easily get the information they need. We want to apply this research to enrich the lives of our citizens.

• Design Convergence Study
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• v.15 no.6
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• pp.229-241
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• 2016

In generative design computer automatically and quickly generates many alternative design solutions, and the computer algorithms which perform the design tasks are important. The main purpose of this study is to propose a computer algorithm which generates three-dimensional shapes from a two-dimensional digital image such as a photograph or a painting. The base geometry of the final shape is a cylinder or sphere. A surface of the cylinder or sphere is deformed depending on the used image. The proposed algorithm was implemented as a computer program, and the program tested with several famous paintings. The algorithm and results presented in this study implicate the possibilities of the generative design which generates three-dimensional shapes from two-dimensional images. It is necessary to find and measure the values of the generated shape, and it will be a future research to find the relations of emotional and cognitive aspects between the input images and the generated shapes. Those studies are expected to expand the possibilities of generative design.

• Korean Institute of Interior Design Journal
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• v.20 no.1
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• pp.89-97
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• 2011

Furniture design is no exception to human desire for pursuit of the nature. In various design fields, it has turned out nature-decorative method in the past, and also recently it has turned out bio-adaptive method which is more root design process using principal of generation in nature world. The purpose of this study is to analyze application methods and characteristics of fractal geometry and voronoi diagram which are most representative principals of generative design in nature by research on the example of furniture design using these principals. The results of having analyzed fumitures by generative design can be summarized as follows; design principals of fractal; superposition, scaling, repetition & gradation, deformation, distortion and voronoi diagram; individual speciation, variational patten, repetition gradation, ambiguous boundary create new design concept and emergent form in furniture design. Application methods are 'form emergence by algorithm', 'conventional process based on principals of generative design', and 'reproduction of pattern from generative design'. Biological reinterpretations and new explorations of principals of nature generation offer unbounded possibilities for furniture design.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.233-238
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• 2014

Creativity is crucial in designing and producing attractive accessaries and daily supplies as well as art works. Generative design can be a paradigm to be used to obtain novel ideas or motifs for creative design works. This paper introduces a generative design method which comes up with unique ring models using genetic algorithm. It presents how the genetic algorithm works in terms of candidate solution coding, operators, and fitness evaluation function. The proposed method allows the customers to express their personal preference and later the preference to be reflected in fitness evaluation. In the final stage of the proposed method, several ring models are suggested for customers to choose on their own. The chosen ring models can be put into physical rings with the help of a 3D printer because the models are expressed in 3D geometric structures.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2011.04a
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• pp.504-507
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• 2011

3D graphic softwares have brought design spaces beyond the limitations of Euclidean space. Moreover, as computational geometry has been considered together with algorithms, generative algorithms are being evolved. Recently 3D graphic softwares with the embedded generative algorithms allow designers to design free form curves and surfaces in a systematic way. While architectural design has been greatly affected by the advancement of 3D graphic technology, such attention has not given in the realm of structural design. Grasshopper is a platform in Rhino to deal with these Generative Algorithms and Associative modelling techniques. This study has tried to develop a module for preliminary structural configuration using Rhino with Grasshopper. To verify the proposed concept in this study, a module for designing a basic type of suspension structure is introduced.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.986-1005
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• 2022

Text steganography is one of the most imminent and promising research interests in the information security field. With the unprecedented success of the neural network and natural language processing (NLP), the last years have seen a surge of research on generative linguistic steganography (GLS). This paper provides a thorough and comprehensive review to summarize the existing key contributions, and creates a novel taxonomy for GLS according to NLP techniques and steganographic encoding algorithm, then summarizes the characteristics of generative linguistic steganographic methods properly to analyze the relationship and difference between each type of them. Meanwhile, this paper also comprehensively introduces and analyzes several evaluation metrics to evaluate the performance of GLS from diverse perspective. Finally, this paper concludes the future research work, which is more conducive to the follow-up research and innovation of researchers.

• Korean Institute of Interior Design Journal
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• v.15 no.1 s.54
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• pp.30-38
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• 2006

The new aspect of contemporary architectural design is the computer simulation of morphogenesis and evolution of the organic body. Morphogenesis and evolution is the kind of emergence that is the process of complex pattern formation from simpler rules in complex system. The development comprises the sequence of pattern formation, differentiation, morphogenesis, growth. This study analyzes the application methodology of various biomorphism in contemporary architecture. The methods of generative application by computation in architecture are self-organization, differentiation, growth algorithm via MoSS. And the methods of evolution by computation are genetic algorithm, multi-parameter in environments, phylogenetic cross-over, competing as natural selection, mutation+external constraints, generative algorithm+genetic algorithm via Genr8.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1761-1777
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• 2021

An image with infrared features and visible details is obtained by processing infrared and visible images. In this paper, a fusion method based on Laplacian pyramid and generative adversarial network is proposed to obtain high quality fusion images, termed as Laplacian-GAN. Firstly, the base and detail layers are obtained by decomposing the source images. Secondly, we utilize the Laplacian pyramid-based method to fuse these base layers to obtain more information of the base layer. Thirdly, the detail part is fused by a generative adversarial network. In addition, generative adversarial network avoids the manual design complicated fusion rules. Finally, the fused base layer and fused detail layer are reconstructed to obtain the fused image. Experimental results demonstrate that the proposed method can obtain state-of-the-art fusion performance in both visual quality and objective assessment. In terms of visual observation, the fusion image obtained by Laplacian-GAN algorithm in this paper is clearer in detail. At the same time, in the six metrics of MI, AG, EI, MS_SSIM, Q_abf and SCD, the algorithm presented in this paper has improved by 0.62%, 7.10%, 14.53%, 12.18%, 34.33% and 12.23%, respectively, compared with the best of the other three algorithms.