• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.6
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• pp.1181-1186
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• 2019

Recently, we have been able to quickly order and pay with kiosks even at fast food restaurants, small private restaurants and cafes. However, people with disabilities who are uncomfortable with their arms and who are sitting in wheelchairs are difficult to use by pressing graphical buttons to use kiosks. Older people also feel uncomfortable to use kiosks because of their cognitive abilities to accept new information as they get older. In this paper, to solve this problem, we design and implement a order-payment system to add the voice command element of the AI speaker to the visual command element when the user interacts with the kiosk.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.6
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• pp.1137-1156
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• 2023

With the advent of artificial intelligence (AI) during the Fourth Industrial Revolution, the fashion industry has simplified the production process and overcome the technical difficulties of design. This study anticipates likely changes in the digital age and develops a model that will allow consumers to design textile patterns using AI technology. Previous studies and industrial examples of AI technology's use in the textile design industry were investigated, and a textile pattern was developed using an AI algorithm. A new textile design model was then proposed based on its application to both virtual and physical clothing. Inspired by traditional Korean masks and props, AI technology was used to input color data from open application programming interface images. By inserting these into various repeating structures, a textile design was developed and simulated as garments for both virtual and real garments. We expect that this study will establish a new textile design development method for Generation Z, who favor customized designs. This study can inform the use of personalization in generative textile design as well as the systemization of technology-driven methods for customized and participatory textile design.

• Steel and Composite Structures
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• v.47 no.2
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• pp.167-184
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• 2023

In this study, a new recentering friction device (RFD) to retrofit steel moment frame structures is introduced. The device provides both self-centering and energy dissipation capabilities for the retrofitted structure. A hybrid performance-based seismic design procedure considering multiple limit states is proposed for designing the device and the retrofitted structure. The design of the RFD is achieved by modifying the conventional performance-based seismic design (PBSD) procedure using computational intelligence techniques, namely, genetic algorithm (GA) and artificial neural network (ANN). Numerous nonlinear time-history response analyses (NLTHAs) are conducted on multi-degree of freedom (MDOF) and single-degree of freedom (SDOF) systems to train and validate the ANN to achieve high prediction accuracy. The proposed procedure and the new RFD are assessed using 2D and 3D models globally and locally. Globally, the effectiveness of the proposed device is assessed by conducting NLTHAs to check the maximum inter-story drift ratio (MIDR). Seismic fragilities of the retrofitted models are investigated by constructing fragility curves of the models for different limit states. After that, seismic life cycle cost (LCC) is estimated for the models with and without the retrofit. Locally, the stress concentration at the contact point of the RFD and the existing steel frame is checked being within acceptable limits using finite element modeling (FEM). The RFD showed its effectiveness in minimizing MIDR and eliminating residual drift for low to mid-rise steel frames models tested. GA and ANN proved to be crucial integrated parts in the modified PBSD to achieve the required seismic performance at different limit states with reasonable computational cost. ANN showed a very high prediction accuracy for transformation between MDOF and SDOF systems. Also, the proposed retrofit showed its efficiency in enhancing the seismic fragility and reducing the LCC significantly compared to the un-retrofitted models.

• Journal of Mechanical Science and Technology
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• v.18 no.11
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• pp.1923-1931
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• 2004

Manufacturing of complex surface plates in stern and stem is a major factor in cost of a preliminary ship design by computing process. If these hull plate parts are effectively classified, it helps to compute the processing cost and find the way to cut-down the processing cost. This paper presents a new method to classify surface plates effectively in the preliminary ship design using neural network. A neural-network-based ship hull plate classification program was developed and tested for the automatic classification of ship design. The input variables are regarded as Gaussian curvature distributions on the plate. Various applicable rules of network topology are applied in the ship design. In automation of hull plate classification, two different numbers of input variables are used. By observing the results of the proposed method, the effectiveness of the proposed method is discussed. As a result, high prediction rate was achieved in the ship design. Accordingly, to the initial design stage, the ship hull plate classification program can be used to predict the ship production cost. And the proposed method will contribute to reduce the production cost of ship.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.259-278
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• 2022

With the spread of Artificial Intelligence (AI), various AI-based services are expanding in the financial sector such as service recommendation, automated customer response, fraud detection system(FDS), credit scoring services, etc. At the same time, problems related to reliability and unexpected social controversy are also occurring due to the nature of data-based machine learning. The need Based on this background, this study aimed to contribute to improving trust in AI-based financial services by proposing a checklist to secure fairness in AI-based credit scoring services which directly affects consumers' financial life. Among the key elements of trustworthy AI like transparency, safety, accountability, and fairness, fairness was selected as the subject of the study so that everyone could enjoy the benefits of automated algorithms from the perspective of inclusive finance without social discrimination. We divided the entire fairness related operation process into three areas like data, algorithms, and user areas through literature research. For each area, we constructed four detailed considerations for evaluation resulting in 12 checklists. The relative importance and priority of the categories were evaluated through the analytic hierarchy process (AHP). We use three different groups: financial field workers, artificial intelligence field workers, and general users which represent entire financial stakeholders. According to the importance of each stakeholder, three groups were classified and analyzed, and from a practical perspective, specific checks such as feasibility verification for using learning data and non-financial information and monitoring new inflow data were identified. Moreover, financial consumers in general were found to be highly considerate of the accuracy of result analysis and bias checks. We expect this result could contribute to the design and operation of fair AI-based financial services.

• Korean Journal of Computational Design and Engineering
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• v.5 no.2
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• pp.127-135
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• 2000

Emergent computing paradigms such as genetic algorithms have found increased use in problems in engineering design. These computational tools have been shown to be applicable in the solution of generically difficult design optimization problems characterized by nonconvexities in the design space and the presence of discrete and integer design variables. Another aspect of these computational paradigms that have been lumped under the bread subject category of soft computing, is the domain of artificial intelligence, knowledge-based expert system, and machine learning. The paper explores a machine learning paradigm referred to as teaming classifier systems to construct the high-quality global function approximations between the design variables and a response function for subsequent use in design optimization. A classifier system is a machine teaming system which learns syntactically simple string rules, called classifiers for guiding the system's performance in an arbitrary environment. The capability of a learning classifier system facilitates the adaptive selection of the optimal number of training data according to the noise and multimodality in the design space of interest. The present study used the polynomial based response surface as global function approximation tools and showed its effectiveness in the improvement on the approximation performance.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.733-738
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• 2020

It is really hard to find an infant's App, especially for the age under 5, even though there are lots of Apps developed and distributed nowadays. The selection of the proper infant's App is difficult since the infants' App should be useful, safe and helpful for the development of their intelligence. In this research, we design the useful infant's App for the development of their intelligence by applying the AI technology for increasing the learning effect in order to satisfy the characteristics of the infants' needs. A proposed App is the collection of interesting games for infants such as picture puzzle game, coloring shapes game, pasting stickers game, and fake mobile phone feature enables them to play interesting phone game. Furthermore, the proposed App is also designed to collect and analyze the log information generated while they are playing games, share and compare with other infants' log information to increase the learning effect. After then, it figures out and learns their game tendency, intelligibility, workmanship, and apply them to the next game in order to increase their interests and concentration of the game.

• Archives of design research
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• v.11 no.2
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• pp.83-92
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• 1998

If the Industrial Revolution had been the first industrial revolution. our 21st century will witness a second industrial Revolution. Namely. we will attest to a revolution whereby we will be freed from brain work by automation systems. computers and artificial intelligence. The technological revolution of the Information society has also resulted in various changes in the area of design. Designers almost depend on the newest computers of advanced functions to drastically reduce the production time. maximize the effects. save the cost and differentiate the design products for a stronger competitiveness. Accordingly. the media of design expression are changing. In short. the design works which had been done on the plane are now being expressed on the three-dimensional cyber space. Thus, this study alms to review the effects. positive and negative. of such a trend on the design.

• Journal of Fisheries and Marine Sciences Education
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• v.25 no.1
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• pp.260-273
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• 2013

This study aims to reflect experts' opinions in analyzing a design thinking as foundation of multidisciplinary education. For this purpose, a delphi survey was conducted with 20 experts in three sessions from May 1 to June 25, 2012. To analyze the collected data, descriptive statistics, including frequency, percentage, the mean, and standard deviation were implemented, and internal reliability test on the survey instrument was carried out for statistical processing. The main results are as follows : First, the delphi analysis on intuitive thinking of design thinking suggested 7 items(to pursue the possibility of outside, to pursue the possibility of applying new forms of technology, content planning, facing a complex real-world phenomena etc.). Second, the delphi analysis on logical thinking of design thinking suggested 7 items(executed repeatedly, reasoning and verification, artificial intelligence, a decision support system etc.) Third, the delphi analysis on subjective thinking of design thinking suggested 9 items(user experience measuring, user satisfaction ratings, user requirements analysis, user interface design, behavioral responses of the human etc.). Fourth, the delphi analysis on objective information of design thinking suggested 8 items(information management system, simulation, production process, information exchange and sharing etc.). According to the results of the delphi analysis, design thinking can be seen as the foundation of multidisciplinary education. Suggestions were made for discussion about the main results and further researches.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.445-450
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• 2004

This paper describes an optimal design system for multi-disciplinary structural design. An automatic finite element (FE) mesh generation technique, which is based on the fuzzy knowledge processing and computational geometry technique, is incorporated into the system, together with a commercial FE analysis code and a commercial solid modelers. An optimum design solution or satisfactory solutions are then automatically searched using the genetic algorithms modified for real search space, together with the automated FE analysis system. With an aid of genetic algorithms, the present design system allows us to effectively obtain a multi-dimensional solutions. The developed system is successfully applied to the shape design of a micro accelerometer based on a tunnel current concept.