• Korean Journal of Computational Design and Engineering
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• v.4 no.2
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• pp.139-152
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• 1999

This paper presents a feature-based approach to extracting machining features fro a feature-based design model. In the approach, a design feature to machining feature conversion process incrementally converts each added design feature into a machining feature or a set of machining features. The proposed approach an efficiently handle protrusion features and interacting features since it takes advantage of design feature information, design intent, and functional requirements during feature extraction. Protrusion features cannot be directly mapped into machining features so that the removal volumes surrounding protrusion features are extracted and converted it no machining features. By utilizing feature information as well as geometry information during feature extraction, the proposed approach can easily overcome inherent problems relating to feature recognition such as feature interactions and loss of design intent. In addition, a feature extraction process can be simplified, and a large set of complex part can be handled with ease.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.212-220
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• 2013

Recently, there has been tremendous increase in human-computer/machine interaction system, where the goal is to provide with an appropriate service to the user at the right time with minimal human inputs for human augmented cognition system. To develop an efficient human augmented cognition system based on human computer/machine interaction, it is important to interpret the user's implicit intention, which is vague, in addition to the explicit intention. According to cognitive visual-motor theory, human eye movements and pupillary responses are rich sources of information about human intention and behavior. In this paper, we propose a novel approach for the identification of human implicit visual search intention based on eye movement pattern and pupillary analysis such as pupil size, gradient of pupil size variation, fixation length/count for the area of interest. The proposed model identifies the human's implicit intention into three types such as navigational intent generation, informational intent generation, and informational intent disappearance. Navigational intent refers to the search to find something interesting in an input scene with no specific instructions, while informational intent refers to the search to find a particular target object at a specific location in the input scene. In the present study, based on the human eye movement pattern and pupillary analysis, we used a hierarchical support vector machine which can detect the transitions between the different implicit intents - navigational intent generation to informational intent generation and informational intent disappearance.

• (The) Korean Journal of Advertising
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• v.29 no.7
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• pp.29-53
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• 2018

In our study, we investigated the effects of position of endorser and endorser's gaze direction(direct/averted_image/averted_text) on advertising attitude, purchase intent and brand recognition using eye-tracking method. Focusing on the printed cosmetic ads which the role of endorser is important and indirect persuade route is relatively is emphasized, we conducted experiment on 36 participants in 20s. As prior studies, our results shows that participants paid attention to more and faster on specific element which the endorser is gazing at. But it was not reflected to ad attitude and purchase intent directly. When the endorser is positioned in left the side, the highest purchase intent was shown in direct gaze condition, while when the endorser is on the right side, the highest ad attitude was shown in gazing image condition. Additionally, the brand recognition task following eye-tracking experiment shows that recognition accuracy was higher only in condition which the endorser is in the left side looking at the product image. These results demonstrated that the gaze direction of endorser plays a role as attentional guidance, which means it can lead customer's attention to particular region in the printed ad, but the effect can be varied depending on the position of endorser and which type of information the endorser is gazing at. Therefore, ultimately, to increase customer's ad attitude and purchase intent, complex consideration of not only the gazing direction of the endorser, but the position of endorser and other diverse elements is necessary.

• The Korean Journal of Food And Nutrition
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• v.25 no.2
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• pp.348-356
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• 2012

This study aimed to analyze the effect of demographic characteristics of consumers and quality recognition factors on purchase intention of organic wine, and to provide preliminary data necessary for the development of wine industry. By factor analysis of collected surveys, quality recognition factors of both the experienced and non-experienced group of organic wine environment/health, varieties of grapes, price, and four brand elements. First, among demographic characteristics, only income level hae a significant influence on the changes in quality recognition causes. Each of quality recognition causes of organic wine had a significant relation with purchase intent. The result of our analysis suggested that 'environment/health' was most influential for the experienced group, and 'health' was most influential for the non-experienced group. Therefore, this hypothesis is supported.

• Journal of the Korean Society for Railway
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• v.20 no.3
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• pp.389-399
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• 2017

This study analyzes the impact on continuous use of railroad logistics by mediating the logistics performance of recognition on the logistics service quality. According to the results, economic quality, information quality and relationship quality have impacts on the intent of continuous use by fully mediating logistics performance. Based on these results, a model for intent of continuous use of railroad logistics was proposed. As for the results of this study, it can be seen that the continuous use of railroad logistics is formed by the logistics performance due to the use of railroad logistics and, for this, a practical direction is suggested: the improvement of service is required, by which the recognition can be enhanced for the economic quality, information quality and relationship quality of the customers.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.8
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• pp.738-744
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• 2013

According to the cognitive science research, the interaction intent of humans can be estimated through an analysis of the representing behaviors. This paper proposes a novel methodology for reliable intention analysis of humans by applying this approach. To identify the intention, 8 behavioral features are extracted from the 4 characteristics in human-human interaction and we outline a set of core components for nonverbal behavior of humans. These nonverbal behaviors are associated with various recognition modules including multimodal sensors which have each modality with localizing sound source of the speaker in the audition part, recognizing frontal face and facial expression in the vision part, and estimating human trajectories, body pose and leaning, and hand gesture in the spatial part. As a post-processing step, temporal confidential reasoning is utilized to improve the recognition performance and integrated human model is utilized to quantitatively classify the intention from multi-dimensional cues by applying the weight factor. Thus, interactive robots can make informed engagement decision to effectively interact with multiple persons. Experimental results show that the proposed scheme works successfully between human users and a robot in human-robot interaction.

• The Journal of Korea Robotics Society
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• v.18 no.4
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• pp.496-504
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• 2023

This paper recognizes the motion intention of the wearer using a muscle stiffness sensor and proposes a control system for a wearable robot based on this. The proposed system recognizes the onset time of the motion using sensor data, determines the assistance mode, and provides assistive torque to the hip flexion/extension motion of the wearer through the generated reference trajectory according to the determined mode. The onset time of motion was detected using the CUSUM algorithm from the muscle stiffness sensor, and by comparing the detection results of the onset time with the EMG sensor and IMU, it verified its applicability as an input device for recognizing the intention of the wearer before motion. In addition, the stability of the proposed method was confirmed by comparing the results detected according to the walking speed of two subjects (1 male and 1 female). Based on these results, the assistance mode (gait assistance mode and muscle strengthening mode) was determined based on the detection results of onset time, and a reference trajectory was generated through cubic spline interpolation according to the determined assistance mode. And, the practicality of the proposed system was also confirmed by applying it to an actual wearable robot.

• Journal of Information Technology Applications and Management
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• v.30 no.4
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• pp.11-28
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• 2023

This paper proposes a method of integrating ChatGPT with traditional chatbot systems to enhance conversational artificial intelligence(AI) and create more efficient conversational systems. Traditional chatbot systems are primarily based on classification models and are limited to intent classification and simple response generation. In contrast, ChatGPT is a state-of-the-art AI technology for natural language generation, which can generate more natural and fluent conversations. In this paper, we analyze the business service areas that can be integrated with ChatGPT and traditional chatbots, and present methods for conducting conversational scenarios through case studies of service types. Additionally, we suggest ways to integrate ChatGPT with traditional chatbot systems for intent recognition, conversation flow control, and response generation. We provide a practical implementation example of how to integrate ChatGPT with traditional chatbots, making it easier to understand and build integration methods and actively utilize ChatGPT with existing chatbots.

• Journal of Radiation Protection and Research
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• v.42 no.4
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• pp.205-211
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• 2017

Background: Radiation is used in a variety of areas, but it also poses potential risks. Although radiation is often used with great effectiveness in many applications, people perceive potential risks associated with radiation and feel anxious about the possibility of radiation exposure. Various methods of measuring radiation doses have been developed, but there is no way for the general public to measure their doses with ease. Currently, many people use smartphones, which provide information about the location of an individual phone through network connections. If a smartphone application could be developed for measuring radiation dosage, it would be a very effective way to measure individuals' radiation doses. Thus, we conducted a survey study to assess the social acceptance of such a technology by the general public and their intent to use that technology to measure radiation doses, as well as to investigate whether such an intention is correlated with anxiety and attitudes toward the use of radiation. Materials and Methods: A nationwide online survey was conducted among 355 Koreans who were 20 years old or older. Results and Discussion: Significant differences were found between the genders in attitudes, perceptions of radiation risk, and fears of exposure to radiation. However, a significant difference according to age was observed only in the intent to use a smartphone dose measurement application. Attitudes towards the use of radiation exerted a negative effect on radiation risk perception and exposure anxiety, whereas attitudes towards the use of radiation, risk perception, and anxiety about exposure were found to have a positive impact on the intent to use a smartphone application for dose measurements. Conclusion: A survey-based study was conducted to investigate how the general public perceives radiation and to examine the acceptability of a smartphone application as a personal dose monitoring device. If such an application is developed, it could be used not only to monitor an individual's dose, but also to contribute to radiation safety information infrastructure by mapping radiation in different areas, which could be utilized as a useful basis for radiation research.

• The Journal of Korea Robotics Society
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• v.14 no.3
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• pp.228-235
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• 2019

This paper presents a multiple DoFs (degrees-of-freedom) prosthetic forearm and sEMG (surface electromyogram) pattern recognition and motion intent classification of forearm amputee. The developed prosthetic forearm has 9 DoFs hand and single-DoF wrist, and the socket is designed considering wearability. In addition, the pattern recognition based on sEMG is proposed for prosthetic control. Several experiments were conducted to substantiate the performance of the prosthetic forearm. First, the developed prosthetic forearm could perform various motions required for activity of daily living of forearm amputee. It was able to control according to shape and size of the object. Additionally, the amputee was able to perform 'tying up shoe' using the prosthetic forearm. Secondly, pattern recognition and classification experiments using the sEMG signals were performed to find out whether it could classify the motions according to the user's intents. For this purpose, sEMG signals were applied to the multilayer perceptron (MLP) for training and testing. As a result, overall classification accuracy arrived at 99.6% for all participants, and all the postures showed more than 97% accuracy.