• Journal of KIISE
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• v.43 no.12
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• pp.1365-1375
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• 2016

One of the most important capabilities for autonomous service robots working in living environments is to recognize and understand the correct context in dynamically changing environment. To generate high-level context knowledge for decision-making from multiple sensory data streams, many technical problems such as multi-modal sensory data fusion, uncertainty handling, symbolic knowledge grounding, time dependency, dynamics, and time-constrained spatio-temporal reasoning should be solved. Considering these problems, this paper proposes an effective dynamic context management and spatio-temporal reasoning method for intelligent service robots. In order to guarantee efficient context management and reasoning, our algorithm was designed to generate low-level context knowledge reactively for every input sensory or perception data, while postponing high-level context knowledge generation until it was demanded by the decision-making module. When high-level context knowledge is demanded, it is derived through backward spatio-temporal reasoning. In experiments with Turtlebot using Kinect visual sensor, the dynamic context management and spatio-temporal reasoning system based on the proposed method showed high performance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.203-209
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• 2016

Digital tourism is the digital support of the tourist experience before, during and after the tourist activity[1]. The GPS-enabled mobile phones provide location-based mobile applications such as tour guide and storytelling services. In this paper, we propose the smart tour guide service platform based on GIS and develop the mobile application to provide the smart tour guide service. The proposed smart tour guide service platform consists of CMS, the multi-modal navigation system, the tour attraction content creation and management system, the tour commodity creation and management system, the smart search system, and the user terminal. The smart tour guide application supports digital tourism in the pre-tour, during tour, and post-tour using the proposed smart tour guide service platform in the popular tourist attractions in Jeju.

• Journal of KIISE:Software and Applications
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• v.35 no.4
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• pp.245-254
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• 2008

This paper proposes a unified multi-modal input framework to interface the recognition engines such as IBM ViaVoice and Microsoft handwriting-recognition system with general window applications, particularly, for pen-input displays. As soon as user pushes a hardware button attached to the pin-input display with one hand, the current window of focus such as a internet search window and a word processor is overlaid with a transparent window covering the whole desktop; upon which user inputs handwriting with the other hand, without losing the focus of attention on working context. As well as freeform handwriting on this transparent input overlay as a sketch pad, the user can dictate some words and draw diagrams to communicate with the system.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.71-77
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• 2022

In this paper, a database is collected for extending the speech synthesis model to a model that synthesizes speech according to emotions and generating facial expressions. The database is divided into male and female data, and consists of emotional speech and facial expressions. Two professional actors of different genders speak sentences in Korean. Sentences are divided into four emotions: happiness, sadness, anger, and neutrality. Each actor plays about 3300 sentences per emotion. A total of 26468 sentences collected by filming this are not overlap and contain expression similar to the corresponding emotion. Since building a high-quality database is important for the performance of future research, the database is assessed on emotional category, intensity, and genuineness. In order to find out the accuracy according to the modality of data, the database is divided into audio-video data, audio data, and video data.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.1-9
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• 2022

In this paper, we propose the Deep Learning-Based Companion Animal Abnormal Behavior Detection Service, which using video and sensor data. Due to the recent increase in households with companion animals, the pet tech industry with artificial intelligence is growing in the existing food and medical-oriented companion animal market. In this study, companion animal behavior was classified and abnormal behavior was detected based on a deep learning model using various data for health management of companion animals through artificial intelligence. Video data and sensor data of companion animals are collected using CCTV and the manufactured pet wearable device, and used as input data for the model. Image data was processed by combining the YOLO(You Only Look Once) model and DeepLabCut for extracting joint coordinates to detect companion animal objects for behavior classification. Also, in order to process sensor data, GAT(Graph Attention Network), which can identify the correlation and characteristics of each sensor, was used.

• Journal of the Korea Society of Computer and Information
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• v.29 no.4
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• pp.47-54
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• 2024

The importance of cultural arts education utilizing digital tools is increasing in terms of enhancing tech literacy, self-expression, and developing convergent capabilities. The creation process and evaluation of innovative multi-modal AI, provides expanded creative audio-visual experiences in users. In particular, the process of creating music with AI provides innovative experiences in all areas, from musical ideas to improving lyrics, editing and variations. In this study, we attempted to empirically analyze the process of performing tasks using an Audio and Music Generative AI platform and discussing with fellow learners. As a result, 12 services and 10 types of evaluation criteria were collected through voluntary participation, and divided into usage patterns and purposes. The academic, technological, and policy implications were presented for AI-powered liberal arts education with learners' perspectives.

• Journal of Korea Multimedia Society
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• v.15 no.11
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• pp.1384-1390
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• 2012

It is well known that the exercising and stimulating of fingers have an important bearing on the brain. We take note of the fact and develope a game device for improving one's health and brain ability in respect of the education and training. Especially, we develope the device focused on the balanced exercising of five finger for improving brain function. The game device is possible to used in two-ways, namely online and off-line mode. In online mode, the device is connected with other visual devices such as smart phone and smart TV and communicated with Bluetooth and it is used as a MMI(multi-modal interface) device. Whereas, in off-line mode the game device works independently and it makes possible to enjoy auditorial and tactual games without video images for promotion of brain activity and emotional cultivation. For certification of the device, we implement two games(a fishing game for off-line mode and a shooting game for online mode) for people of all age, especially good for the elderly. It is usable as a game device to offering the elderly a great help for preventing impairment of the cognitive functions.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.316-322
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• 2014

A movie recommendation system is proposed to learn a preference model of a viewer by using multimodal features of a video content and their evoked implicit responses of the viewer in synchronized manner. In this system, facial expression, body posture, and physiological signals are measured to estimate the affective states of the viewer, in accordance with the stimuli consisting of low-level and affective features from video, audio, and text streams. Experimental results show that it is possible to predict arousal response, which is measured by electrodermal activity, of a viewer from auditory and text features in a video stimuli, for estimating interestingness on the video.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.27-35
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• 2009

A paradigm of medical industry is changing quickly to u-healthcare according to entry toward an aging society and improvement of quality of life(QoL). The change toward u-healthcare is meaningful since meaning of healthcare is redefined by prevention and management instead of medical service such as diagnosis of disease and treatment. However, the interest about u-healthcare is only concentrated to derivation of new healthcare service, development of medical measurement appliances(Sensors), and integration and standardization of medical information. Therefore, in this paper, the main ai of this study is trying to realize and implement u-healthcare technology through primary philosophies of ubiquitous composition such as Disappear Computing, Invisible Computing, and Calm Computing and development of user-centered technology.

• Journal of Advanced Technology Convergence
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• v.1 no.2
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• pp.01-09
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• 2022

Recently, safety issues in companies and public institutions are no longer a task that can be postponed, and when a major safety accident occurs, not only direct financial loss, but also indirect loss of social trust in the company and public institution is greatly increased. In particular, in the case of a fatal accident, the damage is even more serious. Accordingly, as companies and public institutions expand their investments in industrial safety education and prevention, open AI learning model creation technology that enables safety management services without being affected by user behavior in industrial sites where high-risk situations exist, edge terminals System development using inter-AI collaboration technology, cloud-edge terminal linkage technology, multi-modal risk situation determination technology, and AI model learning support technology is underway. In particular, with the development and spread of artificial intelligence technology, research to apply the technology to safety issues is becoming active. Therefore, in this paper, an open cloud platform design method that can support AI model learning for high-risk site safety management is presented.