• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.172-174
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• 2007

In this paper, we designed a embedded system that will perform a primary role of Tangible Space implementation. This hardware includes function of image capture through camera interface, image process and sending off image information by LAN(local area network) or WLAN(wireless local area network). We define this hardware as a network based Visual Agent Platform for Tangible Space, This Visual Agent Platform includes the software that is RTLinux and CORBA

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.258-260
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• 2006

In this paper, we designed a embedded system that will perform a primary role of Tangible Space implementation. This hardware includes function of image capture through camera interface, image process and sending off image information by LAN (local area network) or WLAN(wireless local area network). We define this hardware as a network based Visual Agent Platform for Tangible Space

• 한국정보컨버전스학회:학술대회논문집
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• 2008.06a
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• pp.53-56
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• 2008

This paper reports on the ACQA(Animated agent for Conversational Question Answering) project conducted at LIMSI. The aim is to design an expressive animated conversational agent(ACA) for conducting research along two main lines: 1/ perceptual experiments(eg perception of expressivity and 3D movements in both audio and visual channels): 2/ design of human-computer interfaces requiring head models at different resolutions and the integration of the talking head in virtual scenes. The target application of this expressive ACA is a real-time question and answer speech based system developed at LIMSI(RITEL). The architecture of the system is based on distributed modules exchanging messages through a network protocol. The main components of the system are: RITEL a question and answer system searching raw text, which is able to produce a text(the answer) and attitudinal information; this attitudinal information is then processed for delivering expressive tags; the text is converted into phoneme, viseme, and prosodic descriptions. Audio speech is generated by the LIMSI selection-concatenation text-to-speech engine. Visual speech is using MPEG4 keypoint-based animation, and is rendered in real-time by Virtual Choreographer (VirChor), a GPU-based 3D engine. Finally, visual and audio speech is played in a 3D audio and visual scene. The project also puts a lot of effort for realistic visual and audio 3D rendering. A new model of phoneme-dependant human radiation patterns is included in the speech synthesis system, so that the ACA can move in the virtual scene with realistic 3D visual and audio rendering.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.16 no.1
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• pp.41-47
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• 2018

Radioactive substances, especially $^{137}Cs$ discharged in the course of Nuclear Power Plant Accident or maintenance of power plants, cause contamination of the soil. For habitation of residents and reuse of industrial land, it is inevitably necessary to decontaminate the soil. This study examines a soil washing process that has actually been used for washing of radioactive-contaminated soil. The soil washing process uses a washing agent to weaken surface tension of the soil and cesium, separating cesium from the soil. In this study, in order to raise the efficiency of the process, a flocculating agent was added to the washing water to remove fine soil and cesium. The cesium concentrations before and after applying the flocculating agent to cesium solution were measured through ICP-OES. When using 0.1 g of J-AF flocculating agent in the experiment, the maximum Cs removal performance was approximately 88%; the minimum value was 67%. Species combinations between cesium and soil were predicted using Visual MINTEQ Code; the ability to reuse the washing water or not, and the removal rate of the fine soil, determined via measurement of the turbidity after applying the flocculating agent, were determined.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.853-873
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• 2021

In recent years, deep reinforcement learning (DRL) models are enjoying great interest as their success in a variety of challenging tasks. Deep Q-Network (DQN) is a widely used deep reinforcement learning model, which trains an intelligent agent that executes optimal actions while interacting with an environment. This model is well known for its ability to surpass skilled human players across many Atari 2600 games. Although DQN has achieved excellent performance in practice, there lacks a clear understanding of why the model works. In this paper, we present a visual analytics system for understanding deep Q-network in a non-blind matter. Based on the stored data generated from the training and testing process, four coordinated views are designed to expose the internal execution mechanism of DQN from different perspectives. We report the system performance and demonstrate its effectiveness through two case studies. By using our system, users can learn the relationship between states and Q-values, the function of convolutional layers, the strategies learned by DQN and the rationality of decisions made by the agent.

• The Journal of Korea Robotics Society
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• v.19 no.3
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• pp.293-310
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• 2024

In this paper, we propose an agent model for Language-Driven Zero-Shot Object Navigation (L-ZSON) tasks, which takes in a freeform language description of an unseen target object and navigates to find out the target object in an inexperienced environment. In general, an L-ZSON agent should able to visually ground the target object by understanding the freeform language description of it and recognizing the corresponding visual object in camera images. Moreover, the L-ZSON agent should be also able to build a rich spatial context map over the unknown environment and decide efficient exploration actions based on the map until the target object is present in the field of view. To address these challenging issues, we proposes AML (Agent Model for L-ZSON), a novel L-ZSON agent model to make effective use of AI foundation models such as Large Language Model (LLM) and Vision-Language model (VLM). In order to tackle the visual grounding issue of the target object description, our agent model employs GLEE, a VLM pretrained for locating and identifying arbitrary objects in images and videos in the open world scenario. To meet the exploration policy issue, the proposed agent model leverages the commonsense knowledge of LLM to make sequential navigational decisions. By conducting various quantitative and qualitative experiments with RoboTHOR, the 3D simulation platform and PASTURE, the L-ZSON benchmark dataset, we show the superior performance of the proposed agent model.

• Science of Emotion and Sensibility
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• v.10 no.4
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• pp.523-538
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• 2007

This study examined effects of gender and empathic emotional expression of an anthropomorphic interface agent on users. assessment of the agent. In addition, it examined effects of gender and emotional expression regardless of whether visual fidelity of the agent. In Study 1, The agents were manipulated by photographs of human face. The agent expressed empathic emotion by making an other-oriented emotional response congruent with another's perceived welfare. Subjects participated in a task with the agent and then they assessed the agent by rating interpersonal assessment scale. The result reported their preference to the female agent. In addition, they tended to make positive assessment to the agent of opposite gender. In the study 2, gender and expressed emotion of the agent with low fidelity was manipulated. Subjects participated in a task with the agent and then they assessed the agent by rating the same interpersonal assessment scale as study 1. The result reported their preference to the female agent. In addition, they preferred the agent expressing empathic emotion to the agent expressing self-oriented emotion or no emotion. Though the agent had low visual fidelity, its gender and expressed empathic emotion could make a significant effect on users' assessment.

• Journal of Digital Convergence
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• v.14 no.12
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• pp.397-403
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• 2016

This research reviews the concept of Visual Literacy which is the critical base for performing convergence-style educational program of fine arts. The Visual Literacy means the ability to understand and properly deal with the visual information given to the agent such as the literacy to the written language. It is beyond doubt that the necessity of the Visual Literacy is raised because there is different visual information through new media for the entire life of young generation. Therefore, the Visual Literacy is the base for performing convergence-style education when it comes to performing convergence-style educational programs. It covers the communication abilities to utilize new media and exchange visual information one another.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.6
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• pp.584-590
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• 2000

Urban traffic situations are extremely complex and highly interactive. The multi-agent systems approach can provide a new desirable solution. Currently, a traffic simulator is needed to understand and explore the difficulties in an agent-oriented traffic control. This paper presents an agent-oriented fuzzy logic controller for multiple crossroads simulation. A fuzzy logic control simulation with variables of arrival, queue, and traffic volume could alleviate traffic congestion. We developed an agent-oriented simulator suitable for traffic junctions with η$\times$η intersections in Visual C++. The proposed method adaptively controls the cycle of traffic signals even though the traffic volume varies. The effectiveness of this method was shown through simulation of multiple intersections.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.1
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• pp.121-126
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• 2013

In the past several years there has been increasing the studies using P2P technology in the distributed system areas. In these P2P systems, the server to support the contents-information have less overloads than the composed system as the server to have resources generally. In this paper, we propose the system to support a social network P2P service based on the social network P2P system. The object of this study was to widen the use of this menu system to determine the price based on visual information by a software agent. Therefore, this system is suitable for micro, small and medium industries in the use of P2P servers and is more usable system interface for owners than previous study.