• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.354-356
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• 2003

The study of pedestrian behavior covers wide topics, including way finding, choice and decision make, as well as spatial cognition and environmental perception. To address the problem, simulation is now put forward as suitable technique and method for analyzing human spatial behavior. In the paper we present a development architecture for simulating tracking pedestrian in a distributed environment. We introduce and explore the potential of using mobile agent-enabled distributed implementation model as a tool for development and implementation of the simulation. Three kinds of mobile agents are designed for implementation of managing and querying data of pedestrian. Finally, simulation result of JR 10,000 passengers’ movement is developed and implemented as a case study.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.05b
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• pp.803-806
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• 2003

정보통신기술의 발전과 더불어 디지털 컨텐츠 유통시장의 환경 또한 정보, 네트워크, 기기가 하나의 큰 프레임워크를 형성하는 통합적인 형태로 변해가고 있으며, 예전의 물리적 형태의 전자상거래 환경에서 디지털화본 컨텐츠의 유통환경으로 발전해 가고 있다 그러나 디지털 컨텐츠는 신속하고 빠르게 복제가 되는 문제점 때문에 전자적 형태의 유통에 걸림돌로 자용하고 있다. 따라서 디지털 컨텐츠 유통을 위한 효율적, 지속적인 관리체계와 디지털 컨텐츠의 불법 복사/배포를 방지하는 방법이 고려되어야 한다. 본 논문에서는 디지털 컨텐츠 관리 및 저작권 보호, 컨텐츠의 출판, 유통 관리 보호 솔루션을 위한 DOI 기반의 Agent DRM 모델을 제안한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.9-11
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• 2022

Applying Reinforcement Learning in everyday applications and varied environments has proved the potential of the of the field and revealed pitfalls along the way. In robotics, a learning agent takes over gradually the control of a robot by abstracting the navigation model of the robot with its inputs and outputs, thus reducing the human intervention. The challenge for the agent is how to implement a feedback function that facilitates the learning process of an MDP problem in an environment while reducing the time of convergence for the method. In this paper we will implement a reward shaping system avoiding sparse rewards which gives fewer data for the learning agent in a ROS environment. Reward shaping prioritizes behaviours that brings the robot closer to the goal by giving intermediate rewards and helps the algorithm converge quickly. We will use a pseudocode implementation as an illustration of the method.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.349-352
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• 2015

Size of building has a direct relationship with building cost, energy use and space maintenance cost. Therefore, minimizing building size during a project development is of paramount importance against such wastes. However, incautious reduction of building size may result in crowded space, and therefore harms the functionality despite the fact that building is supposed to satisfactorily support users' activity. A well-balanced design solution is, therefore, needed at an optimum level that minimizes building size in tandem with providing sufficient space to maintain functionality. For such design, architects and engineers need to be informed accurate and reliable space-use information. We present in this paper a conceptual framework of an agent-based space-use prediction simulation system that provides individual level space-use information over time in a building in consideration of project specific user information and activity schedules, space preference, ad beavioural rules. The information will accordingly assist architects and engineers to optimize space of the building as appropriate.

• Journal of Internet Computing and Services
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• v.13 no.2
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• pp.87-98
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• 2012

Understanding agent's intent is an essential component of the human-computer interaction of ubiquitous computing. Because correct inference of subject's intention in ubiquitous computing system helps particularly to understand situations that involve collaboration among multiple agents or detection of situations that can pose a particular activity. This paper, inspired by people have a mechanism for interpreting one another's actions and for inferring the intentions and goals that underlie action, proposes an approach that allows a computing system to quickly recognize the intent of agents based on experience data acquired through prior capabilities of activities recognition. To proceed intention recognition, proposed method uses formulations of Hidden Markov Models (HMM) to model a system's prior experience and agents' action change, then makes for system infer intents in advance before the agent's actions are finalized while taking the perspective of the agent whose intent should be recognized. Quantitative validation of experimental results, while presenting an accurate rate, an early detection rate and a correct duration rate with detecting the intent of several people performing various activities, shows that proposed research contributes to implement effective intent recognition system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.4
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• pp.60-66
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• 2016

Compound logistics is a service aimed to enhance logistics efficiency by supporting that shippers and consigners jointly use logistics facilities. Many of these services have taken place both domestically and internationally, but the joint logistics services for e-commerce have not been spread yet, since the number of the parcels that the consigners transact business is usually small. As one of meaningful ways to improve utilization of compound logistics, we propose a brokerage service for shipper and consigners based on the hybrid recommendation system using very well-known classification and clustering methods. The existing recommendation system has drawn a relatively low satisfaction as it brought about one-to-one matches between consignors and logistics vendors in that such matching constrains choice range of the users to one-to-one matching each other. However, the implemented hybrid recommendation system based brokerage agent service system can provide multiple choice options to mutual users with descending ranks, which is a result of the recommendation considering transaction preferences of the users. In addition, we applied feature selection methods in order to avoid inducing a meaningless large size recommendation model and reduce a simple model. Finally, we implemented the hybrid recommendation system based brokerage agent service system that shippers and consigners can join, which is the system having capability previously described functions such as feature selection and recommendation. As a result, it turns out that the proposed hybrid recommendation based brokerage service system showed the enhanced efficiency with respect to logistics management, compared to the existing one by reporting two round simulation results.

• The KIPS Transactions:PartC
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• v.11C no.2
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• pp.171-176
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• 2004

This paper presents the design of a certain highly efficient security policy negotiation of SPS(Security Policy System) for secure network management using mobile agent system. The conventional IP security systems for secure network management have some problems. A drawback to these systems is that the required policy between each security area is different. Another problem is not possible to guarantee whether a packet is transmitted through the same path by both directions and is protected by the same policy due to the topology of the network. Unlike conventional systems, the model developed herein can be resolved by using a mobile agent technology. If each domain needs a negotiation of security policy, a mobile agent manages the result of the negotiation in the form of a passport and guarantees the authentication and reliability each other by using the passport.

• Journal of the Korea Society for Simulation
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• v.20 no.2
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• pp.29-40
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• 2011

This paper focuses on the sensitivity analysis for the calibration of an agent-based simulation that analyzes the brand-level diffusion dynamics of competing products in the domestic premium mid-sized car market. In this paper, we employ a consumer-agent model that imitates the purchasing characteristics and behaviors of the consumers. The group of consumer agents that are socially interconnected represents a virtual market. By spreading the product information from previous adopters to potential consumer agents in the virtual market, the word-of-mouth phenomenon emerges like in the real market. The phenomenon influences the product choice of potential consumer agents that causes the variation of the product diffusion dynamics. In this simulation model, it is important to calibrate the virtual market parameters(e.g., ratio of innovators, social network structure, purchase time decision method) so that the virtual market can simulate the real market. However, it is difficult to measure these parameters directly from the real market. In this paper, we analyze the diffusion dynamics of simulations under various conditions in comparison with real sales data to calibrate the parameters.

• Journal of the Korean Recycled Construction Resources Institute
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• v.10 no.1
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• pp.80-91
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• 2022

This study is to provide an prediction model of setting time of super retarding mortar based on equivalent age method under various super retarding agent contents, curing temperature, and water-binder ratio (W/B). An equation for predicting setting time using maturity was proposed. Test results indicated that the setting time can be predicted by determining the curing temperature, W/B, and super retarding agent contents and substituting it into the equation proposed in this study. The coefficient of determination of the equation is 0.9 or more, and the reliability was confirmed through the F-test. Finally, using the equation proposed in this paper, reasonable quality control is possible regarding the setting of super retarding concrete in practice.

• Journal of Biomedical Engineering Research
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• v.43 no.4
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• pp.193-198
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• 2022

Contrast enhanced magnetic resonance imaging using gadolinium-based contrast agent (GBCA) is a very useful in vivo technique to visualize the inner ear pathology including endolymphatic hydrops. Although systemic intravenous (IV) administration can visualize the perilymph space, the visualization was possible by indirect passage of contrast agent through blood-perilymph barrier. All animal experimental procedures were performed under anesthesia with 5% isoflurane. Lipopolysaccharide (LPS) was instilled into the left tympanic cavity through the tympanic membrane using a sterile 27gauge needle to induce hydrops model. Tucker-Davis Technologies system was used to measure Auditory Brainstem Responses (ABRs). For intracerebroven-tricular (ICV) administration, 25 µmol of GADOVIST (Bayer, Berlin, Germany) was used and diluted GADOVIST injection was 10 µl. MR imaging was acquired with a 9.4 Tesla MRI scanner. Transmit-receive volume coil with 40 mm inner diameter and 75 mm out diameter was used. ICV administration well demonstrated the strong enhancement along the cerebrospinal fluid (CSF) microcirculation pathway including CSF fluid in the subarachnoid space and CSF space of the inner ear structures. On the other hand, IV administration showed no contrast enhancement along the CSF microcirculation pathway and showed weak enhancement in the inner ear structures. In case of rat hydrops model, ICV administration showed that the reduced contrast enhancement in the perilymph space of the hydrops induced inner ear compared to the contrast enhancement in the perilymph space of the normal inner ear. New systemic ICV administration method provide contrast enhancement of GBCA in the inner ear through CSF microcirculation pathway.