• Journal of KIISE:Computer Systems and Theory
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• v.33 no.7
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• pp.440-447
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• 2006

Grid computing is the complex deployments of various hardware and software components. The Grid environment should provide a mechanism for real-time monitoring and notification. It is very important to implement a monitoring mechanism in the Grid environment. Most existing monitoring systems only focus on their own requirements. With the development of Grid computing technology, the extensible monitoring systems become more and more feasible and popular. In this paper, we describe our research and development works on M-Mon, a novel framework for the flexible and adaptive Grid monitoring system. M-Mon system focuses on some critical issues like scalability, reusability, runtime extensibility, protocol transparency and uniform data representation. To provide interoperability with other monitoring systems and to reuse legacy facilities with a minimum effort, our monitoring system has been developed using service-oriented architecture.

• Korean Journal of Materials Research
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• v.27 no.4
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• pp.192-198
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• 2017

Carbon nanofiber (CNF) is used as an electrode material for electrical double layer capacitors (EDLCs), and is being consistently researched to improve its electrochemical performance. However, CNF still faces important challenges due to the low mesopore volume, leading to a poor high-rate performance. In the present study, we prepared the unique architecture of the activated mesoporous CNF with a high specific surface area and high mesopore volume, which were successfully synthesized using PMMA as a pore-forming agent and the KOH activation. The activated mesoporous CNF was found to exhibit the high specific surface area of $703m^2g^{-1}$, total pore volume of $0.51cm^3g^{-1}$, average pore diameter of 2.9 nm, and high mesopore volume of 35.2 %. The activated mesoporous CNF also indicated the high specific capacitance of $143F\;g^{-1}$, high-rate performance, high energy density of $17.9-13.0W\;h\;kg^{-1}$, and excellent cycling stability. Therefore, this unique architecture with a high specific surface area and high mesopore volume provides profitable synergistic effects in terms of the increased electrical double-layer area and favorable ion diffusion at a high current density. Consequently, the activated mesoporous CNF is a promising candidate as an electrode material for high-performance EDLCs.

• Journal of Information Processing Systems
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• v.11 no.3
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• pp.370-388
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• 2015

The localization of multi-agents, such as people, animals, or robots, is a requirement to accomplish several tasks. Especially in the case of multi-robotic applications, localization is the process for determining the positions of robots and targets in an unknown environment. Many sensors like GPS, lasers, and cameras are utilized in the localization process. However, these sensors produce a large amount of computational resources to process complex algorithms, because the process requires environmental mapping. Currently, combination multi-robots or swarm robots and sensor networks, as mobile sensor nodes have been widely available in indoor and outdoor environments. They allow for a type of efficient global localization that demands a relatively low amount of computational resources and for the independence of specific environmental features. However, the inherent instability in the wireless signal does not allow for it to be directly used for very accurate position estimations and making difficulty associated with conducting the localization processes of swarm robotics system. Furthermore, these swarm systems are usually highly decentralized, which makes it hard to synthesize and access global maps, it can be decrease its flexibility. In this paper, a simple pyramid RAM-based Neural Network architecture is proposed to improve the localization process of mobile sensor nodes in indoor environments. Our approach uses the capabilities of learning and generalization to reduce the effect of incorrect information and increases the accuracy of the agent's position. The results show that by using simple pyramid RAM-base Neural Network approach, produces low computational resources, a fast response for processing every changing in environmental situation and mobile sensor nodes have the ability to finish several tasks especially in localization processes in real time.

• Korean Journal of Materials Research
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• v.20 no.3
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• pp.167-173
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• 2010

In this study, we used activated carbon (AC) and titanium oxysulfate as a titanium precursor to prepare carbon/titania composites. We then mixed it with bentonite in different ratios to make a carbon/titania/bentonite monolith for use in architecture bricks by using Phenolic rosin (PR) as a bonding agent. The physicochemical properties of the prepared composites were analyzed by BET surface area, scanning electron microscopy (SEM), X-ray diffraction (XRD), energy dispersive X-ray analysis (EDX), self-cleaning effect and bactericidal tests. The BET surface areas increased as the ratio of carbon/titania composites increased. The SEM microscopy showed that the $TiO_2$ and bentonite were coated on the surface of the AC. The XRD patterns showed a mixture structure of anatase and rutile of $TiO_2$ with a clear $SiO_2$ structure. The EDX spectra of the carbon/titania/bentonite monolith confirmed the presence of various elements, namely C, O, Ti and Si, as well as other, impure elements. Moreover, to determine the self-cleaning effect of the carbon/titania/bentonite monolith, we used methylene blue (MB, $C_{16}H_{18}N_3S{\cdot}Cl{\cdot}3H_2O$) in an aqueous solution under the irradiation of visible light. Accordingly, all of the samples had excellent degradation of the MB solution. Furthermore, it was observed that the composites with sunlight irradiation had a greater effect on E. coli than any other experimental conditions.

• Journal of the Korean Institute of Landscape Architecture
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• v.40 no.6
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• pp.127-139
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• 2012

This study aims to figure out the main agent of management in the 69 recently constructed neighborhood parks in Busan, and to analyze the present status of the main agents. For this purpose, the work resources on park and landscape management, interview to related staff, and the budget on urban parks were found as the main agents of management. In case the parks were managed by consignment or by other separate organization, this study collected resources through the homepage or personal visits. As a result for the management method on parks, about 48 parks(69.6%) were under direct management by the local governments' main office and its business offices. Eighteen parks(26.1%) were commissioned to corporation or private organizations and three parks(4.3%) were operated by both direct and commissioned management. Because of the overall management result on urban parks, the company under outsourced management is not sufficient for a comprehensive management. Such is mainly focused on the maintenance like landscape or cleaning, but have fewer programs for the users. Forty-six parks cared by the local governments are mainly small sized neighborhood parks. For the management, contract workers or short-term workers are hired. It demonstrates an urgent need to improve professional personnel and organizational system for park management. In addition, any educational or cultural facility in the park is managed by separate institutions. Thus, it is not controlled as a park facility but an independent facility with separate controls. Moreover, to solve such problems, it needs legalization on the proper employment for parks, institutional improvement, cooperative network with NGO, planning and development of the program used according to the change of time, and customer oriented program management.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.3
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• pp.235-245
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• 2005

The rapid development of computer network technology has brought the Internet as the major infrastructure to our society. But the rapid increase in malicious computer intrusions using such technology causes urgent problems of protecting our information society. The recent trends of the intrusions reflect that the intruders do not break into victim host directly and do some malicious behaviors. Rather, they tend to use some automated intrusion tools to penetrate systems. Most of the unknown types of the intrusions are caused by using such tools, with some minor modifications. These tools are mostly similar to the Previous ones, and the results of using such tools remain the same as in common patterns. In this paper, we are describing design and implementation of attacker-traceback system, which traces the intruder based on the multi-agent architecture. The system first applied SOM to classify the unknown types of the intrusion into previous similar intrusion classes. And during the intrusion analysis stage, we formalized the patterns of the tools as a knowledge base. Based on the patterns, the agent system gets activated, and the automatic tracing of the intrusion routes begins through the previous attacked host, by finding some intrusion evidences on the attacked system.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2033-2038
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• 2003

This paper describes an integrated navigation strategy for the autonomous service robot PSR. The PSR is under development at the KIST for service tasks in indoor public environments. The PSR is a multi-functional mobile-manipulator typed agent, which works in daily life. Major advantages of proposed navigation are as follows: 1) Structured control architecture for a systematic integration of various software modules. A Petri net based configuration design enables stable control flow of a robot. 2) A range sensor based generalized scheme of navigation. Any range sensor can be selectively applied using the proposed navigation scheme. 3) No need for modification of environments. (No use of artificial landmarks.) 4) Hybrid approaches combining reactive behavior as well as deliberative planner, and local grid maps as well as global topological maps. A presented experimental result shows that the proposed navigation scheme is useful for mobile service robot in practical applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1396-1414
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• 2018

With the proliferation of the Internet of Things (IoT) healthcare devices, significant interoperability issue arises where devices use proprietary data transfer protocols. The IHE PCD-01 standard has been suggested for the exchange of healthcare data in ISO/IEEE 11073 PHD data model. However, the PCD-01 is not efficient to be used in the IoT environment. This is because the use of SOAP for PCD-01 may be too complex to be implemented in the resource-constrained IoT healthcare devices. In this paper, we have designed a communication system to implement ISO/IEEE 11073 and IHE PCD-01 integration using the IETF CoAP. More specifically, we have designed the architecture and procedures, using CoAP, to seamlessly transmit the bio-signal from the tiny resource-constrained IoT healthcare devices to the server in a standardized way. We have also built the agent, gateway, and PCD-01 interface at the server, all of which are using the CoAP as a communication protocol. In order to evaluate the performance of the proposed system, we have used the PCD data to be transmitted over CoAP, MQTT, and HTTP. The evaluation of the system performance shows that the use of CoAP results in faster transaction and lesser cost than other protocols, with less battery power consumption.

• Journal of Advanced Research in Ocean Engineering
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• v.3 no.3
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• pp.136-148
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• 2017

The paper presents dual arm ROV manipulation using deep reinforcement learning. The purpose of this underwater manipulator is to investigate and excavate natural resources in ocean, finding lost aircraft blackboxes and for performing other extremely dangerous tasks without endangering humans. This research work emphasizes on a self-learning approach using Deep Reinforcement Learning (DRL). DRL technique allows ROV to learn the policy of performing manipulation task directly, from raw image data. Our proposed architecture maps the visual inputs (images) to control actions (output) and get reward after each action, which allows an agent to learn manipulation skill through trial and error method. We have trained our network in simulation. The raw images and rewards are directly provided by our simple Lua simulator. Our simulator achieve accuracy by considering underwater dynamic environmental conditions. Major goal of this research is to provide a smart self-learning way to achieve manipulation in highly dynamic underwater environment. The results showed that a dual robotic arm trained for a 3DOF movement successfully achieved target reaching task in a 2D space by considering real environmental factor.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.180-187
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• 2002

Recently, there has been an increase in the demand to enhance the intelligence of construction equipment and systems. Especially for semiautonomous and autonomous systems that have great potential for impact on the construction industry, artificial intelligence approaches are required to generate instructions and plans necessary to perform tasks in dynamically changing environments on their own. The framework for an intelligent earthwork system (IES) is suggested in this paper. It generates a plan automatically for construction equipment and provides a means of cooperation between construction equipment seamlessly. This paper describes the system architecture, control strategy, task planning method, and resource allocation method for IES.