• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.3231-3239
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• 2014

After 1970-80's rapid economic and urban development, nowadays the old downtown suffers from the deterioration of physical environment, outflow of its function and cavitation of population. And this phenomenon makes urban regeneration as a new paradigm in urban development. This is the case of Myeongdong area (Jungang-dong, Monsung-dong), old downtown of Cheonan around rail station, in the same way. City government has tried many regeneration/ redevelopment projects on this area but all failed due to lack of feasibility. This study intends to suggest new viable strategic regeneration scheme of this area through research and analysis of TOD development, existing condition and problems. As a result, the area needs to be considered as a node that links bus terminal complex and central market place with walkable street. For regeneration of this area, a strategic development scheme of this area is suggested deploying private capital invested rail station, underground shopping mall, transfer center, culture complex and nature park with Myeongdong street mall.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.195-202
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• 2008

In this paper, To improve the effectiveness of security enforcement, the first contribution in this work is that we present a clustered heterogeneous WSN(Wareless Sensor Network) architecture, composed of not only resource constrained sensor nodes, but also a number of more powerful high-end devices acting as cluster heads. Compared to sensor nodes, a high-end cluster head has higher computation capability, larger storage, longer power supply, and longer radio transmission range, and it thus does not suffer from the resource scarceness problem as much as a sensor node does. A distinct feature of our heterogeneous architecture is that cluster heads are equipped with TC(trusted computing) technology, and in particular a TCG(Trusted Computing Group) compliant TPM (Trusted Platform Module) is embedded into each cluster head. According the TCG specifications, TPM is a tamper-resistant, self-contained secure coprocessor, capable of performing cryptographic functions. A TPM attached to a host establishes a trusted computing platform that provides sealed storage, and measures and reports the integrity state of the platform.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.4
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• pp.223-231
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• 2019

A continuum-based design sensitivity analysis(DSA) method is developed for electrostatic problems. To consider high order objective functions, we use 9-node finite element basis functions for analysis and DSA methods. As the design variables are parameterized with B-spline functions, smooth boundary variations are naturally obtained. To solve mesh entanglement problems during the optimization process, a mesh regularization scheme is employed. By minimizing the Dirichlet energy functional, mesh uniformity can be automatically achieved. In numerical examples for maximizing dielectrophoresis forces, the numerical results are compared with well-known electrode geometries and the obtained characteristics are discussed.

• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.37-43
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• 2018

Science DMZ is a network architecture that considers complicated network components such as dedicated network, DTN, and minimum security policy to maximize transfer efficiency. And DTN tuning is an essential component to take full advantage of Science DMZ's available bandwidth. In addition, tuning of network system should be performed concurrently to minimize packet loss due to network bottleneck. In this paper, we propose a tuning method of data transfer node and network system for maximizing transfer efficiency in Science DMZ network architecture. As a result of the performance measurement using the KREONET, the network performance after the DTN tuning shows 180% improvement than that of existing method without DTN tuning. In addition, performance of 9.4Gb/s was shown without loss of performance measurement after tuning network system applying shaping policy.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.12
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• pp.595-602
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• 2021

The robot is developing into a software-oriented shape that recognizes the surrounding situation and is given a task. Cloud Robotics Platform is a method to support Service Oriented Architecture shape for robots, and it is a cloud-based method to provide necessary tasks and motion controllers depending on the situation. As it evolves into a humanoid robot, the robot will be used to help humans in generalized daily life according to the three robot principles. Therefore, in addition to robots for specific individuals, robots as public goods that can help all humans depending on the situation will be universal. Therefore, the importance of information security in the Cloud Robotics Computing environment is analyzed to be composed of people, robots, service applications on the cloud that give intelligence to robots, and a cloud bridge that connects robots and clouds. It will become an indispensable element for In this paper, we propose a Security Scheme that can provide security for communication between people, robots, cloud bridges, and cloud systems in the Cloud Robotics Computing environment for intelligent robots, enabling robot services that are safe from hacking and protect personal information.

• Journal of IKEEE
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• v.26 no.4
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• pp.614-621
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• 2022

This paper proposes RIDS (Random Forest-Based Intrusion Detection), which is an intrusion detection system to detect hacking attack based on random forest. RIDS detects three typical attacks i.e. DoS (Denial of service) attack, fuzzing attack, and spoofing attack. It detects hacking attack based on four parameters, i.e. time interval between data frames, its deviation, Hamming distance between payloads, and its diviation. RIDS was designed in memory-centric architecture and node information is stored in memories. It was designed in scalable architecture where DoS attack, fuzzing attack, and spoofing attack can be all detected by adjusting number and depth of trees. Simulation results show that RIDS has 0.9835 accuracy and 0.9545 F1 score and it can detect three attack types effectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.1
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• pp.131-143
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• 1996

In this paper, we propose the improved structure of fully interconnected ATM Switch to develop the small sized switch element and represent practical implementation of switch network. As the part II of the full study about structure and implementation of fully interconnected ATM Switch, this paper especially describes the implementation of an ATM switching element with 8 input port and 8 output port at 155 Mbits/sec each. The single board switching element is used as a basic switching block in a small sized ATm switch for ATM LAN Hub and customer access node. This switch has dedicated bus in 12 bit width(8 bit data + 4 bit control signal) at each input and output port, bit addressing and cell filtering scheme. In this paper, we propose a practical switch architecture with fully interconnected buses to implement a small-sized switch and to provide multicast function withoutany difficulty. The design of switching element has become feasible using advanced CMOS technology and Embedded Gate Array technology. And, we also represent Application Specific Integrated Circuit(ASIC) of Switch Output Multiplexing Unit(SOMU) and 12 layered Printed Circuit Board for interconnection network of switch.

• Journal of Information Technology Services
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• v.14 no.1
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• pp.159-173
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• 2015

This paper presents a study on the Internet of Things based low-power wireless sensor networks for remote monitoring of wildlife ecosystem due to climate change. Especially, it is targeting the wild vegetation communities ecological monitoring. First, we performed a pre-test and analysis for selecting the appropriate frequency for the sensor network to collect and deliver information reliably in harsh propagation environment of the forest area, and selected for sensors for monitoring wild vegetation communities on the basis of considerations for selecting the best sensor. In addition, we have presented the platform concept and hierarchical function structures for effectively monitoring, analyzing and predicting of ecosystem changes, to apply the Internet of Things in the ecological monitoring area. Based on this, this paper presents the system architecture and design of the Internet of Things based low-power wireless sensor networks for monitoring the ecosystem of the wild vegetation communities. Finally, we constructed and operated the test-bed applied to real wild trees, using the developed prototype based on the design.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.3
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• pp.280-285
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• 2004

This paper is concerned with the modeling and identification of sequencing batch reactor (SBR) via genetic algorithm based polynomial neural network (GA-based PNN). The model describes a biological SBR used in the wastewater treatment process fur nitrogen removal. A conventional polynomial neural network (PNN) is applied to construct a predictive model of SBR process fur nitrogen removal before. But the performances of PNN depend strongly on the number of input variables available to the model, the number of input variables and type (order) of the polynomials to each node. They must be fixed by the designer in advance before the architecture is constructed. So the trial and error method must go with heavy computation burden and low efficiency. To alleviate these problems, we propose GA-based PNN. The order of the polynomial, the number of input variables, and the optimum input variables are encoded as a chromosome and fitness of each chromosome is computed. Simulation results have shown that the complex SBR process can be modeled reasonably well by the present scheme with a much simpler structure compared with the conventional PNN model.

• Structural Monitoring and Maintenance
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• v.3 no.4
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• pp.377-393
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• 2016

The present work develops an expert system for detecting and predicting the crude oil types and properties at normal temperature ${\theta}=25^{\circ}C$, by evaluating the dielectric properties of the fluid transfused inside glass fiber reinforced epoxy (GFRE) composite pipelines, by using electrical capacitance sensor (ECS) technique, then used the data measurements from ECS to predict the types of the other crude oil transfused inside the pipeline, by designing an efficient artificial neural network (ANN) architecture. The variation in the dielectric signatures are employed to design an electrical capacitance sensor (ECS) with high sensitivity to detect such problem. ECS consists of 12 electrodes mounted on the outer surface of the pipe. A finite element (FE) simulation model is developed to measure the capacitance values and node potential distribution of ECS electrodes by ANSYS and MATLAB, which are combined to simulate sensor characteristic. Radial Basis neural network (RBNN), structure is applied, trained and tested to predict the finite element (FE) results of crude oil types transfused inside (GFRE) pipe under room temperature using MATLAB neural network toolbox. The FE results are in excellent agreement with an RBNN results, thus validating the accuracy and reliability of the proposed technique.