• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.1
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• pp.88-97
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• 2017

With the increasing of the penetration rate of large-scale wind farms, a reliable, highly available and cost-effective communication network is needed. As the failure of a WF communication network will significantly impact the control and real-time monitoring of wind turbines, network reliability should be considered into the WF design process. This paper analyzes the network reliability of different WF configurations for the Southwest Offshore project that is located in Korea. The WF consists of 20 WTs with a total capacity of 60 MW. In this paper, the performance is compared according to a variety of indices such as network unavailability, mean downtime and network cost. To increase the network reliability, partial protection and full protection were investigated as strategies that can overcome the impact of a single point of failure. Furthermore, the reliability performances of different network architectures are analyzed, evaluated and compared.

• Journal of Communications and Networks
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• v.1 no.3
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• pp.189-200
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• 1999

For admitting a hard real-time connection to an ATM network, it is required that the end-새둥 delays of cells belong-ing to the connection meet their deadlines without violating the guarantees already provided to the currently active connections. There are two kinds of methods to analyze the end-to-end delay in an ATM network. A decomposed method analyzes the worst case delay for each switch and then computes the total delay as the sum of the delays at individual switches. On the other hand, an integrated method analyzes all the switches involved in an inte-grated manner and derives the total delay directly. In this paper, we present an efficient and effecitive integrated method to compute the end-to-end delay. We evaluate the network performance under different system parameters and we compare the performance of the proposed method with the conventional decomposed and other integrated methods [1], [3], [5]-[9].

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.1
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• pp.38-55
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• 2013

Wireless network systems provide fast data transmission rates and various services to users of mobile devices such as smartphones and smart pads. Because many people use high-performance mobile devices, the use of real-time multimedia services is increasing rapidly. However, the preoccupation of resources by real-time traffic users is causing harm to other services-for example, frequent call interference, lowered service quality, and poor network performance. This paper suggests a resource allocation algorithm for effective traffic service support in a hybrid network. The main objective is to obtain an optimum value of data rates by comparing user requirements with the amount of resources that can be allocated. A new mechanism based on Adaptive-Quality of Service (QoS) and a monitoring system based on Queue-Aware are proposed. Adaptive-QoS supports effective resource control according to the type of traffic service, and the monitoring system based on Queue-Aware measures the amount of resources in order to calculate the maximum that can be allocated. We apply our algorithm to a test system and use Qualnet 4.5.1 to evaluate its performance.

• The Journal of Korea Robotics Society
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• v.12 no.3
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• pp.313-321
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• 2017

One of the most frequently performed tasks in human-robot interaction (HRI), intelligent vehicles, and security systems is face related applications such as face recognition, facial expression recognition, driver state monitoring, and gaze estimation. In these applications, accurate head pose estimation is an important issue. However, conventional methods have been lacking in accuracy, robustness or processing speed in practical use. In this paper, we propose a novel method for estimating head pose with a monocular camera. The proposed algorithm is based on a deep neural network for multi-task learning using a small grayscale image. This network jointly detects multi-view faces and estimates head pose in hard environmental conditions such as illumination change and large pose change. The proposed framework quantitatively and qualitatively outperforms the state-of-the-art method with an average head pose mean error of less than $4.5^{\circ}$ in real-time.

• Journal of Information Technology Services
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• v.10 no.3
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• pp.113-126
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• 2011

The smelting and the continuous casting of steel are important processes that determine the quality of steel products. Especially most of quality defects occur during solidification of the steel continuous casting process. Although quality control techniques such as six sigma, SQC, and TQM can be applied to the continuous casting process for improving quality of steel products, these techniques don't provide real-time analysis to identify the causes of defect occurrence. To solve problems, we have developed a detection model using decision tree which identified abnormal transactions to have a coarse grain structure. And we have compared the proposed model with models using neural network and logistic regression. Experiments on steel data showed that the performance of the proposed model was higher than those of neural network model and logistic regression model. Thus, we expect that the suggested model will be helpful to control the quality of steel products in real-time in the continuous casting process.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.8
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• pp.132-141
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• 2009

In this paper, we describe finger force estimation from surface electromyogram (sEMG) data for intuitive and delicate force control of robotic devices such as exoskeletons and robotic prostheses. Four myoelectric sites on the skin were found to offer favorable sEMG recording conditions. An artificial neural network (ANN) was implemented to map the sEMG to the force, and its structure was optimized to avoid both under- and over-fitting problems. The resulting network was tested using recorded sEMG signals from the selected myoelectric sites of three subjects in real-time. In addition, we discussed performance of force estimation results related to the length of the muscles. This work may prove useful in relaying natural and delicate commands to artificial devices that may be attached to the human body or deployed remotely.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.9
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• pp.923-928
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• 2016

The various technologies related to the monitoring human health in real-time for the emergency situations are developing these days. Mostly the human pulse is used for measuring as the vital signs so far, but the EEG became a major research trend now. However, there are some problems measuring and sending EEG signals of all the people walking down the street to the dedicated server. Especially, there are some restrictions for collecting and sending EEG signals in 2-dimensional space in real-time. Therefore, I suggests an efficient network model using 3-dimensional space of drones to avoid the restrictions. The models are designed, simulated, and evaluated with the Opnet simulator.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.6
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• pp.1229-1234
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• 2012

In this paper, we analyze the problems that the DDS middleware, which is a standard data-centric communication interface, uses the fixed packet transmission method by the pre-defined protocol for exchanging data packets. The packet transmission method selected in a fixed manner cannot handle appropriately the increasing of resource overhead in an environment where the load of the DDS network changes dynamically. If the load on the node and network exceeds the threshold, the performance of the packet transmission may be degraded rapidly. This results in a failure of ensuring the real-time characteristic of DDS middleware. To solve this problem, we propose the scheme of the adaptive packet transmission for adjusting the transmission method in real-time based on the overhead on the DDS network.

• IE interfaces
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• v.24 no.2
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• pp.119-127
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• 2011

Most companies have been increasing temporary work projects to maximize the usage of their resources. They also have been developing the effective techniques for analyzing and managing the state of the projects. In order to monitor the state of a project in real-time and predict the project's future state more accurately, this paper suggests the Bayesian Network (BN) as a tool for discovering the causes of project risk and presenting the failure probability of the project. The proposed BN modeling method with consideration of the Earned Value Management (EVM) method shows how to induce the predictive and conditional probability of the risk occurrence in the future. The advantages of the suggested model are (1) that the cause of a project risk can be easily figured out via the BN, (2) that the future value of the project can be sufficiently increased by updating relevant components of the project, and (3) that more credible prediction can be made in the similar and future situation by using the data obtained in current analysis. A numerical example is also given.

• International Journal of Precision Engineering and Manufacturing
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• v.8 no.4
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• pp.27-32
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• 2007

Gears, crucial components in modern precision machinery for power transmission mechanisms, are required to have low contacting noise with high torque transmission, which makes the use of gear-tooth profile modifications and gear-tooth surface crowning extremely efficient and valuable. Due to the shortcomings of current techniques, such as manual rectification, mechanical modification, and numerically controlled rectification, we propose a novel electrochemical gear-tooth profile modification method based on an artificial neural network control technique. The fundamentals of electrochemical tooth-profile modifications based on real-time control and a mathematical model of the process are discussed in detail. Due to the complex and uncertain relationships among the machining parameters of electrochemical tooth-profile modification processes, we used an artificial neural network to determine the required processing electric current as the tooth-profile modification requirements were supplied. The system was implemented and a practical example was used to demonstrate that this technology is feasible and has potential applications in the production of precision machinery.