• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.6
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• pp.678-685
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• 2010

One of the computer application fields which started showing noticeable new growth trends in recent years is the real time communication distributed computing application field. Object-oriented(OO) real time(RT) distributed computing is a form of real-time distributed computing realized with a distributed computer system structured in the form of an object network. In this paper, we describes the application environment as the patient monitor telemedicine system with TMO structure. Vital sign information web viewer systems is also the standard protocol for medical image and transfer. In order to embrace new technologies as telemedicine service, it is important to develope the standard protocol between different systems in the hospital, as well as the communication with external hospital systems. We implemented integration patient monitor telemedicine system between vital sign web viewer systems and hospital information systems.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.455-462
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• 2020

Noise which is unwanted sound is a serious pollutant that can affect human health, as well as the working and living environment if exposed to humans. However, current noise management on the construction project is generally conducted after the noise exceeds the regulation standard, which increases the conflicts with inhabitants near the construction site and threats to the safety and productivity of construction workers. To overcome the limitations of the current noise management methods, the activities of construction equipment which is the main source of construction noise need to be managed throughout the construction period in real-time. Therefore, this paper proposed a framework for automatically detecting noise sources in construction sites in real-time based on convolutional neural networks (CNNs) according to the following four steps: (i) Step 1: Definition of the noise sources; (ii) Step 2: Data preparation; (iii) Step 3: Noise source classification using the audio CNN; and (iv) Step 4: Noise source detection using the visual CNN. The short-time Fourier transform (STFT) and temporal image processing are used to contain temporal features of the audio and visual data. In addition, the AlexNet and You Only Look Once v3 (YOLOv3) algorithms have been adopted to classify and detect the noise sources in real-time. As a result, the proposed framework is expected to immediately find construction activities as current noise sources on the video of the construction site. The proposed framework could be helpful for environmental construction managers to efficiently identify and control the noise by automatically detecting the noise sources among many activities carried out by various types of construction equipment. Thereby, not only conflicts between inhabitants and construction companies caused by construction noise can be prevented, but also the noise-related health risks and productivity degradation for construction workers and inhabitants near the construction site can be minimized.

• Proceedings of the KAIS Fall Conference
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• 2008.05a
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• pp.248-250
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• 2008

This paper proposes a prediction method to prevent traffic accident and reduce to vehicle waiting time using neural network. Computer simulation results proved reducing average vehicle waiting time which proposed coordinating green time better than electro-sensitive traffic light system dose not consider coordinating green time. Moreover, we present neural network approach for traffic accident prediction with unnormalized (actual or original collected) data. This approach is not consider the maximum value of data and possible use the network without normalizing but the predictive accuracy is better. Also, the unnormalized method shows better predictive accuracy than the normalized method given by maximum value. Therefore, we can make the best use of this model in software reliability prediction using unnormalized data. Computer simulation results proved reducing traffic accident waiting time which proposed neural network better than conventional system dosen't consider neural network.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.8
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• pp.432-444
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• 2004

In this paper, we construct the TMO-based object group model on distributed environment, and analyze and evaluate the executability for distributed real-time service of our object group model by developing the distributed real-time application simulator applying the model. The Time-triggered Message-triggered Object(TMO) is a real-time server object having real-time property itself. The TMO-based object group is defined as a set of objects which logically reconfigured the physically distributed one or more TMOs on network by a given distributed application. For supporting group management of the server objects, the TMO-based object group we suggested provides the functions which register and withdraw the solver objects as a group member to an arbitrary object group, and also provides the functions which insert and delete the access rights of server objects from clients. Also, our model was designed and implemented to support the appropriate object selection and dynamic binding service for a single TMO as well as the duplicated TMOs, and to support the real-time scheduling service for the clients which are requesting the service. Finally, we developed the Defence System against Invading Enemy Planes(DSIEP) simulator as a practical example of distributed real-time application by applying our model, and evaluated the adaptability of distributed service strategies for the group components and the executability of real-time services that the TMO-based object group model provides.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.3
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• pp.181-185
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• 2009

Recently, much attention to a self-organizing mobile ad-hoc network is escalating along with progressive deployment of wireless networks in our everyday life. Being readily deployable, the MANET (mobile ad hoc network) can find its applications to emergency medical service, customized calling service, group-based communications, and military purposes. In this paper we investigate a time slot exchange problem found in the time slot based MAC, that is designed for IEEE 802.11b interfaces composing a MANET. The paper provides a method to maintain the quality of voice call by providing a new time slot when the channel assigned for that time slot gets noisy with interferences induced from other nodes, which belong to the same and/or other subgroups. In order to assess the performance of the proposed algorithm, a set of simulations using the OPNET modeler has been performed assuming that the IEEE 802.11b interfaces are operating under a modified MAC, which is a time slot based reservation MAC implemented in the PCF part of the superframe. In a real-time voice call service over a MANET of a size 500 ${\times}$ 500 meter squares with the number of nodes up to 100, the simulation results are collected and analyzed with respect to the packet loss rate and packet delay. The results show us that the proposed time slot exchange protocol improves the quality of voice call over that of plain DCF.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.11B
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• pp.991-1000
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• 2004

This paper presents an application layer multicast tree constructing algorithm to minimize the average time delay from the sender to end-systems for the effective real-time media delivery. Simultaneously, the proposed algorithm takes into account the computing power and the network condition of each end-system as a control variable and thus avoids the undesirable case that loads are concentrated to only several end-systems. The multicast tree is constructed by clustering technique and modified Dijkstra's algorithm in two steps, i.e. tree among proxy-senders and tree in each cluster. By the experimental results, we show that the proposed algorithm can provide an effective solution.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.12
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• pp.2190-2194
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• 2010

Wind power generation system (WPGS) of Ulleung Island causes frequency and voltage fluctuation due to wind speed variation during night time. Superconducting magnetic energy storage (SMES) system can overcome the fluctuations through the fast response time of energy charging and discharging. The SMES system should be connected to the terminal of the WPGS for frequency stabilization. To demonstrated the effectiveness of SMES system for power quality improvement, Ulleung Island power network was modeled in a real time digital simulator (RTDS). The RTDS-based simulation results of power quality improvement with SMES are investigated and discussed in detail.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.865-870
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• 2018

A machine vision based industrial inspection includes defects detection and classification. Fast inspection is a fundamental problem for many applications of real-time vision systems. It requires little computation time and localizing defects robustly with high accuracy. Deep learning technique have been known not to be suitable for real-time applications. Recently a couple of fast region-based CNN algorithms for object detection are introduced, such as Faster R-CNN, and YOLOv2. We apply these methods for an industrial inspection problem. Three CNN based detection algorithms, VOV based CNN, Faster R-CNN, and YOLOv2, are experimented for defect detection on metal surface. The results for inspection time and various performance indices are compared and analysed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.1
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• pp.59-63
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• 2016

Secondary damage to the user is a problem in biometrics. A brain-wave has no shape and a malicious user may not cause secondary damage to a user. However, if user sends brain-wave signals to an authentication system using a network, a malicious user could easily capture the brain-wave signals. Then, the malicious user could access the authentication system using the captured brain-wave signals. In addition, the dataset containing the brain-wave signals is large and the transfer time is long. However, user authentication requires a real-time processing, and an encryption scheme on brain-wave signals is necessary. In this paper, we propose an efficient encryption scheme using a chaos map and adaptive junk data on the brain-wave signals for user authentication. As a result, the encrypted brain-wave signals are produced and the processing time for authentication is reasonable in real-time.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.1030-1032
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• 2015

In this paper, we developed a system that output and service using vairous contents with the inspection and management industry facilities in the operating system based on wireless network. This system can output to the display device at the same time, work management and a variety of content to the inspection facilities. And it outputs received contents of the advertising service provider in real-time. Therefore, this system support real-time facility management and various contents in the building at the same time.