• Journal of information and communication convergence engineering
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• v.18 no.1
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• pp.8-15
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• 2020

Internet-of-Things (IoT) technologies are used everywhere, and communication is one of its core and essential aspect. To solve the networking and communication of small IoT terminals, in this paper, a communication scheme based on low-cost WiFi is proposed, which also has the advantages of good compatibility and low power consumption. At the same time, it has a convenient one-key configuration mode, which reduces the technical requirements for operators. In this study, a communication protocol is designed that mainly aims at up to dozens of domestic IoT terminals, in which the amount of data is not large, data exchange is not high, and network is unstable. According to the alarm data, update data, and equipment or network fault, the protocol can respectively transmit in real time, regularly and repeatedly. This protocol is open and easy to integrate, and after cooperating with tiny encryption algorithm, information can be safely transmitted.

• Journal of Korean Society of Transportation
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• v.13 no.1
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• pp.95-110
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• 1995

n this research neural -based model was developed to forecast link travel times , And it is also compared wiht other time series forecasting models such as Box-Jenkins model, Kalman filter model. These models are validated to evaluate the accuracy of models with real time series data gathered by the license plate method. Neural network's convergency and generalization were investigated by modifying learning rate, momentum term and the number of hidden layer units. Through this experiment, the optimum configuration of the nerual network architecture was determined. Optimumlearining rate, momentum term and the number of hidden layer units hsow 0.3, 0.5, 13 respectively. It may be applied to DRGS(dynamic route guidance system) with a minor modification. The methods are suggested at the condlusion of this paper, And there is no doubt that this neural -based model can be applied to many other itme series forecating problem such as populationforecasting vehicel volume forecasting et .

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.124-127
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• 1997

In this paper, we propose the new face detection and tracking angorithm in sequential images which have complex background. In order to apply face deteciton algorithm efficently, we convert the conventional RGB coordiantes into CIE coordonates and make the input images insensitive to luminace. And human face shapes and colors are learned using ueural network's backpropagation. For variable face size, we make mosaic size of input images vary and get the face location with various size through neural network. Besides, in sequential images, we suggest face motion tracking algorithm through image substraction processing and thresholding. At this time, for accurate face tracking, we use the face location of previous. image. Finally, we verify the real-time applicability of the proposed algorithm by the simple simulation.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.5
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• pp.343-356
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• 1991

An efficient real-time implementation of digital filtering algorithms using a multiprocessor system in a ring network is investigated. The development time and cost for implementing a high speed signal processing system can be considerably reduced because algorithm are implemented in software using commercially available digital signal processors. This method is based on a parallel block processing approach, where a continuously supplied input data is divided into blocks, and the blocks are processed concurrently by being assigned to each processor in the system. This approach not only requires a simple interconnection network but also reduces the number of communications among the processors very much. The data dependency of the blocks to be processed concurrently brings on dependency problems between the processors in the system. A systematic scheduling method has been developed by using a processors which can be used efficiently, the methods for solving dependency problems between the processors are investigated. Implementation procedures and results for FIR, recursive (IIR), and adaptive filtering algorithms are illustrated.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.822-827
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• 2004

In this paper, an intelligent fault diagnosis system is proposed for induction motors through the combination of feature extraction, genetic algorithm (GA) and neural network (ANN) techniques. Features are extracted from motor vibration signals, while reducing data transfers and making on-line application available. GA is used to select most significant features from whole feature database and optimize the ANN structure parameter. Optimized ANN diagnoses the condition of induction motors online after trained by the selected features. The combination of advanced techniques reduces the learning time and increases the diagnosis accuracy. The efficiency of the proposed system is demonstrated through motor faults of electrical and mechanical origin on the induction motors. The results of the test indicate that the proposed system is promising for real time application.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.91-97
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• 1997

The objective of a traffic management system is to promote safe driving, low pollution, short travel time, and optimized traffic flow by naturally distributing the flow of traffic through the use of suitable telecommunications media. Such traffic management systems will be improved by integrating dynamic traffic data and two-way communication media because cars can work as sensors. The purpose of this paper is to help organizations trying to select the correct telecommunications media for minimal-cost investment options without loss of functionality. The wireless communications for an intelligent transportation system (ITS) are introduced in this paper. We describe which kind of telecommunication media are suitable. FM broadcast type media or cellular phone can be recommended to provide real time traffic and roadway conditions in the first stage of ITS, because existing broadcast base station or cellular network facilities can be used. It is expected that cellular radio network or satellites are used for communication. Finally, the strategy and deployment plan of an ITS are described based on selections of telecommunication media in Korea.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.51 no.2
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• pp.68-73
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• 2002

In compared with air insulated switchgear, GIS has a high efficiency and confidence. Insulation method using $SF_6$ gas has a very excellent insulation characteristic for high voltage equipment but has a characteristic that insulation heredity is changed for internal unequal electric field. So analysis of time varying electromagnetic field in GIS is very important for structure design and trouble diagnosis process. In compared with established method, the SNM(Spatial Network Method) in this Paper can observe variation of electromagnetic field with real time and get result very similar to measurement. In order to Know variation of electromagnetic field distribution in fast moving particle, we make used of SNM.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.737-740
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• 2006

Home network system provides users with various kinds of services such as home device control, entertainment, local information service and etc. There are a lot of on-going researches and developments on home service environment regardless of time and space via convenient home devices. So, in this paper, we guide the specific model for real-time access control to various services and propose the extensible security policy model.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.193-198
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• 2022

Face Detection is one of the most important aspects of image processing, it considers a time-consuming problem in real-time applications such as surveillance systems, face recognition systems, attendance system and many. At present, commodity hardware is getting more and more heterogeneity in terms of architectures such as GPU and MIC co-processors. Utilizing those co-processors along with the existing traditional CPUs gives the algorithm a better chance to make use of both architectures to achieve faster implementations. This paper presents a hybrid implementation of the face detection based on the local binary pattern (LBP) algorithm that is deployed on both traditional CPU and MIC co-processor to enhance the speed of the LBP algorithm. The experimental results show that the proposed implementation achieved improvement in speed by 3X when compared to a single architecture individually.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.157-161
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• 2023

Reliability is one of the computable quality features of the software. To assess the reliability the software reliability growth models(SRGMS) are used at different test times based on statistical learning models. In all situations, Tradational time-based SRGMS may not be enough, and such models cannot recognize errors in small and medium sized applications.Numerous traditional reliability measures are used to test software errors during application development and testing. In the software testing and maintenance phase, however, new errors are taken into consideration in real time in order to decide the reliability estimate. In this article, we suggest using the Weibull model as a computational approach to eradicate the problem of software reliability modeling. In the suggested model, a new distribution model is suggested to improve the reliability estimation method. We compute the model developed and stabilize its efficiency with other popular software reliability growth models from the research publication. Our assessment results show that the proposed Model is worthier to S-shaped Yamada, Generalized Poisson, NHPP.