• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2481-2485
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• 2003

In this paper novel concept of real reality robot game controlled by a mobile server robot is proposed. Real reality robot game means that two real robots controlled by two human operator through the internet are playing a boxing game. The mobile server robot captures playing images of the boxing game and send them to GUI on the screen of human operators’ PC. The human operator can login to boxing game from any computer in any place if he/she is permitted. Remote control of boxing robot by a motion capture system through network is implemented. Successful motion control of a boxing robot remotely controlled by a motion capture system through network can be achieved.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -1
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• pp.50-53
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• 2000

It is effectively removed noise in the image using FCNN(Fuzzy Cellular Neural Network) applying fuzzy theory to CNN(Cellular Neural Network) structure and HD(Hausdorff Distance) commonly used measures for object matching. HD calculates the distance between two point set of pixels in two-dimensional binary images without establishing correspondence. Also, this method is proposed in order to improve the operation speed. In this paper, $\alpha$-LTSHD(Least Trimmed Square HD) operator applying $\alpha$-Trimmed to LTSHD, one field of HD, is applied to FCNN structure, and it is proposed as the modified method in order to remove noise in the image. Also, it is made a comparison with the other filters by using MSE and SNR after removing noise using the FCNNS which are applied $\alpha$-LTSHD operator through the computer simulation. In a result, FCNN performance which is applied the proposed $\alpha$-LTSHD demonstrated the superiority to the other filters in the noise removal.

• 전자공학회논문지B
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• 제29B권10호
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• pp.90-99
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• 1992

In this paper, we propose a neural network model for speech recognition. The model consists of feature extraction parts and recognition parts. The interconnection model based on ${\Delta}^2$G operator was used for frequency analysis. Two features, global feature and local feature, were extracted from this model. Recognition parts consist of global grouping stage and local grouping stage. When the input pattern was coded by slope method, the recognition rate of speakers, A and B, was 100%. When the test was performed with the data of 9 speakers, the recognition rate of 91.4% was obtained.

• 한국철도학회논문집
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• 제10권1호
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• pp.34-38
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• 2007

Rail network authority have to do the safety ensuring activities including the maintenance of railway facilities, integrated performance verification between the facilities and related lolling stock and safety inspections, etc. When constructing the new lines or upgrading the conventional lines, full system commissioning should be done before the revenue service with railway operator. To develop the optimal full system commissioning model, the status of domestic and foreign railway facilities and railway accidents are analysed and the problems of the safety management are derived. As one of countermeasures for the problems, the procedures and criteria for the full system commissioning are developed.

• Journal of Information Processing Systems
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• 제13권5호
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• pp.1259-1276
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• 2017

As technologies related to sensor network are currently emerging and the use of GeoSensor is increasing along with the development of Internet of Things (IoT) technology, spatial query processing systems to efficiently process spatial sensor data are being actively studied. However, existing spatial query processing systems do not support a spatial-temporal data type and a spatial-temporal operator for processing spatialtemporal sensor data. Therefore, they are inadequate for processing spatial-temporal sensor data like GeoSensor. Accordingly, this paper developed a spatial-temporal query processing system, for efficient spatial-temporal query processing of spatial-temporal sensor data in a sensor network. Lastly, this paper verified the utility of System through a scenario, and proved that this system's performance is better than existing systems through performance assessment of performance time and memory usage.

• International Journal of Computer Science & Network Security
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• 제21권4호
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• pp.131-139
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• 2021

In current time, anomaly detection is the primary concern of the administrative authorities. Suspicious activity identification is shifting from a human operator to a machine-assisted monitoring in order to assist the human operator and react to an unexpected incident quickly. These automatic surveillance systems face many challenges due to the intrinsic complex characteristics of video sequences and foreground human motion patterns. In this paper, we propose a novel approach to detect anomalous human activity using a hybrid approach of statistical model and Genetic Programming. The feature-set of local motion patterns is generated by a statistical model from the video data in an unsupervised way. This features set is inserted to an enhanced Genetic Programming based classifier to classify normal and abnormal patterns. The experiments are performed using publicly available benchmark datasets under different real-life scenarios. Results show that the proposed methodology is capable to detect and locate the anomalous activity in the real time. The accuracy of the proposed scheme exceeds those of the existing state of the art in term of anomalous activity detection.

• Journal of Information Processing Systems
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• 제19권4호
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• pp.450-464
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• 2023

To address the problems of large system overhead and low timeliness when dealing with task scheduling in mobile edge cloud computing, a task scheduling and resource management strategy for edge cloud computing based on an improved genetic algorithm was proposed. First, a user task scheduling system model based on edge cloud computing was constructed using the Shannon theorem, including calculation, communication, and network models. In addition, a multi-objective optimization model, including delay and energy consumption, was constructed to minimize the sum of two weights. Finally, the selection, crossover, and mutation operations of the genetic algorithm were improved using the best reservation selection algorithm and normal distribution crossover operator. Furthermore, an improved legacy algorithm was selected to deal with the multi-objective problem and acquire the optimal solution, that is, the best computing task scheduling scheme. The experimental analysis of the proposed strategy based on the MATLAB simulation platform shows that its energy loss does not exceed 50 J, and the time delay is 23.2 ms, which are better than those of other comparison strategies.

• 한국통신학회:학술대회논문집
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• 한국통신학회 2004년도 하계종합학술발표회논문초록집
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• pp.123-123
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• 2004

• 디지털산업정보학회논문지
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• 제6권2호
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• pp.81-89
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• 2010

The major worldwide communication network operators have designed and are building up the NGN with various network capabilities, which conventional Internet do not have. The open network service model makes these network capabilities available to the third party of the value added service providers through the standardized API providing users with more intelligent and enhanced services. This paper proposes the open network service model as NaaS (Network as a Service) and examines service models of several levels. It is believed that these efforts presented in this paper will make the network operators expand their service ranges through the opening of invested network resources producing more various communication services for users.

• 한국생산제조학회지
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• 제18권3호
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• pp.315-320
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• 2009

The purpose of this study is to predict the roundness of Numerical Control Machining so that helps the operator to choose the right machining conditions to produce a product within the given error limits. Learning of neural network is Backpropagation theory. From this study, the base was set to setup the database to produce precisely machined product by predicting the rate of error in the fabrication facility which does not have the environment to analyze it.