• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.5
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• pp.197-203
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• 2008

In this work, we present a novel genetic approach to solve the problem of combining power control and data rate transmission adjustment for the performance enhancement of the next generation CDMA system. We obtained the optimal solution of multi rate and power control problem by compromising slightly on SIR limit values. The proposed algorithm was able to handle many more users with comparable or faster convergent service. While this paper considered two kinds of fitness function such as maximizing the total transmission data rate and maximizing the acceptable mobiles of CDMA cellular network, the evaluation function combining these two cases or others can be also easily implemented. The simulation results showed the effectiveness and validity of our approach.

• 한국공간정보시스템학회:학술대회논문집
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• 2002.03a
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• pp.45-52
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• 2002

Artificial neural networks (ANN) have been successfully used for classifying remotely sensed imagery. However, ANN still is not the preferable choice for classification over the conventional classification methodology such as the maximum likelihood classifier commonly used in the industry production environment. This can be attributed to the ANN characteristic built-in stochastic process that creates difficulties in dealing with unequally represented training classes, and its training performance speed. In this paper we examined some practical aspects of training classes when using a back propagation neural network model for remotely sensed imagery. During the classification process of remotely sensed imagery, representative training patterns for each class are collected by polygons or by using a region-growing methodology over the imagery. The number of collected training patterns for each class may vary from several pixels to thousands. This unequally populated training data may cause the significant problems some neural network empirical models such as back-propagation have experienced. We investigate the effects of training over- or under- represented training patterns in classes and propose the pattern repopulation algorithm, and an adaptive alpha adjustment (AAA) algorithm to handle unequally represented classes. We also show the performance improvement when input patterns are presented in random fashion during the back-propagation training.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.2
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• pp.235-242
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• 1998

This study aims to detect and to reduce the multipath errors which are main errors source in high precious surveying such as GPS-aided aerial triangulation and Car Navigation. which reference receivers being fixed, when kinematic receivers move continuously, multipath is performed using smoothed code measurement and pure code measurement in the network. Through this methods, 3D RMS errors are reduced into about 30% in the single differential code solution to the kinematic receiver. This is based on the fact that the network adjustment are performed at multiple reference receivers, but positioning is carried out by the single differential methods between a reference receiver and a kinematic receiver. So it was supposed that this methods reduced the correlation errors including the atmospheric errors using the nearest receivers and can be mixed with another methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.1805-1824
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• 2013

Recently, the use of wireless body area networks (WBAN) has been increasing rapidly in medical healthcare applications. WBANs consist of smart nodes that can be used to sense and transmit vital data such as heart rate, temperature and ECG from a human body to a medical centre. WBANs depend on limited resources such as energy and bandwidth. In order to utilise these resources efficiently, a very well organized medium access control (MAC) protocol must be considered. In this paper, a new, adaptive and energy-efficient MAC protocol, entitled isMAC, is proposed for WBANs. The proposed MAC is based on multi-channel communication and aims to prolong the network lifetime by effectively employing (i) a collision prevention mechanism, (ii) a coordinator node (WCN) selection algorithm and (iii) a transmission power adjustment approach. The isMAC protocol has been developed and modelled, by using OPNET Modeler simulation software. It is based on a networking scenario that requires especially high data rates such as ECG, for performance evaluation purposes. Packet delay, network throughput and energy consumption have been chosen as performance metrics. The comparison between the simulation results of isMAC and classical IEEE 802.15.4 (ZigBee) protocol shows that isMAC significantly outperforms IEEE 802.15.4 in terms of packet delay, throughput and energy consumption.

• Journal of the Semiconductor & Display Technology
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• v.2 no.1
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• pp.7-9
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• 2003

In order to predict the moldability of an injection molded part, a simulation of filling is needed. Short shot is one of the most frequent troubles encountered during injection molding process. The adjustment of process conditions is the most economic way to troubleshoot the problematic short shot in cost and time since the mold doesn't need to be modified at all. But it is difficult to adjust the process conditions appropriately in no times since it requires an empirical knowledge of injection molding. In this paper, the intelligent CAE system synergistically combines fuzzy-neural network(FNN) for heuristic knowledge with CAE programs for analytical knowledge. To evaluate the intelligent algorithms, a cellular phone flip has been chosen as a finite element model and filling analyses have been performed with a commercial CAE software. As the results, the intelligent CAE system drastically reduces the troubleshooting time of short shot in comparison with the expert's conventional way which is similar to the golden section search algorithm.

• Proceedings of the Korean Society Of Semiconductor Equipment Technology
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• 2002.11a
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• pp.127-129
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• 2002

In order to predict the moldability of an injection molded part, a simulation of filling is needed. Short shot is one of the most frequent troubles encountered during injection molding process. The adjustment of process conditions is the most economic way to troubleshoot the problematic short shot in cost and time since the mold doesn't need to be modified at all. But it is difficult to adjust the process conditions appropriately in no times since it requires an empirical knowledge of injection molding. In this paper, the intelligent CAE system synergistically combines fuzzy-neural network(FNN) for heuristic knowledge with CAE programs for analytical knowledge. To evaluate the intelligent algorithms, a cellular phone flip has been chosen as a finite element model and filling analyses have been performed with a commercial CAE software. As the results, the intelligent CAE system drastically reduces the troubleshooting time of short shot in comparison with the expert's conventional way which is similar to the golden section search algorithm.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.8 no.1
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• pp.23-30
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• 1990

This paper is a study on the adjustment of hybrid network of which the redundants effect its precision. To estimate efficiency of triangulation, triangulation and hybrid networks, this study analyzed the variation of precision to the change of the number of redundants. In the result of this study, the RMSE of the hybrid network was decreased 78 to 82 percent in semi-major axis, 48 to 60 percent in semi-minor axis to the triangulation and 84 to 87 percent in semi-major axis, 29 to 45 percent in semi-minor axis to the triangulation. The corelation with the number of redundant between the precisions is the function of y=464.71429x＋13517.57143. The interease of the number of the redundants can improve the precision, but because the number of redundants is very important in the surveying economics, the optimum number of redundants must be studied in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.4
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• pp.670-676
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• 2008

There is a difficult plane letting a security threat to occur in Internet networks as VoIP service uses technology-based the Internet is inherent, and you protect without adjustment of the existing security solution or changes with real-time service characteristics. It is a voice to single networks The occurrence security threat that it is possible is inherent in IP networks that effort and cost to protect a data network only are complicated relatively as provide service integrated data. This paper about various response way fields to be able to prevent analysis regarding definition regarding VoIP spam and VoIP spam technology and VoIP spam.

• Nuclear Engineering and Technology
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• v.55 no.1
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• pp.100-108
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• 2023

In this study, a neural network model inspired by a one-dimensional convolution U-net is developed to automatically accelerate edge localized mode (ELM) detection from big diagnostic data of fusion devices and increase the detection accuracy regardless of the hyperparameter setting. This model recognizes the input signal patterns and overcomes the problems of existing detection algorithms, such as the prominence algorithm and those of differential methods with high sensitivity for the threshold and signal intensity. To train the model, 10 sets of discharge radiation data from the KSTAR are used and sliced into 11091 inputs of length 12 ms, of which 20% are used for validation. According to the receiver operating characteristic curves, our model shows a positive prediction rate and a true prediction rate of approximately 90% each, which is comparable to the best detection performance afforded by other algorithms using their optimized hyperparameters. The accurate and automatic ELM-burst detection methodology used in our model can be beneficial for determining plasma properties, such as the ELM frequency from big data measured in multiple experiments using machines from the KSTAR device and ITER. Additionally, it is applicable to feature detection in the time-series data of other engineering fields.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.43-48
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• 2003

This study presents the detailed methods for university facilities mapping using GPS and totalstation. In the control survey by GPS network adjustment, the level of significance for the height value of fourth order triangulation stations was estimated about loom. The accuracy analysis of height determination by totalstation for the traverse points showed that the RMSE came out 9mm to the basis of direct leveling, so it indicated that trigonometric leveling by totalstation was correct comparatively. For GPS/RTK method, the result of accuracy analysis about traverse points showed that the RMSE came out 33㎜ in horizontal location to the basis of totalstation's outcome and 15㎜ in height value to the basis of direct leveling. In the construction survey, GPS/RTK surveying is quicker and more economical than totalstation surveying in the feasible areas of GPS surveying, but there were many impossible areas lot GPS/RTK surveying by the obstacles like a building.