• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.9
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• pp.792-797
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• 2013

This paper has derived the conversion loss according to the synchronized condition between the transmitted and locally generated spreading signals for the civil global positioning system (GPS) receiver in the heavy wideband Gaussian noise environments. From this, the outputs of the 2-bit nonuniform quantizer, which has the minimum conversion loss, is set to ${\pm}1$ and ${\pm}2$, while the quantization step size is approximated to the jamming-to-signal power ratio.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.472-474
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• 2019

Because of the difference in network structure and loss function, Verification and identification models have their respective advantages and limitations for person reidentification (re-ID). In this work, we propose a multi-task network simultaneously computes the identification loss and verification loss for person reidentification. Given a pair of images as network input, the multi-task network simultaneously outputs the identities of the two images and whether the images belong to the same identity. In experiments, we analyze the major factors affect the accuracy of person reidentification. To address the occlusion problem and improve the generalization ability of reID models, we use the Random Erasing Augmentation (REA) method to preprocess the images. The method can be easily applied to different pre-trained networks, such as ResNet and VGG. The experimental results on the Market1501 datasets show significant and consistent improvements over the state-of-the-art methods.

• Journal of the Korea Society of Computer and Information
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• v.24 no.2
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• pp.103-109
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• 2019

Recently, as the number of families raising dogs has increased, cases of lost dogs have frequently occurred. According to US statistics, 5% of the total dogs are reported to be alive, with only 18% reporting to their owners. Therefore, a device for preventing the loss of dogs is needed, and the demand for the market is rapidly growing. Therefore, it is necessary to develop a lost device for dogs. In this paper, we developed a loss prevention device that combines low-power broadband wireless communication technology, LoRa communication method, and GPS positioning technology. The result of this study is expected to prevent the loss of dogs. It is also expected that social problems will reduce the problem of lost dogs.

• Spatial Information Research
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• v.19 no.6
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• pp.111-121
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• 2011

In this paper, we proposes a sensor node positioning algorithm that utilizes the geo-spatial elements and considers the factors to represent the propagation loss generated by the various obstacles in the urban wireless environments. First, we measures the propagation loss about the radio frequencies in major road of the urban, and defines the correlation between the measured loss and the environment information for the road and its surrounding get from Urban GIS. Secondly, through the utilization of the loss-environment correlation, we describes the detailed instruction for requiring the radio coverage decision and deploy system implementation for the wireless sensor node in urban. By the consideration of interference factor by the building and the linear structure of road, we can evaluate the path loss below 5dB RMS error. And, we proposes the way to revise the sensor node deployment based on the corelation and the measured path loss.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.291-300
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• 2006

In this research, the performance of widely used Bayesian estimators such as Bayes estimator, empirical Bayes estimator, constrained Bayes estimator and constrained empirical Bayes estimator are compared by means of a measurement under balanced loss function for the typical normal-normal situation. The proposed measurement is a weighted sum of the precisions of first and second moments. As a result, one can gets the criterion according to the size of prior variance against the population variance.

• Journal of Korea Society of Industrial Information Systems
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• v.9 no.3
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• pp.32-37
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• 2004

This paper investigates the mathematical model of multi-server retrial queueing system with the Batch Markovian Arrival Process (BMAP), the Phase type (PH) service distribution and the finite buffer. The sufficient condition for the steady state distribution existence and the algorithm for calculating this distribution are presented. Finally, a formula to solve loss probability in the case of complete admission discipline is derived.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.1
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• pp.1-6
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• 2006

Queueing models are good models for fragments of communication systems and networks, so their investigation is interesting for theory and applications. Theses queues may play an important role for the validation of different decomposition algorithms designed for investigating more general queueing networks. So, in this paper we illustrate that the batch size distribution affects the loss probability, which is the main performance measure of a finite buffer queues.

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.255-261
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• 2005

Many designed experiments require the simultaneous optimization of multiple responses. In this paper, we propose how to simultaneously optimize multiple responses for robust design when data are collected from a combined array. The proposed method is based on the quadratic loss function. An example is illustrated to show the proposed method.

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.371-382
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• 2005

The paper compares the performance of some widely used Bayesian estimators such as Bayes estimator, empirical Bayes estimator, constrained Bayes estimator and constrained Bayes estimator by means of a new measurement under squared error loss function for the typical normal-normal situation. The proposed measurement is a weighted sum of the precisions of first and second moments. As a result, one can gets the criterion according to the size of prior variance against the population variance.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.905-912
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• 2006

Support vector classification(SVC) provides more complete description of the linear and nonlinear relationships between input vectors and classifiers. In this paper we propose to solve the optimization problem of SVC with a modified hinge loss function, which enables to use an iterative reweighted least squares(IRWLS) procedure. We also introduce the approximate cross validation function to select the hyperparameters which affect the performance of SVC. Experimental results are then presented which illustrate the performance of the proposed procedure for classification.