• Journal of Internet Computing and Services
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• v.9 no.5
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• pp.85-97
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• 2008

Recently, service-oriented systems have been issued by their properties of reducing software development time and effort by reusing functional service units. The reusability of services can effectively promote through loose coupling between services and loose coupling between services depends on component-based system. That is, the component-based system is designed by grouping the tightly coupled classes of the object-oriented system and the service-oriented system is designed by the component-based system. Therefore, to design the component-based system and service-oriented system efficiently, a metric to measure the coupling between classes accurately needs. In this paper, we propose a coupling metric between classes applying a structural property, a dynamic property, and the normalized value by 0-1. We prove the theoretical soundness of the proposed metric by the axioms of briand et al, and suggest the accuracy and practicality through a case study. We suggest the evaluation results of the proposed metric through a comparison with the conventional metrics.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.6
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• pp.18-25
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• 2006

Existing outdoor lighting evaluation methods for the city beautification at night, the measurements are limited by one point to analyze the photometric data. However, this methods could not represent the diversity of photometric result from the distance. This study aims to propose the new outdoor lighting evaluation method of structure surface luminance in accordance with the measuring distance. For the purpose, the field measurement and simulation of an illuminated structure were conducted by CS-100, Digital Photometry Instrument ProMetric 1400, and the Lightscape v 3.2 from the distance of 100[m], 300[m], 500[m]. The result shows that evaluation of the surface luminance by the distance should be measured from about 100[m] of an illuminated object for getting the familiar result from computer simulation.

• Journal of the Korean Society of Radiology
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• v.16 no.5
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• pp.595-602
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• 2022

This study tried to suggest the most efficient learning rate for accurate and efficient automatic diagnosis of medical images for chest X-ray pneumonia images using deep learning. After setting the learning rates to 0.1, 0.01, 0.001, and 0.0001 in the Inception V3 deep learning model, respectively, deep learning modeling was performed three times. And the average accuracy and loss function value of verification modeling, and the metric of test modeling were set as performance evaluation indicators, and the performance was compared and evaluated with the average value of three times of the results obtained as a result of performing deep learning modeling. As a result of performance evaluation for deep learning verification modeling performance evaluation and test modeling metric, modeling with a learning rate of 0.001 showed the highest accuracy and excellent performance. For this reason, in this paper, it is recommended to apply a learning rate of 0.001 when classifying the presence or absence of pneumonia on chest X-ray images using a deep learning model. In addition, it was judged that when deep learning modeling through the application of the learning rate presented in this paper could play an auxiliary role in the classification of the presence or absence of pneumonia on chest X-ray images. In the future, if the study of classification for diagnosis and classification of pneumonia using deep learning continues, the contents of this thesis research can be used as basic data, and furthermore, it is expected that it will be helpful in selecting an efficient learning rate in classifying medical images using artificial intelligence.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1899-1909
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• 2015

Glaucoma is one of the most common causes of blindness which is caused by increase of fluid pressure in the eye which damages the optic nerve and eventually causing vision loss. An automated technique to diagnose glaucoma disease can reduce the physicians’ effort in screening of Glaucoma in a person through the fundal retinal images. In this paper, optimal hyper analytic wavelet transform for Glaucoma detection technique from fundal retinal images is proposed. The optimal coefficients for transformation process are found out using the hybrid GSO-Cuckoo search algorithm. This technique consists of pre-processing module, optimal transformation module, feature extraction module and classification module. The implementation is carried out with MATLAB and the evaluation metrics employed are accuracy, sensitivity and specificity. Comparative analysis is carried out by comparing the hybrid GSO with the conventional GSO. The results reported in our paper show that the proposed technique has performed well and has achieved good evaluation metric values. Two 10- fold cross validated test runs are performed, yielding an average fitness of 91.13% and 96.2% accuracy with CGD-BPN (Conjugate Gradient Descent- Back Propagation Network) and Support Vector Machines (SVM) respectively. The techniques also gives high sensitivity and specificity values. The attained high evaluation metric values show the efficiency of detecting Glaucoma by the proposed technique.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.12
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• pp.1172-1183
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• 2012

Aure's tonality was considered as the sound metrics for the expression of the tonality of gear whine sound in a previous research. It was failed to use the Aure's tonality as a sound metric for the tonal impression. Thus Aures's tonality, was developed for tonal impression in previous research. However, this metric did not express well the tonality of gear whine sound since the whine sound is a non-stationary signal with frequency modulation and amplitude modulation. In this study, the new method for the tonality evaluation for a non-stationary signal is presented. It is developed based on the prominence ratio, tonality impression function, and lower threshold level. It improves the accuracy and reliability of the sound quality index being used for the sound quality evaluation of the axle-gear whine sound.

• The KIPS Transactions:PartC
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• v.12C no.4 s.100
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• pp.543-550
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• 2005

Many routing algorithms, proposed for ad-hoc wireless networks, we based on source routing scheme and shortest path route has short lifetime especially in highly dense ad-hoc wireless networks. So some routing protocols such as SSA and ABR are considering the link stability and try finding more stable route. In this paper we propose a new routing algorithm considering utilization metric based on SSA routing algerian in Ad-Hoc networks. To reduce the bottleneck by specific metric of SSA, proposed scheme makes load balancing in networks by distributing the connections to several routes. For the evaluation of the performance we compare our scheme with existent routing protocol AODV and SSA. And the results, obtained using the ns-2 network simulation platform, show good performance that reduced the number of reconstructions remarkably by distributing the whole traffic to several routes when there are several stable routes.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.6
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• pp.145-150
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• 2017

Software maintenance accounts for a large portion of the software life cycle cost. In the software maintenance phase, comprehending the legacy source code is inevitable, which takes most of the time. Source code readability is a metric of the extent of code readers' difficulty of code comprehension based on the source code itself. The better the code is readable, the easier it is for code readers to comprehend the source code. This paper proposes novel source code readability metric to quantitative measure the extent of current source code under development, which is more enhanced measurement method than previous research that dichotomously judges whether the source code was readable or not. As an evaluation, we carried out a survey and analyzed them with Regression Analysis to find best parameters of the metric.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.1
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• pp.31-38
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• 2017

In this paper, we have designed MIMO system using F-OFDM modulation. And then, we have evaluated and analyzed synchronization performance of the system. In this paper we have considered Schmidl's method, Minn's method, and Park's method. As simulation results, Schmidl's method has wide plateau of timing metric and Park's method has impulse-shape timing metric. Also, we can confirm that timing metric characteristic of synchronization estimator can be degraded by adjusting filter length of F-OFDM system. Especially, we can confirm that timing metric of synchronization estimator is shifted according to filter length of MIMO system using F-OFDM modulation and this timing metric movement can be compensated by using designed filter length.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.1
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• pp.66-73
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• 2010

Vehicles experience the impact due to harsh road conditions. Contact with a barrier on a road induces vehicles to vibrate, which brings about an impact sound. The attenuation of the impact sound is an important issue since passengers may complain about the impact noise. However, the perfect removal of impact noise is not possible as most of impact noise is caused by external conditions. It is thus necessary to make vehicles to possess more desirable sound quality characteristic of impact sound. More research is needed on objective attributes of impact sound; it is not a simple matter since impact noise is transient in nature and has a high level of sound at an instantaneous moment. A new objective attribute of impact noise is designed by using wavelet transform. Wavelet transform is appropriate for the analysis of transient signals such as impact noise. The usefulness of new objective attribute, which is a sound metric, is examined by comparison with the mean subjective rating for real impact noise of passenger cars. The new sound metric has better correlation with the mean subjective rating than already existing sound metrics

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.134-143
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• 2010

This paper proposes a framework for classifying metric-based software quality prediction models, especially case of software criticality, into four types. Models are classified along two vectors: input metric forms and the necessity of past project data. Each type has its own characteristics and its strength and weakness are compared with those of other types using newly defined criteria. Through this qualitative evaluation each organization can choose a proper model to suit its environment. My earlier studies of criticality prediction model implemented specific models in each type and evaluated their prediction performances. In this paper I analyze the experimental results and show that the characteristics of a model type is the another key of successful model selection.