• Journal of the Korea Society of Computer and Information
• /
• v.21 no.3
• /
• pp.39-45
• /
• 2016

In this paper, we propose a log management service model for efficient developments of android applications. The proposed model consists of two major parts which are the log collector and the log manager service. The log collector can capture the log information of a target application without modifications, because the collector is composed by aspect-oriented programming. The collected logs are transformed to chunk of data, and the chunk of data is sent to the log management service. The log management service is an android service component and an independent application in another process. So, the log management service can reduce the workload of logging in the target application. Through a case study, we show that the proposed log management service model can reduce the log processing time compared to other models without modifications of a target application.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.1 no.1
• /
• pp.131-139
• /
• 1993

Low cycle fatigue characteristics of cast aluminum alloy A356 with a yield strength and ultimate strength of 229 and 283 MPa respectively was evaluated using smooth axial specimen under strain controlled condition. Reversals to failure ranged from 16 to 107. The cast aluminum alloy exhibited cyclically strain-gardening behavior. The results of low cycle fatigue tests indicated that the conventional low cycle fatigue tests indicated that the conventional low cycle fatigue life model was not a satisfactory representation of the data. This occurred because the elastic strain-life curve was not-log-log linear and this phenomena caused a nonconservative and unsafe fatigue life prediction at both extremes of long and short lives. A linear log-log total strain-life model and a bilinear log-log elastic strain-life model were proposed in order to improve the representation of data compared to the conventional low cycle fatigue life model. Both proposed fatigue life models were statistically analyzed using F tests and successfully satisfied. However, the low cycle fatigue life model generated by the bilinear log-log elastic strain-life equation yielded a discontinuous curve with nonconservatism in the region of discontinuity. Among the models examined, the linear log-log total strain-life model provided the best representation of the low cycle fatigue data. Low cycle fatigue life prediction method based on the local strain approach could conveniently incorporated both proposed fatigue life models.

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.10
• /
• pp.69-76
• /
• 2016

In this paper, we propose a real-time remote logging model for development of android applications using LBS(Location based Service). The model has two major parts: Mobile Log Management Service and Remote Log Server. Mobile Log Management Service consists of the log collector and the remote log manager. The log collector is an aspect of AOP which can collect logs from the target application without modifications of source codes. The remote log manager has a background service component so that it can receive logs whenever the log collector captures logs from the target application. Remote Log Server communicates with Mobile Log Management Service by socket interface. Therefore, Remote Log Server can show logs in real-time. To validate the efficiency of the proposed model, we show a case study, and compare the model with other models.

• Communications for Statistical Applications and Methods
• /
• v.10 no.2
• /
• pp.291-303
• /
• 2003

This work is proposed an alternative identification method of outlying cell which is one of important issues in categorical data analysis. One finds that there is a strong relationship between the location of an outlying cell and the corresponding parameter estimates of the well-fitted log-linear model. Among parameters of log-linear model, an outlying cell is affected by interaction terms rather than main effect terms. Hence one could identify an outlying cell by investigating of parameter estimates in an appropriate log-linear model.

• Journal of Digital Convergence
• /
• v.16 no.11
• /
• pp.335-340
• /
• 2018

Commercialized speech recognition systems that have an accuracy recognition rates are used a learning model from a type of speaker dependent isolated data. However, it has a problem that shows a decrease in the speech recognition performance according to the quantity of data in noise environments. In this paper, we proposed the vector quantization based speech recognition performance improvement using maximum log likelihood in Gaussian distribution. The proposed method is the best learning model configuration method for increasing the accuracy of speech recognition for similar speech using the vector quantization and Maximum Log Likelihood with speech characteristic extraction method. It is used a method of extracting a speech feature based on the hidden markov model. It can improve the accuracy of inaccurate speech model for speech models been produced at the existing system with the use of the proposed system may constitute a robust model for speech recognition. The proposed method shows the improved recognition accuracy in a speech recognition system.

• Journal of the Korean Data and Information Science Society
• /
• v.22 no.3
• /
• pp.613-618
• /
• 2011

The proposed method is based on a penalized log partial likelihood of Cox proportional hazard model with L1-penalty. We use the iteratively reweighted least squares procedure to solve L1 penalized log partial likelihood function of Cox proportional hazard model. It provide the ecient computation including variable selection and leads to the generalized cross validation function for the model selection. Experimental results are then presented to indicate the performance of the proposed procedure.

• Journal of Advanced Marine Engineering and Technology
• /
• v.40 no.1
• /
• pp.62-68
• /
• 2016

The fingerprint, which is one of the methods of indoor localization using WiFi, has been frequently studied because of its ability to be implemented via wireless access points. This method has low positioning resolution and high computational complexity compared to other methods, caused by its dependence of reference points in the radio map. In order to compensate for these problems, this paper presents a radio map designed algorithm based on the log-distance path loss model fusing a WiFi and BLE fingerprint. The proposed algorithm designs a radio map with variable values using the log-distance path loss model and reduces distance errors using a median filter. The experimental results of the proposed algorithm, compared with existing fingerprinting methods, show that the accuracy of positioning improved by from 2.747 m to 2.112 m, and the computational complexity reduced by a minimum of 33% according to the access points.

• The Korean Journal of Applied Statistics
• /
• v.30 no.5
• /
• pp.775-791
• /
• 2017

We frequently encounter binary data in real life. Logistic, Probit, Cauchit, Complementary log-log models are often used for binary data analysis. In order to analyze binary data, Liu (2004) proposed a Robit model, in which the inverse of cdf of the Student's t distribution is used as a link function. Kim et al. (2008) also proposed a generalized t-link model to make the binary regression model more flexible. The more flexible skewed distributions allow more flexible link functions in generalized linear models. In the sense, we propose a binary data regression model using skewed generalized t distributions introduced in Theodossiou (1998). We implement R code of the proposed models using the glm function included in R base and R sgt package. We also analyze Pima Indian data using the proposed model in R.

• Convergence Security Journal
• /
• v.11 no.4
• /
• pp.85-91
• /
• 2011

Due to the large-scale application software syslmls, software reliability, software development has animportantrole. In this paper, software truncated software reliability growth model was proposed based on log-logistic distribution. According to fixed time, the intensity function, the mean value function, the reliability was estimated and the parameter estimation used to maximum likelihood. In the empirical analysis, Poisson execution time model of the existiog model in this area and the log-logistic model were compared Because log-logistic model is more efficient in tems of reliability, in this area, the log-logistic model as an alternative 1D the existiog model also were able to confim that you can use.

• Communications for Statistical Applications and Methods
• /
• v.7 no.1
• /
• pp.13-22
• /
• 2000

We consider local likelihood method with a smoothed version of the model density in stead of an original model density. For simplicity a model is assumed as the log-linear density then we were able to show that the proposed local density estimator is less affected by changes among observations but its bias increases little bit more than that of the currently used local density estimator. Hence if we use the existing method and the proposed method in a proper way we would derive the local density estimator fitting the data in a better way.