• Communications for Statistical Applications and Methods
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• v.18 no.5
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• pp.667-674
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• 2011

A recent trend in software reliability engineering accounts for the coverage growth behavior during testing. The coverage growth function (representing the coverage growth behavior) has become an essential component of software reliability models. Application of a coverage growth function requires the estimation of the coverage growth function. This paper considers the problem of estimating the coverage growth function. The existing maximum likelihood method is reviewed and corrected. A method of minimizing the sum of squares of the standardized prediction error is proposed for situations where the maximum likelihood method is not applicable.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4804-4822
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• 2017

Coverage problem is a research hot spot in directional sensor networks (DSNs). However, the major problem affecting the performance of the current coverage-enhancing strategies is that they just optimize the coverage of networks, but ignore the maximum number of sleep sensors to save more energy. Aiming to find an approximate optimal method that can cover maximum area with minimum number of active sensors, in this paper, a new scheduling algorithm based on learning automata is proposed to enhance area coverage, and shut off redundant sensors as many as possible. To evaluate the performance of the proposed algorithm, several experiments are conducted. Simulation results indicate that the proposed algorithm have effective performance in terms of coverage enhancement and sleeping sensors compared to the existing algorithms.

• Journal of Biosystems Engineering
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• v.38 no.1
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• pp.18-24
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• 2013

Purpose: This study was conducted to develop an optimal combine scheduling program using Max-Coverage algorithm which derives the maximum efficiency for a specific location in harvest seasons. Methods: The combine scheduling program was operated with information about combine specification and farmland. Four operating types (Max-Coverage algorithm type, Boustrophedon path type, max quality value type, and max area type) were selected to compare quality and working capacity. Result: The working time of Max-Coverage algorithm type was shorter than others, and the total quality value of Max-Coverage algorithm and max quality value type were higher than others. Conclusion: The developed combine scheduling program using Max-Coverage algorithm will provide optimal operation and maximum quality in a limited area and time.

• Smart Media Journal
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• v.13 no.8
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• pp.9-15
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• 2024

Software testing is essential in the software development process. Modified Condition / Decision Coverage (MC/DC) is a test case derivation technique that enhances the stability and reliability of software by effectively verifying complex conditions and decision structures. We propose the MCC Test Cases (MTC) generator in this study. This generator generates Multiple Condition Coverage (MCC) test cases using binary numbers to confirm the maximum coverage value of MC/DC testing. The proposed MTC generator utilizes some conditions from the Traffic Alert and Collision Avoidance System (TCAS)-II specification. It converts them into a Comma-Separated Values (CSV) file and then validates the coverage results through the VectorCAST program. So, MC/DC testing was performed using the MCC test case to confirm the maximum coverage value when performing MC/DC tests for each condition of the TCAS-II specification. This research is helpful for the verification of MC/DC test cases by confirming the maximum coverage value when performing MC/DC tests. Moreover, having more test cases increases the likelihood of discovering defects. Therefore, it can improve the efficiency of software test coverage verification, as well as the quality and stability of software.

• Journal of Astronomy and Space Sciences
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• v.36 no.4
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• pp.225-234
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• 2019

We explore the associations between the total sunspot area, solar north-south asymmetry, and Southern Oscillation Index and the physical characteristics of clouds by calculating normalized cross-correlations, motivated by the idea that the galactic cosmic ray influx modulated by solar activity may cause changes in cloud coverage, and in turn the Earth's climate. Unlike previous studies based on the relative difference, we have employed cloud data as a whole time-series without detrending. We found that the coverage of high-level and low-level cloud is at a maximum when the solar north-south asymmetry is close to the minimum, and one or two years after the solar north-south asymmetry is at a maximum, respectively. The global surface air temperature is at a maximum five years after the solar north-south asymmetry is at a maximum, and the optical depth is at a minimum when the solar north-south asymmetry is at a maximum. We also found that during the descending period of solar activity, the coverage of low-level cloud is at a maximum, and global surface air temperature and cloud optical depth are at a minimum, and that the total column water vapor is at a maximum one or two years after the solar maximum.

• Management Science and Financial Engineering
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• v.17 no.2
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• pp.39-62
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• 2011

In wireless sensor network, since each sensor is equipped with a limited power, efficient use of the energy is important. One possible network management scheme is to cluster the sensors into several sets, so that the sensors in each of the sets can completely perform the monitoring task. Then the sensors in one set become active to perform the monitoring task and the rest of the sensors switch to a sleep state to save energy. Therefore, we rotate the roles of the active set among the sensors to maximize the network lifetime. In this paper, we suggest an optimal algorithm for the maximum lifetime coverage problem which maximizes the network lifetime. For comparison, we implemented both the heuristic proposed earlier and our algorithm, and executed computational experiments. Our algorithm outperformed the heuristic concerning the obtained network lifetimes, and it found the solutions in a reasonable amount of time.

• The Journal of Korean Society for Radiation Therapy
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• v.31 no.2
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• pp.33-41
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• 2019

Purpose: The purpose of this study is to improve the reduction of coverage of PTVs adjacent to organ at risk (OAR) by setting up overlapping Planning Target Volume (PTV) during Volumetric Modulated Arc Therapy(VMAT). Materials and Methods: In patients who received Whole Brain, Gall Bladder and Rectum radiation therapy, We compared the cover change, maximum dose, Homogenicity Index and Conformity Index of PTV and also compared the maximum dose and average dose change of Organ At Risk by organizing treatment plans that are not applied overlaped PTV and treatment plans that are applied overlaped PTV in areas where coverage is insufficient. Results: overage of treatment plans with overlapping PTVs was increased in all patients, and overall coverage was also increased in each of the four patients. The maximum dose for PTV was increased in five patients, and the Homogenicity Index and Conformity Index for all patients did not differ much. The maximum dose of the lens was increased by 1.12 times, and the maximum dose was decreased in two patients for brain stem. The mean dose of the eyeball was increased by a maximum of 1.15 times, and there was no significant difference between both parotid gland. In case of gallbladder cancer patients, the mean dose in the liver and colon was decreased, and the mean dose in the duodenum was increased. In the case of rectal cancer patients, the mean dose was reduced for both femur and bladder set as OARs. The overall MU was shown to be similar in four patients, excluding one. Conclusion: If the critical dose of OAR is considered and used properly, I think it is a useful way to improve coverage of PTV.

• Journal of the Korean Data and Information Science Society
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• v.10 no.2
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• pp.465-472
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• 1999

We considered a bootstrap method for constructing confidenc intervals for a one parameter model using multinomial sampling. The convergence rates or the proposed bootstrap method are calculated for model-based maximum likelihood estimators(MLE) using multinomial sampling. Monte Carlo simulation was used to compare the performance of bootstrap methods with normal approximations in terms of the average coverage probability criterion.

• The Journal of Information Technology
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• v.10 no.2
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• pp.47-64
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• 2007

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. Accurate predictions of software release times, and estimation of the reliability and availability of a software product require quantification of a critical element of the software testing process : test coverage. This model called enhanced non-homogeneous poission process(ENHPP). In this paper, exponential coverage and S-coverage model was reviewed, proposes the exponentiated exponential coverage reliability model, which maked out efficiency substituted for gamma and Weibull model(2 parameter shape illustrated by Gupta and Kundu(2001). In this analysis of software failure data, algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE statistics for the sake of efficient model, was employed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.7B
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• pp.567-574
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• 2008

In this paper, we propose an optimal coverage extension scheme in the OFDMA based mobile multi-hop relay system. First, we propose an optimal frequency and time assignment scheme for maximizing system throughput and analyze the frame efficiency of schemes. Then, under the given BS capacity, we find the maximum number of relay hops that can be used to estimate the maximum coverage area of a BS in a multi-hop relay system. Analytical results show that the proposed scheme is efficient in coverage extension and throughput maximization in OFDMA based multi-hop relay system. Our work may be a rough guideline to control the parameters for multi-hop relay system optimization.