• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.3
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• pp.306-311
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• 2016

Software reliability in the software development process is an important issue. Infinite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, reliability software cost model considering logarithmic and exponential fault detection rate based on observations from the process of software product testing was studied. Adding new fault probability using the Goel-Okumoto model that is widely used in the field of reliability problems presented. When correcting or modifying the software, finite failure non-homogeneous Poisson process model. For analysis of software reliability model considering the time-dependent fault detection rate, the parameters estimation using maximum likelihood estimation of inter-failure time data was made. The logarithmic and exponential fault detection model is also efficient in terms of reliability because it (the coefficient of determination is 80% or more) in the field of the conventional model can be used as an alternative could be confirmed. From this paper, the software developers have to consider life distribution by prior knowledge of the software to identify failure modes which can be able to help.

• ETRI Journal
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• v.42 no.1
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• pp.118-128
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• 2020

A semitransparent photovoltaic-thermal (PV/T) air collector can produce electricity and heat simultaneously. To maximize the thermal and overall efficiency of the semitransparent PV/T air collector, its availability should be maximum; this can be determined through a Markov analysis. In this paper, a Markov model is developed to select an optimized number of semitransparent PV modules in service with five states and two states by considering two parameters, namely failure rate (λ) and repair rate (μ). Three artificial neural network (ANN) models are developed to obtain the minimum cost, minimum temperature, and maximum thermal efficiency of the semitransparent PV/T air collector by setting its type appropriately and optimizing the number of photovoltaic modules and cost. An attempt is also made to achieve maximum thermal and overall efficiency for the semitransparent PV/T air collector by using ANN after obtaining its minimum temperature and available solar radiation.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.801-812
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• 1999

Change-point hazard rate models arise for example in applying "burn-in" techniques to screen defective items and in studing times until undesirable side effects occur in clinical trials. Sometimes in screening defectives it might be sensible to model two stages of burn-in. In a clinical trial there might be an initial hazard rate for a side effect which after a period of time changes to an intermediate hazard rate before settling into a long term hazard rate. In this paper we consider the multiple change points hazard rate model. The classical approach's asymptotics can be poor for the small to all moderate sample sizes often encountered in practice. We propose a Bayesian approach avoiding asymptotics to provide more reliable inference conditional only upon the data actually observed. The Bayesian models can be fitted using simulation methods. Model comparison is made using recently developed Bayesian model selection criteria. The above methodology is applied to a generated data and to a generated data and the Lawless(1982) failure times of electrical insulation.

• Journal of Korea Multimedia Society
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• v.18 no.10
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• pp.1225-1230
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• 2015

Mobile Sensor Networks (MSN) is composed of a distributed collection of mobile sensor nodes, each of which has sensing, computation, communication and locomotion capabilities. Since the routing path can be broken when some nodes on the path move to other position, MSN may have a high rate of communication failure. So, MSN has to provide a means for low-cost and low-power routing to support mobility of sensor nodes. In this paper, a limited flooding scheme for routing in MSN is proposed to allow efficient energy utilization without requiring any complicated tasks for path maintenance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.371-388
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• 2014

Cognitive Radio (CR) has been recently proposed as a promising technology to remedy the problems of spectrum scarcity and spectrum underutilization by enabling unlicensed users to opportunistically utilize temporally unused licensed spectrums in a cautious manner. In Cognitive Radio Ad Hoc Networks (CRAHNs), data routing is one of the most challenging tasks since the channel availability and node mobility are unpredictable. Moreover, the network performance is severely degraded due to large numbers of path failures. In this paper, we propose the Fault-Tolerant Cognitive Ad-hoc Routing Protocol (FTCARP) to provide fast and efficient route recovery in presence of path failures during data delivery in CRAHNs. The protocol exploits the joint path and spectrum diversity to offer reliable communication and efficient spectrum usage over the networks. In the proposed protocol, a backup path is utilized in case a failure occurs over a primary transmission route. Different cause of a path failure will be handled by different route recovery mechanism. The protocol performance is compared with that of the Dual Diversity Cognitive Ad-hoc Routing Protocol (D2CARP). The simulation results obviously prove that FTCARP outperforms D2CARP in terms of throughput, packet loss, end-to-end delay and jitter in the high path-failure rate CRAHNs.

• Journal of Power Electronics
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• v.3 no.3
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• pp.145-150
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• 2003

Reliability, availability, and cost have been the major concerns for photovoltaic hybrid systems since their beginning as primary sources for much critical applications like communication units and repeaters. This paper descnbes the performance of two hybrid systems, photovoltaic-battery, wind-turbine coupled with the public-grid (PVBWG) hybrid system and photovoltaic-battery, wind-turbine coupled With the diesel generator (PVBWD) hybrid system The systems are sized to power a typical 300W/48V de telecommunication load continuously throughout the year Such hybrid systems consist of subsystems, which in turn consist of components Failure of anyone of these components may cause failure of the entire system. The reliability and availability basics, and estimation procedure for the two proposals are introduced also in this paper. The PVBWG and PVBWD system configurations are shown with the relevant mean-time-between-faIlure (MTBF) and failure rate (${\lambda}$) of each component. The characteristics equations of the two systems are deduced as a function of operating hours and the percentage of sun and wind availabilities per day. The system probability failure as well as the reliability is estimated based on the fault tree analysis technique. The results show that, by using standard or normal components MTBF, the PVBWG is more reliable and the time of periodic maintenance period is more than one year especially in the rich sites of both sun and wind, but PVBWD competes else Also, in the first five years from the system installation, the system is quit reliable and may not require any maintenance. The results show also, as the sun and wind are available, as the system reliable and available.

• Journal of the Korea Society for Simulation
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• v.25 no.2
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• pp.31-40
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• 2016

Wireless sensor networks have been used in many applications such as marine environment, army installation, etc. The sensor data is very important, because all these applications depend on sensor data. The possibility of communication failures becomes high since the surrounding environment of a wireless sense network has an sensitive effect on its communications. In particular, communication failures in underwater communications occur more frequently because of a narrow bandwidth, slow transmission speed, noises from the surrounding environments and so on. In cases of communication failures, the sensor data can be lost in the sensor data delivery process and these kinds of sensor data losses can make critical huge physical damages on human or environments in applications such as fire surveillance systems. For this reason, although a few of studies for storing and compressing sensor data have been proposed, there are lots of difficulties in actual realization of the studies due to none-existence of the framework using network communications. In this paper, we propose a framework for reducing loss of the sensor data and analyze its performance. The our analyzed results in non-framework application show a decreasing data recovery rate, T/t, as t time passes after a network failure, where T is a time period to fill the storage with sensor data after the network failure. Moreover, all the sensor data generated after a network failure are the errors impossible to recover. But, on the other hand, the analyzed results in framework application show 100% data recovery rate with 2~6% data error rate after data recovery.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.5
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• pp.345-353
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• 2015

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do parameter inference for software reliability models based on finite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision to market software, the conditional failure rate is an important variables. In this case, finite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outlier, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, proposed a control mechanism based on NHPP using mean value function of polynomial hazard function.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.6
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• pp.483-490
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• 2015

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do likelihood inference for software reliability models based on finite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision about when to market software, the conditional failure rate is an important variables. The infinite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outlier, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, proposed a control mechanism based on NHPP using mean value function of Musa-Okumo and Power law type property.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.645-650
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• 2018

Software stability is the possibility of operating without any malfunction in the operating environment over time. In a finite failure NHPP for software failure analysis, the failure occurrence rate may be constant, monotonically increasing, or monotonically decreasing. In this study, based on the NHPP model and based on the software failure time data, we compared and analyzed the attributes of the software development cost model using the exponential distribution Rayleigh distribution and inverse exponential distribution considering the shape parameter of the Weibull distribution as the life distribution. The results of this study show that the Rayleigh model is the fastest release time and has the economic cost compared to the inverse-exponential model and the Goel-Okumoto model. Using the results of this study, it can be expected that software developers and operators will be able to predict the optimal release time and economic development cost.