Markov Modeling for Reliability Analysis Using Hypoexponential Distribution

The probability of failure free software operation for a specified period of time in a specified environment is called Reliability, it is one of the attributes of software quality and study about it come back to 1384. Exposition and spreading of new software systems and profound effect of it to human life emphasize the importance of software reliability analysis, until it poses formal definition at 1975. First race of reliability analysis methods that we called classic methods has stochastic process approach and in this way, attempt to predict the software behavior in future. Due to the ambiguity in fruitfulness of these solutions the challenge about reliability analysis continued till now. Great tendency in applying intelligence systems at variety of applications can be seen at 90 decade, and software reliability attracts some research direction to itself. Until now variety of methods in reliability analysis on the base of intelligence systems approach exhibited. In this survey the taxonomy of these methods represented with brief description of each one. Also comparison between these methods can be seen at the end of survey.

The focused ion beam system has been widely used as a critical failure analysis tool as microprocessor technology advances at a ramping speed. It has become an essential step in failure analysis to reveal physical defects after electrical fault isolation. In the highly competitive and challenging environment prevalent at present, failure analysis throughput time is of utmost important. Therefore, a quick, efficient and reliable physical failure analysis technique is needed. This paper discusses the applications of FIB as a defect localization and root cause determination tool through the passive charge contrast technique and pattern FIB analysis.

Focused ion beam system has been widely used as a critical failure analysis tool as microprocessor technology advances at a ramping speed. It has become an essential step in failure analysis to reveal physical defects post electrical fault isolation. In this highly competitive and challenging environment prevalent today, failure analysis throughput time is of utmost important. Therefore quick, efficient and reliable physical failure analysis technique is needed to avoid potential issues from becoming bigger. This paper will discuss the applications of FIB as a defect localization and root cause determination tool through the passive charge contrast technique and pattern FIB analysis.

Ever shrinking device structures are one of the main reasons for a growing inherent unreliability of embedded system components. As a remedy, various means to increase the reliability of complex embedded systems at several levels of abstraction are available. In fact, their efficient application is a key factor for the successful design of reliable embedded systems. While analysis approaches that evaluate these techniques and their advantages and disadvantages at particular levels exist, an overall system analysis that has to work cross-level is still lacking. This paper introduces a framework for cross-level reliability analysis that enables a seamless and flexible combination of various reliability analysis techniques across different levels of abstraction. For this purpose, a proposed framework provides mechanisms for (a) the composition and decomposition of the system during analysis and (b) the connection of different levels of abstraction by adapters that convert and abstract analysis results. As a case-study, the framework extends and combines three analysis approaches from the MPSoC domain: (I) a BDD-based reliability analysis considers redundancies in the system structure, (II) an analytical behavioral model to consider computational activity, and (III) a temperature simulator for processor cores. This enables to capture thermal reliability threats at transistor level in an overall system analysis. The approach is seamlessly integrated in an automatic Electronic System Level (ESL) tool flow.KeywordsReliability AnalysisEmbed SystemField Programmable Gate ArrayReliability FunctionDesign Space ExplorationThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Traditional reliability analysis generally uses probability approach to quantify the uncertainty, while it needs a great amount of information to construct precise distributions of the uncertain parameters. In this paper, a new reliability analysis technique is developed based on a hybrid uncertain model, which can deal with problems with limited information. All uncertain parameters are treated as random variables, while some of their distribution parameters are not given precise values but variation intervals. Due to the existence of the interval parameters, a limit-state strip enclosed by two bounding hyper-surfaces will be resulted in the transformed normal space, instead of a single hyper-surface as we usually obtain in conventional reliability analysis. All the limit-state strips are then summarized into two different classes and corresponding reliability analysis models are proposed for them. A monotonicity analysis is carried out for probability transformations of the random variables, through which effects of the interval distribution parameters on the limit state can be well revealed. Based on the monotonicity analysis, two algorithms are then formulated to solve the proposed hybrid reliability models. Three numerical examples are investigated to demonstrate the effectiveness of the present method.

Maintenance, rehabilitation and replacement of existing bridges by using cost effective management are increasingly important topics in efforts to deal with aging and deteriorating infrastructure. Recently, engineers have shifted the emphasis from design and construction of new bridges to maintenance and rehabilitation of existing bridges. This paper uses the structural reliability method with a predefined performance function to assess the component performance of the main load carrying members of an inner span in a multi-span bridge. The performance of the components is a function of various random variables with certain probabilistic distributions. The analysis is extended using the same performance function to evaluate the reliability of the bay as subsystem and bridge as a system. System reliability in this case is defined as the probability that a system (bridge) performs its intended function under operating conditions for a specified period of time using second order reliability method (SORM) and Monte Carlo simulations. In addition, deterioration in the main carrying elements (components) due to environmental impacts is introduced and the sensitivity parameters for certain random variables are re-evaluated to determine the inspection and maintenance period of the bridge. The deterioration is imposed as a percentage reduction in certain random variables. The paper involves use of multi reliability analysis at component, sub-system and system levels. Results show that probability of failure (Pf) increases with decrease in distance of the bridge from source of deterioration. Reliability index (β) decreased with increase in the age of the bridge because of corrosion of reinforcing steel. Results also show that the rate of probability of failure for bridges exposed to deteriorating effects increased dramatically after 45-50 years.

Analysis of descriptive epidemiological characteristics of pancreatic cancer in Vojvodina, Serbia. The study covers population of Vojvodina in the period from 2000 to 2009. The method used for data processing was the descriptive. The data, referring to a specified period of time, were analyzed from chronological and demographic aspects and according to histological diagnosis. In the period from 2000 to 2009, there were 2,108 registered cases of pancreatic cancer of which 1,886 had a fatal outcome. Standardized incidence rates varied between 5.7 and 9.1 per 100,000 population in males and between 4.2 and 5.3 in females. Linear incidence trends in males in the specified period of time, based on crude (r=0.7883, p<0.05) and standardized (r=0,6373, p<0,05) incidence rates, demonstrated increase. Annual percent increase in the crude incidence rate was 4.5% in males, and 2.8% in females. Age-standardized mortality rates varied between 5.2 and 7.5 per 100,000 population in males and 3.6 and 4.7 in females. Linear mortality trends in males in the specified period of time, based on crude (r=0.8795, p<0.05) and standardized (r=0.7669, p<0.05) mortality rates, also demonstrated annual percent increase. Data analysis shows unfavorable onco-epidemiological situation related to pancreatic cancer in Vojvodina, in aspects of both incidence and mortality. Absence of primary and secondary prevention does not allow medical institutions to successfully fight against this disease.

At the LKAB Kiruna Iron Ore Mine in Sweden, reliability and maintainability analysis techniques have been gradually accepted as standard tools for planning and operation of automatic and complex mining systems since the mid-1980s. The reliability analysis and modeling of the production system at the Kiruna mine are discussed. Since a large number of random variables (phenomena) are involved in the analysis, a simulation program SIMURES was developed to model the reliability characteristics of the production process and analyze the criticality of the various units and operations. This program has helped in evaluating the gain in production volume with improvement in reliability of the various units, and thus forms a basis for future investment for increasing the production system efficiency and capability. >

Klout, a famous App, could measure people's social network influence power. Klout score is measured according to the data from past 90 days and an individual who has high Klout score is thought as having high social influence power. Lots of businesses or organizations like to hire high Klout score people to help them to diffuse their brand images. However, Klout score cannot tell us who has high influence power in a specific short time period. For example, it is possible that some of the users might always have high influence power on Monday or on Monday morning. These time-dependent influential users probably have low Klout scores in average but have high influence power in some specific time periods. Businesses should not just know who are the high Klout score users but also they should identify who are the time-dependent influential users because all of them may have some sort of power to influence other users' buying decisions. In this study, a framework based on frequent pattern mining is proposed to find the time-dependent influential users. First of all, the framework will divide a predefined long time period into successive short time segments and then influential transactions that contain Facebook fans' influence power data will be defined in each time segment. From the frequent patterns, the proper time for time-dependent influence users to spread information can be found. A theoretical experiment is given to verify the effectiveness of the proposed framework.

The purpose of this study is to develop and evaluate a probabilistic framework for reliability analysis of information-theoretic computer-assisted detection (IT-CAD) systems in mammography. The study builds upon our previous work on a feature-based reliability analysis technique tailored to traditional CAD systems developed with a supervised learning scheme. The present study proposes a probabilistic framework to facilitate application of the reliability analysis technique for knowledge-based CAD systems that are not feature-based. The study was based on an information-theoretic CAD system developed for detection of masses in screening mammograms from the Digital Database for Screening Mammography (DDSM). The experimental results reveal that the query-specific reliability estimate provided by the proposed probabilistic framework is an accurate predictor of CAD performance for the query case. It can also be successfully applied as a base for stratification of CAD predictions into clinically meaningful reliability groups (i.e., HIGH, MEDIUM, and LOW). Based on a leave-one-out sampling scheme and ROC analysis, the study demonstrated that the diagnostic performance of the IT-CAD is significantly higher for cases with HIGH reliability (A(z) = 0.92 +/- 0.03) than for those stratified as MEDIUM (A(z) = 0.84 +/- 0.02) or LOW reliability predictions (A(z) = 0.78 +/- 0.02).

Along with the development of object-oriented technology, component development is gradually extended to commercial off-the-shelf (COTS) components and component-based software development (CBSD) has gradually become the dominant orientation of the field of software engineering. The claims of high reliability need further investigation based on reliability analysis techniques that are applicable to component-based applications. This paper introduces a new reliability analysis technique applicable to high-level designs. The technique is named reliability analysis based on rewrite logic (RABRL). RABRL is specific for component-based software whose analysis is strictly based on its operational profile and specification. Specification based on rewrite logic can be executed with the help of rewrite technique of Maude, driven by test cases designed from the operational profile. By analyzing the execution process with statistics, we can get the transition probability between components and expected number of visits to components approximately. The paper also adapts the probabilistic model "component-dependency graph" (CDG) proposed by Sherif M. Yacoub to model the component-based software, which is named "adapted component-dependency graph" (ACDG). ACDGs are directed graphs that represent components, component reliabilities, transitions, and transition probabilities. Based on ACDGs, an algorithm is presented to analyze the reliability of the application as the function of reliabilities of its components. A simple case study illustrates the applicability of the algorithm. The RABRL is also used to identify critical components.

Compared with the probability model, the convex model approach only requires the bound information on the uncertainty, and can make it possible to conduct the reliability analysis for many complex engineering problems with limited samples. Presently, by introducing the well-established techniques in probability-based reliability analysis, some methods have been successfully developed for convex model reliability. This paper aims to reveal some different phenomena and furthermore some severe paradoxes when extending the widely used first-order reliability method (FORM) into the convex model problems, and whereby provide some useful suggestions and guidelines for convex-model-based reliability analysis. Two FORM-type approximations, namely, the mean-value method and the design-point method, are formulated to efficiently compute the nonprobabilistic reliability index. A comparison is then conducted between these two methods, and some important phenomena different from the traditional FORMs are summarized. The nonprobabilistic reliability index is also extended to treat the system reliability, and some unexpected paradoxes are found through two numerical examples.

The reliability is the probability that a device will perform its required function under stated conditions for a specified period of time. The Common Cause Failure (CCFs) is the multiple failures and has long been recognized (U.S. NRC, 1975) as an important issue in the Probabilistic Safety Assessment (PSA) and uncertainty and sensitivity analysis has the important information for the evaluation of system reliability. In this study, two cases has been considered, in the first case, author have made the analysis of reliability of PWR safety system by GO-FLOW methodology alternatively to Fault Tree Analysis and Even Tree because it is success-oriented system analysis technique and comparatively easy to conduct the reliability analysis of the complex system. In the second case, sensitivity analysis has been made in order to prioritize the important parameters which have largest contribution to system reliability and also for common cause failure analysis and uncertainty analysis. For an example of phased mission system, PWR containment spray system has been considered.

Subsystem of heat supply is one of three subsystems constituting heat supply system together with subsystem of heat production and subsystem of heat distribution. An analysis of failures in the heat supply subsystem has been presented in the article. The analysis of variety, frequency and causes of failures, for individual kinds of district heating network: main ones, distributional ones and heat supply connections in the example of heat supply system of 200000-inhabitants-city has been presented in the work. An analysis has been based on a real exploitation data of the heat distribution network, which had been obtained from Municipal Heat Supply Company during the period of time from 2003 to 2012. This paper contains the failure analysis of the heat distribution network depending on the technology of construction, diameters and age of network, kinds and causes of damages, place and time of failures' occurrences for various kinds of heat distribution networks. There have been determined basic reliability parameters such as: mean time between failures and the failure rate in the exemplary subsystem of heat supply. The failure analysis of heat distribution networks allows the operating instructions to develop, which can serve as a basis to determine the optimal repair periods and periods of highest danger emergency. It also influences on making more accurate decisions considering maintenance and repairs. This reduces the consequences of the failure, which is related to the maximum shortening of repair time and to decreasing the negative results of interruptions in the heat supply to the customers.

There is intense interest in understanding the stochastic and dynamical properties of the global Foreign Exchange (FX) market, whose daily transactions exceed one trillion US dollars. This is a formidable task since the FX market is characterized by a web of fluctuating exchange rates, with subtle inter-dependencies which may change in time. In practice, traders talk of particular currencies being 'in play' during a particular period of time -- yet there is no established machinery for detecting such important information. Here we apply the construction of Minimum Spanning Trees (MSTs) to the FX market, and show that the MST can capture important features of the global FX dynamics. Moreover, we show that the MST can help identify momentarily dominant and dependent currencies.