Narrow Results

Use of enzyme-linked immunosorbent assay (ELISA) is recommended for control of Johne's disease (JD) in the cattle industry. A recent report showed that prevalence of JD in dairy farms could be reduced by applying an ELISA-based control strategy, even though the sensitivity of the current ELISA has been reported to be lower than 30%. We previously developed a more sensitive ELISA test (EVELISA; Ethanol Vortex ELISA) for diagnosis of JD and, in this report, aimed to evaluate cost-effectiveness of the EVELISA in JD control compared to that of a current ELISA test. For simulation of population dynamics, we developed a deterministic, discrete-time mathematical model incorporating contact structure, possibility of adult infection and the concept of order of events. In our model, the number of animals infected with the causative agent of JD, Mycobacterium avium subsp. paratuberculosis (MAP), increases in a 10-year simulation if no JD control measure is applied. When test results of ELISA or EVELISA are used for JD control, the increase in MAP-infected animals is less significant. According to our model, EVELISA-based control measures increase the annual per capita revenue of US dairy farms when compared to no JD control and ELISA-based JD control, respectively.

This paper discusses about the availability of a complex system, which consists of two independent repairable subsystems A and B in (1-out-of-2: F) and (1-out-of-n: F) arrangement respectively. Subsystem A has two identical units arranged in parallel redundancy (1-out-of-2: G), subsystem B has n unit in series (1-out-of-n: F) with two types of failure, viz., partial and catastrophic. Except at two transitions where two types of repair namely exponential and general possible all other transitions have single possibility between any two states. The failure and repair time for both subsystems follow exponential and general distributions respectively. The model is analyzed under "preemptive-resume repair discipline" where A is considered to be in priority while B is non-priority. By employing supplementary variable technique, Laplace transformation and Gumbel-Hougaard family copula various transition state probabilities, availability, Mean Time to Failure (MTTF) and cost analysis (expected profit) are obtained along with steady-state behaviour of the system. Inversions have also been carried out so as to obtain time dependent probabilities, which determine availability of the system at any instant. At last some special cases of the system have been taken.

This paper deal with the study of reliability of a complex system consists of three subsystems, (subsystem-1, subsystem-2 and subsystem-3) connected in series configuration. The subsystem-1 has three units and working under the policy 2-out-of-3: F policy, subsystem-2 has two units in parallel configuration and is working under 1-out-of-2: G policy and subsystem-3 is connected with subsystem-2. All three subsystems are connected in series configuration. The system has two types of failure, partial failure and completely failure. It is assumed that the partial failure bring the system to degraded state, while the complete failure stop functioning in the system. All failure rates are constant and assumed to follow exponential time distribution, but the repair follow two types of distribution, i.e., general distribution and exponential distribution. It is assumed that the system in partially failed/degraded states are repaired by employing general time distribution but the completely failed states are repaired by Gumbel–Hougaard family copula distribution. The system is analyzed by supplementary variable technique. Some crucial measures of reliability such as Availability, mean-time-to-failure (MTTF) and profit analysis have been discussed. Some computations are taken as special case by evaluating Availability, MTTF and profit by taking different failure rates.

At present, the cloud computing with big data is known as a next-generation software service paradigm. However, the effective methods of software reliability analysis considering the big data and cloud computing have been only few presented. In particular, it is important to consider the optimal data partitioning in terms of cloud computing with big data. Considering the cloud computing with big data, it will be useful for the software managers to estimate the total software cost in order to make allocations the optimal data area to the cloud user. We propose the method of component-oriented reliability assessment based on neural network in order to the optimal data partitioning for cloud computing with big data in this paper. Moreover, we propose the method of system-wide reliability assessment based on the jump diffusion process model considering the big data on cloud computing. Furthermore, we propose the optimal maintenance problem based on the jump diffusion model. Considering the contract cost for the maximum number of subscriber as the cloud user, we find the optimum maintenance time by minimizing the total software cost.

Roads have always been the main source of transportation all over the world. Easy accessibility and more safety are the most important features of road transportation. Improvements in these areas are constantly required and invited. Solar road studs are one of the remarkable improvements in road safety. Solar road studs use solar energy, which is the most sustainable and pollution-free source of energy that provides reliable power supplies and fuel diversification. Solar road studs are flashing solar cell-powered LED lighting devices used in road construction to delineate road edges and centerlines. This research work is dedicated to evaluating the reliability measures which include availability, mean time to failure (MTTF), cost analysis, and sensitivity analysis with their graphical representation by using the Markov process. Along with reliability assessment, Particle Swarm Optimization (PSO) technique is applied to optimize the cost of the system.

This paper is the stochastic analysis of a complex repairable system comprising of subsystems in a series arrangement under the $k$-out-of-$n$: $G$ type configuration. Both of the subsystems are in series arrangement and having auto transfer switches when some unit fails. Subsystem 1 is supposed to work under the $k$-out-of-$n$: $G$, scheme, and subsystem 2 which has four indistinguishable units in parallel arrangement with an auto switch functioning under the 1-out-of-4: $G$ scheme. A catastrophic failure is characterized as causing damage to the entire system. Units’ failure, switch failures, and catastrophic failure rates are constant, but repair rates are treated as variables with two types of distributions: general distribution and copula distribution. The model is analyzed using a supplementary variables approach, with probabilistic measures such as availability, reliability, MTSF, and profit functions derived.

Many models and methods have been proposed in the literature to evaluate the reliability of fault-tolerant systems. In this paper, we study systems with one degradation mode. We introduce a static model and present efficient algorithms for the evaluation of the system performance and cost. For the special case of a system consisting of identical units we derive an efficient procedure for the determination of an optimal system design with respect to a minimum system cost.