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In this research, we will study the reliability of the mixed system and how to increase its reliability using the repetition technique. We use the unit repetition method, and then find the reliability of the system after using the reduction method without repetition and after iteration to find out the amount of increase in the reliability of the system.

The issue of optimizing the reliability of complex networks is one of the contemporary issues, which has evolved with the development of methodologies for solutions with the development of modern engineering technology. Algorithms that mimic nature are among the most powerful algorithms used in optimization. In this study, the bat algorithm was presented to obtain the best reliability for a complex network that was selected at the lowest possible cost using three different cost functions, the logarithmic, the exponential and the tangent functions. Where we got different results according to the cost function used and the comparison was made between those results and we were found that the result of the logarithmic function is the best.

Energy consumption in human society has increased as more energy supplies are required to meet the needs of the world’s growing population. However, there is a major concern about fulfilling energy demand while reducing reliance on fossil fuels. Bamboo-based biomass has great potential for use as a raw material for the production of biofuels and bioenergy. Bamboo possesses excellent fuel qualities that can be converted into solid, liquid, and gaseous biofuels. Hence, the cultivation and harvesting operations must be performed efficiently to ensure that the availability of this biomass is sufficient to meet the demand for biofuel production. Several studies have shown that the micropropagation technique has increased bamboo production and that proper bamboo plantation management can benefit both the environment and society. Nevertheless, there are several challenges in bamboo cultivation and biofuel production, such as environmental impact from land management and economic risk from the industrial supply chain. Bamboo-producing countries, including Malaysia, have initiated several policies to propose strategies for sustaining the bamboo industry.

The term waswas appears five times in the Quran and seven times in seven Hadith books collections. Its interpretations by exegetes and scholars in Islamic studies vary, but one is associated with obsessive-compulsive disease (OCD). This is a study of the term waswas with the express objective of identifying its components that correspond to a contemporary understanding of OCD. This is a qualitative study that employs content and document analysis to examine chosen Islamic interpretation of the al-Quran, Hadith and traditional scholar viewpoints, with an emphasis on three characteristics of OCD: obsession, compulsive behaviour, and causation. The Quran and Hadith constitute the final miracle, transcending geographical and generational boundaries. Although OCD appears to be a recent diagnosis, its essence is mentioned in the magnificent Al-Quran. Keywords: Waswas, Obsessive-compulsive disorder (OCD), al-Quran, Hadith

Waswas (suspicious) are the subtle disturbances that have existed since the creation of Adam A.S and Eve by Allah SWT and is still being discussed till this day whether in term of definition, division, cause and treatment. The term suspicious was mentioned in al- Quran five times in various forms in four surahs. However, the debate on the synonym for the term suspicious according to Islamic scholars is still lacking attention. Thus, the study discusses the relationship of the term suspicious and the term synonymous with the debate of Islamic scholars. This study completely used the qualitative method in the components of documentation through the Book of Fiqh, Tasawwuf and Psychology. The results found that there are five terms associated with the term suspicious which are worry, doubt, talk, caution and inspire. All of these five terms indicate the difference significant to the term of suspicion.

The allocation of reliability and optimization for each part of the complex system has been determined in this paper, in order to solve the problem of allocation and to improve network stability we will use Bees Colony Optimization (BCO). The three cost functions are also introduced (exponential behavior with feasibility factor model, exponential behavior model and logarithmic model). After solving the allocation problem. The aim of this paper is to compare the effects of the three cost functions using Bees Colony algorithm in terms of reliability allocation and optimization to determine which is more efficient.

In this article, we will look at the importance of each unit in a mixed system and attempt to estimate the impact of their effect on the system’s overall performance depending on their importance. We will also demonstrate how to use an addition technique to enhance the efficiency of the units that have a greater impact on the system’s overall performance than others.

The reduction process, which will permit us to transform a mixed system into a sequential system in order to resolve the problem of reliability allocation for this type of system, will be used in this research to measure the reliability allocation for mixed systems.

Consider a complex network whose components either work or fail, there probabilities are known. Our paper study two methods for the exact computation of the reliability network, the first one is a decomposition method which may be used even after the community can go through no further modular decomposition, is based on a partition the vertices of network into sets that can be analyzed them sequentially. This method involves choosing one component as a key and then calculate the reliability network twice the first when the key work and the other if the key failed. These two probabilities are then combined to obtain the reliability network. The second method is inclusion-exclusion method which is one of the earliest techniques to compute complex network reliability expressions using the probability laws. We get the same polynomial by using two methods. In both methods, we need to calculate all of the minimum paths so we calculated them by use the adjacency matrix.

To find the reliability of any complex network, we need to convert it into a simple network to facilitate the process of reliability calculation. In this paper we simplify a complex network into a simple network by using two techniques, in the first technique “reduction method” the complex network was converted into a parallel network, while in the second technique “delta - star method”, the complex network has been transformed into a series network. The 2nd technique is based on the 1st technique in finding the reliability of a subnetwork. At the end of the research, a comparison between these two methods was made.

This paper focuses on the reliability of complex networks, which has been calculated as a complex system by using minimal cuts. The reliability of this system has been assigned to study the possible approaches to reliability values based on the reduction of total costs in this system. The genetic algorithm (GA) has been used to solve the allocation problem. Reliability and ability to solve complex problems and optimization also found in structures of engineering. Generally high implementation costs require high further duplicates. In addition to using GA, optimizing the swarm (PSO) and this algorithm is based on the action of the organisms living that accumulate. PSO is very close to GA because of the fact that these evolutionary approaches are all strategies, Using some probabilistic and some probable values. The main objective of this article is to investigate and compare between two algorithms GA and PSO.

This paper focuses on the reliability of complex system that has been measured as a complex system using minimal paths. The reliability of this system has been assigned to research the possible approaches of the assignment reliability values based on reducing the total cost of this method. The results originally included: (i) Three cost functions were used to measure the cost of the complex system: First, the exponential behavior model with the feasibility factor model. Second, the exponential behavior model. Third, the logarithm model. (ii) The reliability of every component of the system was calculated using Particle Swarm algorithm to solve the problems of optimizing the given reliability of the complex system.

In this paper the allocation of reliability and optimization has been calculated for each component of the complex system. Use (genetic algorithm) to solve the problem of allocation and to optimize system reliability. Also discussed are the three expense functions (exponential behavior with feasibility factor model, exponential behavior model and logarithmic model). The reliability importance of each component of the system was calculated after solving the allocation problem. The aim of this paper was to compare the results of the three cost functions by using GA in terms of reliability allocation and optimization, accurate reliability, reliability importance, and then whatever is more efficient than another.

In this paper we shall introduce two equivalent techniques in order to evaluate reliability analysis of electrical aircrafts systems (EAS): (i) graph theory technique, and (ii) simplifying diffeomorphism technique. Geometric modeling of reliability models is based on algebraic hypersurfaces, whose intrinsic properties are able to select those models which are relevant for applications. The basic idea is to cover the reliability hypersurfaces by exponentially decay curves. Most of the calculations made in this paper have used Maple and Matlab software.

This paper, introduces the minimal path method in order to solve the network model, which represents an electric system used inside spacecraft, and its reliability polynomial have been obtained. Factually, this polynomial has big number of terms, which makes it difficult to deal with in order to obtain useful information. For that reason, another technique, called the Reduction technique was introduced, for a simplified reliability polynomial. This technique transforms a complex network to its equivalent series and parallel form. Geometrically, a diffeomorphism has been used to change the initial reliability polynomial into a simplified form. Due to this original outcome, we formulate and prove some original results, regarding the “reliability”1 hypersurface for a given network model, and to find the critical points of the reliability polynomial, which proved the nontrivial compatibility of the system. In addition, we had analyzed and computed the Hessian Matrix of reliability polynomial, and try to algebraically interpret the manner in which the reliability polynomial had been convex or concave, which reveals that the reliability of the system is increased or decreased. Most of the calculations and figures made in this paper have used Mathematica software.1In the present work, the term “reliability” refers to extending of the standard definition of reliability; i.e. $\mathrm {R}_{\mathrm {i}}\in (-\infty, \infty )$.

This paper focuses on the reliability of Reduction Oxygen Supply System (ROSS) of a Spacecraft which was calculated as a complex system using probability theory. The reliability of this system was assigned to study the possible approaches of the allocation of reliability values based on the minimization of the total cost in this system. The original results was included: (i) a critical point is a fixed purpose of a appropriate application. (ii) Using the reduction oxygen supply system of a spacecraft of with the cost of exponential behavior model. (iii) The results also obtained by genetic algorithim to solve the optimization problems of the given reliability network.