Process-centered software engineering environments (PSEEs) facilitate managing software projects. According to the change of enactment environments and the increment of software development complexity, PSEE features should be enhanced. We designed a knowledge-based PSEE named KPSEE. It offers the features: (1) maximizing the degree of process parallelism, (2) enhancing process flexibility, (3) managing product consistency, (4) integrating PSEEs, (5) keeping pace with significant process change, (6) preventing technique leakage, and (7) offering project monitoring ability.

Dynamic economic dispatch (DED) is a complicated nonlinear constrained optimization problem and one of the most important problems in operation of power systems. In this paper two novel optimization algorithms have been proposed to be applied on DED problem. The first method, Krill herd (KHA) is a novel meta heuristic algorithm for solving optimization problems which is based on the simulation of the herding of the krill swarms as a biological and environmental inspired method and is applied on DED problem with two configurations named KHA1 and KHA2. The second algorithm is based on how the streams and rivers flow downhill toward the sea and change back in nature, named Water Cycle (WCA) method. Two common case studies considering various constraints have been used to show the effectiveness of these methods. The results and convergence characteristics show that the proposed methods are capable of giving high quality results which are better than many other previously applied algorithms.

In today’s highly competitive business environment, the rapidly changing customer demands and with the advent of enterprise wide information systems, the managers are bound to think beyond the conventional business processes and devise new ways to squeeze out costs and improve the performance without compromising on the quality at the same time. Supplier evaluation and selection is one such area which determines the success of any manufacturing firm. Supplier selection is the problem wherein the company decides which vendor to select to have that strategic and operational advantage of meeting the customers’ varying demands and fight the fierce competition. This paper presents a simple model based on Analytic Hierarchy Process (AHP) to help decision makers in supplier evaluation and selection, taking into account the firm’s requirements. The article is intended to help new scholars and researchers understand the AHP model and see different facets in first sight.

Text-to-speech synthesis is the process of converting written text to speech. The lack of research on the growth of and the need for the Arabic language is notable. Therefore, this paper reports an empirical study that systematically compares two screen readers, namely, NonVisual Desktop Access (NVDA) and IBSAR. We measured the quality of these two systems in terms of standard pronunciation and intelligibility tests with visually impaired or blind people. The results revealed that NVDA outperformed IBSAR on the pronunciation tests. However, both systems gave competitive performance on the intelligibility tests.

This paper presents a quantum behaved particle swarm algorithm for solving the multi-objective reactive power dispatch problem .Particle swarm optimization (PSO) is a population-based swarm intellect algorithm that share various similarities with evolutionary computation methods. Yet, PSO is determined by the imitation of a societal psychosomatic metaphor aggravated by cooperative behaviours of bird and other societal organisms instead of, the endurance of the fittest individual. Stimulated by the traditional PSO method and quantum procedure theories, this work presents a new Quantum behaved PSO (QPSO). The simulation results reveal high-quality performance of the QPSO in solving an optimal reactive power dispatch problem. In order to appraise the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms.

Time trends of precipitation in the north of Algeria from meteorological radar are analysed. A probabilistic approach presented here proposes to study the evolution of the rainfall phenomenon in two distinct study areas, one located in sea and other located in ground. A decision criterion is established and based on radar reflectivity in order to classify the precipitation events located in both areas. At each radar observation, a state of precipitation is classified, either convective (heavy precipitation) or stratiform (average precipitation) both for the "sea" and for the "ground". In all, a time series of precipitation composed of three states; no raining, stratiform precipitation and convective precipitation, is obtained for each of the two areas. Thereby, we studied and characterized the behavior of precipitation in time by a Markov chain of order one with three states. Transition probabilities are calculated. The results show that rainfall is well described by a Markov chain of order one with three states. Indeed, the stationary probabilities, which are calculated by using the Markovian model, and the actual probabilities are almost identical.

The main goal of the structural optimization is to minimize the weight of structure or the vertical deflection of loaded joint while satisfying all design requirements imposed by design codes. In general fuzzy sets are used to analyze the fuzzy structural optimization. In this paper, a planer truss structural model in intuitionistic fuzzy environment has been developed. This paper proposes an intuitionistic fuzzy optimization approach to solve a non-linear programming problem in the context of a structural application. This approximation approach is used to solve structural optimization model with weight as objective function. This intuitionistic fuzzy optimization (IFO) approach is illustrated on two-bar truss structural design problem. The result of the intuitionistic fuzzy optimization obtained is compared with the other results of optimization algorithms from the literary sources. It is shown that the proposed intuitionistic fuzzy optimization approach is more efficient than the analogous fuzzy technique for structural design.

The minimum rule base Proportional Integral Derivative (PID) Fuzzy backstepping Controller for three dimensions spherical motor is presented in this research. The popularity of PID Fuzzy backstepping controller can be attributed to their robust performance in a wide range of operating conditions and partly to their functional simplicity. The process of setting of PID Fuzzy backstepping controller can be determined as an optimization task. Over the years, use of intelligent strategies for tuning of these controllers has been growing. PID methodology has three inputs and if any input is described with seven linguistic values, and any rule has three conditions we will need 7 × 7 × 7 = 343 rules. It is too much work to write 343 rules. In this research the PID-like fuzzy controller can be constructed as a parallel structure of a PI-like controller and a PD-like fuzzy controller to have the minimum rule base. However backstepping controller is work based on cancelling decoupling and nonlinear terms of dynamic parameters of each dimension, this controller is work based on spherical motor dynamic model and this technique is highly sensitive to the knowledge of all parameters of nonlinear three dimension spherical motor’s dynamic equation. This research is used to reduce or eliminate the backstepping controller problem based on minimum rule base fuzzy logic theory to control of spherical motor system and testing of the quality of process control in the simulation environment of MATLAB/SIMULINK Simulator.