Fuzzy logic is a new and innovative technology that was used in order to develop a realization of engineering control. In recent years, fuzzy logic proved its great potential especially applied to automatization of industrial process control, where it enables the control design to be formed based on experience of experts and results of experiments. The projects that have been realized reveal that the application of fuzzy logic in the technological process control has already provided us with better decisions compared to that of standard control technique. Fuzzy logic provides an opportunity to design an advisory system for decision-making based on operator experience and results of experiments not taking a mathematical model as a basis. The present work deals with a specific technological process ─ designing a support decision making information system for the operational control of the lime kiln with the use of fuzzy logic based on creation of the relevant expert-objective knowledge base.

Parallel algorithms are popular method of increasing system performance. Apart from showing their properties using asymptotic analysis, proof-of-concept implementation and practical experiments are often required. In order to speed up the development and provide simple and easily accessible testing environment that enables execution of reliable experiments, the paper proposes a platform with multi-core computational accelerator: Intel Xeon Phi, and modern programming language: Java. The article includes the description of integration Java with Xeon Phi, as well as detailed information about all of the software components. Finally, the set of tests proves, that proposed platform is able to prepare reliable experiments of parallel algorithms implemented in modern programming language.

Email still plays an important role in today's business communication thanks to its simplicity, flexibility, low cost, and compatibility of diversified types of information. However processing the large amount of emails received consumes tremendous time and human power for a business. In order to quickly deciphering information and locate business-related information from emails received from a business, a computerized solution is required. In this paper, we have proposed a comprehensive mechanism to extract important information from emails. The proposed solution integrates semantic web technology with natural language processing and information retrieval. It enables automatic extraction of important entities from an email and makes batch processing of business emails efficient. The proposed mechanism has been used in a Transportation company.

Previous studies on estimating software reliability employed statistical functions for next system failure prediction. These models used parameters based on assumptions regarding the nature of software faults and debugging process. However, none of the existing models, attempted on ensuring reliable runtime system operation. To serve the current demand of autonomous, reliable, service-oriented software, we present a novel approach for runtime reliability estimation of executable software. The approach can help control software execution at runtime by monitoring software state-to-state transition at runtime. The approach involves representing executable software as an automata using opcode extracted from executable code. The extracted opcode is then used to learn stochastic finite state machine (SFSM) representation of executable software which is later employed to trace software state-to-state transition at each runtime instance. An evaluation of our approach on Java-based Chart generator application is also discussed to explain how we can ensure reliable software execution and prevent software failures at runtime with the proposed approach.

To achieve successful reusability of components a disciplined development approach is required which is the component based software engineering(CBSE).The software component selection is a vital part of this approach. It consists of defining an evaluation criteria based on user requirements and depending on this the repository is searched and shortlisted components are presented to the user. Due to availability of large number of components offering same type of functionality it is difficult to select a particular component based on available description. This paper presents a multiobjective optimization model for component selection purpose and solves it using preemptive goal programming approach by using an optimization tool LINDO. Subsequently, an illustrative case study is given where the components are taken from an online repository and goal programming is applied for getting the most optimal component. However, this model is applicable when the repository is small but for larger set of components it needs to be validated.

Typical methods of quantum/reversible synthesis are based on using the binary character of quantum computing. However, multi-valued logic is a promising choice for future computer technologies, given a set of advantages when comparing to binary circuits. In this work, we have developed a genetic algorithm-based synthesis of ternary reversible circuits using Muthukrishnan-Stroud gates. The method for chromosomes coding that we present, as well as a judicious choice of algorithm parameters, allowed obtaining circuits for half-adder and full adder which are better than other published methods in terms of cost, delay times and amount of input ancillary bits. A structure of the circuits is analyzed in details, based on their decomposition.

Reusability is the quality of a piece of software, which enables it to be used again, be it partial, modified or complete. A wide range of modeling techniques have been proposed and applied for software quality predictions. Complexity and size metrics have been used to predict the number of defects in software components. Estimation of cost is important, during the process of software development. There are two main types of cost estimation approaches: algorithmic methods and non-algorithmic methods. In this work, using genetic programming which is a branch of evolutionary algorithms, a new algorithmic method is presented for software development cost estimation, using the implementation of this method; new formulas were obtained for software development cost estimation in which reusability of components is given priority. After evaluation of these formulas, the mean and standard deviation of the magnitude of relative error is better than related algorithmic methods such as COCOMO formulas.

Cloud computing as a new paradigm has grown from a promising idea to one of the fastest research and development paradigm in education sector. It is a hot research area that applies in all sectors where we require high performance and fast access to resources and services. Cloud computing usability in education is wide-ranging, as acknowledged by many educational institutions around the world. This paper attempts to address the need for utilizing cloud computing in higher education in Kingdom of Saudi Arabia for all the disciplines to raise its level and solve the obstacles that faced the learning process. In addition, cloud computing facilitates educators and students to be more experienced in cloud computing and it prepares them to get benefits of usefulness to become more motivated and effective. Survey is used as a research design to validate the proposed solution. The results show that the proposal to improve higher education is highly supported by the professionals working in the industry and academia.

Conventional sources like fossil fuels were used earlier to satisfy the energy demands. Nowadays these are being replaced by renewable sources like photo-voltaic sources. Photo-voltaic is a method of generating electrical power by converting the energy from the sun into direct current with the use of semiconductor devices that exhibit photovoltaic effect. They do not cause environmental pollution and do not require any moving parts. Different types of DC-DC Converters have been proposed in literature but Inter-leaved boost Converter (IBC) is widely used because of its fast dynamic response and high power density. This paper presents an analysis of the voltage mode control strategies employed by Ripple Cancellation Network (RCN) based two phase Interleaved boost Converter (IBC) for photo-voltaic applications. After analyzing the different Boost converter topologies, the results illustrate that IBC is more efficient than conventional boost converter as it reduces the input current ripple, output voltage ripple, component size and improves its transient response. On adding the Ripple Cancellation Network to the conventional IBC, the output voltage and input current ripple are further reduced without increasing the diode current stress. Adopting the closed loop voltage mode control, the ripple components are found to decrease significantly at the output thereby achieving a higher level of efficiency. A comparison is drawn between open and closed loop voltage control ripple component values. Simulations are carried out using MATLAB/SIMULINK software to verify with the theoretical results.