Regression testing is a re-testing technique to test the changes, which is taken in the modified or enhanced application to ensure that the changes do not impairment the accessible behavior of the application. Modifications in the applications mainly focus on three types namely binding, process and interfaces. In order to accomplish the regression testing for a modified portion of an application, test cases are selected from a test suite. Selection and generation of the test cases are more important and also it is a tough process in regression testing. In this article, we proposed a technique to automatically generate the test cases for testing the changes of various versions of BPEL (Business Process Execution Language) dataset. We construct a hierarchical test tree (HTT) for both the new and old versions composite services that are modified for an application and also for the unmodified. The changes are tracked by analyzing the control flow of both trees constructed above using the BPEL dataset. We analyzed the performance of the proposed technique and the experimental results showed that our method performs well than the earlier techniques.

With penetration of distributed energy sources and generation electricity from them in power systems, controlling the stability of network has been more complicated in recent years. In this respect, researchers showed a tendency to use different methodologies to simplify the control of network stability. Nowadays, engineers divide the distribution system to many subsystems which are called microgrid. A microgrid works in two different modes: grid-connected and island mode that require different methods to control. The control methods can be divided to two different forms, with communication and without communication. This paper is a short survey on controlling microgrids with distributed renewable energy resources especially in Island mode and discusses Multi-agent systems and droop characteristic strategies.

Starting system plays crucial role in vehicle operation and failure in which causes engine staring problem. Vehicle starting system failure detection is a challenging task, especially for the inexperienced mechanics and drivers. The success of finding the fault is extremely dependent on the expertise of the individual. To avoid unnecessary breakdown of the vehicle due to starting system problem which cause monetary loss to individuals and overcome the problem of dependent on the expertise individual, in this study, a fuzzy logic based fault detection and diagnosis system has been developed. For this purpose information of current and voltage values of starting system with various fault conditions are acquired by conducting set of tests on vehicles and practiced using fuzzy logic fault diagnosis system (FLFDS). A graphical user interface (GUI) software is also developed using MATLAB® GUI software and it is interfaced with PIC18F4520 controller for implementation on petrol and diesel cars. With the help of this electronic control unit, starting system faults like starter motor brush fault, armature fault, field winding fault, short circuit fault, battery fault and open circuit fault can be detected for further corrective action. The developed graphical user interface (GUI) software was tested (off-board) using sample data obtained from real time starting system and validated these results (on-board) using the developed electronic control unit by conducting field trials on petrol and diesel cars.

This work deals with simulation and implementation of UPQC system to improve the power quality in multibus system. The UPQC system is modeled using the elements of Simulink and it is simulated using MATLAB. A sag is created by applying a heavy load at the receiving end. The sag is compensated by using the UPQC. The harmonics required at the receiving end are supplied by the inverter part of UPQC. The DC required by the UPQC is supplied by Solar cell and Boost converter system. The hardware is fabricated and tested. The experimental results are compared with simulation results.

The uniqueness of the problem of sustainability becomes more complex when dynamic quantitative variables are components of the model in design. In a natural resource management scenario, sustainability becomes more challenging when one considers the variables like people, time, place, quantity, depletion, degradation, regeneration, and threshold. The dynamic relationship of these variables in deciding the truth value of sustainability is the focus of the study. Time, quantity, depletion, degradation, regeneration and threshold are taken into account for the study.

Careful and judicious use of nanotechnology, a recently emerging discipline, finding use in all fields including agriculture can promote growth of various crops. Silver nanoparticles (SNPs) have various uses in agriculture and are expected to improve growth and yield of wheat crop. In these experiments silver nanoparticles were synthesized by chemical reduction method using silver nitrate and tri-sodium citrate. X-ray diffraction indicated presence of 10-20 nm sized nanoparticles. Three separate experiments were conducted to explore the effects of SNPs on germination, growth and yield of wheat cultivar NARC-2009. SNP concentrations used were 0, 25, 50, 75, 100, 125 and 150 ppm. SNPs were found to have either no effect or decreased germination and germination index. Application of 25 and 50 ppm SNPs significantly increased number of seminal roots. To determine the role of SNPs on growth, one week old wheat seedlings were transferred to nutrient medium with different concentrations (0, 25, 50, 75, 100, 125 and 150 ppm) of SNPs. Leaf area, fresh weight, dry weight, root biomass, relative growth rate and net assimilation rate increased at 25 ppm SNPs as compared to control during first week but decreased during the following weeks. Wheat seedlings were transferred to soil filled pots where SNPs solution of different concentrations equivalent to field capacity were applied except control where distilled water was applied. Number of grains per spike was maximum for 25 ppm followed by 50 ppm concentrations. Maximum 100 grain weight was obtained for 25 and 125 ppm SNPs while grain yield per pot was highest for 25 and 50 ppm SNPs. Comprehensive experimentation is required to establish the most suitable concentration of SNPs for higher growth and maximum yield of wheat.