World has become a global village. With the advent of technology, the concept of Cloud Computing has evolved a lot. Cloud computing offers various benefits in terms of storage, computation, cost and flexibility. It focuses on delivering combination of technological components such as applications, platforms, infrastructure, security and web hosted services over the internet. One of the major elements of Cloud Computing infrastructure is Data centre. Companies host there applications and services online through Data centres, whose probability of downtime is expected to be very low. Since, data centre consists of number of servers; the rate of service failure is usually high. In this paper we have analysed service failure rate of a conventional data centre. The Fault Trend of network failure by assuming there occurrence as a Poisson Process was made. The accurate prediction of fault rate helps in managing the up gradation, replacement and other administrative issues of data centre components.

Vehicle Make and Model Recognition (VMMR) has emerged as a significant element of vision based systems because of its application in access control systems, traffic control and monitoring systems, security systems and surveillance systems, etc. So far a number of techniques have been developed for vehicle recognition. Each technique follows different methodology and classification approaches. The evaluation results highlight the recognition technique with highest accuracy level. In this paper we have pointed out the working of various vehicle make and model recognition techniques and compare these techniques on the basis of methodology, principles, classification approach, classifier and level of recognition After comparing these factors we concluded that Locally Normalized Harris Corner Strengths (LHNS) performs best as compared to other techniques. LHNS uses Bayes and K-NN classification approaches for vehicle classification. It extracts information from frontal view of vehicles for vehicle make and model recognition.

In Project management, team’s motivation is one of the most important factors in the success of a project. Project Managersmanage the whole project by assuring that all the members are performing the duties they are assigned. Emotional Intelligence is the ability to identify the attitude of a team member towards a project. In developing countrieslack of emotional intelligence factors may cost people their jobs. In this paper conflict management, technical management, interest development and stress management problems are discussed with reference to developing countries and an efficient approach to resolve these issues is also proposed. Therefore project managers should raise their EI (emotional intelligence) and also help members to raise their EI. This paper explores the related work in EI, and then finds the useful Emotional Intelligence factors which are appropriate for the project manager. Then this paper also determinesa framework which is useful for project managers.

Managing risks in Software Process Improvement (SPI) is a key point of software success. A software risk is considered as an essential characteristic of software development process which if ignored will increase the chance of project failure. For this purpose different risk management approaches are developed. These approaches lead to the identification, assessment and control of risk occurrence in software projects. Collaborative Practice Research (CPR) is one of the action research approaches for managing risk in SPI. In this approach the focus is on gathering information regarding SPI and acknowledging risk management in process development by developing risk assessment strategies and models. The main challenge of this action research approach is to validate the developed risk approach. This paper has a critical review on the existing research approach i.e. CPR. It also provides an enhanced form of CPR which modifies the current CPR approach by including a risk validation activity.