The Hybrid-Agile Design of Experiments Methodology

A DOE (Design of Experiments) is the laying out of a detailed experimental plan in advance of doing the experiment. Optimal DOEs maximize the amount of information that can be obtained for a given amount of experimental effort. The traditional DOE methodology is waterfall-type methodology implying a sequential and linear life-cycle process. The success of the experiment and usefulness of the results are highly dependent on the initial experimental setup and assumptions, and does not allow to go back and change something that was not well-documented or thought upon in the design stage. The fast-changing software development industry have made it understandable that the traditional waterfall methodology for developing systems, which follows similar patters to the traditional DOE, lacks the agility required for developing robust systems. These limitations have triggered the development of agile: a type of incremental model of software development based on principles that focuses more on flexible responses to change, instead of in-depth planning at the design stage. This paper proposes the hybrid-agile DOE methodology – a methodology that incorporates agile principles in traditional waterfall DOE methodologies – to design effective experimental layouts that allow for improvement during the experimental trial process. The methodology is applied to the natural ageing of adhesives tapes for building applications. This methodology can overcome traditional DOE, by adding agility in the whole process, especially in cases where the investigated products lack prior information and are characterised by large variability.

Prioritize the Sequence of Test Cases and Increase the DRE Rate by Implementing Orthogonal Array Testing Strategy

Software testing is an emerging technology which is use to increase the rate of error detection as early as possible in the software testing life cycle process. Test case prioritization technique plays a crucial role in organizing the test cases in sequencing order both ascending and descending such that test cases having high priority or high severity are planned to get executed doing a proper risk-based analysis. This prioritization technique effectively addresses two important organization constraints namely “Time” and “Budget”, also improve the quality of service. The proposed work is all about how effectively we can sequence the application modules for testing during Test plan phase using fuzzy logic and how to write optimized test cases efficiently design during Orthogonal Array Test Strategy (OATS) in Test design phase of testing life Cycle.

Big data-drive agent-based modeling of online polarized opinions

Under the mobile internet and big data era, more and more people are discussing and interacting online with each other. The forming process and evolutionary dynamics of public opinions online have been heavily investigated. Using agent-based modeling, we expand the Ising model to explore how individuals behave and the evolutionary mechanism of the life cycles. The big data platform of Douban.com is selected as the data source, and the online case “NeiYuanWaiFang” is applied as the real target, for our modeling and simulations to match. We run 10,000 simulations to find possible optimal solutions, and we run 10,000 times again to check the robustness and adaptability. The optimal solution simulations can reflect the whole life cycle process. In terms of different levels and indicators, the fitting or matching degrees achieve the highest levels. At the micro-level, the distributions of individual behaviors under real case and simulations are similar to each other, and they all follow normal distributions; at the middle-level, both discrete and continuous distributions of supportive and oppositive online comments are matched between real case and simulations; at the macro-level, the life cycle process (outbreak, rising, peak, and vanish) and durations can be well matched. Therefore, our model has properly seized the core mechanism of individual behaviors, and precisely simulated the evolutionary dynamics of online cases in reality.

The Life Cycle Process Model

This chapter describes the core features of life cycle models of organizational change. These models of change are also referred to as regulated, mandated, prescribed, imposed, logically necessary, or prefigured in advance of their execution. Life-cycle models do not imply that an actor must passively comply with mandated changes; actors may be proactive individuals who adapt to their environments and make use of rules to accomplish their purposes. The strengths, challenges, and stages of life cycle models are examined, and future developments advancing life cycle models by considering the role of choice and of multiple forms of agency are advocated.

ADDRESSING PRESENT CHALLENGES IN THE LIFE-CYCLE OF WETLANDS MANAGEMENT TO SUCCESSFULLY INTEGRATE SUSTAINABILITY AND GOOD GOVERNANCE

The assessment of management effectiveness during the whole life-cycle process of protected areas (PAs) has become increasingly important, due to the lack of holistic background assessment work on management processes leading to a deeper knowledge of sustainable development (SD) principles. This paper aims to serve as a practical guide through a gradation model of integrated protected area management (IPAM) by carrying out an exhaustive trans-dimensional assessment of management effectiveness, identifying a critical field of activities and developing a framework mix of strategic recommendations leading to the implementation of an effective planning process. Our results could aid in the prioritisation of key decisions towards a more in-depth understanding of how to set up a balanced IPAM, as well as to enable managers and decision-makers to focus on activities that can further pre-established aims and reach the goal of five-dimensional sustainability in terms of SD and good governance.

Information Security Assessment in Big Data Environment using Fuzzy Logic

In recent years, it has been observed that disclosure of information leads to the risk. Without restrict the accessibility of information providing security is difficult. So, there is a demand of time to fill the gap between security and accessibility of information. In fact, security tools should be usable for improving the security as well as the accessibility of information. Though security and accessibility are not related directly, but some of their factors indirectly affect each other. Attributes play an important role in connecting the gap among security and accessibility. In this paper, finds the main attributes of security and accessibility that impact directly and indirectly each other such as confidentiality, integrity and availability and severity. The significance of every attribute in terms of their weight is important for their effect on the overall security during the big data security life cycle process. To calculate proposed work, researchers used the Fuzzy Analytic Hierarchy Process (Fuzzy AHP).