A Structured Cloud-Based Software Testing Model with a Case Study Implementation

Cloud-based testing methodologies were gaining significant popularity and adoption in the software testing industry. Cloud-based testing offers several advantages, such as scalability, flexibility, cost-effectiveness, and the ability to access a wide range of testing tools and environments without the need for extensive infrastructure setup. Cloud testing methods are having challenges with respect to testing priority, practical use cases, performance, lengthy test time, integrating and streamlining, data security, etc. since they are addressing specific purposes. To address these challenges, there is a need for a structured testing model with respect to the cloud environment. This article proposes a new structured cloud-based testing model for enhancing the testing service in the cloud environment. The proposed model addresses the order of testing and the priority, data security, and performance by using Smoke and Sanity testing methods

Assessment of adaptation measures against flooding in the city of Dhaka, Bangladesh

Dhaka is one of the world’s largest megacities with a high rate of urbanization. Due to the setting of greater Dhaka in a deltaic plain, it is extremely prone to detrimental flooding. Risks associated with flood are expected to increase in the coming years because of the global climate change impacts as well as the high rate of urbanization the city is facing. The low lying part of Dhaka (Dhaka East) faces most severe risk of flooding. Traditionally, this part has been efficiently storing the excess water caused by excessive rainfall and the canals connected to the rivers gradually drained the water to the rivers. But the alarmingly increasing population of Dhaka is leading towards the encroachment of these water retention areas because of the land scarcity. The natural drainage for the city is not performing well and the area is still unprotected from flooding, which causes major threats to its inhabitants. This situation increases the urgency to effectively adapt to current floods caused by climate variability and to the impacts of future climate changes. The government is planning several adaptive measures to protect the area whereas a systematic framework to analyze and assess them is lacking. The objective of the paper is to develop an integrated framework for the assessment of various (current and potential) adaptation measures aimed at protecting vulnerable areas from flooding. The study firstly assesses current and future risks from flooding in the most sensitive region of the city. Subsequently, the study identifies, analyses and assesses adaptive initiatives and measures to address flood risks in the Eastern fringe area. Adaptation assessment is conducted within the framework of Multi Criteria Analysis methodology which allows both normative judgment and technical expertise in the assessment process. Based on the assessment and analysis, adaptive measures are prioritized to enable more effective action. Such a participatory integrated assessment of adaptation options is a new approach in flood management in least developed countries and in Bangladesh in particular. A framework for prioritization of adaptation measures is lacking in the decision making process in Bangladesh which could immensely assist in informed and structured decisions while developing adaptation strategies

Intellectual property related development aid: is supply aligned with demand?

We assessed to what extent developed country development aid programmes are likely to have interacted with, and potentially contributed to the promotion of country-appropriate sustainable changes in IP strategies and technological capacities over the period 2005-10. This was done primarily on the basis of an imputed impact assessments of four emerging and transition economies; namely Brazil, India, Poland and Thailand. Through an analysis of various measures of the domestic economic, technological and Intellectual Property context, we studied to what extent the supply of IP-related development aid provided between 2005 and 2010 responded to the likely needs of recipient countries. While the data shows that technical and financial assistance in this area could be of great use, and there is clearly a need for well-targeted IP TA and much scope for useful IP TA interventions, there seemed to only be a partial alignment between country needs and the direction of IP TA. On the whole, most IP-related development aid and technical assistance ended to focus on similar areas in each country, regardless of the development context. In Brazil and India’s case, training on IP administration may have influenced increased efficiency (from a low base) at the INPI and IP India, while the substantial EU support to raise SME IP awareness in Poland is likely to have had some significant impacts. In India, sustained development aid in this area likely influenced legislation on plant variety protection, as did WIPO TA on legislative reforms in Thailand. In all cases, the substantial US (and to a more limited extent EC) focus on development aid directed towards enforcement coincided with improvements in this area, though the political and economic pressures by both providers, and especially the US Section 301 System probably dwarfed the impact of this type of aid. Further, the typology and direction of IP related development aid reflects the comparative advantage of IP TA providers, as well as political and diplomatic interests, trade priorities and colonial ties, among many other things. As such, it is important to understand that IP TA is also highly political – a fact often concealed in the emphasis on its “technical” nature.Intellectual Property and development, aid and technical assistance technological capacities in Brazil, India, Poland, Thailand, taxonomy of development, funding flows Intellectual Property and development, aid and technical assistance technological capacities in Brazil, India, Poland, Thailand, taxonomy of development, funding flows Intellectual Property and development, aid and technical assistance, technological capacities in Brazil, India, Poland, Thailand, taxonomy of development, funding flows Intellectual Property and development, aid and technical assistance technological capacities in Brazil, India, Poland, Thailand, taxonomy of development, funding flows

Resilience assessment and planning in power distribution systems:Past and future considerations

Over the past decade, extreme weather events have significantly increased worldwide, leading to widespread power outages and blackouts. As these threats continue to challenge power distribution systems, the importance of mitigating the impacts of extreme weather events has become paramount. Consequently, resilience has become crucial for designing and operating power distribution systems. This work comprehensively explores the current landscape of resilience evaluation and metrics within the power distribution system domain, reviewing existing methods and identifying key attributes that define effective resilience metrics. The challenges encountered during the formulation, development, and calculation of these metrics are also addressed. Additionally, this review acknowledges the intricate interdependencies between power distribution systems and critical infrastructures, including information and communication technology, transportation, water distribution, and natural gas networks. It is important to understand these interdependencies and their impact on power distribution system resilience. Moreover, this work provides an in-depth analysis of existing research on planning solutions to enhance distribution system resilience and support power distribution system operators and planners in developing effective mitigation strategies. These strategies are crucial for minimizing the adverse impacts of extreme weather events and fostering overall resilience within power distribution systems.Comment: 27 pages, 7 figures, submitted for review to Renewable and Sustainable Energy Review

Improvement of Work Process Performance with Task Assignments and Mental Workload Balancing

The outcome of a work process depends heavily on which tasks assigned to which employees. However, sometimes-optimized assignments based on employees’ qualifications may result in an uneven and ineffective workload distribution among them. Likewise, an even workload distribution without considering the employee\u27s qualifications may cause unproductive employee-task matching that results in low performance of employees. This trade-off is even more noticeable for work processes during critical time junctions, such as in military command centers and emergency rooms that require being fast and effective without making errors. This study proposes that optimizing task-employee assignments according to their capabilities while also keeping them under a workload threshold, results in better performance for work processes, especially during critical time junctions. The goal is to select the employee-task assignments in order to minimize the average duration of a work process while keeping the employees under a workload threshold to prevent errors caused by overload. Due to uncertainties inherent in the problem related with the inter-arrival time of work orders, task durations and employees\u27 instantaneous workload, a utilized simulation-optimization approach solves this problem. More specifically, a discrete event human performance simulation model evaluates the objective function of the problem coupled with a genetic algorithm based meta-heuristic optimization approach to search the solution space. This approach proved to be useful in determining the right task-agent assignments by taking into consideration the employees\u27 qualifications and mental workload in order to minimize the average duration of a work process. Use of a sample work process shows the effectiveness of the developed simulation-optimization approach. Numerical tests indicate that the proposed approach finds better solutions than common practices and other simulation-optimization methods. Accordingly, by using this method, organizations can increase performance, manage excess-level workloads, and generate higher satisfactory environments for employees, without modifying the structure of the process itself

Adapting to Climate Change: The Case of Multi-level Governance and Municipal Adaptation Planning in Nova Scotia, Canada

Nova Scotia is the only province in Canada to use the gas tax as a financial incentive to create a regulatory mandate for ‘Municipal Climate Change Action Plans’ (MCCAPs). The MCCAP adaptation policy mandate initiated and enabled climate change vulnerability assessment and the development of climate risk priorities and adaptation plans to uniformly occur at the local scale in 53 Nova Scotian municipalities. This dissertation seeks to answer the question: What are the social factors that impacted municipal climate change adaptation policy and planning processes in the multi-level governance context of Nova Scotia’s MCCAP? The study develops and operationalizes a thematic, functional conceptual framework and exploratory, descriptive case study research approach for conducting adaptation case studies and comparative analysis of municipal adaptation planning processes in multi-level governance contexts. The framework enables thematic investigation and discussion about the social factors impacting municipal adaptation policy and planning processes in multi-level governance and municipal case settings. The study utilizes content analysis of adaptation plans in combination with focus groups, an iterative online survey and targeted interviews conducted with adaptation stakeholders to explore, describe and illustrate what and how social factors impacted the MCCAP process in Nova Scotia municipalities. The mixed methodology provides a pragmatic approach to generate data from which to compare evidence of the social impact factors that affect municipalities’ adaptation planning and policy development processes in multi-level governance contexts. The study offers new empirical and conceptual insights into the ‘how and what’ of municipal climate change adaptation policy making processes in multi-level adaptation governance contexts. The study conceptually affirms that significant resource and capacity-building gaps, a lack of governmental coordination, low levels of public demand and aspects of cross-scalar political leadership hinder and constrain adaptation capacity building and policy integration in municipal processes. Institutional fragmentation and lack of multi-level policy coordination may be key social factors impacting Nova Scotia municipalities’ adaptive capacities and the prospects for long-term resiliency and adaptation to climate change risks impacting communities at the local scale

Regression testing framework for test cases generation and prioritization

A regression test is a significant part of software testing. It is used to find the maximum number of faults in software applications. Test Case Prioritization (TCP) is an approach to prioritize and schedule test cases. It is used to detect faults in the earlier stage of testing environment. Code coverage is one of the features of a Regression Test (RT) that detects more number of faults from a software application. However, code coverage and fault detection are reducing the performance of existing test case prioritization by consuming a lot of time for scanning an entire code. The process of generating test cases plays an important role in the prioritization of test cases. The existing automated generation and prioritization techniques produces insufficient test cases that cause less fault detection rate or consumes more computation time to detect more faults. Unified Modelling Language (UML) based test case generation techniques can extract test cases from UML diagrams by covering maximum part of a module of an application. Therefore, a UML based test case generation can support a test case prioritization technique to find a greater number of faults with shorter execution time. A multi-objective optimization technique able to handle multiple objectives that supports RT to generate more number of test cases as well as increase fault detection rate and produce a better result. The aim of this research is to develop a framework to detect maximum number of faults with less execution time for improving the RT. The performance of the RT can be improved by an efficient test case generation and prioritization method based on a multi-objective optimization technique by handling both test cases and rate of fault detection. This framework consists of two important models: Test Case Generation (TCG) and TCP. The TCG model requires an UML use case diagram to extract test cases. A meta heuristic approach is employed that uses tokens for generating test cases. And, TCP receives the extracted test cases with faults as input to produce the prioritized set of test cases. The proposed research has modified the existing Hill Climbing based TCP by altering its test case swapping feature and detect faults in a reasonable execution time. The proposed framework intends to improve the performance of regression testing by generating and prioritizing test cases in order to find a greater number of faults in an application. Two case studies are conducted in the research in order to gather Test Case (TC) and faults for multiple modules. The proposed framework yielded a 92.2% of Average Percentage Fault Detection with less amount of testing time comparing to the other artificial intelligence-based TCP. The findings were proved that the proposed framework produced a sufficient amount of TC and found the maximum number of faults in less amount of time

Optimizing Turning Parameters for The Turning Operations of Inconel X750 Alloy with Nanofluids Using Direct and Aspect Ratio-based Taguchi Methods

For the turning process, the computation of optimal parametric settings for parameters has been traditionally achieved using standard parametric values, but comparative values between the standard parameters have been ignored. But these aspect ratios reveal some evaluation dimensions that account for robust measurement schemes that promote enhanced effectiveness of the process. To address the issue, an aspect-ratio-based mechanism has been introduced to optimize the turning parameters in three Taguchi methodical variants of classical Taguchi, Taguchi-Pareto, and Taguchi-ABC methods. A total of twelve alternatives were developed, with each alternative containing three standard parameters and two aspect ratios since only three standard parameters are involved in the evaluation. The evaluation of parameters in non-prioritized and prioritized forms was considered for each alternative. The Taguchi method accounts for the non-prioritized method, while Taguchi-Pareto and Taguchi-ABC methods are the prioritized parametric structures. The delta values and ranks across the prioritized and non-prioritized parameters were evaluated by their mean values. The optimal parametric settings were evaluated for all alternatives in the prioritized and non-prioritized forms of evaluation. The results, using literature data, confirmed the feasibility of using the approach. The outcome of the methods is in enhancing the planning scheme for the turning operation. The benefit of the study is an enhanced analysis of turning operation’s improvements and estimation of related economic advantages through turning resources conservation

Modeling the Co-Production of Public Sector Innovation: Strategic Dimensions of Organizational Innovation within the Public Maritime Ports of the Pacific Northwest

Innovation is vital to employing resources in times when the complexity and the demand for public goods and services strain organizational capacities. While innovation in the private sector is the subject of intense academic interest, the study of this phenomenon in the public sector pales in comparison. This is troubling because innovation is an important tool for overcoming resource limitations that plague the public sector. This dissertation\u27s unique contribution to the field is the creation and empirical validation of a model that explains and predicts the co-production of public sector innovation. The model explains the causal mechanism of innovation and has predictive value. No generally agreed upon or empirically tested theory exists for understanding or predicting the social interactions that lead to public sector innovation. This dissertation closes this gap by using prior research and empirical observations to build and validate a model that explains the co-production of public sector innovation at the nexus of leadership, the organization, and the customer or client of the organization. The findings, conclusions, and recommendations of this study bridge theory and practice to define the conditions that lead to co-production of public sector innovation. This dissertation employed a deductive-inductive typological approach that used grounded theory to describe the conditions present when innovation occurs. These conditions exist as antecedents that include adaptive interest alignment, client-based prioritization, co-production readiness, organizational incentives, and organizational structure and culture. This study defined and then measured six independent variables that indicate the antecedents\u27 presence. These antecedents served to predict the opening of a pathway to co-production of public sector innovation. Empirical measurement of the six independent variables served to indicate the presence or absence of the antecedents that operate in three intersecting domains (leadership, organization, and clients or customers). The independent variables are present when the dependent variable of co-produced public sector innovation emerged. The creation of two unique indices provided an aggregate summary of the variables. The indices served as proxy measures of co-produced public sector innovation. Special districts served as the empirical setting for this research. A case study approach served to validate the model using indices of the expected and actual measurement of co-production of innovation in the public sector. This dissertation validated the theoretical framework that served as a heuristic tool for conceptualizing the dynamics that moderate the co-production of public sector innovation within a defined political economy. The findings, conclusions, and recommendations that emerged from this research contribute to the ongoing dialogue about the conditions necessary for public sector innovation to occur