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Enterprise architecture (EA) has provided organizations with powerful frameworks with which to plan, manage, model and coordinate the alignment of organizational IS/ IT portfolios with organizational strategy. However, for the benefits of EA to be realized, it needs to also contribute to the process of implementing the specified systems and platforms. Whilst implementation was seen by early authors as an integral aspect of the EA process, it has since generally been ignored by authors, or investigated through an ontological lens of discreet technical architecture activities that does not account for the social context of an EA implementation (EAI). Drawing on an actual case study of an EAI in a large Australian financial services organization, I examine the importance of the EAI process to the delivery of the systems and platforms specified in the EA plans and highlight an alternative perspective that has the potential to sensitize scholars and practitioners appreciate to the social context of an EAI.

As the COVID-19 pandemic entered and disturbed activities in every nation, managing manual agricultural practices are slowly shifting towards automation such as the use of the Internet of Things (IoT) and machine learning. This trend can be seen both in the global and local setting, which they termed precision agriculture or commonly known as smart farming. The purpose of this study was to explore the role of smart farming technologies both in urban and rural areas especially in the Philippines. The results showed that the impact on agriculture in terms of the economic aspect expanded by about 1.6% in its GDP despite the pandemic, that is experienced all over the globe. Furthermore, key performance indicators in aspects of economic, industry/manufacturing including labor and social were determined, which yielded out to be positive despite some barriers or constraints identified. In the end, there were - going programs and projects under precision agriculture that will support labor and employment, human development through government laws/policy, and research and development/innovation until the post-pandemic era or the new normal.

Graph theory can be applied to ecological questions in many ways, and more insights can be gained by expanding the range of graph theoretical concepts applied to a specific system. But how do you know which methods might be used? And what do you do with the graph once it has been obtained? This book provides a broad introduction to the application of graph theory in different ecological systems, providing practical guidance for researchers in ecology and related fields. Readers are guided through the creation of an appropriate graph for the system being studied, including the application of spatial, spatio-temporal, and more abstract structural process graphs. Simple figures accompany the explanations to add clarity, and a broad range of ecological phenomena from many ecological systems are covered. This is the ideal book for graduate students and researchers looking to apply graph theoretical methods in their work

"Ecology is about understanding how organisms interact with other organisms and the environment they inhabit (i.e. fundamental and realised niches). It is easy to imagine an individual organism of any kind as a dot with all sorts of arrows impinging upon it, an arrow can represent abiotic factors (temperature, light, etc.), as well as many arrows for all the other organisms (biotic factors, intra- and inter-specific interactions) that affect it. Ecology aims therefore to determine the magnitude and rate associated with some of the arrows, and which are the most important and why. Each organism also has its own effects on the same list of factors, even if the effects may be small, so we can also imagine arrows going out from the same dot, one to each of the same list of factors (they can be dots too). Again, a challenge is to determine the associated weights and importance for the arrows, some of which are directed toward other organisms. As soon as we consider more than a single organism, even just a few, we immediately have a complex structure of dots and arrows: an ecological network! It is an obvious step to consider ecological systems as ecological networks, and as such to assess how network theory (concepts and methods) might be applied to them. Network theory and the mathematics of graph theory that underlie network analysis provide simple concepts that can applied to systems that are complex both in structure and dynamics. It is those concepts that allow us to provide a sorted set of methods for the quantitative analysis of 10 ecological networks, along with thoughts and advice on how best to proceed. Through the years, the need to take a network analysis framework to study complex system has arisen in many fields (physics, computer science, communication science (transportation, electricity, social), and bio- and ecoinformatics), and there is a challenging diversity of approaches, methods, and measures that should be understood, or at least sorted, before applying them to our own data. The overarching goal of this book is to help ecologists in selecting the appropriate network methods to represent, analyse, and model their ecological system using network theory"--