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Cutting Edge Data Analytical Tools
Published in Chong Ho Alex Yu, Data Mining and Exploration, 2022
The open source movement was started in the late 1970s and early 1980s by Richard Stallman, a computer programmer at MIT. In September 1983, Stallman created the GNU project (GNU stands for GNU’s Not Unix—a recursive acronym) with the goal of giving a UNIX-like operating system to the world for free. In 1997 software engineer Eric Raymond published his seminal essay, entitled “The Cathedral and the Bazaar.” The Cathedral model refers to the software development process in which code developed between releases is restricted to an exclusive group, whereas the Bazaar model refers to an open system in which the code is distributed across the Internet so that everyone can contribute to debugging. To actualize what he proclaims, in 1998 Raymond released the source code of Netscape, an early Web browser, to the public. In the same year the term “open source” was coined by Christine Peterson to describe this type of free software (Haff 2018). Python and the R Language are two major tools for data science.
Lean Startup
Published in Yves Caseau, The Lean Approach to Digital Transformation, 2022
Lean startup is often associated with disruptive innovation—inventing a new product—in the B2C world of the general public. In fact, this approach is much more general and applies to the majority of product and service developments in the digital world. Many of the startups whose analyses led to the formalization of lean startup, by Steve Blank and by Eric Ries, come from the world of enterprise software. There is no “size effect” that would make the principles we have just presented—and that we will detail later—valid only for a large number of customers. Lean startup, in particular design thinking and growth hacking, can be applied with a handful of customers. In the same way, even if design thinking is particularly suitable for inventing new products, it is also suitable for designing new functionalities for existing products and services, and especially for designing new interfaces or digital modalities (experiences) around a traditional product. The process described in the previous figure, therefore, has very wide applicability, especially as a support for digital transformation. This is confirmed in the book Lean Enterprise: “However, the founding principles of Lean Startup can be applied to all kinds of activities in the enterprise, such as internal tool development, process improvement, organizational changes, legacy system replacements, and governance, risk management and regulatory compliance management programs.”
Overview of the Product Life Cycle
Published in Jon M. Quigley, Kim L. Robertson, Configuration Management, 2019
Jon M. Quigley, Kim L. Robertson
For some, it may be easier to understand how software radiates using a different example from nature. In the laboratory, Escherichia coli (E. coli) bacteria are often the organism of choice due to their rapid reproduction rate. In one case, scientists at the Georgia Institute of Technology have inserted 500 million-year-old Paleozoic-era bacteria genes into E. coli to determine if it will evolve the same way it did the first time around or whether it will evolve into a different, new organism. As of July 2012, 1,000 generations had been observed. The new bacteria grew about two times slower than their modern-day counterpart at first and have since mutated rapidly to become stronger and healthier than today's bacteria. The ancient gene has not yet mutated to become more like its modern form, but rather, the bacteria found a new evolutionary trajectory.27 Software follows a similar evolutionary path to that described by Betul Kacar and Eric Gaucher for the modified E. coli bacteria.
RRI legacies: co-creation for responsible, equitable and fair innovation in Horizon Europe
Published in Journal of Responsible Innovation, 2021
Douglas K. R. Robinson, Angela Simone, Marzia Mazzonetto
The potential of user-led innovation has been extensively studied by researchers such as Eric Von Hippel (2005): users have developed innovative products and services in areas as diverse as software engineering (e.g. the Open Source movement), medical tools, sports equipment or music systems. However, even when led by science engagement institutions, co- creation processes reach their full potential when they lead to a real influence of all stakeholders – including citizens – on the products and services that reach the market.6. To what extent co-creation can be considered a trigger for effectively enabling and advancing (Open) Innovation, thus generating concrete and effective outcomes thanks to its potential to better respond to specific socially-driven innovation needs, and not just a ‘virtue’ in itself which does not need to be legitimized (Voorberg, Bekkers, and Tummers 2015), is still to be explored and definitely not sufficiently addressed in the SwafS context.
Service-oriented invisible numerical control application: architecture, implementation, and test
Published in International Journal of Production Research, 2022
Lisi Liu, Yingxue Yao, Jianguang Li
DDD, designed by Eric Evans, is a software development approach for building complex applications that is centred on the development of an object-oriented domain model (Evans 2019). In contrast to the traditional software development approach that creates a single model for the entire application, DDD identifies subdomains as identifying business capabilities of an application and defines a separate domain model for each subdomain. A domain model captures knowledge about a domain in a form that can be used to solve problems within that domain. The scope of a domain model is called a bounded context and the relationship among bounded contexts is called context mapping. Generally, a bounded context maps nicely to a microservice within an MSA (Richardson 2019).
A novel cyber-physical resilience-based strategy for water quality sensor placement in water distribution networks
Published in Urban Water Journal, 2023
Dionysios Nikolopoulos, Christos Makropoulos
This section describes the optimization problem formulation for cyber-physical resilient water quality sensors placement, assuming the known topology and characteristics of a WDN in EPANET’s 2.2 format. The WDN’s analysis is performed using Python with the WNTR (Klise et al. 2017) package for handling EPANET files and simulations, NetworkX (Hagberg, Schult, and Swart 2008) for graph algorithms, Pandas (McKinney 2010) for handling result dataframes and SciPy (Jones, Eric, Travis Oliphant, Pearu Peterson, and others 2001) for the optimization routine.