Technologies to develop technology: the impact of new technologies on the organisation of the innovation process.

Companies are under increasing pressure to develop new product more effectively and efficiently. In order to meet this challenge, the organisation of the new product development process has received ample attention both in the academic literature and in the practitioner literature. As a consequence, a myriad of methods to design new products has been developed. These methods aim at facilitating concurrent product design and engineering. However, it is only recently, through the advent of families of new design technologies, that concurrency really becomes possible. In this paper, research on the impact of new design technologies on the product development process is reported and discussed. It is demonstrated that these technologies can have a significant impact on the organisation of innovation processes.Processes;

Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World

This report documents the program and the outcomes of GI-Dagstuhl Seminar 16394 "Software Performance Engineering in the DevOps World". The seminar addressed the problem of performance-aware DevOps. Both, DevOps and performance engineering have been growing trends over the past one to two years, in no small part due to the rise in importance of identifying performance anomalies in the operations (Ops) of cloud and big data systems and feeding these back to the development (Dev). However, so far, the research community has treated software engineering, performance engineering, and cloud computing mostly as individual research areas. We aimed to identify cross-community collaboration, and to set the path for long-lasting collaborations towards performance-aware DevOps. The main goal of the seminar was to bring together young researchers (PhD students in a later stage of their PhD, as well as PostDocs or Junior Professors) in the areas of (i) software engineering, (ii) performance engineering, and (iii) cloud computing and big data to present their current research projects, to exchange experience and expertise, to discuss research challenges, and to develop ideas for future collaborations

Technology Readiness Levels for Machine Learning Systems

The development and deployment of machine learning (ML) systems can be executed easily with modern tools, but the process is typically rushed and means-to-an-end. The lack of diligence can lead to technical debt, scope creep and misaligned objectives, model misuse and failures, and expensive consequences. Engineering systems, on the other hand, follow well-defined processes and testing standards to streamline development for high-quality, reliable results. The extreme is spacecraft systems, where mission critical measures and robustness are ingrained in the development process. Drawing on experience in both spacecraft engineering and ML (from research through product across domain areas), we have developed a proven systems engineering approach for machine learning development and deployment. Our "Machine Learning Technology Readiness Levels" (MLTRL) framework defines a principled process to ensure robust, reliable, and responsible systems while being streamlined for ML workflows, including key distinctions from traditional software engineering. Even more, MLTRL defines a lingua franca for people across teams and organizations to work collaboratively on artificial intelligence and machine learning technologies. Here we describe the framework and elucidate it with several real world use-cases of developing ML methods from basic research through productization and deployment, in areas such as medical diagnostics, consumer computer vision, satellite imagery, and particle physics

A Review of the Open Educational Resources (OER) Movement: Achievements, Challenges, and New Opportunities

Examines the state of the foundation's efforts to improve educational opportunities worldwide through universal access to and use of high-quality academic content

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

Engineering Automation for Reliable Software Interim Progress Report (10/01/2000 - 09/30/2001)

Prepared for: U.S. Army Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211The objective of our effort is to develop a scientific basis for producing reliable software that is also flexible and cost effective for the DoD distributed software domain. This objective addresses the long term goals of increasing the quality of service provided by complex systems while reducing development risks, costs, and time. Our work focuses on "wrap and glue" technology based on a domain specific distributed prototype model. The key to making the proposed approach reliable, flexible, and cost-effective is the automatic generation of glue and wrappers based on a designer's specification. The "wrap and glue" approach allows system designers to concentrate on the difficult interoperability problems and defines solutions in terms of deeper and more difficult interoperability issues, while freeing designers from implementation details. Specific research areas for the proposed effort include technology enabling rapid prototyping, inference for design checking, automatic program generation, distributed real-time scheduling, wrapper and glue technology, and reliability assessment and improvement. The proposed technology will be integrated with past research results to enable a quantum leap forward in the state of the art for rapid prototyping.U. S. Army Research Office P.O. Box 12211 Research Triangle Park, NC 27709-22110473-MA-SPApproved for public release; distribution is unlimited