Abstract
Service design and innovation are receiving greater attention from the service research community because they play crucial roles in creating new forms of value cocreation with customers, organizations, and societal actors in general. Service innovation involves a new process or service offering that creates value for one or more actors in a service network. Service design brings new service ideas to life through a human-centered and holistic design thinking approach. However, service design and innovation build on dispersed multidisciplinary contributions that are still poorly understood. The special issue that follows offers important contributions through the examination of service design and innovation literature, the links between service design and innovation, the role of customers in service design and innovation, and service design and innovation for well-being. Building on these contributions, this article develops a future research agenda in three areas: (1) reinforcing and expanding the foundations of service design and innovation by integrating multiple perspectives and methods; (2) advancing service design and innovation by improving the connection between the two areas, deepening actor involvement, and leveraging the role of technology; and (3) upframing service design and innovation to strengthen research impact by innovating complex value networks and service ecosystems and by building a cornerstone for transformative service research.

Abstract
Since the introduction of Single Instruction Multiple Thread (SIMT) GPU architectures, vectorization has seldom been recommended. However, for efficient use of 8-bit and 16-bit data types, vector types are necessary even on these GPUs. When only integer types were natively supported in sizes of less than 32-bits, the usefulness of vectors was limited, but the introduction of hardware support for packed half-precision floating point computations in recent GPU architectures changes this, as now floating-point programs can also benefit from vector types. Given a GPU kernel, using smaller data-types might not be sufficient to achieve the optimal performance for a given device, even on hardware with native support for half-precision, because the compiler targeting the GPU may not able to automatically vectorize the code. In this paper, we present a number of examples that make use of the OpenCL vector data-types, which we are currently implementing in our tool for automatic vectorization. We present a number of experiments targeting a graphics card with an AMD Vega 10 XT GPU, which has 2x peak arithmetic throughput using half-precision when compared with single-precision. For comparison, we also target an older GPU architecture, without native support for half-precision arithmetic. We found that, on an AMD Vega 10 XT GPU, half-precision vectorization leads to performance improvements over the scalar version using the same precision (geometric mean speedup of 1.50x), which can be attributed to the GPU being able to make use of native native support for arithmetic over packed half-precision data. However, we found that most of the performance improvement of vectorization is caused by related transformations, such as thread coarsening or loop unrolling.

Abstract
This documents introduces \Energyware" as a software engineering discipline aiming at defining, analyzing and optimizing the energy consumption by software systems. In this paper we present energyware analysis in the context of programming languages, software data structures and program's source code. For each of these areas we describe the research work done in the context of the Green Software Laboratory at Minho University: we describe energyaware techniques, tools, libraries, and repositories. © 2018 by the paper's authors.

Abstract
The recent technological advances on telecommunications create a new reality on mobility sensing. Nowadays, we live in an era where ubiquitous digital devices are able to broadcast rich information about human mobility in real-Time and at a high rate. Such fact exponentially increased the availability of large-scale mobility data which has been popularized in the media as the new currency, fueling the future vision of our smart cities that will transform our lives. The reality is that we just began to recognize significant research challenges across a spectrum of topics. Consequently, there is an increasing interest among different research communities (ranging from civil engineering to computer science) and industrial stakeholders on building knowledge discovery pipelines over such data sources. However, such availability also raises privacy issues that must be considered by both industrial and academic stakeholders on using these resources. © 2000-2011 IEEE.

Abstract
This paper presents the perception system designed for the underwater mine exploration UNEXMIN robot. This autonomous underwater vehicle was designed in the context of the European 112020 ENEXIVIIN project to explore flooded underground mines The presented work addresses the sensor choice and placement options, the characterization of the system with results obtained in test tank and on field missions in mines. The perception software and computational architecture is also discussed with details on its distributed features. This perception system is comprised of one multibeam imaging/profiling sonar, one mechanically scanning sonar, digital cameras and a set of custom developed laser based structured light systems. The presented results from the Kaatiala mine (Finland) field trials and the Idrija mine tests (Slovenia) are discussed and allow for the performance analysis of the system.

Abstract
Individuals and companies have a feeling of insecurity in the Internet, as every day a reasonable amount of attacks take place against users’ privacy and confidentiality. The use of digital equipment in illicit and unlawful activities has increasing. Attorneys, criminal polices, layers and courts staff have to deal with crimes committed with digital “weapons”, whose evidences have to be examined and reported by applying digital forensics methods. Digital forensics is a recent and fast-growing area of study which needs more graduated professionals. This fact has leveraged higher education institutions to develop courses and curricula to accommodate digital forensics topics and skills in their curricular offers. This paper aims to present the development of a cybersecurity and digital forensics master course in Polytechnic of Leiria, a public higher education institution in Portugal. The authors depict the roadmap and the general milestones that lead to the development of the course. The strengths and opportunities are identified and the major students’ outcomes are pointed out. The way taken and the decisions made are also approached, with a view to understanding the performance obtained so far. © 2020, Springer Nature Switzerland AG.