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Abstract: In order to provide cost-efficient and rapid protection against the key link failures dynamically, an intelligent p-cycle protection strategy based on network coding is proposed. Data units are combined from different links using network coding method at the on-cycle nodes, and then they are transmitted downstream for recovering data units lost due to failures. Under static traffic, an integer linear program (ILP) is formulated to provision the optimal p-cycles. Furthermore, according to the dynamic variation of the link importance degree, a heuristic cycle construction algorithm for generating, extending and contracting p-cycle is introduced to achieve intelligent and self-adaptive protection. The key of the proposed protection strategy is how to set the key link as a straddling link of the p-cycle as possible. The experiments demonstrate that the proposed strategy can guarantee instantaneous recovery of data units upon the failure of a key link with a low blocking rate and resource cost. [Copyright &y& Elsevier]

Abstract: This paper introduces a multi-tiered test automation architecture to optimize test automation in an Agile software development environment while increasing both the test coverage and depth of each tier. Test Automation is the act of converting manual test cases into automated scripts that can be executed autonomously. In general, testing accounts for roughly 60% of the overall development budget and approximately 50% of that is attributed to regression testing. In recent years software organizations have begun migrating to Agile software development practices and automated testing in hopes of reducing the cost, lengthy regression cycles, and time to market. Traditionally, test automation is conducted on stable, non-changing applications. In an Agile environment where the code constantly changes, automated test cases become obsolete and must constantly be refactored in order to provide meaningful feedback about the system's quality. In most instances the cost of maintenance of automated test code completely overshadows the entire automation effort and negates any possible Return on Investment (RoI). An n-Tiered Test Automation Architecture seeks to retain the RoI by abstracting the automation project into separate distinct tiers; Presentation, Business, Data, and Services. These abstractions allow automated testing to continue providing feedback despite the constant revision of the system. A case study was conducted using this method and the observations showed that the automation architecture was resilient to change while increasing the test coverage, the depth of testing, and the overall quality of the application under test. [Copyright &y& Elsevier]

Abstract: Processes in product development are becoming more and more complex. A multitude of engineering disciplines are involved in the development of new products. New lean and agile methods arise. Pulse methodology is a lean deviation management methodology introduced by Scania in 2003, and since then many Swedish companies adapted it. It is based on synchronizing the company by frequently having short meetings (aka. pulse meetings) and visualizing the deviations using traffic coded magnets on whiteboards (aka. pulse boards). Even though the whiteboards lack providing efficient communication between distributed teams, still the users appreciate the simplicity of them. In this research, we presented a new methodology called hybrid pulse methodology, which solves the communication issues exist in the baseline methodology. We tested the methodology at the workshops we held in the companies, in simulated global meeting settings, using the demonstrator we developed for the methodology. This research contributes to the lean literature with a new methodology that ensures the synchronization of global organizations by providing efficient communication between distributed teams without damaging the baseline methodology. [Copyright &y& Elsevier]

Abstract: This is a discussion of the essential features of product development traceability maps in relation to requirements, architecture, functional models, components, and tests as a set of order type hierarchies and their cross-links. This paper lays out the structure of these ideal traceability relationships that define the essence of the product under development. The importance of the trace relationships to the product is clarified and then the abandonment of traceability in the Agile approach is discussed. Following that, a way to transform between synthetic canonical narrative (story) representations that appear in the product backlog and the traditionally separate hierarchical form of the trace structure of the product will be examined. The fact that it is possible to transform back and forth between the canonic narrative and traditional hierarchical representations of trace structures, and the fact that trace structures can be produced in a ‘just in time’ fashion that evolves during product development demonstrate that these trace structures can be used in both an Agile and Lean fashion within the development process. Also, we can show that when the trace structure is produced outside the narrative representation it can have the additional benefit of helping to determine the precedent order of development so that rework can be avoided. The lack of the extrinsic external trace structure of the product that gives access to its intelligibility is, in fact, a form of technical debt. Thus, traditional trace structures using this model can be seen as an essential tool for product owners to produce sound and coherent development narratives and for structuring and prioritizing the backlog in the Agile and Lean approaches to software and systems development. [Copyright &y& Elsevier]

Abstract: This paper serves as a tutorial lecture on the use of network coding to provide resource efficient and agile proactive protection. Network coding, which was introduced in Ahlswede et al. (2000) [1], allows intermediate network nodes to form linear combinations of packets received on different input links. The use of network coding results in capacity enhancement. This capacity enhancement is used to provide protection channels which are used to carry combinations of redundant data, and are solved by the receivers in order to recover data lost due to network failures. The paper starts by addressing network coding-based protection of bidirectional unicast connections, and explains the use of p-Cycles to carry linear combinations of the redundant data units. The paper also discusses an earlier protection strategy which is based on diversity coding, in which the linear combinations are formed at special nodes, including sources, and is used to protect unidirectional connections. A generalized network coding-based protection which uses a tree to carry the linear combinations will be presented. Protection of multicast connections using network coding is also explained. [Copyright &y& Elsevier]

Abstract: This paper presents a study of the integration of agile methods into mechatronics design education, as performed at KTH Royal Institute of Technology. The chosen method, Scrum, and the context of the studied capstone course are presented. With the integration of Scrum into the capstone projects, an educational favorable alternative is identified, to previously used design methodologies such as more traditional stage-gate methods as the Waterfall or method or the V-model. This is due to the emphasis on early prototyping, quick feedback and incremental development. It still might not be the favorable method for use in large scale industrial development projects where formal procedures might still be preferred, but the pedagogical advantages in mechatronics education are valuable. Incremental development and rapid prototyping for example gives many opportunities for students to reflect and improve. The Scrum focus on self-organizing teams also provides a platform to practice project organization, by empowering students to take responsibility for the product development process. Among the results of this study, it is shown that it is possible and favorable to integrate Scrum in a mechatronics capstone course and that this can enhance student preparation for a future career as mechatronics designers or product developers. It is also shown that this prepares the students with a larger flexibility to handle the increased complexity in mechatronics product development and thereby enabling the project teams to deliver results faster, more reliable and with higher quality. [Copyright &y& Elsevier]

Abstract: This paper presents the InterMod methodology. By combining the widely accepted Agile Methods, Model-Driven Developments and User-Centred Design it allows us to develop high-quality interactive applications. As a main characteristic, it plans and organises the software project as a series of iterations that are guided by the User Objectives in an agile and user-centred manner. At each iteration, the software development work can be distributed to different teams according to some developmental and integration activities. Each activity is driven by models that are validated by a multidisciplinary team composed of developers and users. The requirements are incrementally collected and formalised by means of models based on user-centred design. Besides, the Semantically Enriched Human–Computer Interaction model is proposed to speed up project validation. This model enriches a human–computer interaction model with some visual characteristics and the application semantic. Thus, the enriched model provides enough information to generate prototypes so users and developers can easily validate this model. Diagram project is a real case study that is used to illustrate the application of the InterMod methodology through the whole paper. [Copyright &y& Elsevier]

As an important branch of wearable electronics, flexible pressure sensors have aroused extensive concern owing to their wide range of applications, such as human health monitoring, human–machine interfaces, and artificial intelligence. Therefore, higher requirements are put forward for the dominating performances of sensitivity, pressure measurement range and response time about flexible pressure sensors. Here, we present a flexible piezoresistive pressure sensor (FPPS) based on carbon fibers (CFs)/carbon nanotubes (CNTs)-polydimethylsiloxane (PDMS) composite and interdigital electrode, which displays a wide measurement range of stress and an agile response at loading and unloading forces. Due to the cooperating advantages of the multiscale carbon fillers, the microstructures on the surface of the piezoresistive film and the interdigital electrode, the FPPS reveals a wide measurement range (from 0 kPa to 185.9 kPa) and a high sensitivity (2.02 kPa‐1 at pressures between 36 Pa and 50.2 kPa). Meanwhile, owing to the carefully designed trilateral double-sided adhesive structure, the FPPS exhibits an agile response (response time of 43 ms) and a stable output (test time of 9000 s). Moreover, the FPPS is capable of identifying clapping and trampling motions, demonstrating its effectiveness as a flexible sensing unit. The novel pressure sensor was integrated with additional software and hardware to realize a real-time pressure acquisition and display system, providing a potential use of the device in an intelligent industry application. [Display omitted] • Developed a FPPS based on multiscale CFs/CNTs-PDMS composite and interdigital electrode. • The FPPS reveals a wide pressure measurement range from 0 to 185.9 kPa. • The FPPS reveals an agile response time of 43 ms. • The FPPS is integrated with software and hardware to realize a pressure display system. [ABSTRACT FROM AUTHOR]

• Dextr is a semi-automated data extraction tool that can capture complex data. • Dextr connects extracted entities to support hierarchical data extraction. • Dextr supports development of annotated datasets within a standard review workflow. • Dextr's user verification option assures user-driven semi-automated data extraction. There has been limited development and uptake of machine-learning methods to automate data extraction for literature-based assessments. Although advanced extraction approaches have been applied to some clinical research reviews, existing methods are not well suited for addressing toxicology or environmental health questions due to unique data needs to support reviews in these fields. To develop and evaluate a flexible, web-based tool for semi-automated data extraction that: 1) makes data extraction predictions with user verification, 2) integrates token-level annotations, and 3) connects extracted entities to support hierarchical data extraction. Dextr was developed with Agile software methodology using a two-team approach. The development team outlined proposed features and coded the software. The advisory team guided developers and evaluated Dextr's performance on precision, recall, and extraction time by comparing a manual extraction workflow to a semi-automated extraction workflow using a dataset of 51 environmental health animal studies. The semi-automated workflow did not appear to affect precision rate (96.0% vs. 95.4% manual, p = 0.38), resulted in a small reduction in recall rate (91.8% vs. 97.0% manual, p < 0.01), and substantially reduced the median extraction time (436 s vs. 933 s per study manual, p < 0.01) compared to a manual workflow. Dextr provides similar performance to manual extraction in terms of recall and precision and greatly reduces data extraction time. Unlike other tools, Dextr provides the ability to extract complex concepts (e.g., multiple experiments with various exposures and doses within a single study), properly connect the extracted elements within a study, and effectively limit the work required by researchers to generate machine-readable, annotated exports. The Dextr tool addresses data-extraction challenges associated with environmental health sciences literature with a simple user interface, incorporates the key capabilities of user verification and entity connecting, provides a platform for further automation developments, and has the potential to improve data extraction for literature reviews in this and other fields. [ABSTRACT FROM AUTHOR]

• Systematic Literature Review about Metamodel-Based Simulation Optimization (MBSO). • The integration of new machine learning tools could improve metamodels. • The main applications, concepts and state of the art in MBSO were discussed. • The research found and discussed gaps that can be addressed by future studies. Over the past few decades, modeling, simulation, and optimization tools have received attention for their ability to represent and improve complex systems. The use of metamodeling techniques in optimization via simulation problems has grown considerably in recent years to promote more robust and agile decision-making, determining the best scenario in the solution space. The objective of this article is to conduct a systematic literature review of metamodeling-based simulation optimization (MBSO). The main contributions of this paper are related to systematically gather, analyze, and discuss the knowledge disseminated in this area, support future research and expand the literature related to MBSO techniques. Research questions were planned to assist MBSO researchers and practitioners, by presenting the most frequent contexts, applications, methods, tools, and metrics found in metamodeling studies in optimization via simulation problems. We considered papers published in scientific journals and listed in the Web of Science, Scopus, ACM Digital Library, IEEE Xplore, and Science Direct databases. The conclusion related the gaps, opportunities, and future perspectives found during the development of this research, suggesting that this research area is growing in the past 15 years. [ABSTRACT FROM AUTHOR]

• Influence Diagram accounts for uncertainties affecting lead time estimation. • Interactive tool to visually communicate probabilistic estimates to stakeholders. • Sensitivity analysis identified team velocity to most drastically impact lead time. • Cumulative distribution function can be an aid to prioritize project backlog queue. This research introduces an influence diagram based approach to estimating task lead times for Agile Kanban project management. Derived from the principles of lean manufacturing, Agile methodologies including Scrum, Scrumban, and Kanban are common in the software industry and are spreading to other fields. Many teams estimate task delivery to better manage stakeholder expectations and improve decision making. However, the current technique involves calculating a team's story point completion velocity, requiring hours of weekly effort while overlooking the addition, removal, and reprioritization of backlog tasks. While these factors may be critical in Scrum, teams practicing Kanban experience these conditions frequently due to the emphasis on continuous integration and reprioritization. Our alternative approach applies an influence diagram, or Bayesian belief network, to model the uncertainties affecting the lead time. To partially automate the estimation process, an influence diagram based expert system is developed and populated with data from a practicing Kanban team and used to generate a cumulative distribution function to facilitate the communication of probabilistic estimates. A sensitivity analysis is conducted to better understand how each factor influences lead times. This system can assist Kanban teams' stakeholder communication and reduce estimation workload through a more holistic model of lead times. [ABSTRACT FROM AUTHOR]

Abstract: The demands in the software industry of estimating development effort in the early phases of development are met by measuring software size from user requirements. A large number of companies have adapted themselves with Agile processes, which, although, promise rapid software development, pose a huge burden on the development teams for continual decision making and expert judgement, when estimating the size of the software components to be developed at each iteration. COSMIC, on the other hand, is an ISO/IEC international standard that presents an objective method of measuring the functional size of the software from user requirements. However, its measurement process is not compatible with Agile processes, as COSMIC requires user requirements to be formalised and decomposed at a level of granularity where external interactions with the system are visible to the human measurer. This time-consuming task is avoided by agile processes, leaving it with the only option of quick subjective judgement by human measurers for size measurement that often tends to be erroneous. In this article, we address these issues by presenting an approach to approximate COSMIC functional size from informally written textual requirements demonstrating its applicability in popular agile processes. We also discuss the results of a preliminary experiment studying the feasibility of automating our approach using supervised text mining. [Copyright &y& Elsevier]

Abstract: This paper shows the early experiences transferring architectural knowledge from Academic to Industry within an R+D+I project. This is done through the design and development of an Intelligent Transportation System (ITS) Architecture following SOA and RM-ODP principles, to facilitate openness, reusability, scalability and interoperability. Rationale selection of standards, technologies and platforms, considering system''s requirements (real time, cost ellipsis) has been done. An iterative agile development process, with incremental stages from design to final prototype, has been used. Early outcomes are centered in two services; multimedia flow management and notification. They have been developed using CORBA and are embedded in system''s devices. [Copyright &y& Elsevier]

Abstract: Software design is an often neglected issue in ecological models, even though bad software design often becomes a hindrance for re-using, sharing and even grasping an ecological model. In this paper, the methodology of agile software design was applied to the domain of ecological models. Thus the principles for a universal design of ecological models were arrived at. To exemplify this design, the open-source software Universal Simulator was constructed using C++ and XML and is provided as a resource for inspiration. [Copyright &y& Elsevier]

Abstract: The current state of the art of aircraft systems integration is similar to the traditional serial software engineering waterfall method. Agile methods transformed software engineering with a focus on incremental iterative value added design. This paper reviews selected non software agile case studies for lessons that are applicable to implementing agile methods to transform the aircraft systems integration process. [Copyright &y& Elsevier]

Abstract: Knowledge-based systems (KBSs) have been built and practically applied in various contexts for decades. Yet, they still challenge developers by their complexity: Apart from a sound knowledge base they likewise require comprehensive user interface (UI) and interaction design for supporting the task at hand optimally. However, current KBS-Engineering methodologies still mostly focus on knowledge base development, regarding UI/interaction design a more incidental, low priority task. Thus, the UI often is developed in a rather ad hoc manner, thereby neglecting the potential of experimental design and creating reusable solutions. The integration of (rapid) evolutionary prototyping activities with KBS Engineering offers the chance for incorporating UI/interaction design more prominently into the process while at the same time leveraging the overall development task; specifically, we propose Extensible Prototyping as a tailored prototyping approach and we suggest its integration with the Agile Process Model for knowledge-based systems in this paper. For practical support, we further introduce the customized prototyping and knowledge systems engineering tool ProKEt, and we report on practical experiences with applying both the approach and the tool. [Copyright &y& Elsevier]

The computational power required to an enterprise system changes dynamically depending on services and the number of users. Massive concurrent computing is excellent in scalability, so that the paper proposes utilizing it for designing and implementing enterprise systems. The proposed accounting system is developed using Agile software development method to study the scalability of massive concurrent systems. When combining two subsystems in Agile, an attaching function is introduced. The system is designed using Model-View-Control software architecture and communicating sequential processes and then implemented with JCSP. Before implementation, the validity of the model is verified using verification tools. It reduces development cost and time. [ABSTRACT FROM AUTHOR]

Abstract: Test-Driven Development (TDD) is an extreme programming development method in which a software system is developed in short iterations. In this paper we present the Test-Driven Conceptual Modeling (TDCM) method, which is an application of TDD for conceptual modeling, and we show how to develop a conceptual schema using it. In TDCM, a system''s conceptual schema is incrementally obtained by performing three kinds of tasks: (1) Write a test the system should pass; (2) Change the schema to pass the test; and (3) Refactor the schema to improve its qualities. We also describe an integration approach of TDCM into a broad set of software development methodologies, including the Unified Process development methodology, the MDD-based approaches, the storytest-driven agile methods and the goal and scenario-oriented requirements engineering methods. We deal with schemas written in UML/OCL, but the TDCM method could be adapted to the development of schemas in other languages. [Copyright &y& Elsevier]

Abstract: All-terrain robot locomotion is an active topic of research. Search and rescue maneuvers and exploratory missions could benefit from robots with the abilities of real animals. However, technological barriers exist to ultimately achieving the actuation system, which is able to meet the exigent requirements of these robots. This paper describes the locomotion control of a leg prototype, designed and developed to make a quadruped walk dynamically while exhibiting compliant interaction with the environment. The actuation system of the leg is based on the hybrid use of series elasticity and magneto-rheological dampers, which provide variable compliance for natural-looking motion and improved interaction with the ground. The locomotion control architecture has been proposed to exploit natural leg dynamics in order to improve energy efficiency. Results show that the controller achieves a significant reduction in energy consumption during the leg swing phase thanks to the exploitation of inherent leg dynamics. Added to this, experiments with the real leg prototype show that the combined use of series elasticity and magneto-rheological damping at the knee provide a 20 % reduction in the energy wasted in braking the knee during its extension in the leg stance phase. [Copyright &y& Elsevier]

Abstract: The paper shows experiences with using Extreme Programming (XP) for specific projects. XP practices Test-Driven Development, pair programming, short interaction, a team code ownership and acceptance tests. Author writes about possibilities of information technologies when improving communicative skills of children with specific disorders, such as autistic spectrum disorders, Down syndrome, mental retardation, etc. The development of an application stemming from the communication system PECS (The Picture Exchange Communication System) and its Czech variant VOKS is the base of this paper to show specificity of the development and verification of software for the given group of handicapped users. The paper shows suitability of using agile methods of software development for a concrete application which is designed for users with specific disorders. It tries to show advantages and disadvantages of new methodologies, particularly Extreme Programming. This agile method prefers fast reaction to a change before the plan completion, which proved to be important in the case of the developed software. There were plenty of changes and new requirements during the development, and their solution was more important for the output quality than following the time schedule of the development. [Copyright &y& Elsevier]

Understanding and fulfilling each individual customer requirements has been recognized as a pressing challenge for software industries. To produce high quality software products and meeting stakeholder's requirement is a major challenge in software requirement. Poor requirements and changes to requirements are one of the causes for project overrun and quality issues in the delivered software. The paper discusses about how the different agile methodologies follow requirement management steps in a project. It tries to give an idea to those organizations who undergo projects with frequent change in the requirements so that they can produce quality products and survive in the market strategy. [ABSTRACT FROM AUTHOR]

Abstract: The notion of knowledge artifact has rapidly gained popularity in the fields of general knowledge management and more recently knowledge-based systems. The main goal on this paper is to propose and discuss a methodology for the design and implementation of knowledge-based systems founded on knowledge artifacts. We advocate that the systems built according to this methodology can be effective to convey the flow of knowledge between different communities of practice. Our methodology has been developed from the ground up, i.e. we have built some concrete systems based on the abstract notion of knowledge artifact and synthesized our methodology based on reflections upon our experiences building these systems. In this paper, we also describe the most relevant systems we have built and how they have guided us to the synthesis of our proposed methodology. [Copyright &y& Elsevier]

• Digital transformation strategies need to include new generation process engineering solutions and agile methodologies need to be adopted throughout the enterprise. • A software platform approach to process simulation, with AVEVA process Simulation, to replace the single-purpose software to be used over the entire project lifecycle. • Combining process simulation with an engineering and design database, with AVEVA unified Engineering, allows collaboration of process engineers with other engineering disciplines, building up a digital twin. • An agile workflow to process engineering with a combined physical and behavioral digital twin enables simultaneous engineering with continuous validation. The process engineering discipline has been largely excluded from Digital Transformation trends. The objective of this paper is to provide an overview of the obstacles to Digital Transformation for the process discipline and explain how these can be overcome. A special emphasis will be given on the role of the process simulation tool (white box modeling) as a catalyst for transformational change. The paper will examine several challenges specific to process engineering: 1) Process simulators are divided into single-purpose point solutions. Separate models may be created for process design, control strategy design, operator training simulation, performance monitoring and online optimization. 2) Process simulators are typically poorly integrated into engineering workflows beyond the process world, and if so, with a single directional information flow. 3) Legacy process simulators are overloaded with niche features and functions only usable by experts. Industry stakeholders see the Digital Twin as the most important building block for Digital Transformation of the process industries. While legacy simulators are well-suited to accurately simulate processes, their decades-old architectures mean they are not ideal to serve the entire plant lifecycle and support the Digital Transformation. We will use the AVEVA Process Simulation as an example of how the identified obstacles can be overcome with a next generation process simulator. [ABSTRACT FROM AUTHOR]

Abstract: With the recent emergence of agile software development technologies, the software community is awaiting sound, empirical investigation of the impacts of agile practices in a live setting. One means of conducting such research is through industrial case studies. There are a number of influencing factors that contribute to the success of such a case study. In this paper, we describe a case study performed at Sabre Airline SolutionsTM evaluating the effects of adopting Extreme Programming (XP) practices with a team that had characteristically plan-driven risk factors. We compare the team’s business-related results (productivity and quality) to two published sources of industry averages. Our case study found that the Sabre team yielded above-average post-release quality and average to above-average productivity. We discuss our experience in conducting this case study, including specifics of how data was collected, the rationale behind our process of data collection, and what obstacles were encountered during the case study. We identify four factors that potentially impact the outcome of industrial case studies: availability of data, tool support, cooperative personnel and project status. Recognizing and planning for these factors is essential to conducting industrial case studies. [Copyright &y& Elsevier]

Umple is an open-source software modeling tool and compiler. It incorporates textual language constructs for UML modeling, including associations and state machines. It includes traits, aspects, and mixins for separation of concerns. It supports embedding methods written in many object-oriented languages, enabling it to generate complete multilingual systems. It provides comprehensive analysis of models and generates many kinds of diagrams, some of which can be edited to update the Umple code. Umple runs on the command line, in a web browser or in integrated development environments. It is designed to help developers reduce code volume, while they develop in an agile, model-driven manner. Umple is also targeted at educational users where students are motivated by its ability to generate real systems from their software models. • Easy-to-use tool to generate code from software models such as state machines and UML associations. • Allows editing and compilation of models and code from the web, the command line, Eclipse and other IDEs. • Blends model representation seamlessly with traditional code in languages like Java and C++. • Incorporates traits, mixins and aspects for separation of concerns, that operate on code and models. [ABSTRACT FROM AUTHOR]

[Display omitted] • Co-production and agile software development methods were used to create a video-game based DSS. • The DSS was developed and applied in workshops for the design of multifunctional open space. • Co-production with residents can result in improved processes and outcomes. • Residents required additional information to orient themselves in the DSS. • Realism and DSS ease of use contribute to dialogue during co-design sessions. Collaborative processes of co-production between end-users and designers can be an effective means to produce shared understanding about a system and has been shown to improve the quality of, and support for, design outcomes. In spatial design and planning, co-production usually involves engaging community members in the design and planning of their local environment (co-design). However, to support co-design of landscapes it has been recommended that decision support systems (DSS) be developed for both the specific decision setting, and in conjunction with meaningful public guidance and input, to transition professional practice to working with rather than for the public. The research presented here responds to these recommendations by developing and evaluating a process for involving end user residents in the co-production and application of the Land.Info DSS in the design of multifunctional landscapes within their communities. The research used participatory workshops incorporating a structured elicitation process, agile software development, and user evaluation to design and test a video game-based DSS in context of two real-world design settings in Detroit, MI, USA. In this paper, we describe and evaluate the process and outcomes, with the results showing improved evaluation over the course of development and overall positive outcomes from this type of collaboration. We also found that residents required additional information to orient themselves in the DSS. In addition, visualization realism and ease of use of the DSS contributing to dialogue during co-design sessions. The paper ends with recommendations for future development and research. [ABSTRACT FROM AUTHOR]

The structural health monitoring of civil structures has been highlighted by the perception that the cost involved in the prevention of structural accidents is lower than the cost of correcting them. In addition, in the case of large structures (e.g. bridges, dams and industrial sheds), it is desired that the damage diagnosis should occur quickly from real-time monitoring without interrupting the use of the structure. The structural diagnosis may be performed based on vibration measurements, considering that the structural damages modify modal parameters of the structure (e.g. frequencies and mode shapes). With these dynamic responses, the application of appropriate computational tools to recognize and classify structural damage is intended, and artificial neural networks (ANN) have gained a lot of attention in achieving these goals. In this work, the methodology of diagnosing structures by real-time monitoring is originally developed and based on initial definition of the optimal topology, avoiding both the use of multiple hidden layers and the combination of several neural networks, and by applying of non-adaptive and adaptive first-order algorithms for agile network training, in order to be mathematically suitable for continuous and real-time monitoring, which allows updating both the dataset and neural parameters without greater computational effort. As some of these algorithms were not addressed in the diagnosis of civil structures with the aforementioned hypotheses, until this research, the performance of each algorithm was verified in case studies that simulate classic structural systems adopted in most civil buildings. Finally, the results endorse the feasibility of improving the structural diagnosis based on the training of a simple neural network, with one hidden layer, associated with non-adaptive or adaptive first-order optimizers that guarantee the agile assessment of structural integrity in real time. • Large structures may be monitored without interrupting their operation. • Damage diagnosis based on vibration measurements is an efficient practice. • Individual neural network with single hidden layer enable the damage diagnosis. • First-order learning methods are appropriate for real-time structural health monitoring. • The proposed approach allows continuous assessment of structural integrity. [ABSTRACT FROM AUTHOR]

Software project development is a dynamic process by nature, since it is common that events such as changes in the software requirements and in the development team occur during the execution of the original project plan. When such disruptive events occur, the project plan needs to be adjusted, and the activity of adjusting the original plan in order to comply with the date and costs constraints of the project is called project rescheduling. This situation is not exclusive to whole-project plan-driven approaches to software development, as it is also present when software projects are developed following agile methodologies such as Scrum. In Scrum, shorter period project plans, called release plans, are used and when disruptive events occur release plan rescheduling needs to be performed. Plan rescheduling can be modeled as a multi-objective optimization problem, however, there have been no studies that investigate the release plan rescheduling problem (RPRP) and its solution by means of multi-objective optimizers. The study presented in this paper intends to address the lack of studies of the release plan rescheduling problem and covers three fundamental topics. First, a model for the release plan rescheduling problem is proposed, which considers metrics that are particularly important to define a release plan, including story points and velocity. Second, three evolutionary multi-objective algorithms are utilized for solving a number of problem instances and an appropriate in-depth analysis of their solutions is provided. Finally, a careful examination of the solutions with respect to their practicability is performed. • Release plan rescheduling, in the context of agile software development, is modeled. • Five criteria are defined for the multi-objective optimization problem. • Three evolutionary multi-objective algorithms are applied to test instances. • Analysis of results include conflict between the objectives and algorithm performance. • Results are examined regarding the practicability of the rescheduled release plans. [ABSTRACT FROM AUTHOR]

Global Software Development (GSD) has gained great attention during the past decade or so, and it is also being adopted by most of the software development organizations. The GSD approach is practiced by the software development organizations in China and a wide range of firms have established its operations in various Chinese cities. However, GSD practices becomes more challenging for the projects based on the agile concepts. The aim of this study is to develop a taxonomy of the factors that could positively impact the scaling process of agile methods in the Chinese GSD industry. The factors are identified by exploring the available literature and conducting industrial study with the Chinese agile and GSD practitioners. The finally reported factors are categorized, prioritized and developed their taxonomy using the multi-criterion decision making (MCDM) Fuzzy AHP approach. The given taxonomy is significant and progressive for GSD industry to assess and improve the scaling process of agile methods. • Explore the factors that could positively impact the agile scaling process in Chinese global software development (GSD) industry. • Develop the conceptual mapping of the identified factors. • Conceptual mapping is empirically validated. • The fuzzy AHP approach used to priorities the identified factors and the respective categories. • Develop the recommendation taxonomy of the factors based on the fuzzy AHP findings. [ABSTRACT FROM AUTHOR]

Maptables are increasingly used to support collaborative spatial planning processes. Despite the proven benefits and claimed potential of using a maptable in such processes, software applications specifically designed for this device are still scarce. Moreover, often-used applications do not fully exploit the touch functionality of a maptable, or have low usability. To address this gap, we developed and evaluated the Open Geospatial Interactive TOol (OGITO), an open-source software application designed to support collaborative spatial planning processes with a maptable. To develop such tool, we combined human-centred design and Agile software development principles in a co-design effort with intended users and stakeholders. Through iterative development cycles and feedback from users, OGITO was evolved until it satisfied user expectations. In a case study on community mapping in Sumatra, Indonesia, a sample of users evaluated OGITO's usability. Case study participants reported high satisfaction with this tool for the tasks and context given. Our research shows the added value of iterative development and user feedback for improving and further development of the tool's usability and functionality. • OGITO: a new open-source application for maptables to support collaborative planning. • Human-centred design and Agile methods effectively shaped the co-design of OGITO. • OGITO's usability was positively rated by collaborative mapping workshop participants. • Iterative development and user feedback improved usability of the planning tool. [ABSTRACT FROM AUTHOR]

• Evidence-based decision making for Quality Requirements management. • Product quality assessment visualization. • Prediction and what-if analysis supporting quality management processes. Software and data analytics solutions support improving development processes and the quality of the software produced in Agile Software Development (ASD). However, decision makers in software teams (e.g., product owner, project manager) are demanding powerful tools providing evidence data that support their strategic decision-making processes. In this paper, we present and provide access to QaSD, a Quality-aware Strategic Dashboard supporting decision makers in ASD. The dashboard allows decision makers to define high-level strategic indicators (e.g., customer satisfaction, process performance) related to software quality and to measure, explore, simulate and forecast the values of those indicators in order to explain and justify their decisions. Moreover, we also provide the results of a conducted evaluation of the dashboard quality in a real environment that evaluated the QaSD as usable, easy to use, with good navigation, and reliable. [ABSTRACT FROM AUTHOR]

We study a self-organizing wireless network in which the number of active connections to the typical user equipment (UE) is dynamic, in order to sustain temporally varying network traffic. Using tools of stochastic geometry, we show that even though the signal coverage improves with a higher degree of connectivity, the per-user throughput may degrade. Consequently, the operator needs to reconfigure the UE association throughout the network as the UE density and the network requirements change. To optimize this trade-off in an online manner, we propose a reinforcement-learning (RL) based framework in which a given number of base station (BS) connections to the UE is modeled as an arm of the multi-armed bandit (MAB) problem. We propose a refresh-based Thompson sampling (TS) approach for the MAB problem and show that it is able to track the temporally optimal static association rule, in terms of signal coverage and throughput. Our study highlights that in the future fifth-generation (5G) and beyond wireless networks, elastic multi-connectivity must be employed in order to sustain agile quality-of-service (QoS) requirements and dynamic UE traffic. [ABSTRACT FROM AUTHOR]

• The existing algorithms are not agile enough to adapt to different data structures. • ML approaches are compared to determine suitable ones for the search process. • Neural foresting method is proposed to increases the accuracy of the search results. The increasing amount of pressure to digitalize what we are used to consider a conventional data has created a need to analyze, search and process unique data structures in a timely manner. The progressive world has created a justified need not only for a fast query searches but also the most related and meaningful searches with a minimal guidance. This article explores the potential benefits of using unorthodox solutions, including Artificial Intelligence algorithms in processing big data that are unconventional data structures. One of such big data sources was created as part of digitalization of historic heritage materials, documents and artifacts. The article calls out the benefits and disadvantages of some Artificial Intelligence algorithms and explores ways to use a few of those algorithms for the purposes of the digital heritage. It also offers the solution to maximize the potential of the search engine that could be built for digital heritage or any other unstructured data. [ABSTRACT FROM AUTHOR]

The AGILE project has developed the next generation of aircraft Multidisciplinary Design and Optimization processes providing significant reductions in aircraft development costs and time to market - ultimately leading to more cost-effective and greener aircraft solutions. A novel product development methodology is formulated, enabling collaborative, large scale design and optimization processes. The main elements enabling the developed "AGILE Paradigm" are the Knowledge Architecture and the Collaborative Architecture. The Knowledge Architecture formalizes setting up the product development process. It guides the engineers in formulating the design problem and choosing the appropriate solution strategy. This paper focuses on the Collaborative Architecture, which at its turn formalizes the way in which the involved agents interact within the product development process and enables cross-organizational and cross-the-nation integration of design competences. The principles of the architecture are of a non-intrusive nature and allow legacy processes to be connected in fully automated cross-organization collaborative design workflows. Within the project, it is used to seamlessly integrate the capabilities of nineteen project partners located in nine different countries. A realistic aircraft design use case – addressing an automated systems-of-systems analysis involving the design competences of multiple project partners – demonstrates a working implementation of the Collaborative Architecture. The effective interconnection of simulation capabilities between organizations allows the agents to spend more time on creative, knowledge-intensive design tasks - opening new possibilities for collaboratively resolving the future challenges faced by the aerospace and other industries. [ABSTRACT FROM AUTHOR]

Background and Purpose: Health information systems (HIS) are expected to be effective and efficient in improving healthcare services, but empirical observation of HIS reveals that most perform poorly in terms of these metrics. Theoretical factors of HIS performance are widely studied, and solutions to mitigate poor performance have been proposed. In this paper we implement effective methods to eliminate some common drawbacks of HIS design and demonstrate the synergy between the methods. JointCalc, the first comprehensive patient-facing web-based decision support tool for joint replacement, is used as a case study for this purpose.Methods and Results: User-centred design and thorough end-user involvement are employed throughout the design and development of JointCalc. This is supported by modern software production paradigms, including continuous integration/continuous development, agile and service-oriented architecture. The adopted methods result in a user-approved application delivered well within the scope of project.Conclusion: This work supports the claims of high potential efficiency of HIS. The methods identified are shown to be applicable in the production of an effective HIS whilst aiding development efficiency. [ABSTRACT FROM AUTHOR]

The potential applications for drones, especially those in manned areas or into non-segregated airspace, are currently not possible without the development and validation of certain key enabling technologies: "detect and avoid", "air traffic management", "command and control (C2) link", and "security and cyber resilience". This issue has a high impact on European innovation as identified by SESAR JU and demands R&D investments and incentives for the convergence of shared technologies and markets. In this paper, we discuss the vision of COMP4DRONES project to complement SESAR JU efforts with a particular focus on safe software and hardware drone architectures. COMP4DRONES will bear a holistically designed ecosystem ranging from application to electronic components. The ecosystem aims at supporting (1) efficient customization and incremental assurance of drone-embedded platforms, (2) safe autonomous decision making concerning individual or cooperative missions, (3) trustworthy drone-to-drone and drone-to- ground communications even in presence of malicious attackers and under the intrinsic platform constraints, and (4) agile and cost-effective design and assurance of drone modules and systems. Lead applications driving ecosystem development and benchmarking on the fields of transport, inspection, logistic, precision agriculture, and parcel delivery will be produced. [ABSTRACT FROM AUTHOR]

The unique maneuverability, ease of deployment, simplicity in logistics, and relatively low costs of multicopters render them effective vehicles for low atmospheric research. While many efforts have contributed to the fundamental success of atmospheric applications of multicopters in the past, several challenges remain, including limited measurable variables, possible response-delay in real-time observations, insufficient measurement accuracy, endurance of harsh conditions and tolerance towards interferences. To address these challenges and further fortify the applicability in diversified research disciplines, this study developed an optimized multicopter UAV sounding technique (MUST). The MUST serves as an integrated platform by combining self-developed algorithms, optimized working environments for sensors/monitors, and retrofitted sampling devices to probe a comprehensive set of atmospheric variables. These variables of interest include meteorological parameters (temperature, relative humidity, pressure, wind direction and speed), the chemical composition (speciated VOCs, CO, CO 2 , CH 4 , CO 2 isotopologues, O 3 , PM2.5, and black carbon), and the radiation flux, as well as visible and thermal images. The aim of this study is to achieve the following objectives: 1. to easily probe a comprehensive set of near-surface atmospheric variables; 2. to improve data quality by correcting for sensors' delay in real-time observations and minimizing environmental interferences; and 3. to enhance the versatility and applicability of aerial measurements by incorporating necessary hardware and software. Field launching cases from the surface to a maximum height of 1000 m were conducted to validate the robustness of the integrated MUST platform with sufficient speed, accuracy and resolution for the target variables. Image 1 • Versatile observation techniques are integrated with an agile multicopter. • A comprehensive set of near-surface atmospheric variables can be probed with ease. • Data quality is improved by optimizing sensing/sampling and reducing interferences. • Potential for environmental and climate studies is demonstrated. [ABSTRACT FROM AUTHOR]

• The paper presents a review of 45 studies related to software risk in the context of the software life cycle. • A large number of studies reviewed involve other knowledge areas to support decision-making in the risk management activities. • A few proposals for risk management use internationally recognised standards or de facto models to its definition. • It is especially important to define a framework and model for risk management in the software life cycle using an agile approach. • It is important that agile approaches include risk management practices which are in line with the already accepted ones in traditional approaches. Risk management (RM) plays a key role in project management, as it allows identification and prompt management of threats that may arise during project execution. Furthermore, project management within the software industry is evolving rapidly nowadays, a fact that implies new challenges, because the emergence and use of fresh approaches has brought a greater degree of complexity to the RM process. The objective of this paper is to carry out a systematic literature review (SLR) in the field of software risk, in an attempt to characterize and present the state of the art of this field, identifying gaps and opportunities for further research. From the analysis of the results of this SLR it could be observed that interest on the part of the scientific community has turned away from the definition of research work that addressed an integrated risk management process, to pay attention to work that concentrates on specific activities of this process. It was also possible to see that there is a clear lack of scientific rigour as regards the process of validation in the different studies, and a deficiency in the use of standards or of de facto models to define these. [ABSTRACT FROM AUTHOR]

• An exploratory case study of agile software development within a safety critical systems engineering environment is undertaken. • Extensive interviews are undertaken with practitioners from the organization using a combination of exploratory, semi-structured and workshop formats. • Thirteen challenges are identified in the material and related to the existing literature. • Insights as to how the company are adapting agile practices to fit a safety critical context are reported. This study explores the introduction of agile software development within an avionics company engaged in safety-critical system engineering. There is increasing pressure throughout the software industry for development efforts to adopt agile software development in order to respond more rapidly to changing requirements and make more frequent deliveries of systems to customers for review and integration. This pressure is also being experienced in safety-critical industries, where release cycles on typically large and complex systems may run to several years on projects spanning decades. However, safety-critical system developments are normally highly regulated, which may constrain the adoption of agile software development or require adaptation of selected methods or practices. To investigate this potential conflict, we conducted a series of interviews with practitioners in the company, exploring their experiences of adopting agile software development and the challenges encountered. The study also explores the opportunities for altering the existing software process in the company to better fit agile software development to the constraints of software development for safety-critical systems. We conclude by identifying immediate future research directions to better align the tempo of software development for safety-critical systems and agile software development. [ABSTRACT FROM AUTHOR]

The microservices architectural approach has important benefits regarding the agile applications' development and the delivery of complex solutions. However, to convey the information and to share the data amongst services in a verifiable and stateless way, there is a need to enable appropriate access control methods and authorisations. In this paper, we study the use of policy-driven authorisations with independent fine-grained microservices in the case of a real-world machine-to-machine (M2M) scenario using a hybrid cloud-based infrastructure and Internet of Things (IoT) services. We also model the authentication flows which facilitate the message exchanges between the involved entities, and we propose a containerised authorisation and policy-driven architecture (CAPODAZ) using the microservices paradigm. The proposed architecture implements a policy-based management framework and integrates in an on-going work regarding a Cloud-IoT intelligent transportation service. For the in-depth quantitative evaluation, we treat multiple distributions of users' populations and assess the proposed architecture against other similar microservices. The numerical results based on the experimental data show that there exists significant performance preponderance in terms of latency, throughput and successful requests. [ABSTRACT FROM AUTHOR]

• Agile mature companies can be also conformant with ISO process reference models. • Conformance with five ISO/IEC/IEEE 12207 Technical Management processes is analysed. • Conformance with two ISO/IEC TR 29110-5-1-2 Project Management process activities is analysed. • Agile approaches propose different metrics for monitoring team performance. • Agile approaches are not faced with traditional process models. Agile approaches are well perceived in software development companies. These approaches are not faced with traditional process models. This research analyses how by defining and monitoring a set of Agile metrics, Agile mature companies can be also conformant with the best practices proposed by the targeted ISO process reference models. Conformance has been identified with five Technical Management processes of the ISO/IEC/IEEE 12207 standard and with two activities of the Project Management process of the ISO/IEC TR 29110-5-1-2 standard. The findings may be of the interest of those Agile settings that need to work according to the process model established in the company. [ABSTRACT FROM AUTHOR]

• Efficient and safe storage of breeding data through different types of blockchain and multi databases. • Easy and quick acquisition of breeding data from the dimensions of crop planting location and breeding process. • Easy extension of the architecture to improve system performance as data volume grows. • Low cost of system hardware. This paper presents an architecture to store high-throughput crop breeding data efficiently and safely, by using improved blockchain technology in a breeding information management system, Golden Seed Breeding Cloud Platform (GSBCP). The storage architecture was devised to ensure (a) efficient and safe storage of breeding data, (b) easy and quick acquisition of breeding data from the dimensions of crop planting location and breeding process, (c) easy extension of the architecture to improve system performance as data volume grows, and (d) low cost of system hardware. This storage architecture uses a light blockchain to save key breeding data. Different types of blockchains are used to store different types of breeding data. Proxy encryption technology is used to guarantee data security. To strike a balance between data security and system performance, important data are assigned a higher level of security. This storage architecture can significantly improve the efficiency of GSBCP when the amount of data is large, especially when breeders query breeding data. In addition, increasing the number of blockchain nodes can greatly improve the concurrency of the system. [ABSTRACT FROM AUTHOR]

Increasingly, software development organizations are scaling agile practices in the global software development (GSD) environment in order to meet the requirements of the quickly changing and regularly developing business environment. The main objectives of this study are to investigate the key barriers and develop a prioritization-based taxonomy of the barriers for scaling agile development in the GSD environment. Total twenty-two barriers were extracted from the available literature and categorized into five categories, i.e. "human resources management", 'coordination", "technology", "project management", and "software methodology". In the next phase, the identified barriers and their categories were further validated using the questionnaire survey. In the final phase, fuzzy-AHP method, a multi-criterion decision making (MCDM) technique, was applied to prioritize and taxonomy of identified barriers and their related categories was designed. The contribution of this study is not limited to investigate the barriers, but it also provides the roadmap to tackle the issues related to the scaling agile methods in the GSD environment. • Identifying the barriers which negatively impact on the scaling programs of agile development in GSD environment. • Categorizing the identified barriers according to their types. • Validation of the identified barriers using the questionnaire survey. • Prioritizing the barriers using fuzzy AHP method by collecting responses of pair-wise comparison of factors. [ABSTRACT FROM AUTHOR]

Social media can be used to manage information flow in teams, thereby empowering knowledge management, which can be linked to innovation. This study develops a model to test the influence of social media on transactive memory system, absorptive capacities (potential and realized capacity), and team innovation performance. Partial least squares analysis on 61 software development teams indicates the positive impact of social media on transactive memory system and potential and realized absorptive capacity, which in turn can influence team innovation performance. This article presents theoretical contributions and describes implications for social media adoption in knowledge-intensive teams. • Framework to investigate role of social media for team innovation performance is defined. • Social media facilities teams to explore and exploit external knowledge to innovate. • A well-developed transactive memory system plays role to support social media to enhance absorptive capacities. • Both absorptive capacities of a team are effective in enhancing the team innovation performance. [ABSTRACT FROM AUTHOR]