High-level Functional Requirements Research Articles

Addressing European Ocean Energy Challenge: The DTOceanPlus Structured Innovation Tool for Concept Creation and Selection

The whole energy system requires renewables that scale and produce reliable, valuable energy at an acceptable cost. The key to increasing the deployment of ocean energy is bringing down development and operating costs. This paper proposes a structured approach to innovation in ocean energy systems that would spur innovation and expand the market for ocean energy. This approach can be used by a wide range of stakeholders—including technology and project developers and investors—when considering creating or improving designs. The Structured Innovation design tool within the DTOceanPlus suite is one of a kind beyond the current state-of-the-art. It enables the adaptation and integration of systematic problem-solving tools based on quality function deployment (QFD), the theory of inventive thinking (TRIZ), and the failure modes and effects analysis (FMEA) methodologies for the ocean energy sector. In obtaining and assessing innovative concepts, the integration of TRIZ into QFD enables the designers to define the innovation problem, identifies trade-offs in the system, and, with TRIZ as a systematic inventive problem-solving methodology, generates potential design concepts for the contradicting requirements. Additionally, the FMEA is used to assess the technical risks associated with the proposed design concepts. The methodology is demonstrated using high-level functional requirements for a small array of ten tidal turbines to improve the devices layout and power cabling architecture. The Structured Innovation design tool output comprises critical functional requirements with the highest overall impact and the least organisational effort to implement, along with appropriate alternative solutions to conflicting requirements.

Artificial Intelligence Tools for Better Use of Axiomatic Design

Axiomatic Design (AD) provides a powerful thinking framework for solving complex engineering problems through the concept of design domains and diligent mapping and decomposition between functional and physical domains. Despite this utility, AD is yet to be implemented for widespread use by design practitioners solving real world problems in industry and exists primarily in the realm of academia. This is due, in part, to a high level of design expertise and familiarity with its methodology required to apply the AD approach effectively. It is difficult to correctly identify, extract, and abstract top-level functional requirements (FRs) based on early-stage design research. Furthermore, guiding early-stage design by striving to maintain functional independence, the first Axiom, is difficult at a systems level without explicit methods of quantifying the relationship between high-level FRs and design parameters (DPs). To address these challenges, Artificial Intelligence (AI) methods, specifically in deep learning (DL) assisted Natural Language Processing (NLP), have been applied to represent design knowledge for machines to understand, and, following AD principles, support the practice of human designers. NLP-based question-answering is demonstrated to automate early-stage identification of FRs and to assist design decomposition by recursively mapping and traversing down along the FR-DP hierarchical structure. Functional coupling analysis could then be conducted with vectorized FRs and DPs from NLP-based language embeddings. This paper presents a framework for how AI can be applied to design based on the principles of AD, which will enable a virtual design assistant system based on both human and machine intelligence.

Factors Influencing Motivation and Engagement in Mobile Health Among Patients With Sickle Cell Disease in Low-Prevalence, High-Income Countries: Qualitative Exploration of Patient Requirements.

BackgroundSickle cell disease (SCD) is a hematological genetic disease affecting over 25 million people worldwide. The main clinical manifestations of SCD, hemolytic anemia and vaso-occlusion, lead to chronic pain and organ damages. With recent advances in childhood care, high-income countries have seen SCD drift from a disease of early childhood mortality to a neglected chronic disease of adulthood. In particular, coordinated, preventive, and comprehensive care for adults with SCD is largely underresourced. Consequently, patients are left to self-manage. Mobile health (mHealth) apps for chronic disease self-management are now flooding app stores. However, evidence remains unclear about their effectiveness, and the literature indicates low user engagement and poor adoption rates. Finally, few apps have been developed for people with SCD and none encompasses their numerous and complex self-care management needs.ObjectiveThis study aimed to identify factors that may influence the long-term engagement and user adoption of mHealth among the particularly isolated community of adult patients with SCD living in low-prevalence, high-income countries.MethodsSemistructured interviews were conducted. Interviews were audiotaped, transcribed verbatim, and analyzed using thematic analysis. Analysis was informed by the Braun and Clarke framework and mapped to the COM-B model (capability, opportunity, motivation, and behavior). Results were classified into high-level functional requirements (FRs) and nonfunctional requirements (NFRs) to guide the development of future mHealth interventions.ResultsOverall, 6 males and 4 females were interviewed (aged between 21 and 55 years). Thirty FRs and 31 NFRs were extracted from the analysis. Most participants (8/10) were concerned about increasing their physical capabilities being able to stop pain symptoms quickly. Regarding the psychological capability aspects, all interviewees desired to receive trustworthy feedback on their self-care management practices. About their physical opportunities, most (7/10) expressed a strong desire to receive alerts when they would reach their own physiological limitations (ie, during physical activity). Concerning social opportunity, most (9/10) reported wanting to learn about the self-care practices of other patients. Relating to motivational aspects, many interviewees (6/10) stressed their need to learn how to avoid the symptoms and live as normal a life as possible. Finally, NFRs included inconspicuousness and customizability of user experience, automatic data collection, data shareability, and data privacy.ConclusionsOur findings suggest that motivation and engagement with mHealth technologies among the studied population could be increased by providing features that clearly benefit them. Self-management support and self-care decision aid are patients’ major demands. As the complexity of SCD self-management requires a high cognitive load, pervasive health technologies such as wearable sensors, implantable devices, or inconspicuous conversational user interfaces should be explored to ease it. Some of the required technologies already exist but must be integrated, bundled, adapted, or improved to meet the specific needs of people with SCD.

Collaboration through analysis: A journey in digital content management workflow analysis

Analysing workflows is a vital component in ensuring reliable, long-term preservation, access and support to collections. It further supports goals to involve more diverse voices in the development of workflows and to streamline processes in order to better serve the community. In June 2017, the State Library of North Carolina’s Government & Heritage Library began an extensive evaluation of its digital content management. In the first stage, an interdepartmental working group determined high-level functional requirements for digital content — from acquisition to preservation to access — and conducted an evaluation of the primary tools used. The second stage included interviews with cataloguers, the State Agency Liaison and digital staff, resulting in a complete workflow chart of current processes. The third stage consisted of a workflow analysis and the development of solutions for prominent breakdowns and issues. This article provides a project overview, lessons learned and tactics for analysing library workflows and tools. Through the process, an openness to exploration and evaluation fostered stronger collaborations across disciplines and among different professionals. By taking the time to step back, to look at workflows, to evaluate who is involved and what is used, the library better positioned itself for future projects, collaborations and problem-solving.

Robot Removes Operators From Extreme Environments

This article, written by Special Publications Editor Adam Wilson, contains highlights of paper SPE 181409, “A Robot That Removes Operators From Extreme Environments,” by Ian Peerless, SPE, IPKA Consultancy, and Adam Serblowski and Berry Mulder, Shell Global Solutions International, prepared for the 2016 SPE Annual Technical Conference and Exhibition, Dubai, 26–28 September. The paper has not been peer reviewed. Robots have the potential to move human operators away from uncomfortable, potentially risky environments and into comfortable, safe control rooms. Remotely operated vehicles have already achieved this for subsea fields; however, before this approach can be extended to surface facilities, the robots must be reliable and safe in potentially explosive environments. The Sensabot robot has addressed these challenges and could be the foundation on which future generations of robots are built. Introduction In 2010, a technology plan was prepared that focused on the specific challenges facing projects in the Kashagan Field in Kazakhstan: Climatic temperatures typically ranging from −25°C to +35°C High hydrogen sulfide concentrations in produced gas Raw-gas-injection pressures as high as 690 bara Ice-bound unmanned artificial islands in the winter These challenges require operators to wear breathing apparatuses and cumbersome insulated clothing in winter that hampers their movement. In summer, the breathing apparatus creates the risk of heat exhaustion. One contribution to the technology plan was the concept of remotely operated robots. These could remain permanently on location and could be driven by operators located in a safe environment. The Robot Concept The first stage of the Sensabot project was to identify the robot’s high-level functional requirements. These fall into three categories: user acceptance, safety, and independence. User Acceptance. The project team recognized that, although the upstream oil and gas industry has been using remotely operated vehicles for many years in subsea environments, there has been little significant use of robots for surface facilities. The team felt that onshore operators would view the robot with suspicion, so it needed to work reliably to build confidence. By simplifying its functional requirements, the project team could focus on fewer features and decrease the risk of failures. In this context, it was decided to focus on simple sensing tasks rather than the manipulation of items such as valves and switches. Therefore, Sensabot was designed to perform daily operator inspections of the plant. It was equipped with a range of sensors that replicated those of a human operator (Fig. 1): cameras (sight), gas detectors (smell), a vibration detector (touch), and a microphone (hearing). Later in the development, a thermal imaging camera was added. Another important design decision was to minimize the amount of automation. Sensabot was not designed to eliminate the need for human operators, just to relocate them to a safe and comfortable environment.

Unmanned aircraft systems in the national airspace system

As the technological and operational capabilities of unmanned aircraft systems (UAS) have grown, so too have international efforts to integrate UAS into civil airspace. However, one of the major concerns that must be addressed in realizing this integration is that of safety. For example, UAS lack an on-board pilot to comply with the legal requirement that pilots see and avoid other aircraft. This requirement has motivated the development of a detect and avoid (DAA) capability for UAS that provides situational awareness and maneuver guidance to UAS operators to aid them in avoiding and remaining well clear of other aircraft in the airspace. The NASA Langley Research Center Formal Methods group has played a fundamental role in the development of this capability. This article gives a selected survey of the formal methods work conducted in support of the development of a DAA concept for UAS. This work includes specification of low-level and high-level functional requirements, formal verification of algorithms, and rigorous validation of software implementations.

Risk monitor riskangel for risk-informed applications in nuclear power plants

This paper studied the requirements of risk monitor software and its applications as a plant specific risk monitor, which supports risk-informed configuration risk management for the two CANDU 6units at the Third Qinshan nuclear power plant (TQNPP) in China. It also describes the regulatory prospective on risk-informed Probabilistic Safety Assessment (PSA) applications and the use of risk monitor at operating nuclear power plants, high level technical and functional requirements for the development of CANDU specific risk monitor software, and future development trends.

Automated Planning as an Early Verification Tool for Distributed Control

We present a new modelling formalism which is suitable for capturing high level functional specifications and requirements of reactive control systems. This formalism is a simple extension of the classical planning formalism. We show that if specifications are thus formalized, then it is possible to use existing automated planners and model checkers to find logical faults in them. Our extension to classical planning consists of introducing a separate class of actions, referred as control actions, which have higher priority than regular actions.We present several illustrative examples of high-level modelling and verification of modern automotive features with our proposed formalism. We present several compilation schemes to solve the proposed problem using well-known planners and the model checkers. We present a comparative study of the performance of a number of well-known tools on our problem.We also present some novel optimization techniques which help the solution scale much better with most of the studied tools.

Personalized information retrieval and access: concepts, methods, and practices

Global information retrieval and anywhere, anytime information access has stimulated a need to design and model the personalized information search in a flexible and agile way that can use the specific personalization techniques, algorithms, and available technology infrastructure to satisfy high-level functional requirements for personalization. Personalized Information Retrieval and Access: Concepts, Methods and Practices surveys the main concepts, methods, and practices of personalized information retrieval and access in todays data intensive, dynamic, and distributed environment, and provides students, researchers, and practitioners with authoritative coverage of recent technological advances that are shaping the future of globally distributed information retrieval and anywhere, anytime information access

Decision support at the wheel—rail interface: The development of system functional requirements

Railway decision support systems (DSSs) tend to address track and vehicle assets separately. This paper describes the development of a comprehensive set of high-level functional requirements for an integrated support system that optimizes the system as a whole. Interviews and workshops were held with key industry stakeholders covering regulation, infrastructure, condition monitoring, mass transit, and light rail to elicit their issues, needs, and desires. The needs were checked for relevance, duplication, and overlapping; and rephrased, decomposed, grouped, classified, and prioritized in order to achieve a consistent, complete, and unambiguous set of system stakeholder requirements. They were then used to derive a set of high-level system functional requirements for the DSS. The paper also demonstrates the importance of complete traceability between the two sets of requirements.

MULTI-PERSPECTIVE SPECIFICATION, DESIGN AND IMPLEMENTATION OF SOFTWARE COMPONENTS USING ASPECTS

Current approaches to component-based systems engineering tend to focus on low-level software component interface design and implementation. This often leads to the development of components whose services are hard to understand and combine, make too many assumptions about other components they can be composed with and component documentation that is too low-level. Aspect-oriented component engineering is a new methodology that uses a concept of different system capabilities ("aspects") to categorise and reason about inter-component provided and required services. It supports the identification, description and reasoning about high-level component functional and non-functional requirements grouped by different systemic aspects, and the refinement of these requirements into design-level software component service implementation aspects. Aspect information is used to help implement better component interfaces and to encode knowledge of a component's capabilities for other components, developers and end users to access. We describe and illustrate the use of aspect-oriented component engineering techniques and notations to specify, design and implement software components, report on some basic tool support, and our experiences using the approach to build some complex, component-based software systems.

Decision support for managing organizational design dynamics

Changes in the business environment and the advent of new Information Technologies (IT) create new challenges and opportunities for redesigning the organization. Organizational design encompasses a large number of factors including IT, incentives, business processes, and the scope of decision authority. Further, a design configuration based on a given business and technological environment may have to be modified with changes in the environment. We suggest using an approach called business value complementarity [8] as a systematic basis to ensure that design decisions contribute maximally to bottom-line performance measures such as profitability. It is based on the notion of creating a business value model showing relationships between key performance measures and design decision variables involving IT, incentives, etc. Complementarity between the variables in the business value model provides a basis for choosing the levels of design variables. We derive some results which specify conditions under which the overall performance measure(s) are complementary in the design variables. We suggest that a Decision Support System (DSS) would be appropriate for helping senior management in the complex process of developing and maintaining a business value model and in choosing a suitable organizational design. We also enumerate high level functional requirements of such a DSS.