Periodicals
Results of PREVENT III: A multicenter, randomized trial of edifoligide for the prevention of vein graft failure in lower extremity bypass surgery
[no abstract]
Architecture & Planning• 2006• Elsevier BV
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in Architecture & Planning
Periodicals
Evaluation of Sentinel-2 Red-Edge Bands for Empirical Estimation of Green LAI and Chlorophyll Content
ESA's upcoming satellite Sentinel-2 will provide Earth images of high spatial, spectral and temporal resolution and aims to ensure continuity for Landsat and SPOT observations. In comparison to the latter sensors, Sentinel-2 incorporates three new spectral bands in the red-edge region, which are centered at 705, 740 and 783 nm. This study addresses the importance of these new bands for the retrieval and monitoring of two important biophysical parameters: green leaf area index (LAI) and chlorophyll content (Ch). With data from several ESA field campaigns over agricultural sites (SPARC, AgriSAR, CEFLES2) we have evaluated the efficacy of two empirical methods that specifically make use of the new Sentinel-2 bands. First, it was shown that LAI can be derived from a generic normalized difference index (NDI) using hyperspectral data, with 674 nm with 712 nm as best performing bands. These bands are positioned closely to the Sentinel-2 B4 (665 nm) and the new red-edge B5 (705 nm) band. The method has been applied to simulated Sentinel-2 data. The resulting green LAI map was validated against field data of various crop types, thereby spanning a LAI between 0 and 6, and yielded a RMSE of 0.6. Second, the recently developed "Normalized Area Over reflectance Curve" (NAOC), an index that derives Ch from hyperspectral data, was studied on its compatibility with simulated Sentinel-2 data. This index integrates the reflectance curve between 643 and 795 nm, thereby including the new Sentinel-2 bands in the red-edge region. We found that these new bands significantly improve the accuracy of Ch estimation. Both methods emphasize the importance of red-edge bands for operational estimation of biophysical parameters from Sentinel-2.
Architecture & Planning• 2011• Multidisciplinary Digital Publishing Institute
Periodicals
Industry 4.0 and Sustainability Implications: A Scenario-Based Analysis of the Impacts and Challenges
The new evolution of the production and industrial process called Industry 4.0, and its related technologies such as the Internet of Things, big data analytics, and cyber–physical systems, among others, still have an unknown potential impact on sustainability and the environment. In this paper, we conduct a literature-based analysis to discuss the sustainability impact and challenges of Industry 4.0 from four different scenarios: deployment, operation and technologies, integration and compliance with the sustainable development goals, and long-run scenarios. From these scenarios, our analysis resulted in positive or negative impacts related to the basic production inputs and outputs flows: raw material, energy and information consumption and product and waste disposal. As the main results, we identified both positive and negative expected impacts, with some predominance of positives that can be considered positive secondary effects derived from Industry 4.0 activities. However, only through integrating Industry 4.0 with the sustainable development goals in an eco-innovation platform, can it really ensure environmental performance. It is expected that this work can contribute to helping stakeholders, practitioners and governments to advance solutions to deal with the outcomes emerging through the massive adoption of those technologies, as well as supporting the expected positive impacts through policies and financial initiatives.
Architecture & Planning• 2018• Multidisciplinary Digital Publishing Institute
Periodicals
Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models
Deep generative models are a class of techniques that train deep neural networks to model the distribution of training samples. Research has fragmented into various interconnected approaches, each of which make trade-offs including run-time, diversity, and architectural restrictions. In particular, this compendium covers energy-based models, variational autoencoders, generative adversarial networks, autoregressive models, normalizing flows, in addition to numerous hybrid approaches. These techniques are compared and contrasted, explaining the premises behind each and how they are interrelated, while reviewing current state-of-the-art advances and implementations.
Architecture & Planning• 2021• Durham University
Periodicals
Advancing Neuromorphic Computing With Loihi: A Survey of Results and Outlook
Deep artificial neural networks apply principles of the brain's information processing that led to breakthroughs in machine learning spanning many problem domains. Neuromorphic computing aims to take this a step further to chips more directly inspired by the form and function of biological neural circuits, so they can process new knowledge, adapt, behave, and learn in real time at low power levels. Despite several decades of research, until recently, very few published results have shown that today's neuromorphic chips can demonstrate quantitative computational value. This is now changing with the advent of Intel's Loihi, a neuromorphic research processor designed to support a broad range of spiking neural networks with sufficient scale, performance, and features to deliver competitive results compared to state-of-the-art contemporary computing architectures. This survey reviews results that are obtained to date with Loihi across the major algorithmic domains under study, including deep learning approaches and novel approaches that aim to more directly harness the key features of spike-based neuromorphic hardware. While conventional feedforward deep neural networks show modest if any benefit on Loihi, more brain-inspired networks using recurrence, precise spike-timing relationships, synaptic plasticity, stochasticity, and sparsity perform certain computation with orders of magnitude lower latency and energy compared to state-of-the-art conventional approaches. These compelling neuromorphic networks solve a diverse range of problems representative of brain-like computation, such as event-based data processing, adaptive control, constrained optimization, sparse feature regression, and graph search.
Architecture & Planning• 2021• Institute of Electrical and Electronics Engineers
Periodicals
On the Inertia of Future More-Electronics Power Systems
Inertia plays a vital role in maintaining the frequency stability of power systems. However, the increase of power electronics-based renewable generation can dramatically reduce the inertia levels of modern power systems. This issue has already challenged the control and stability of small-scale power systems. It will soon be faced by larger power systems as the trend of large-scale renewable integration continues. In view of the urgent demand for addressing the inertia concern, this paper presents a comprehensive review of inertia enhancement methods covering both proven techniques and emerging ones and also studies the effect of inertia on frequency control. Among those proven techniques, the inertia emulation by wind turbines has successfully demonstrated its effectiveness and will receive widespread adoptions. For the emerging techniques, the virtual inertia generated by the dc-link capacitors of power converters has a great potential due to its low cost. The same concept of inertia emulation can also be applied to ultracapacitors. In addition, batteries will serve as an alternative inertia supplier, and the relevant technical challenges as well as the solutions are discussed in this paper. In future power systems where most of the generators and loads are connected via power electronics, virtual synchronous machines will gradually take over the responsibility of inertia support. In general, it is concluded that advances in semiconductors and control promise to make power electronics an enabling technology for inertia control in future power systems.
Architecture & Planning• 2018• Institute of Electrical and Electronics Engineers
Periodicals
The International Reference Ionosphere 2012 – a model of international collaboration
The International Reference Ionosphere (IRI) project was established jointly by the Committee on Space Research (COSPAR) and the International Union of Radio Science (URSI) in the late sixties with the goal to develop an international standard for the specification of plasma parameters in the Earth’s ionosphere. COSPAR needed such a specification for the evaluation of environmental effects on spacecraft and experiments in space, and URSI for radiowave propagation studies and applications. At the request of COSPAR and URSI, IRI was developed as a data-based model to avoid the uncertainty of theory-based models which are only as good as the evolving theoretical understanding. Being based on most of the available and reliable observations of the ionospheric plasma from the ground and from space, IRI describes monthly averages of electron density, electron temperature, ion temperature, ion composition, and several additional parameters in the altitude range from 60 km to 2000 km. A working group of about 50 international ionospheric experts is in charge of developing and improving the IRI model. Over time as new data became available and new modeling techniques emerged, steadily improved editions of the IRI model have been published. This paper gives a brief history of the IRI project and describes the latest version of the model, IRI-2012. It also briefly discusses efforts to develop a real-time IRI model. The IRI homepage is at http://IRImodel.org.
Architecture & Planning• 2014• EDP Open
Periodicals
An operational model for mainstreaming ecosystem services for implementation
Research on ecosystem services has grown markedly in recent years. However, few studies are embedded in a social process designed to ensure effective management of ecosystem services. Most research has focused only on biophysical and valuation assessments of putative services. As a mission-oriented discipline, ecosystem service research should be user-inspired and user-useful, which will require that researchers respond to stakeholder needs from the outset and collaborate with them in strategy development and implementation. Here we provide a pragmatic operational model for achieving the safeguarding of ecosystem services. The model comprises three phases: assessment, planning, and management. Outcomes of social, biophysical, and valuation assessments are used to identify opportunities and constraints for implementation. The latter then are transformed into user-friendly products to identify, with stakeholders, strategic objectives for implementation (the planning phase). The management phase undertakes and coordinates actions that achieve the protection of ecosystem services and ensure the flow of these services to beneficiaries. This outcome is achieved via mainstreaming, or incorporating the safeguarding of ecosystem services into the policies and practices of sectors that deal with land- and water-use planning. Management needs to be adaptive and should be institutionalized in a suite of learning organizations that are representative of the sectors that are concerned with decision-making and planning. By following the phases of our operational model, projects for safeguarding ecosystem services are likely to empower stakeholders to implement effective on-the-ground management that will achieve resilience of the corresponding social-ecological systems.
Architecture & Planning• 2008• National Academy of Sciences
Periodicals
Remote sensing of the terrestrial carbon cycle: A review of advances over 50 years
[no abstract]
Architecture & Planning• 2019• Elsevier BV
Periodicals
Modulation of the Root Microbiome by Plant Molecules: The Basis for Targeted Disease Suppression and Plant Growth Promotion
Plants host a mesmerizing diversity of microbes inside and around their roots, known as the microbiome. The microbiome is composed mostly of fungi, bacteria, oomycetes, and archaea that can be either pathogenic or beneficial for plant health and fitness. To grow healthy, plants need to surveil soil niches around the roots for the detection of pathogenic microbes, and in parallel maximize the services of beneficial microbes in nutrients uptake and growth promotion. Plants employ a palette of mechanisms to modulate their microbiome including structural modifications, the exudation of secondary metabolites and the coordinated action of different defence responses. Here, we review the current understanding on the composition and activity of the root microbiome and how different plant molecules can shape the structure of the root-associated microbial communities. Examples are given on interactions that occur in the rhizosphere between plants and soilborne fungi. We also present some well-established examples of microbiome harnessing to highlight how plants can maximize their fitness by selecting their microbiome. Understanding how plants manipulate their microbiome can aid in the design of next-generation microbial inoculants for targeted disease suppression and enhanced plant growth.
Architecture & Planning• 2020• Frontiers Media
Periodicals
Complex network approaches to nonlinear time series analysis
[no abstract]
Architecture & Planning• 2018• Elsevier BV
Periodicals
Acute Septic Arthritis
Acute septic arthritis may develop as a result of hematogenous seeding, direct introduction, or extension from a contiguous focus of infection. The pathogenesis of acute septic arthritis is multifactorial and depends on the interaction of the host immune response and the adherence factors, toxins, and immunoavoidance strategies of the invading pathogen. Neisseria gonorrhoeae and Staphylococcus aureus are used in discussing the host-pathogen interaction in the pathogenesis of acute septic arthritis. While diagnosis rests on isolation of the bacterial species from synovial fluid samples, patient history, clinical presentation, laboratory findings, and imaging studies are also important. Acute nongonococcal septic arthritis is a medical emergency that can lead to significant morbidity and mortality. Therefore, prompt recognition, rapid and aggressive antimicrobial therapy, and surgical treatment are critical to ensuring a good prognosis. Even with prompt diagnosis and treatment, high mortality and morbidity rates still occur. In contrast, gonococcal arthritis is often successfully treated with antimicrobial therapy alone and demonstrates a very low rate of complications and an excellent prognosis for full return of normal joint function. In the case of prosthetic joint infections, the hardware must be eventually removed by a two-stage revision in order to cure the infection.
Architecture & Planning• 2002• American Society for Microbiology
Periodicals
Machine learning in cardiovascular flows modeling: Predicting arterial blood pressure from non-invasive 4D flow MRI data using physics-informed neural networks
[no abstract]
Architecture & Planning• 2019• Elsevier BV
Periodicals
Preparations, Properties, and Applications of Polyaniline and Polyaniline Thin Films—A Review
Polyaniline (PANI) is a famous conductive polymer, and it has received tremendous consideration from researchers in the field of nanotechnology for the improvement of sensors, optoelectronic devices, and photonic devices. PANI is doped easily by different acids and dopants because of its easy synthesis and remarkable environmental stability. This review focuses on different preparation processes of PANI thin film by chemical and physical methods. Several features of PANI thin films, such as their magnetic, redox, and antioxidant, anti-corrosion, and electrical and sensing properties, are discussed in this review. PANI is a highly conductive polymer. Given its unique properties, easy synthesis, low cost, and high environmental stability in various applications such as electronics, drugs, and anti-corrosion materials, it has attracted extensive attention. The most important PANI applications are briefly reviewed at the end of this review.
Architecture & Planning• 2021• Multidisciplinary Digital Publishing Institute
Periodicals
Experience-based Co-design and Healthcare Improvement: Realizing Participatory Design in the Public Sector
Over the last decade, growing attention has been paid to the potential value of design theory and practice in improving public services. Experience-based Co-design (EBCD) is a participatory research approach that draws upon design tools and ways of thinking in order to bring healthcare staff and patients together to improve the quality of care. The co-design process that is integral to EBCD is powerful but also challenging, as it requires both staff and patients to renegotiate their roles and expectations as part of a reconfiguration of the relationships of power between citizens and public services. In this paper, we reflect upon the implementation and adaptation of EBCD in a variety of projects and on the challenges of co-design work within healthcare settings. Our discussion aims to contribute to the growing field of service design and to encourage further research into how co-design processes shape—and are shaped by—the power relations that characterize contemporary public services.
Architecture & Planning• 2015• Routledge
Periodicals
Machine Learning Methods for Attack Detection in the Smart Grid
Attack detection problems in the smart grid are posed as statistical learning problems for different attack scenarios in which the measurements are observed in batch or online settings. In this approach, machine learning algorithms are used to classify measurements as being either secure or attacked. An attack detection framework is provided to exploit any available prior knowledge about the system and surmount constraints arising from the sparse structure of the problem in the proposed approach. Well-known batch and online learning algorithms (supervised and semisupervised) are employed with decision- and feature-level fusion to model the attack detection problem. The relationships between statistical and geometric properties of attack vectors employed in the attack scenarios and learning algorithms are analyzed to detect unobservable attacks using statistical learning methods. The proposed algorithms are examined on various IEEE test systems. Experimental analyses show that machine learning algorithms can detect attacks with performances higher than attack detection algorithms that employ state vector estimation methods in the proposed attack detection framework.
Architecture & Planning• 2015• Institute of Electrical and Electronics Engineers
Periodicals
Mechanical metamaterials and beyond
Mechanical metamaterials enable the creation of structural materials with unprecedented mechanical properties. However, thus far, research on mechanical metamaterials has focused on passive mechanical metamaterials and the tunability of their mechanical properties. Deep integration of multifunctionality, sensing, electrical actuation, information processing, and advancing data-driven designs are grand challenges in the mechanical metamaterials community that could lead to truly intelligent mechanical metamaterials. In this perspective, we provide an overview of mechanical metamaterials within and beyond their classical mechanical functionalities. We discuss various aspects of data-driven approaches for inverse design and optimization of multifunctional mechanical metamaterials. Our aim is to provide new roadmaps for design and discovery of next-generation active and responsive mechanical metamaterials that can interact with the surrounding environment and adapt to various conditions while inheriting all outstanding mechanical features of classical mechanical metamaterials. Next, we deliberate the emerging mechanical metamaterials with specific functionalities to design informative and scientific intelligent devices. We highlight open challenges ahead of mechanical metamaterial systems at the component and integration levels and their transition into the domain of application beyond their mechanical capabilities.
Architecture & Planning• 2023• Nature Portfolio
Periodicals
Digital Twins in Health Care: Ethical Implications of an Emerging Engineering Paradigm
Personalized medicine uses fine grained information on individual persons, to pinpoint deviations from the normal. ‘Digital Twins’ in engineering provide a conceptual framework to analyse these emerging data-driven health care practices, as well as their implications for therapy, preventative care and human enhancement. Digital Twins stands for a specific engineering paradigm, where individual physical artefacts are paired with a digital model that dynamically reflects the status of that artefact. When applied to persons, Digital Twins are an emerging technology that builds in silico representations of an individual that dynamically reflect molecular status, physiological status and life style over time. We use Digital Twins as the hypothesis that one would be in the possession of very detailed bio-physical and lifestyle information of a person over time. This perspective redefines the concept of ‘normality’ or ‘health’, as a set of patterns that are regular for a particular individual, against the backdrop of patterns observed in the population. This perspective also will impact what is considered therapy and what is enhancement, as can be illustrated with the cases of the ‘asymptomatic ill’ and life extension via anti-ageing medicine. This changes are the consequence of how meaning is derived, in case measurement data is available. Moral distinctions namely will be based on patterns found in these data and the meanings that are grafted on these patterns. Ethical and societal implications of Digital Twins are explored. Digital Twins imply a data-driven approach to health care. This approach has the potential to deliver significant societal benefits, and can function as a social equalizer, by allowing for effective equalizing enhancement interventions. It can as well though be a driver for inequality, given the fact that a digital twin might not be an accessible technology for everyone, and given the fact that patterns identified across a population of digital twins can lead to segmentation and discrimination. This duality calls for governance as this emerging technology matures, including measures that ensure transparency of data usage and derived benefits, and data privacy.
Architecture & Planning• 2018• Frontiers Media
Periodicals
The Metaverse as a Virtual Form of Smart Cities: Opportunities and Challenges for Environmental, Economic, and Social Sustainability in Urban Futures
Data infrastructures, economic processes, and governance models of digital platforms are increasingly pervading urban sectors and spheres of urban life. This phenomenon is known as platformization, which has in turn given rise to the phenomena of platform society, where platforms have permeated the core of urban societies. A recent manifestation of platformization is the Metaverse, a global platform project launched by Meta (formerly Facebook) as a globally operating platform company. The Metaverse represents an idea of a hypothetical “parallel virtual world” that incarnate ways of living and working in virtual cities as an alternative to smart cities of the future. Indeed, with emerging innovative technologies—such as Artificial Intelligence, Big Data, the IoT, and Digital Twins—providing rich datasets and advanced computational understandings of human behavior, the Metaverse has the potential to redefine city designing activities and service provisioning towards increasing urban efficiencies, accountabilities, and quality performance. However, there still remain ethical, human, social, and cultural concerns as to the Metaverse’s influence upon the quality of human social interactions and its prospective scope in reconstructing the quality of urban life. This paper undertakes an upper-level literature review of the area of the Metaverse from a broader perspective. Further, it maps the emerging products and services of the Metaverse, and explores their potential contributions to smart cities with respect to their virtual incarnation, with a particular focus on the environmental, economic, and social goals of sustainability. This study may help urban policy makers to better understand the opportunities and implications of the Metaverse upon tech-mediated practices and applied urban agendas, as well as assess the positives and negatives of this techno-urban vision. This paper also offers thoughts regarding the argument that the Metaverse has disruptive and substantive effects on forms of reconstructing reality in an increasingly platformized urban society. This will hopefully stimulate prospective research and further critical perspectives on the topic.
Architecture & Planning• 2022• Multidisciplinary Digital Publishing Institute
Periodicals
Distributed Power-Generation Systems and Protection
Continuously expanding deployments of distributed power-generation systems (DPGSs) are transforming the conventional centralized power grid into a mixed distributed electrical network. The modern power grid requires flexible energy utilization but presents challenges in the case of a high penetration degree of renewable energy, among which wind and solar photovoltaics are typical sources. The integration level of the DPGS into the grid plays a critical role in developing sustainable and resilient power systems, especially with highly intermittent renewable energy resources. To address the challenging issues and, more importantly, to leverage the energy generation, stringent demands from both utility operators and consumers have been imposed on the DPGS. Furthermore, as the core of energy conversion, numerous power electronic converters employing advanced control techniques have been developed for the DPGS to consolidate the integration. In light of the above, this paper reviews the power-conversion and control technologies used for DPGSs. The impacts of the DPGS on the distributed grid are also examined, and more importantly, strategies for enhancing the connection and protection of the DPGS are discussed.
Architecture & Planning• 2017• Institute of Electrical and Electronics Engineers
Periodicals
Internet of Things in Smart Grid: Architecture, Applications, Services, Key Technologies, and Challenges
Internet of Things (IoT) is a connection of people and things at any time, in any place, with anyone and anything, using any network and any service. Thus, IoT is a huge dynamic global network infrastructure of Internet-enabled entities with web services. One of the most important applications of IoT is the Smart Grid (SG). SG is a data communications network which is integrated with the power grid to collect and analyze data that are acquired from transmission lines, distribution substations, and consumers. In this paper, we talk about IoT and SG and their relationship. Some IoT architectures in SG, requirements for using IoT in SG, IoT applications and services in SG, and challenges and future work are discussed.
Architecture & Planning• 2019• Multidisciplinary Digital Publishing Institute
Periodicals
Tuberculous Granulomas Are Hypoxic in Guinea Pigs, Rabbits, and Nonhuman Primates
Understanding the physical characteristics of the local microenvironment in which Mycobacterium tuberculosis resides is an important goal that may allow the targeting of metabolic processes to shorten drug regimens. Pimonidazole hydrochloride (Hypoxyprobe) is an imaging agent that is bioreductively activated only under hypoxic conditions in mammalian tissue. We employed this probe to evaluate the oxygen tension in tuberculous granulomas in four animal models of disease: mouse, guinea pig, rabbit, and nonhuman primate. Following infusion of pimonidazole into animals with established infections, lung tissues from the guinea pig, rabbit, and nonhuman primate showed discrete areas of pimonidazole adduct formation surrounding necrotic and caseous regions of pulmonary granulomas by immunohistochemical staining. This labeling could be substantially reduced by housing the animal under an atmosphere of 95% O(2). Direct measurement of tissue oxygen partial pressure by surgical insertion of a fiber optic oxygen probe into granulomas in the lungs of living infected rabbits demonstrated that even small (3-mm) pulmonary lesions were severely hypoxic (1.6 +/- 0.7 mm Hg). Finally, metronidazole, which has potent bactericidal activity in vitro only under low-oxygen culture conditions, was highly effective at reducing total-lung bacterial burdens in infected rabbits. Thus, three independent lines of evidence support the hypothesis that hypoxic microenvironments are an important feature of some lesions in these animal models of tuberculosis.
Architecture & Planning• 2008• American Society for Microbiology
Periodicals
Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future
The upcoming fifth generation (5G) of wireless networks is expected to lay a foundation of intelligent networks with the provision of some isolated artificial intelligence (AI) operations. However, fully intelligent network orchestration and management for providing innovative services will only be realized in Beyond 5G (B5G) networks. To this end, we envisage that the sixth generation (6G) of wireless networks will be driven by on-demand self-reconfiguration to ensure a many-fold increase in the network performance and service types. The increasingly stringent performance requirements of emerging networks may finally trigger the deployment of some interesting new technologies, such as large intelligent surfaces, electromagnetic-orbital angular momentum, visible light communications, and cell-free communications, to name a few. Our vision for 6G is a massively connected complex network capable of rapidly responding to the users' service calls through real-time learning of the network state as described by the network edge (e.g., base-station locations and cache contents), air interface (e.g., radio spectrum and propagation channel), and the user-side (e.g., battery-life and locations). The multi-state, multi-dimensional nature of the network state, requiring the real-time knowledge, can be viewed as a quantum uncertainty problem. In this regard, the emerging paradigms of machine learning (ML), quantum computing (QC), and quantum ML (QML) and their synergies with communication networks can be considered as core 6G enablers. Considering these potentials, starting with the 5G target services and enabling technologies, we provide a comprehensive review of the related state of the art in the domains of ML (including deep learning), QC, and QML and identify their potential benefits, issues, and use cases for their applications in the B5G networks. Subsequently, we propose a novel QC-assisted and QML-based framework for 6G communication networks while articulating its challenges and potential enabling technologies at the network infrastructure, network edge, air interface, and user end. Finally, some promising future research directions for the quantum- and QML-assisted B5G networks are identified and discussed.
Architecture & Planning• 2019• Institute of Electrical and Electronics Engineers
Periodicals
Value-Oriented and Ethical Technology Engineering in Industry 5.0: A Human-Centric Perspective for the Design of the Factory of the Future
Although manufacturing companies are currently situated at a transition point in what has been called Industry 4.0, a new revolutionary wave—Industry 5.0—is emerging as an ‘Age of Augmentation’ when the human and machine reconcile and work in perfect symbiosis with one another. Recent years have indeed assisted in drawing attention to the human-centric design of Cyber-Physical Production Systems (CPPS) and to the genesis of the ‘Operator 4.0’, two novel concepts that raise significant ethical questions regarding the impact of technology on workers and society at large. This paper argues that a value-oriented and ethical technology engineering in Industry 5.0 is an urgent and sensitive topic as demonstrated by a survey administered to industry leaders from different companies. The Value Sensitive Design (VSD) approach is proposed as a principled framework to illustrate how technologies enabling human–machine symbiosis in the Factory of the Future can be designed to embody elicited human values and to illustrate actionable steps that engineers and designers can take in their design projects. Use cases based on real solutions and prototypes discuss how a design-for-values approach aids in the investigation and mitigation of ethical issues emerging from the implementation of technological solutions and, hence, support the migration to a symbiotic Factory of the Future.
Architecture & Planning• 2020• Multidisciplinary Digital Publishing Institute