Academic Digital Library for institutions, students, and solo learners

Discovery

Content search and filters

This is the first search surface for the seven content types. Next we will connect full-text search and metadata-specific filters.

Results 1,892

Periodicals

Combining brain-computer interfaces and assistive technologies: state-of-the-art and challenges

In recent years, new research has brought the field of electroencephalogram (EEG)-based brain-computer interfacing (BCI) out of its infancy and into a phase of relative maturity through many demonstrated prototypes such as brain-controlled wheelchairs, keyboards, and computer games. With this proof-of-concept phase in the past, the time is now ripe to focus on the development of practical BCI technologies that can be brought out of the lab and into real-world applications. In particular, we focus on the prospect of improving the lives of countless disabled individuals through a combination of BCI technology with existing assistive technologies (AT). In pursuit of more practical BCIs for use outside of the lab, in this paper, we identify four application areas where disabled individuals could greatly benefit from advancements in BCI technology, namely, "Communication and Control", "Motor Substitution", "Entertainment", and "Motor Recovery". We review the current state of the art and possible future developments, while discussing the main research issues in these four areas. In particular, we expect the most progress in the development of technologies such as hybrid BCI architectures, user-machine adaptation algorithms, the exploitation of users' mental states for BCI reliability and confidence measures, the incorporation of principles in human-computer interaction (HCI) to improve BCI usability, and the development of novel BCI technology including better EEG devices.

Architecture & Planning• 2010• Frontiers Media
Access Full TextView Details
Periodicals

Deep Learning Algorithms for Bearing Fault Diagnostics—A Comprehensive Review

In this survey paper, we systematically summarize existing literature on bearing fault diagnostics with deep learning (DL) algorithms. While conventional machine learning (ML) methods, including artificial neural network, principal component analysis, support vector machines, etc., have been successfully applied to the detection and categorization of bearing faults for decades, recent developments in DL algorithms in the last five years have sparked renewed interest in both industry and academia for intelligent machine health monitoring. In this paper, we first provide a brief review of conventional ML methods, before taking a deep dive into the state-of-the-art DL algorithms for bearing fault applications. Specifically, the superiority of DL based methods are analyzed in terms of fault feature extraction and classification performances; many new functionalities enabled by DL techniques are also summarized. In addition, to obtain a more intuitive insight, a comparative study is conducted on the classification accuracy of different algorithms utilizing the open source Case Western Reserve University (CWRU) bearing dataset. Finally, to facilitate the transition on applying various DL algorithms to bearing fault diagnostics, detailed recommendations and suggestions are provided for specific application conditions. Future research directions to further enhance the performance of DL algorithms on health monitoring are also discussed.

Architecture & Planning• 2020• Institute of Electrical and Electronics Engineers
Access Full TextView Details
Periodicals

A Review of Deep-Learning-Based Medical Image Segmentation Methods

As an emerging biomedical image processing technology, medical image segmentation has made great contributions to sustainable medical care. Now it has become an important research direction in the field of computer vision. With the rapid development of deep learning, medical image processing based on deep convolutional neural networks has become a research hotspot. This paper focuses on the research of medical image segmentation based on deep learning. First, the basic ideas and characteristics of medical image segmentation based on deep learning are introduced. By explaining its research status and summarizing the three main methods of medical image segmentation and their own limitations, the future development direction is expanded. Based on the discussion of different pathological tissues and organs, the specificity between them and their classic segmentation algorithms are summarized. Despite the great achievements of medical image segmentation in recent years, medical image segmentation based on deep learning has still encountered difficulties in research. For example, the segmentation accuracy is not high, the number of medical images in the data set is small and the resolution is low. The inaccurate segmentation results are unable to meet the actual clinical requirements. Aiming at the above problems, a comprehensive review of current medical image segmentation methods based on deep learning is provided to help researchers solve existing problems.

Architecture & Planning• 2021• Multidisciplinary Digital Publishing Institute
Access Full TextView Details
Periodicals

Evaluation of Different Machine Learning Methods and Deep-Learning Convolutional Neural Networks for Landslide Detection

There is a growing demand for detailed and accurate landslide maps and inventories around the globe, but particularly in hazard-prone regions such as the Himalayas. Most standard mapping methods require expert knowledge, supervision and fieldwork. In this study, we use optical data from the Rapid Eye satellite and topographic factors to analyze the potential of machine learning methods, i.e., artificial neural network (ANN), support vector machines (SVM) and random forest (RF), and different deep-learning convolution neural networks (CNNs) for landslide detection. We use two training zones and one test zone to independently evaluate the performance of different methods in the highly landslide-prone Rasuwa district in Nepal. Twenty different maps are created using ANN, SVM and RF and different CNN instantiations and are compared against the results of extensive fieldwork through a mean intersection-over-union (mIOU) and other common metrics. This accuracy assessment yields the best result of 78.26% mIOU for a small window size CNN, which uses spectral information only. The additional information from a 5 m digital elevation model helps to discriminate between human settlements and landslides but does not improve the overall classification accuracy. CNNs do not automatically outperform ANN, SVM and RF, although this is sometimes claimed. Rather, the performance of CNNs strongly depends on their design, i.e., layer depth, input window sizes and training strategies. Here, we conclude that the CNN method is still in its infancy as most researchers will either use predefined parameters in solutions like Google TensorFlow or will apply different settings in a trial-and-error manner. Nevertheless, deep-learning can improve landslide mapping in the future if the effects of the different designs are better understood, enough training samples exist, and the effects of augmentation strategies to artificially increase the number of existing samples are better understood.

Architecture & Planning• 2019• Multidisciplinary Digital Publishing Institute
Access Full TextView Details
Periodicals

Constructing an understanding of mind: The development of children's social understanding within social interaction

Theories of children's developing understanding of mind tend to emphasize either individualistic processes of theory formation, maturation, or introspection, or the process of enculturation. However, such theories must be able to account for the accumulating evidence of the role of social interaction in the development of social understanding. We propose an alternative account, according to which the development of children's social understanding occurs within triadic interaction involving the child's experience of the world as well as communicative interaction with others about their experience and beliefs (Chapman 1991; 1999). It is through such triadic interaction that children gradually construct knowledge of the world as well as knowledge of other people. We contend that the extent and nature of the social interaction children experience will influence the development of children's social understanding. Increased opportunity to engage in cooperative social interaction and exposure to talk about mental states should facilitate the development of social understanding. We review evidence suggesting that children's understanding of mind develops gradually in the context of social interaction. Therefore, we need a theory of development in this area that accords a fundamental role to social interaction, yet does not assume that children simply adopt socially available knowledge but rather that children construct an understanding of mind within social interaction.

Architecture & Planning• 2004• Cambridge University Press
Access Full TextView Details
Periodicals

Digital Transformation in Healthcare: Technology Acceptance and Its Applications

Technological innovation has become an integral aspect of our daily life, such as wearable and information technology, virtual reality and the Internet of Things which have contributed to transforming healthcare business and operations. Patients will now have a broader range and more mindful healthcare choices and experience a new era of healthcare with a patient-centric culture. Digital transformation determines personal and institutional health care. This paper aims to analyse the changes taking place in the field of healthcare due to digital transformation. For this purpose, a systematic bibliographic review is performed, utilising Scopus, Science Direct and PubMed databases from 2008 to 2021. Our methodology is based on the approach by Wester and Watson, which classify the related articles based on a concept-centric method and an ad hoc classification system which identify the categories used to describe areas of literature. The search was made during August 2022 and identified 5847 papers, of which 321 fulfilled the inclusion criteria for further process. Finally, by removing and adding additional studies, we ended with 287 articles grouped into five themes: information technology in health, the educational impact of e-health, the acceptance of e-health, telemedicine and security issues.

Architecture & Planning• 2023• Multidisciplinary Digital Publishing Institute
Access Full TextView Details
Periodicals

3-D Sound for Virtual Reality and Multimedia

Technology and applications for the rendering of virtual acoustic spaces are reviewed. Chapter 1 deals with acoustics and psychoacoustics. Chapters 2 and 3 cover cues to spatial hearing and review psychoacoustic literature. Chapter 4 covers signal processing and systems overviews of 3-D sound systems. Chapter 5 covers applications to computer workstations, communication systems, aeronautics and space, and sonic arts. Chapter 6 lists resources. This TM is a reprint of the 1994 book from Academic Press.

Architecture & Planning• 1995• The MIT Press
Access Full TextView Details
Periodicals

Quality-of-life measures in chronic diseases of childhood

SCOPE OF THE REPORT: This report is concerned with the evaluation of measures broadly designed to measure quality of life (QoL) in children and adolescents, either by self-report or proxy raters. Four research questions were identified: (1) To what extent are adult measures used in the evaluation of healthcare interventions in children? (2) How appropriate are adult measures for use with children? (3) To what extent do child self-reports correspond with assessments made by parents and carers? (4) How feasible and reliable are proxy measures of QoL in different disease contexts? OBJECTIVES: (1) To review the state of the art with regard to measurement of QoL for children. (2) To make recommendations regarding the value of currently available measures for different purposes. (3) To identify further research needs. METHOD: Electronic databases were searched for the period 1980-July 1999 for articles relating to measures of QoL, health status or well-being in children (under 18 years) with chronic disease. Handsearching of relevant journals and cross-referencing with reference lists in identified articles was also carried out. Key workers in the field were contacted for additional information, and the Internet was searched for relevant websites. RESULTS: Forty-three measures were identified (19 generic and 24 disease-specific). Sixteen measures allowed for completion by children and parent/caregiver; seven only allowed for completion by a proxy, and the remainder (n = 17) allowed only for child completion. The measures were described as QoL (n = 30), health status, (n = 2), perception of illness (n = 1), life satisfaction (n = 1) and quality of well-being (n = 1). RESULTS - TO WHAT EXTENT ARE ADULT MEASURES USED IN THE EVALUATION OF HEALTHCARE INTERVENTIONS IN CHILDREN?: Three studies were identified where adult measures were used with very few changes made for children. In 11 studies involving nine separate measures of QoL, adult measures were used as a model for work with children. RESULTS - HOW APPROPRIATE ARE ADULT MEASURES FOR USE WITH CHILDREN?: Adult measures may fail to tap the specific aspects of QoL that are important to the child. Measures based on adult work impose considerable response burden for children, in terms of length, reading skills and response scale. Wording and format of adult measures may need to be modified to account for children's cognitive and language skills. More basic research is needed to determine the level of response burden that children of different ages can manage. Assessments of difficulty (e.g. reading age) need to be routinely included with information about new measures. RESULTS - TO WHAT EXTENT DO CHILD SELF-REPORTS CORRESPOND WITH ASSESSMENTS MADE BY PARENTS AND CARERS?: Fourteen studies were identified in which concor-dance between child and parent was investigated, often as part of the development of a new measure. There was some evidence for greater concordance between child and parent for physical functioning compared with social and emotional domains, but greater heterogeneity in the latter measures may contribute to inconsistent results. There was no simple relationship between concordance and moderating variables such as age, gender and illness, but this conclusion was addressed only very rarely. RESULTS - HOW FEASIBLE AND RELIABLE ARE PROXY MEASURES OF QOL IN DIFFERENT DISEASE CONTEXTS?: Only five papers fulfilled the review criteria. Evaluation is difficult because authors fail to justify their choice of measures, and do not report critical information such as completion rates or missing data. Use of existing measures can potentially eliminate the time and expense required to develop a comprehensive measure of QoL, but a full battery of standardised tests may be expensive in terms of time for administration and scoring. In addition, battery measures tend to be lengthy and therefore demanding for sick patients. They are not recommended for work with children. RECOMMENDATIONS FOR RESEARCH - MINIMUM CRITERIA FOR NEW MEASURES: A set of procedures needs to be established for the development of new measures. These need to draw on the experience gained in development of child and adult measures to date. Basic research to enhance understanding of how children interpret questions in QoL measures is recommended. We need to understand the differences in meaning of items between children and adults, and between children of different ages. Some attempt to develop measures for children of 6 years or more have been reported, and these should be further developed. (ABSTRACT TRUNCATED)

Architecture & Planning• 2001• NIHR Journals Library
Access Full TextView Details
Periodicals

A Survey on the Role of IoT in Agriculture for the Implementation of Smart Farming

Internet of things (IoT) is a promising technology which provides efficient and reliable solutions towards the modernization of several domains. IoT based solutions are being developed to automatically maintain and monitor agricultural farms with minimal human involvement. The article presents many aspects of technologies involved in the domain of IoT in agriculture. It explains the major components of IoT based smart farming. A rigorous discussion on network technologies used in IoT based agriculture has been presented, that involves network architecture and layers, network topologies used, and protocols. Furthermore, the connection of IoT based agriculture systems with relevant technologies including cloud computing, big data storage and analytics has also been presented. In addition, security issues in IoT agriculture have been highlighted. A list of smart phone based and sensor based applications developed for different aspects of farm management has also been presented. Lastly, the regulations and policies made by several countries to standardize IoT based agriculture have been presented along with few available success stories. In the end, some open research issues and challenges in IoT agriculture field have been presented.

Architecture & Planning• 2019• Institute of Electrical and Electronics Engineers
Access Full TextView Details
Periodicals

Blood Flow Restriction Exercise: Considerations of Methodology, Application, and Safety

The current manuscript sets out a position stand for blood flow restriction (BFR) exercise, focusing on the methodology, application and safety of this mode of training. With the emergence of this technique and the wide variety of applications within the literature, the aim of this position stand is to set out a current research informed guide to BFR training to practitioners. This covers the use of BFR to enhance muscular strength and hypertrophy via training with resistance and aerobic exercise and preventing muscle atrophy using the technique passively. The authorship team for this article was selected from the researchers focused in BFR training research with expertise in exercise science, strength and conditioning and sports medicine.

Architecture & Planning• 2019• Frontiers Media
Access Full TextView Details
Periodicals

The ODD Protocol for Describing Agent-Based and Other Simulation Models: A Second Update to Improve Clarity, Replication, and Structural Realism

by Volker Grimm, Steven F. Railsback, Christian E. Vincenot, Uta Berger, Cara Gallagher, Donald L. DeAngelis, Bruce Edmonds, Jiaqi Ge, Jarl Giske, Jürgen Groeneveld, Alice S.A. Johnston, Alexander Milles, Jacob Nabe-Nielsen, J. Gareth Polhill, Viktoriia Radchuk, Marie-Sophie Rohwäder, Richard A. Stillman, Jan C. Thiele and Daniel Ayllón

Architecture & Planning• 2020• University of Surrey
Access Full TextView Details
Periodicals

Addressing the Challenges of Inquiry-Based Learning Through Technology and Curriculum Design

Inquiry experiences can provide valuable opportunities for students to improve their understanding of both science content and scientific practices. However, the implementation of inquiry learning in classrooms presents a number of significant challenges. We have been exploring these challenges through a program of research on the use of scientific visualization technologies to support inquiry-based learning in the geosciences. In this paper, we describe five significant challenges to implementing inquiry-based learning and present strategies for addressing them through the design of technology and curriculum. We present a design history covering four generations of software and curriculum to show how these challenges arise in classrooms and how the design strategies respond to them. Students at all grade levels and in every domain of science should have the opportunity to use scientific inquiry and develop the ability to think and act in ways associated with inquiry...(National Scie...

Architecture & Planning• 1999• Centre National de la Recherche Scientifique
Access Full TextView Details
Periodicals

Application of Long Short-Term Memory (LSTM) Neural Network for Flood Forecasting

Flood forecasting is an essential requirement in integrated water resource management. This paper suggests a Long Short-Term Memory (LSTM) neural network model for flood forecasting, where the daily discharge and rainfall were used as input data. Moreover, characteristics of the data sets which may influence the model performance were also of interest. As a result, the Da River basin in Vietnam was chosen and two different combinations of input data sets from before 1985 (when the Hoa Binh dam was built) were used for one-day, two-day, and three-day flowrate forecasting ahead at Hoa Binh Station. The predictive ability of the model is quite impressive: The Nash–Sutcliffe efficiency (NSE) reached 99%, 95%, and 87% corresponding to three forecasting cases, respectively. The findings of this study suggest a viable option for flood forecasting on the Da River in Vietnam, where the river basin stretches between many countries and downstream flows (Vietnam) may fluctuate suddenly due to flood discharge from upstream hydroelectric reservoirs.

Architecture & Planning• 2019• Multidisciplinary Digital Publishing Institute
Access Full TextView Details
Periodicals

Whose Knowledge, Whose nature? Biodiversity, Conservation, and the Political Ecology of Social Movements

This paper proposes a framework for rethinking the conservation and appropriation of biological diversity from the perspective of social movements. It argues that biodiversity, although with concrete biophysical referents, is a discourse of recent origin. This discourse fosters a complex network of diverse actors, from international organizations and NGOs to local communities and social movements. Four views of biodiversity produced by this network (centered on global resource management, national sovereignity, biodemocracy, and cultural autonomy, respectively) are discussed in the first part of the paper. The second part focuses on the cultural autonomy perspective developed by social movements. It examines in detail the rise and development of the social movement of black communities in the Pacific rainforest region of Colombia. This movement, it is argued, articulates through their practice an entire political ecology of sustainability and conservation. The main elements of this political ecology are discussed and presented as a viable alternative to dominant frameworks.

Architecture & Planning• 1998• University of Arizona
Access Full TextView Details
Periodicals

A HapMap harvest of insights into the genetics of common disease

The International HapMap Project was designed to create a genome-wide database of patterns of human genetic variation, with the expectation that these patterns would be useful for genetic association studies of common diseases. This expectation has been amply fulfilled with just the initial output of genome-wide association studies, identifying nearly 100 loci for nearly 40 common diseases and traits. These associations provided new insights into pathophysiology, suggesting previously unsuspected etiologic pathways for common diseases that will be of use in identifying new therapeutic targets and developing targeted interventions based on genetically defined risk. In addition, HapMap-based discoveries have shed new light on the impact of evolutionary pressures on the human genome, suggesting multiple loci important for adapting to disease-causing pathogens and new environments. In this review we examine the origin, development, and current status of the HapMap; its prospects for continued evolution; and its current and potential future impact on biomedical science.

Architecture & Planning• 2008• American Society for Clinical Investigation
Access Full TextView Details
Periodicals

Planning for Product Platforms

Kodak has successfully learned the strategy of developing many distinctively different models from a common platform. Between April 1989 and July 1990, Kodak redesigned its base model and introduced 3 additional models, all having common components and common production process steps. The platform approach to product development is an important success factor in many markets. By sharing components and production processes across a platform of products, companies can develop differentiated products efficiently, increase the flexibility and responsiveness of their manufacturing processes, and take market share away from competitors that develop only one product at a time. The fundamentals of platform planning are discussed in detail.

Architecture & Planning• 1998• University of Pennsylvania
Access Full TextView Details
Periodicals

The NKI-Rockland Sample: A Model for Accelerating the Pace of Discovery Science in Psychiatry

The National Institute of Mental Health strategic plan for advancing psychiatric neuroscience calls for an acceleration of discovery and the delineation of developmental trajectories for risk and resilience across the lifespan. To attain these objectives, sufficiently powered datasets with broad and deep phenotypic characterization, state-of-the-art neuroimaging, and genetic samples must be generated and made openly available to the scientific community. The enhanced Nathan Kline Institute-Rockland Sample (NKI-RS) is a response to this need. NKI-RS is an ongoing, institutionally centered endeavor aimed at creating a large-scale (N > 1000), deeply phenotyped, community-ascertained, lifespan sample (ages 6-85 years old) with advanced neuroimaging and genetics. These data will be publically shared, openly, and prospectively (i.e., on a weekly basis). Herein, we describe the conceptual basis of the NKI-RS, including study design, sampling considerations, and steps to synchronize phenotypic and neuroimaging assessment. Additionally, we describe our process for sharing the data with the scientific community while protecting participant confidentiality, maintaining an adequate database, and certifying data integrity. The pilot phase of the NKI-RS, including challenges in recruiting, characterizing, imaging, and sharing data, is discussed while also explaining how this experience informed the final design of the enhanced NKI-RS. It is our hope that familiarity with the conceptual underpinnings of the enhanced NKI-RS will facilitate harmonization with future data collection efforts aimed at advancing psychiatric neuroscience and nosology.

Architecture & Planning• 2012• Frontiers Media
Access Full TextView Details
Periodicals

Doing More with Less: Innovation Input and Output in Family Firms

Family firms are often portrayed as an important yet conservative form of organization that is reluctant to invest in innovation; however, simultaneously, evidence has shown that family firms are flourishing and in fact constitute many of the world’s most innovative firms. Our study contributes to disentangling this puzzling effect. We argue that family firms—owing to the family’s high level of control over the firm, wealth concentration, and importance of nonfinancial goals—invest less in innovation but have an increased conversion rate of innovation input into output and, ultimately, a higher innovation output than nonfamily firms. Empirical evidence from a meta-analysis based on 108 primary studies from 42 countries supports our hypotheses. We further argue and empirically show that the observed effects are even stronger when the CEO of the family firm is a later-generation family member. However, when the CEO of the family firm is the firm’s founder, innovation input is higher and, contrary to our initial expectations, innovation output is lower than that in other firms. We further show that the family firm–innovation input–output relationships depend on country-level factors; namely, the level of minority shareholder protection and the education level of the workforce in the country.

Architecture & Planning• 2015• Academy of Management
Access Full TextView Details
Periodicals

Technological disruptions in services: lessons from tourism and hospitality

Purpose Technological disruptions such as the Internet of Things and autonomous devices, enhanced analytical capabilities (artificial intelligence) and rich media (virtual and augmented reality) are creating smart environments that are transforming industry structures, processes and practices. The purpose of this paper is to explore critical technological advancements using a value co-creation lens to provide insights into service innovations that impact ecosystems. The paper provides examples from tourism and hospitality industries as an information dependent service management context. Design/methodology/approach The research synthesizes prevailing theories of co-creation, service ecosystems, networks and technology disruption with emerging technological developments. Findings Findings highlight the need for research into service innovations in the tourism and hospitality sector at both macro-market and micro-firm levels, emanating from the rapid and radical nature of technological advancements. Specifically, the paper identifies three areas of likely future disruption in service experiences that may benefit from immediate attention: extra-sensory experiences, hyper-personalized experiences and beyond-automation experiences. Research limitations/implications Tourism and hospitality services prevail under varying levels of infrastructure, organization and cultural constraints. This paper provides an overview of potential disruptions and developments and does not delve into individual destination types and settings. This will require future work that conceptualizes and examines how stakeholders may adapt within specific contexts. Social implications Technological disruptions impact all facets of life. A comprehensive picture of developments here provides policymakers with nuanced perspectives to better prepare for impending change. Originality/value Guest experiences in tourism and hospitality by definition take place in hostile environments that are outside the safety and familiarity of one’s own surroundings. The emergence of smart environments will redefine how customers navigate their experiences. At a conceptual level, this requires a complete rethink of how stakeholders should leverage technologies, engage and reengineer services to remain competitive. The paper illustrates how technology disrupts industry structures and stimulates value co-creation at the micro and macro-societal level.

Architecture & Planning• 2019• Emerald Publishing Limited
Access Full TextView Details
Periodicals

Multimodal Learning With Transformers: A Survey

Transformer is a promising neural network learner, and has achieved great success in various machine learning tasks. Thanks to the recent prevalence of multimodal applications and Big Data, Transformer-based multimodal learning has become a hot topic in AI research. This paper presents a comprehensive survey of Transformer techniques oriented at multimodal data. The main contents of this survey include: (1) a background of multimodal learning, Transformer ecosystem, and the multimodal Big Data era, (2) a systematic review of Vanilla Transformer, Vision Transformer, and multimodal Transformers, from a geometrically topological perspective, (3) a review of multimodal Transformer applications, via two important paradigms, i.e., for multimodal pretraining and for specific multimodal tasks, (4) a summary of the common challenges and designs shared by the multimodal Transformer models and applications, and (5) a discussion of open problems and potential research directions for the community.

Architecture & Planning• 2023• IEEE Computer Society
Access Full TextView Details
Periodicals

Late Jurassic to Eocene evolution of the Cordilleran thrust belt and foreland basin system, western U.S.A.

Geochronological, structural, and sedimentological data provide the basis for a regional synthesis of the evolution of the Cordilleran retroarc thrust belt and foreland basin system in the western U.S.A. In this region, the Cordilleran orogenic belt became tectonically consolidated during Late Jurassic time (∼155 Ma) with the closure of marginal oceanic basins and accretion of fringing arcs along the western edge of the North American plate. Over the ensuing 100 Myr, contractile deformation propagated approximately 1000 kilometers eastward, culminating in the formation of the Laramide Rocky Mountain ranges. At the peak of its development, the retroarc side of the Cordillera was divided into five tectonomorphic zones, including from west to east the Luning-Fencemaker thrust belt; the central Nevada (or Eureka) thrust belt; a high-elevation plateau (the "Nevadaplano"); the topographically rugged Sevier fold-thrust belt; and the Laramide zone of intraforeland basement uplifts and basins. Mid-crustal rocks beneath the Nevadaplano experienced high-grade metamorphism and shortening during Late Jurassic and mid- to Late Cretaceous time, and the locus of major, upper crustal thrust faulting migrated sporadically eastward. By Late Cretaceous time, the middle crust beneath the Nevadaplano was experiencing decompression and cooling, perhaps in response to large-magnitude ductile extension and isostatic exhumation, concurrent with ongoing thrusting in the frontal Sevier belt. The tectonic history of the Sevier belt was remarkably consistent along strike of the orogenic belt, with emplacement of regional-scale Proterozoic and Paleozoic megathrust sheets during Early Cretaceous time and multiple, more closely spaced, Paleozoic and Mesozoic thrust sheets during Late Cretaceous--Paleocene time. Coeval with emplacement of the frontal thrust sheets, large structural culminations in Archean-Proterozoic crystalline basement developed along the basement step formed by Neoproterozoic rifting. A complex foreland basin system evolved in concert with the orogenic wedge. During its early and late history (∼155 - 110 Ma and ∼70 - 55 Ma) the basin was dominated by nonmarine deposition, whereas marine waters inundated the basin during its midlife (∼110 - 70 Ma). Late Jurassic basin development was controlled by both flexural and dynamic subsidence. From Early Cretaceous through early Late Cretaceous time the basin was dominated by flexural subsidence. From Late Cretaceous to mid-Cenozoic time the basin was increasingly partitioned by basement-involved Laramide structures. Linkages between Late Jurassic and Late Cretaceous Cordilleran arc-magmatism and westward underthrusting of North American continental lithosphere beneath the arc are not plainly demonstrable from the geological record in the Cordilleran thrust belt. A significant lag-time (∼20 Myr) between shortening and coeval underthrusting, on the one hand, and generation of arc melts, on the other, is required for any linkage to exist. However, inferred Late Jurassic lithospheric delamination may have provided a necessary precondition to allow relatively rapid Early Cretaceous continental underthrusting, which in turn could have catalyzed the Late Cretaceous arc flare-up.

Architecture & Planning• 2004• Yale University
Access Full TextView Details
Periodicals

A Tutorial on 5G NR V2X Communications

The Third Generation Partnership Project (3GPP) has recently published its Release 16 that includes the first Vehicle-to-Everything (V2X) standard based on the 5G New Radio (NR) air interface. 5G NR V2X introduces advanced functionalities on top of the 5G NR air interface to support connected and automated driving use cases with stringent requirements. This article presents an in-depth tutorial of the 3GPP Release 16 5G NR V2X standard for V2X communications, with a particular focus on the sidelink, since it is the most significant part of 5G NR V2X. The main part of the paper is an in-depth treatment of the key aspects of 5G NR V2X: the physical layer, the resource allocation, the quality of service management, the enhancements introduced to the Uu interface and the mobility management for V2N (Vehicle to Network) communications, as well as the co-existence mechanisms between 5G NR V2X and LTE V2X. We also review the use cases, the system architecture, and describe the evaluation methodology and simulation assumptions for 5G NR V2X. Finally, we provide an outlook on possible 5G NR V2X enhancements, including those identified within Release 17.

Architecture & Planning• 2021• Institute of Electrical and Electronics Engineers
Access Full TextView Details
Previous1...6061626364...79Next