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in Architecture & Planning
Periodicals

Survey on 6G Frontiers: Trends, Applications, Requirements, Technologies and Future Research

Emerging applications such as Internet of Everything, Holographic Telepresence, collaborative robots, and space and deep-sea tourism are already highlighting the limitations of existing fifth-generation (5G) mobile networks. These limitations are in terms of data-rate, latency, reliability, availability, processing, connection density and global coverage, spanning over ground, underwater and space. The sixth-generation (6G) of mobile networks are expected to burgeon in the coming decade to address these limitations. The development of 6G vision, applications, technologies and standards has already become a popular research theme in academia and the industry. In this paper, we provide a comprehensive survey of the current developments towards 6G. We highlight the societal and technological trends that initiate the drive towards 6G. Emerging applications to realize the demands raised by 6G driving trends are discussed subsequently. We also elaborate the requirements that are necessary to realize the 6G applications. Then we present the key enabling technologies in detail. We also outline current research projects and activities including standardization efforts towards the development of 6G. Finally, we summarize lessons learned from state-of-the-art research and discuss technical challenges that would shed a new light on future research directions towards 6G.

Architecture & Planning• 2021• IEEE Communications Society
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Periodicals

Lead‐Free Inverted Planar Formamidinium Tin Triiodide Perovskite Solar Cells Achieving Power Conversion Efficiencies up to 6.22%

Efficient lead (Pb)-free inverted planar formamidinium tin triiodide (FASnI3) perovskite solar cells (PVSCs) are demonstrated. Our FASnI3 PVSCs achieved average power conversion efficiencies (PCEs) of 5.41% ± 0.46% and a maximum PCE of 6.22% under forward voltage scan. The PVSCs exhibit small photocurrent–voltage hysteresis and high reproducibility. The champion cell shows a steady-state efficiency of ≈6.00% for over 100 s.

Architecture & Planning• 2016
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Periodicals

Survey on Multi-Access Edge Computing for Internet of Things Realization

The Internet of Things (IoT) has recently advanced from an experimental technology to what will become the backbone of future customer value for both product and service sector businesses. This underscores the cardinal role of IoT on the journey toward the fifth generation of wireless communication systems. IoT technologies augmented with intelligent and big data analytics are expected to rapidly change the landscape of myriads of application domains ranging from health care to smart cities and industrial automations. The emergence of multi-access edge computing (MEC) technology aims at extending cloud computing capabilities to the edge of the radio access network, hence providing real-time, high-bandwidth, low-latency access to radio network resources. IoT is identified as a key use case of MEC, given MEC's ability to provide cloud platform and gateway services at the network edge. MEC will inspire the development of myriads of applications and services with demand for ultralow latency and high quality of service due to its dense geographical distribution and wide support for mobility. MEC is therefore an important enabler of IoT applications and services which require real-time operations. In this survey, we provide a holistic overview on the exploitation of MEC technology for the realization of IoT applications and their synergies. We further discuss the technical aspects of enabling MEC in IoT and provide some insight into various other integration technologies therein.

Architecture & Planning• 2018• Institute of Electrical and Electronics Engineers
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Periodicals

Sampling-Based Robot Motion Planning: A Review

Motion planning is a fundamental research area in robotics. Sampling-based methods offer an efficient solution for what is otherwise a rather challenging dilemma of path planning. Consequently, these methods have been extended further away from basic robot planning into further difficult scenarios and diverse applications. A comprehensive survey of the growing body of work in sampling-based planning is given here. Simulations are executed to evaluate some of the proposed planners and highlight some of the implementation details that are often left unspecified. An emphasis is placed on contemporary research directions in this field. We address planners that tackle current issues in robotics. For instance, real-life kinodynamic planning, optimal planning, replanning in dynamic environments, and planning under uncertainty are discussed. The aim of this paper is to survey the state of the art in motion planning and to assess selected planners, examine implementation details and above all shed a light on the current challenges in motion planning and the promising approaches that will potentially overcome those problems.

Architecture & Planning• 2014• Institute of Electrical and Electronics Engineers
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Periodicals

Additive Engineering for Efficient and Stable Perovskite Solar Cells

Abstract Perovskite solar cells (PSCs) have reached a certified 25.2% efficiency in 2019 due to their high absorption coefficient, high carrier mobility, long diffusion length, and tunable direct bandgap. However, due to the nature of solution processing and rapid crystal growth of perovskite thin films, a variety of defects can form as a result of the precursor compositions and processing conditions. The use of additives can affect perovskite crystallization and film formation, defect passivation in the bulk and/or at the surface, as well as influence the interface tuning of structure and energetics. Here, recent progress in additive engineering during perovskite film formation is discussed according to the following common categories: Lewis acid (e.g., metal cations, fullerene derivatives), Lewis base based on the donor type (e.g., O‐donor, S‐donor, and N‐donor), ammonium salts, low‐dimensional perovskites, and ionic liquid. Various additive‐assisted strategies for interface optimization are then summarized; additives include modifiers to improve electron‐ and hole‐transport layers as well as those to modify perovskite surface properties. Finally, an outlook is provided on research trends with respect to additive engineering in PSC development.

Architecture & Planning• 2019• Wiley
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Periodicals

The detailed snowpack scheme Crocus and its implementation in SURFEX v7.2

Abstract. Detailed studies of snow cover processes require models that offer a fine description of the snow cover properties. The detailed snowpack model Crocus is such a scheme, and has been run operationally for avalanche forecasting over the French mountains for 20 yr. It is also used for climate or hydrological studies. To extend its potential applications, Crocus has been recently integrated within the framework of the externalized surface module SURFEX. SURFEX computes the exchanges of energy and mass between different types of surface and the atmosphere. It includes in particular the land surface scheme ISBA (Interactions between Soil, Biosphere, and Atmosphere). It allows Crocus to be run either in stand-alone mode, using a time series of forcing meteorological data or in fully coupled mode (explicit or fully implicit numerics) with atmospheric models ranging from meso-scale models to general circulation models. This approach also ensures a full coupling between the snow cover and the soil beneath. Several applications of this new simulation platform are presented. They range from a 1-D stand-alone simulation (Col de Porte, France) to fully-distributed simulations in complex terrain over a whole mountain range (Massif des Grandes Rousses, France), or in coupled mode such as a surface energy balance and boundary layer simulation over the East Antarctic Ice Sheet (Dome C).

Architecture & Planning• 2012• Copernicus Publications
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Periodicals

Identification of Apple Leaf Diseases Based on Deep Convolutional Neural Networks

Mosaic, Rust, Brown spot, and Alternaria leaf spot are the four common types of apple leaf diseases. Early diagnosis and accurate identification of apple leaf diseases can control the spread of infection and ensure the healthy development of the apple industry. The existing research uses complex image preprocessing and cannot guarantee high recognition rates for apple leaf diseases. This paper proposes an accurate identifying approach for apple leaf diseases based on deep convolutional neural networks. It includes generating sufficient pathological images and designing a novel architecture of a deep convolutional neural network based on AlexNet to detect apple leaf diseases. Using a dataset of 13,689 images of diseased apple leaves, the proposed deep convolutional neural network model is trained to identify the four common apple leaf diseases. Under the hold-out test set, the experimental results show that the proposed disease identification approach based on the convolutional neural network achieves an overall accuracy of 97.62%, the model parameters are reduced by 51,206,928 compared with those in the standard AlexNet model, and the accuracy of the proposed model with generated pathological images obtains an improvement of 10.83%. This research indicates that the proposed deep learning model provides a better solution in disease control for apple leaf diseases with high accuracy and a faster convergence rate, and that the image generation technique proposed in this paper can enhance the robustness of the convolutional neural network model.

Architecture & Planning• 2017• Multidisciplinary Digital Publishing Institute
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Periodicals

What Is Stochastic Resonance? Definitions, Misconceptions, Debates, and Its Relevance to Biology

Stochastic resonance is said to be observed when increases in levels of unpredictable fluctuations--e.g., random noise--cause an increase in a metric of the quality of signal transmission or detection performance, rather than a decrease. This counterintuitive effect relies on system nonlinearities and on some parameter ranges being "suboptimal". Stochastic resonance has been observed, quantified, and described in a plethora of physical and biological systems, including neurons. Being a topic of widespread multidisciplinary interest, the definition of stochastic resonance has evolved significantly over the last decade or so, leading to a number of debates, misunderstandings, and controversies. Perhaps the most important debate is whether the brain has evolved to utilize random noise in vivo, as part of the "neural code". Surprisingly, this debate has been for the most part ignored by neuroscientists, despite much indirect evidence of a positive role for noise in the brain. We explore some of the reasons for this and argue why it would be more surprising if the brain did not exploit randomness provided by noise--via stochastic resonance or otherwise--than if it did. We also challenge neuroscientists and biologists, both computational and experimental, to embrace a very broad definition of stochastic resonance in terms of signal-processing "noise benefits", and to devise experiments aimed at verifying that random variability can play a functional role in the brain, nervous system, or other areas of biology.

Architecture & Planning• 2009• Public Library of Science
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New Tools for New Research in Psychiatry: A Scalable and Customizable Platform to Empower Data Driven Smartphone Research

BACKGROUND: A longstanding barrier to progress in psychiatry, both in clinical settings and research trials, has been the persistent difficulty of accurately and reliably quantifying disease phenotypes. Mobile phone technology combined with data science has the potential to offer medicine a wealth of additional information on disease phenotypes, but the large majority of existing smartphone apps are not intended for use as biomedical research platforms and, as such, do not generate research-quality data. OBJECTIVE: Our aim is not the creation of yet another app per se but rather the establishment of a platform to collect research-quality smartphone raw sensor and usage pattern data. Our ultimate goal is to develop statistical, mathematical, and computational methodology to enable us and others to extract biomedical and clinical insights from smartphone data. METHODS: We report on the development and early testing of Beiwe, a research platform featuring a study portal, smartphone app, database, and data modeling and analysis tools designed and developed specifically for transparent, customizable, and reproducible biomedical research use, in particular for the study of psychiatric and neurological disorders. We also outline a proposed study using the platform for patients with schizophrenia. RESULTS: We demonstrate the passive data capabilities of the Beiwe platform and early results of its analytical capabilities. CONCLUSIONS: Smartphone sensors and phone usage patterns, when coupled with appropriate statistical learning tools, are able to capture various social and behavioral manifestations of illnesses, in naturalistic settings, as lived and experienced by patients. The ubiquity of smartphones makes this type of moment-by-moment quantification of disease phenotypes highly scalable and, when integrated within a transparent research platform, presents tremendous opportunities for research, discovery, and patient health.

Architecture & Planning• 2016• JMIR Publications
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From Practice to Field: A Multilevel Model of Practice-Driven Institutional Change

This article develops a model of practice-driven institutional change—or change that originates in the everyday work of individuals but results in a shift in field-level logic. In demonstrating how improvisations at work can generate institutional change, we attend to the earliest moments of change, which extant research has neglected; and we contrast existing accounts that focus on active entrepreneurship and the contested nature of change. We outline the specific mechanisms by which change emerges from everyday work, becomes justified, and diffuses within an organization and field, as well as precipitating and enabling dynamics that trigger and condition these mechanisms.

Architecture & Planning• 2012• Academy of Management
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Progress in the Development of CdTe and CdZnTe Semiconductor Radiation Detectors for Astrophysical and Medical Applications

Over the last decade, cadmium telluride (CdTe) and cadmium zinc telluride (CdZnTe) wide band gap semiconductors have attracted increasing interest as X-ray and gamma ray detectors. Among the traditional high performance spectrometers based on silicon (Si) and germanium (Ge), CdTe and CdZnTe detectors show high detection efficiency and good room temperature performance and are well suited for the development of compact and reliable detection systems. In this paper, we review the current status of research in the development of CdTe and CdZnTe detectors by a comprehensive survey on the material properties, the device characteristics, the different techniques for improving the overall detector performance and some major applications. Astrophysical and medical applications are discussed, pointing out the ongoing Italian research activities on the development of these detectors.

Architecture & Planning• 2009• Multidisciplinary Digital Publishing Institute
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‘Hypernudge’: Big Data as a mode of regulation by design

This paper draws on regulatory governance scholarship to argue that the analytic phenomenon currently known as ‘Big Data’ can be understood as a mode of ‘design-based’ regulation. Although Big Data decision-making technologies can take the form of automated decision-making systems, this paper focuses on algorithmic decision-guidance techniques. By highlighting correlations between data items that would not otherwise be observable, these techniques are being used to shape the informational choice context in which individual decision-making occurs, with the aim of channelling attention and decision-making in directions preferred by the ‘choice architect’. By relying upon the use of ‘nudge’ – a particular form of choice architecture that alters people’s behaviour in a predictable way without forbidding any options or significantly changing their economic incentives, these techniques constitute a ‘soft’ form of design-based control. But, unlike the static Nudges popularised by Thaler and Sunstein [(2008). Nudge. London: Penguin Books] such as placing the salad in front of the lasagne to encourage healthy eating, Big Data analytic nudges are extremely powerful and potent due to their networked, continuously updated, dynamic and pervasive nature (hence ‘hypernudge’). I adopt a liberal, rights-based critique of these techniques, contrasting liberal theoretical accounts with selective insights from science and technology studies (STS) and surveillance studies on the other. I argue that concerns about the legitimacy of these techniques are not satisfactorily resolved through reliance on individual notice and consent, touching upon the troubling implications for democracy and human flourishing if Big Data analytic techniques driven by commercial self-interest continue their onward march unchecked by effective and legitimate constraints.

Architecture & Planning• 2016• Routledge
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A Review of Vat Photopolymerization Technology: Materials, Applications, Challenges, and Future Trends of 3D Printing

Additive manufacturing (3D printing) has significantly changed the prototyping process in terms of technology, construction, materials, and their multiphysical properties. Among the most popular 3D printing techniques is vat photopolymerization, in which ultraviolet (UV) light is deployed to form chains between molecules of liquid light-curable resin, crosslink them, and as a result, solidify the resin. In this manuscript, three photopolymerization technologies, namely, stereolithography (SLA), digital light processing (DLP), and continuous digital light processing (CDLP), are reviewed. Additionally, the after-cured mechanical properties of light-curable resin materials are listed, along with a number of case studies showing their applications in practice. The manuscript aims at providing an overview and future trend of the photopolymerization technology to inspire the readers to engage in further research in this field, especially regarding developing new materials and mathematical models for microrods and bionic structures.

Architecture & Planning• 2021• Multidisciplinary Digital Publishing Institute
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Tracing anthropogenic carbon dioxide and methane emissions to fossil fuel and cement producers, 1854–2010

This paper presents a quantitative analysis of the historic fossil fuel and cement production records of the 50 leading investor-owned, 31 state-owned, and 9 nation-state producers of oil, natural gas, coal, and cement from as early as 1854 to 2010. This analysis traces emissions totaling 914 GtCO 2 e—63 % of cumulative worldwide emissions of industrial CO 2 and methane between 1751 and 2010—to the 90 “carbon major” entities based on the carbon content of marketed hydrocarbon fuels (subtracting for non-energy uses), process CO 2 from cement manufacture, CO 2 from flaring, venting, and own fuel use, and fugitive or vented methane. Cumulatively, emissions of 315 GtCO 2 e have been traced to investor-owned entities, 288 GtCO 2 e to state-owned enterprises, and 312 GtCO 2 e to nation-states. Of these emissions, half has been emitted since 1986. The carbon major entities possess fossil fuel reserves that will, if produced and emitted, intensify anthropogenic climate change. The purpose of the analysis is to understand the historic emissions as a factual matter, and to invite consideration of their possible relevance to public policy.

Architecture & Planning• 2013• Springer Science+Business Media
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Dynamic Daylight Performance Metrics for Sustainable Building Design

The objective of this document is to promote the use of dynamic daylight performance measures for sustainable building design. The paper initially explores the shortcomings of conventional, static daylight performance metrics which concentrate on individual sky conditions, such as the common daylight factor. It then provides a review of previously suggested dynamic daylight performance metrics, discussing the capability of these metrics to lead to superior daylighting designs and their accessibility to nonsimulation experts. Several example offices are examined to demonstrate the benefit of basing design decisions on dynamic performance metrics as opposed to the daylight factor.

Architecture & Planning• 2006• Taylor & Francis
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Artificial Intelligence and Human Trust in Healthcare: Focus on Clinicians

Artificial intelligence (AI) can transform health care practices with its increasing ability to translate the uncertainty and complexity in data into actionable-though imperfect-clinical decisions or suggestions. In the evolving relationship between humans and AI, trust is the one mechanism that shapes clinicians' use and adoption of AI. Trust is a psychological mechanism to deal with the uncertainty between what is known and unknown. Several research studies have highlighted the need for improving AI-based systems and enhancing their capabilities to help clinicians. However, assessing the magnitude and impact of human trust on AI technology demands substantial attention. Will a clinician trust an AI-based system? What are the factors that influence human trust in AI? Can trust in AI be optimized to improve decision-making processes? In this paper, we focus on clinicians as the primary users of AI systems in health care and present factors shaping trust between clinicians and AI. We highlight critical challenges related to trust that should be considered during the development of any AI system for clinical use.

Architecture & Planning• 2020• JMIR Publications
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Assessing Tumor-Infiltrating Lymphocytes in Solid Tumors: A Practical Review for Pathologists and Proposal for a Standardized Method from the International Immuno-Oncology Biomarkers Working Group: Part 2: TILs in Melanoma, Gastrointestinal Tract Carcinomas, Non–Small Cell Lung Carcinoma and Mesothelioma, Endometrial and Ovarian Carcinomas, Squamous Cell Carcinoma of the Head and Neck, Genitourinary Carcinomas, and Primary Brain Tumors

Assessment of the immune response to tumors is growing in importance as the prognostic implications of this response are increasingly recognized, and as immunotherapies are evaluated and implemented in different tumor types. However, many different approaches can be used to assess and describe the immune response, which limits efforts at implementation as a routine clinical biomarker. In part 1 of this review, we have proposed a standardized methodology to assess tumor-infiltrating lymphocytes (TILs) in solid tumors, based on the International Immuno-Oncology Biomarkers Working Group guidelines for invasive breast carcinoma. In part 2 of this review, we discuss the available evidence for the prognostic and predictive value of TILs in common solid tumors, including carcinomas of the lung, gastrointestinal tract, genitourinary system, gynecologic system, and head and neck, as well as primary brain tumors, mesothelioma and melanoma. The particularities and different emphases in TIL assessment in different tumor types are discussed. The standardized methodology we propose can be adapted to different tumor types and may be used as a standard against which other approaches can be compared. Standardization of TIL assessment will help clinicians, researchers and pathologists to conclusively evaluate the utility of this simple biomarker in the current era of immunotherapy.

Architecture & Planning• 2017• Lippincott Williams & Wilkins
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Mapping Human Whole-Brain Structural Networks with Diffusion MRI

Understanding the large-scale structural network formed by neurons is a major challenge in system neuroscience. A detailed connectivity map covering the entire brain would therefore be of great value. Based on diffusion MRI, we propose an efficient methodology to generate large, comprehensive and individual white matter connectional datasets of the living or dead, human or animal brain. This non-invasive tool enables us to study the basic and potentially complex network properties of the entire brain. For two human subjects we find that their individual brain networks have an exponential node degree distribution and that their global organization is in the form of a small world.

Architecture & Planning• 2007• Public Library of Science
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Mobile Edge Computing via a UAV-Mounted Cloudlet: Optimization of Bit Allocation and Path Planning

Unmanned aerial vehicles (UAVs) have been recently considered as means to provide enhanced coverage or relaying services to mobile users (MUs) in wireless systems with limited or no infrastructure. In this paper, a UAV-based mobile cloud computing system is studied in which a moving UAV is endowed with computing capabilities to offer computation offloading opportunities to MUs with limited local processing capabilities. The system aims at minimizing the total mobile energy consumption while satisfying quality of service requirements of the offloaded mobile application. Offloading is enabled by uplink and downlink communications between the mobile devices and the UAV, which take place by means of frequency division duplex via orthogonal or nonorthogonal multiple access schemes. The problem of jointly optimizing the bit allocation for uplink and downlink communications as well as for computing at the UAV, along with the cloudlet's trajectory under latency and UAV's energy budget constraints is formulated and addressed by leveraging successive convex approximation strategies. Numerical results demonstrate the significant energy savings that can be accrued by means of the proposed joint optimization of bit allocation and cloudlet's trajectory as compared to local mobile execution as well as to partial optimization approaches that design only the bit allocation or the cloudlet's trajectory.

Architecture & Planning• 2017• Institute of Electrical and Electronics Engineers
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A Survey on Quality of Experience of HTTP Adaptive Streaming

Changing network conditions pose severe problems to video streaming in the Internet. HTTP adaptive streaming (HAS) is a technology employed by numerous video services that relieves these issues by adapting the video to the current network conditions. It enables service providers to improve resource utilization and Quality of Experience (QoE) by incorporating information from different layers in order to deliver and adapt a video in its best possible quality. Thereby, it allows taking into account end user device capabilities, available video quality levels, current network conditions, and current server load. For end users, the major benefits of HAS compared to classical HTTP video streaming are reduced interruptions of the video playback and higher bandwidth utilization, which both generally result in a higher QoE. Adaptation is possible by changing the frame rate, resolution, or quantization of the video, which can be done with various adaptation strategies and related client- and server-side actions. The technical development of HAS, existing open standardized solutions, but also proprietary solutions are reviewed in this paper as fundamental to derive the QoE influence factors that emerge as a result of adaptation. The main contribution is a comprehensive survey of QoE related works from human computer interaction and networking domains, which are structured according to the QoE impact of video adaptation. To be more precise, subjective studies that cover QoE aspects of adaptation dimensions and strategies are revisited. As a result, QoE influence factors of HAS and corresponding QoE models are identified, but also open issues and conflicting results are discussed. Furthermore, technical influence factors, which are often ignored in the context of HAS, affect perceptual QoE influence factors and are consequently analyzed. This survey gives the reader an overview of the current state of the art and recent developments. At the same time, it targets networking researchers who develop new solutions for HTTP video streaming or assess video streaming from a user centric point of view. Therefore, this paper is a major step toward truly improving HAS.

Architecture & Planning• 2014• Institute of Electrical and Electronics Engineers
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