Periodicals
Advancing sustainable urban transformation
[no abstract]
Architecture & Planning• 2013• Elsevier BV
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in Architecture & Planning
Periodicals
Towards Post-Quantum Blockchain: A Review on Blockchain Cryptography Resistant to Quantum Computing Attacks
Blockchain and other Distributed Ledger Technologies (DLTs) have evolved significantly in the last years and their use has been suggested for numerous applications due to their ability to provide transparency, redundancy and accountability. In the case of blockchain, such characteristics are provided through public-key cryptography and hash functions. However, the fast progress of quantum computing has opened the possibility of performing attacks based on Grover's and Shor's algorithms in the near future. Such algorithms threaten both public-key cryptography and hash functions, forcing to redesign blockchains to make use of cryptosystems that withstand quantum attacks, thus creating which are known as post-quantum, quantum-proof, quantum-safe or quantum-resistant cryptosystems. For such a purpose, this article first studies current state of the art on post-quantum cryptosystems and how they can be applied to blockchains and DLTs. Moreover, the most relevant post-quantum blockchain systems are studied, as well as their main challenges. Furthermore, extensive comparisons are provided on the characteristics and performance of the most promising post-quantum public-key encryption and digital signature schemes for blockchains. Thus, this article seeks to provide a broad view and useful guidelines on post-quantum blockchain security to future blockchain researchers and developers.
Architecture & Planning• 2020• Institute of Electrical and Electronics Engineers
Periodicals
A Framework for Assessing the Vulnerability of Communities in the Canadian Arctic to Risks Associated with Climate Change
Adaptation to climate change is recognized as an important policy issue by international bodies such as the United Nations and by various national governments. Initiatives to identify adaptation needs and to improve adaptive capacity increasingly start with an assessment of the vulnerability of the system of interest, in terms of who and what are vulnerable, to what stresses, in what way, and what capacity exists to adapt to changing risks. Notwithstanding the scholarship on climate change itself, there are few studies on the nature of Arctic communities' vulnerability to climate-change risks. We review existing literature on implications of climate change for Arctic communities, develop a conceptual model of vulnerability, and present an analytical approach to assessing climate hazards and coping strategies in Arctic communities. Vulnerability is conceptualized as a function of exposure to climatic stresses and the adaptive capacity to cope with these stresses. The analytical framework employs place-specific case studies involving community residents and integrates information from multiple sources, both to document current exposures and adaptations and to characterize future exposures and adaptive capacity.
Architecture & Planning• 2004• Arctic Institute of North America
Periodicals
Recommendations for daytime, evening, and nighttime indoor light exposure to best support physiology, sleep, and wakefulness in healthy adults
Ocular light exposure has important influences on human health and well-being through modulation of circadian rhythms and sleep, as well as neuroendocrine and cognitive functions. Prevailing patterns of light exposure do not optimally engage these actions for many individuals, but advances in our understanding of the underpinning mechanisms and emerging lighting technologies now present opportunities to adjust lighting to promote optimal physical and mental health and performance. A newly developed, international standard provides a SI-compliant way of quantifying the influence of light on the intrinsically photosensitive, melanopsin-expressing, retinal neurons that mediate these effects. The present report provides recommendations for lighting, based on an expert scientific consensus and expressed in an easily measured quantity (melanopic equivalent daylight illuminance (melaponic EDI)) defined within this standard. The recommendations are supported by detailed analysis of the sensitivity of human circadian, neuroendocrine, and alerting responses to ocular light and provide a straightforward framework to inform lighting design and practice.
Architecture & Planning• 2022• Public Library of Science
Periodicals
Security and Privacy in Smart Farming: Challenges and Opportunities
Internet of Things (IoT) and smart computing technologies have revolutionized every sphere of 21stcentury humans. IoT technologies and the data driven services they offer were beyond imagination just a decade ago. Now, they surround us and influence a variety of domains such as automobile, smart home, healthcare, etc. In particular, the Agriculture and Farming industries have also embraced this technological intervention. Smart devices are widely used by a range of people from farmers to entrepreneurs. These technologies are used in a variety of ways, from finding real-time status of crops and soil moisture content to deploying drones to assist with tasks such as applying pesticide spray. However, the use of IoT and smart communication technologies introduce a vast exposure to cybersecurity threats and vulnerabilities in smart farming environments. Such cyber attacks have the potential to disrupt the economies of countries that are widely dependent on agriculture. In this paper, we present a holistic study on security and privacy in a smart farming ecosystem. The paper outlines a multi layered architecture relevant to the precision agriculture domain and discusses the security and privacy issues in this dynamic and distributed cyber physical environment. Further more, the paper elaborates on potential cyber attack scenarios and highlights open research challenges and future directions.
Architecture & Planning• 2020• Institute of Electrical and Electronics Engineers
Periodicals
Discrete event simulation for performance modelling in health care: a review of the literature
Discrete Event Simulation (DES) has been widely used in modelling health-care systems for many years and a simple citation analysis shows that the number of papers published has increased markedly since 2004. Over the last 30 years several significant reviews of DES papers have been published and we build on these to focus on the most recent era, with an interest in performance modelling within hospitals. As there are few papers that propose or illustrate general approaches, we classify papers according to the areas of application evident in the literature, discussing the apparent lack of genericity. There is considerable diversity in the objectives of reported studies and in the consequent level of detail: We discuss why specificity dominates and why more generic approaches are rare.
Architecture & Planning• 2010• Taylor & Francis
Periodicals
Smart hospitality—Interconnectivity and interoperability towards an ecosystem
[no abstract]
Architecture & Planning• 2017• Elsevier BV
Periodicals
The ADaptation and Anticipation Model (ADAM) of sensorimotor synchronization
A constantly changing environment requires precise yet flexible timing of movements. Sensorimotor synchronization (SMS)-the temporal coordination of an action with events in a predictable external rhythm-is a fundamental human skill that contributes to optimal sensory-motor control in daily life. A large body of research related to SMS has focused on adaptive error correction mechanisms that support the synchronization of periodic movements (e.g., finger taps) with events in regular pacing sequences. The results of recent studies additionally highlight the importance of anticipatory mechanisms that support temporal prediction in the context of SMS with sequences that contain tempo changes. To investigate the role of adaptation and anticipatory mechanisms in SMS we introduce ADAM: an ADaptation and Anticipation Model. ADAM combines reactive error correction processes (adaptation) with predictive temporal extrapolation processes (anticipation) inspired by the computational neuroscience concept of internal models. The combination of simulations and experimental manipulations based on ADAM creates a novel and promising approach for exploring adaptation and anticipation in SMS. The current paper describes the conceptual basis and architecture of ADAM.
Architecture & Planning• 2013• Frontiers Media
Periodicals
When Small Words Foretell Academic Success: The Case of College Admissions Essays
The smallest and most commonly used words in English are pronouns, articles, and other function words. Almost invisible to the reader or writer, function words can reveal ways people think and approach topics. A computerized text analysis of over 50,000 college admissions essays from more than 25,000 entering students found a coherent dimension of language use based on eight standard function word categories. The dimension, which reflected the degree students used categorical versus dynamic language, was analyzed to track college grades over students' four years of college. Higher grades were associated with greater article and preposition use, indicating categorical language (i.e., references to complexly organized objects and concepts). Lower grades were associated with greater use of auxiliary verbs, pronouns, adverbs, conjunctions, and negations, indicating more dynamic language (i.e., personal narratives). The links between the categorical-dynamic index (CDI) and academic performance hint at the cognitive styles rewarded by higher education institutions.
Architecture & Planning• 2014• Public Library of Science
Periodicals
Role of Physical Activity on Mental Health and Well-Being: A Review
In addition to the apparent physical health benefits, physical activity also affects mental health positively. Physically inactive individuals have been reported to have higher rates of morbidity and healthcare expenditures. Commonly, exercise therapy is recommended to combat these challenges and preserve mental wellness. According to empirical investigations, physical activity is positively associated with certain mental health traits. In nonclinical investigations, the most significant effects of physical exercise have been on self-concept and body image. An attempt to review the current understanding of the physiological and psychological mechanisms by which exercise improves mental health is presented in this review article. Regular physical activity improves the functioning of the hypothalamus-pituitary-adrenal axis. Depression and anxiety appear to be influenced by physical exercise, but to a smaller extent in the population than in clinical patients. Numerous hypotheses attempt to explain the connection between physical fitness and mental wellness. Physical activity was shown to help with sleep and improve various psychiatric disorders. Exercise in general is associated with a better mood and improved quality of life. Physical exercise and yoga may help in the management of cravings for substances, especially in people who may not have access to other forms of therapy. Evidence suggests that increased physical activity can help attenuate some psychotic symptoms and treat medical comorbidities that accompany psychotic disorders. The dearth of literature in the Indian context also indicated that more research was needed to evaluate and implement interventions for physical activity tailored to the Indian context.
Architecture & Planning• 2023• Cureus, Inc.
Periodicals
Change Detection Based on Artificial Intelligence: State-of-the-Art and Challenges
Change detection based on remote sensing (RS) data is an important method of detecting changes on the Earth’s surface and has a wide range of applications in urban planning, environmental monitoring, agriculture investigation, disaster assessment, and map revision. In recent years, integrated artificial intelligence (AI) technology has become a research focus in developing new change detection methods. Although some researchers claim that AI-based change detection approaches outperform traditional change detection approaches, it is not immediately obvious how and to what extent AI can improve the performance of change detection. This review focuses on the state-of-the-art methods, applications, and challenges of AI for change detection. Specifically, the implementation process of AI-based change detection is first introduced. Then, the data from different sensors used for change detection, including optical RS data, synthetic aperture radar (SAR) data, street view images, and combined heterogeneous data, are presented, and the available open datasets are also listed. The general frameworks of AI-based change detection methods are reviewed and analyzed systematically, and the unsupervised schemes used in AI-based change detection are further analyzed. Subsequently, the commonly used networks in AI for change detection are described. From a practical point of view, the application domains of AI-based change detection methods are classified based on their applicability. Finally, the major challenges and prospects of AI for change detection are discussed and delineated, including (a) heterogeneous big data processing, (b) unsupervised AI, and (c) the reliability of AI. This review will be beneficial for researchers in understanding this field.
Architecture & Planning• 2020• Multidisciplinary Digital Publishing Institute
Periodicals
Multisource and Multitemporal Data Fusion in Remote Sensing: A Comprehensive Review of the State of the Art
This article brings together the advances of multisource and multitemporal data fusion approaches with respect to the various research communities and provides a thorough and discipline-specific starting point for researchers at different levels (i.e., students, researchers, and senior researchers) willing to conduct novel investigations on this challenging topic by supplying sufficient detail and references. More specifically, this work provides a bird's-eye view of many important contributions specifically dedicated to the topics of pansharpening and resolution enhancement, point cloud data fusion, hyperspectral and lidar data fusion, multitemporal data fusion, and big data and social media. In addition, the main challenges and possible future research in each area are outlined and discussed.
Architecture & Planning• 2019• Institute of Electrical and Electronics Engineers
Periodicals
Understanding platform business models: A mixed methods study of marketplaces
[no abstract]
Architecture & Planning• 2017• Elsevier BV
Periodicals
The Challenge of Feeding the World
The aim of the present research is to provide a comprehensive review about the current challenges related to food security and hidden hunger. Issues are presented according to major factors, such as growing population, changing dietary habits, water efficiency, climate change and volatile food prices. These factors were compiled from reports of major international organizations and from relevant scientific articles on the subject. Collecting the results and presenting them in an accessible manner may provide new insight for interested parties. Accessibility of data is extremely important, since food security and its drivers form a closely interconnected but extremely complex network, which requires coordinated problem solving to resolve issues. According to the results, the demand for growing agricultural products has been partly met by increasing cultivated land in recent decades. At the same time, there is serious competition for existing agricultural areas, which further limits the extension of agricultural land in addition to the natural constraints of land availability. Agricultural production needs to expand faster than population growth without further damage to the environment. The driving force behind development is sustainable intensive farming, which means the more effective utilization of agricultural land and water resources. Current global trends in food consumption are unsustainable, analyzed in terms of either public health, environmental impacts or socio-economic costs. The growing population should strive for sustainable food consumption, as social, environmental and health impacts are very important in this respect as well. To this end, the benefits of consuming foods that are less harmful to the environment during production are also to be emphasized in the scope of consumption policy and education related to nutrition as opposed to other food types, the production of which causes a major demand for raw materials.
Architecture & Planning• 2019• Multidisciplinary Digital Publishing Institute
Periodicals
Who are the victims of low-carbon transitions? Towards a political ecology of climate change mitigation
This study critically examines 20 years of geography and political ecology literature on the energy justice implications of climate change mitigation. Grounded in an expert guided literature review of 198 studies and their corresponding 332 case studies, it assesses the linkages between low carbon transitions—including renewable electricity, biofuel, nuclear power, smart grids, electric vehicles, and land use management—with degradation, dispossession and destruction. It draws on a framework that envisions the political ecology of low-carbon transitions as consisting of four distinct processes: enclosure (capture of land or resources), exclusion (unfair planning), encroachment (destruction of the environment), or entrenchment (worsening of inequality or vulnerability). The study vigorously interrogates how these elements play out by country and across countries, by type of mitigation option, by type of victim or affected group, by process, and by severity, e.g. from modern slavery to organized crime, from violence, murder and torture to the exacerbation of child prostitution or the destruction of pristine ecosystems. It also closely examines the locations, disciplinary affiliations, methods and spatial units of analysis employed by this corpus of research, with clear and compelling insights for future work in the space of geography, climate change, and energy transitions. It suggest five critical avenues for future research: greater inclusivity and diversity, rigor and comparative analysis, focus on mundane technologies and non-Western case studies, multi-scalar analysis, and focus on policy and recommendations. At times, low-carbon transitions and climate action can promote squalor over sustainability and leave angry communities, disgruntled workers, scorned business partners, and degraded landscapes in their wake. Nevertheless, ample opportunities exist to make a future low-carbon world more pluralistic, democratic, and just.
Architecture & Planning• 2021• Elsevier BV
Periodicals
Recruitment to the Nuclear Periphery Can Alter Expression of Genes in Human Cells
The spatial organisation of the genome in the nucleus has a role in the regulation of gene expression. In vertebrates, chromosomal regions with low gene-density are located close to the nuclear periphery. Correlations have also been made between the transcriptional state of some genes and their location near the nuclear periphery. However, a crucial issue is whether this level of nuclear organisation directly affects gene function, rather than merely reflecting it. To directly investigate whether proximity to the nuclear periphery can influence gene expression in mammalian cells, here we relocate specific human chromosomes to the nuclear periphery by tethering them to a protein of the inner nuclear membrane. We show that this can reversibly suppress the expression of some endogenous human genes located near the tethering sites, and even genes further away. However, the expression of many other genes is not detectably reduced and we show that location at the nuclear periphery is not incompatible with active transcription. The dampening of gene expression around the nuclear periphery is dependent on the activity of histone deacetylases. Our data show that the radial position within the nucleus can influence the expression of some, but not all, genes. This is compatible with the suggestion that re-localisation of genes relative to the peripheral zone of the nucleus could be used by metazoans to modulate the expression of selected genes during development and differentiation.
Architecture & Planning• 2008• Public Library of Science
Periodicals
A Review of Smart Cities Based on the Internet of Things Concept
With the expansion of smart meters, like the Advanced Metering Infrastructure (AMI), and the Internet of Things (IoT), each smart city is equipped with various kinds of electronic devices. Therefore, equipment and technologies enable us to be smarter and make various aspects of smart cities more accessible and applicable. The goal of the current paper is to provide an inclusive review on the concept of the smart city besides their different applications, benefits, and advantages. In addition, most of the possible IoT technologies are introduced, and their capabilities to merge into and apply to the different parts of smart cities are discussed. The potential application of smart cities with respect to technology development in the future provides another valuable discussion in this paper. Meanwhile, some practical experiences all across the world and the key barriers to its implementation are thoroughly expressed.
Architecture & Planning• 2017• Multidisciplinary Digital Publishing Institute
Periodicals
Using Blockchain for Electronic Health Records
Blockchain have been an interesting research area for a long time and the benefits it provides have been used by a number of various industries. Similarly, the healthcare sector stands to benefit immensely from the blockchain technology due to security, privacy, confidentiality and decentralization. Nevertheless, the Electronic Health Record (EHR) systems face problems regarding data security, integrity and management. In this paper, we discuss how the blockchain technology can be used to transform the EHR systems and could be a solution of these issues. We present a framework that could be used for the implementation of blockchain technology in healthcare sector for EHR. The aim of our proposed framework is firstly to implement blockchain technology for EHR and secondly to provide secure storage of electronic records by defining granular access rules for the users of the proposed framework. Moreover, this framework also discusses the scalability problem faced by the blockchain technology in general via use of off-chain storage of the records. This framework provides the EHR system with the benefits of having a scalable, secure and integral blockchain-based solution.
Architecture & Planning• 2019• Institute of Electrical and Electronics Engineers
Periodicals
A Review on Challenges of Autonomous Mobile Robot and Sensor Fusion Methods
Autonomous mobile robots are becoming more prominent in recent time because of their relevance and applications to the world today. Their ability to navigate in an environment without a need for physical or electro-mechanical guidance devices has made it more promising and useful. The use of autonomous mobile robots is emerging in different sectors such as companies, industries, hospital, institutions, agriculture and homes to improve services and daily activities. Due to technology advancement, the demand for mobile robot has increased due to the task they perform and services they render such as carrying heavy objects, monitoring, search and rescue missions, etc. Various studies have been carried out by researchers on the importance of mobile robot, its applications and challenges. This survey paper unravels the current literatures, the challenges mobile robot is being faced with. A comprehensive study on devices/sensors and prevalent sensor fusion techniques developed for tackling issues like localization, estimation and navigation in mobile robot are presented as well in which they are organised according to relevance, strengths and weaknesses. The study therefore gives good direction for further investigation on developing methods to deal with the discrepancies faced with autonomous mobile robot.
Architecture & Planning• 2020• Institute of Electrical and Electronics Engineers
Periodicals
Comprehensive investigation on hydrogen and fuel cell technology in the aviation and aerospace sectors
[no abstract]
Architecture & Planning• 2019• Elsevier BV
Periodicals
Hierarchical task analysis: Developments, applications, and extensions
[no abstract]
Architecture & Planning• 2005• Elsevier BV
Periodicals
Building a chemical ontology using Methontology and the Ontology Design Environment
Methontology provides guidelines for specifying ontologies at the knowledge level, as a specification of a conceptualization. ODE enables ontology construction, covering the entire life cycle and automatically implementing ontologies. To meet the challenge of building ontologies, we have developed Methontology, a framework for specifying ontologies at the knowledge level, and the Ontology Development Environment. We present our experience in using Methontology and ODE to build the chemical ontology.
Architecture & Planning• 1999• Institute of Electrical and Electronics Engineers
Periodicals
Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study
BACKGROUND: Non-small-cell lung cancer (NSCLC) patients often demonstrate varying clinical courses and outcomes, even within the same tumor stage. This study explores deep learning applications in medical imaging allowing for the automated quantification of radiographic characteristics and potentially improving patient stratification. METHODS AND FINDINGS: We performed an integrative analysis on 7 independent datasets across 5 institutions totaling 1,194 NSCLC patients (age median = 68.3 years [range 32.5-93.3], survival median = 1.7 years [range 0.0-11.7]). Using external validation in computed tomography (CT) data, we identified prognostic signatures using a 3D convolutional neural network (CNN) for patients treated with radiotherapy (n = 771, age median = 68.0 years [range 32.5-93.3], survival median = 1.3 years [range 0.0-11.7]). We then employed a transfer learning approach to achieve the same for surgery patients (n = 391, age median = 69.1 years [range 37.2-88.0], survival median = 3.1 years [range 0.0-8.8]). We found that the CNN predictions were significantly associated with 2-year overall survival from the start of respective treatment for radiotherapy (area under the receiver operating characteristic curve [AUC] = 0.70 [95% CI 0.63-0.78], p < 0.001) and surgery (AUC = 0.71 [95% CI 0.60-0.82], p < 0.001) patients. The CNN was also able to significantly stratify patients into low and high mortality risk groups in both the radiotherapy (p < 0.001) and surgery (p = 0.03) datasets. Additionally, the CNN was found to significantly outperform random forest models built on clinical parameters-including age, sex, and tumor node metastasis stage-as well as demonstrate high robustness against test-retest (intraclass correlation coefficient = 0.91) and inter-reader (Spearman's rank-order correlation = 0.88) variations. To gain a better understanding of the characteristics captured by the CNN, we identified regions with the most contribution towards predictions and highlighted the importance of tumor-surrounding tissue in patient stratification. We also present preliminary findings on the biological basis of the captured phenotypes as being linked to cell cycle and transcriptional processes. Limitations include the retrospective nature of this study as well as the opaque black box nature of deep learning networks. CONCLUSIONS: Our results provide evidence that deep learning networks may be used for mortality risk stratification based on standard-of-care CT images from NSCLC patients. This evidence motivates future research into better deciphering the clinical and biological basis of deep learning networks as well as validation in prospective data.
Architecture & Planning• 2018• Public Library of Science
Periodicals
Energy Forecasting: A Review and Outlook
Forecasting has been an essential part of the power and energy industry. Researchers and practitioners have contributed thousands of papers on forecasting electricity demand and prices, and renewable generation (e.g., wind and solar power). This article offers a brief review of influential energy forecasting papers; summarizes research trends; discusses importance of reproducible research and points out six valuable open data sources; makes recommendations about publishing high-quality research papers; and offers an outlook into the future of energy forecasting.
Architecture & Planning• 2020• Institute of Electrical and Electronics Engineers