Periodicals
Contributions of the circular economy to the UN sustainable development goals through sustainable construction
[no abstract]
Architecture & Planning• 2021• Elsevier BV
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Periodicals
Finding a roadmap to achieve large neuromorphic hardware systems
Neuromorphic systems are gaining increasing importance in an era where CMOS digital computing techniques are reaching physical limits. These silicon systems mimic extremely energy efficient neural computing structures, potentially both for solving engineering applications as well as understanding neural computation. Toward this end, the authors provide a glimpse at what the technology evolution roadmap looks like for these systems so that Neuromorphic engineers may gain the same benefit of anticipation and foresight that IC designers gained from Moore's law many years ago. Scaling of energy efficiency, performance, and size will be discussed as well as how the implementation and application space of Neuromorphic systems are expected to evolve over time.
Architecture & Planning• 2013• Frontiers Media
Periodicals
A Survey on Concepts, Applications, and Challenges in Cyber-Physical Systems
The Cyber-Physical System (CPS) is a term describing a broad range of complex, multi-disciplinary, physically-aware next generation engineered system that integrates embedded computing technologies (cyber part) into the physical world. In order to define and understand CPS more precisely, this article presents a detailed survey of the related work, discussing the origin of CPS, the relations to other research fields, prevalent concepts, and practical applications. Further, this article enumerates an extensive set of technical challenges and uses specific applications to elaborate and provide insight into each specific concept. CPS is a very broad research area and therefore has diverse applications spanning different scales. Additionally, the next generation technologies are expected to play an important role on CPS research. All of CPS applications need to be designed considering the cutting-edge technologies, necessary system-level requirements, and overall impact on the real world.
Architecture & Planning• 2014• Korea Society of Internet Information
Periodicals
Navigating the Back Loop: Fostering Social Innovation and Transformation in Ecosystem Management
Biggs, R., F. R. Westley, and S. R. Carpenter. 2010. Navigating the back loop: fostering social innovation and transformation in ecosystem management. Ecology and Society 15(2): 9. https://doi.org/10.5751/ES-03411-150209
Architecture & Planning• 2010• Resilience Alliance
Periodicals
SELECTION OF THE EFFECTIVE DWELLING HOUSE WALLS BY APPLYING ATTRIBUTES VALUES DETERMINED AT INTERVALS
The higher life quality standards, the changes of habits and new well‐being requirements have led to an increase in the demand for housing. Decision‐making problems in construction management often involve a complex decision‐making process in which multiple requirements and conditions have to be taken into consideration simultaneously. However, not every attribute used in multidimensional scaling is equally and precisely weighted in the real world. Thus quantitative and qualitative assessments are often required to deal with uncertainty, subjective and imprecise data. The accuracy of performance measures in common multi-attribute methods is usually assumed to be accurate. Grey theory is a new technique for performing prediction, relational analysis and decision‐making in many areas. This paper considers the application of grey relations methodology for defining the utility of an alternative and is proposed as a method of multiple criteria COmplex PRoportional Assessment of alternatives with Grey relations (COPRAS‐G). In this model parameters of the alternatives are determined by the grey relational grade and are expressed in intervals. A case study of assessing external walls of four alternatives was used to demonstrate the applicability and the effectiveness of the proposed approach. The results show that this method can be implemented as an effective decision aid in multi‐attribute selection. Santrauka Straipsnio tikslas – pasiūlyti alternatyvią daugelio rodiklių vertinimo metodiką. Šios metodikos išskirtinumas – rodiklių reikšmės, aprašomos intervalais. Tai labiau atitinka realias aplinkos sąlygas ir galimas reikšmes. Modelis su intervaluose pateiktomis efektyvumo rodiklių reikšmėmis pritaikytas E. K. Zavadsko ir A. Kaklausko sukurtam metodui COPRAS (Complex Proportional Evaluation). Taip gautas naujas metodas COPRAS-G. Šis metodas pritaikytas daugiabučių namų išorinių sienų efektyvumo vertinimo uždaviniui spręsti. Sudaryta efektyvumo rodiklių sistema, nustatyta efektyvumo rodiklių reikšmė, rodiklių rangas. Pagal sudarytą modelį pritaikę COPRAS-G metodą, galime spręsti daugelį statybos, vadybos alternatyvų vertinimo uždavinių.
Architecture & Planning• 2008• Taylor & Francis
Periodicals
Editors’ perspectives: road vehicle suspension design, dynamics, and control
This paper provides an overview of the latest advances in road vehicle suspension design, dynamics, and control, together with the authors’ perspectives, in the context of vehicle ride, handling, and stability. The general aspects of road vehicle suspension dynamics and design are discussed, followed by descriptions of road-roughness excitations with a particular emphasis on road potholes. Passive suspension system designs and their effects on road vehicle dynamics and stability are presented in terms of in-plane and full-vehicle arrangements. Controlled suspensions are also reviewed and discussed. The paper concludes with some potential research topics, in particular those associated with the development of hybrid and electric vehicles.
Architecture & Planning• 2010• Taylor & Francis
Periodicals
Generative AI in Medicine and Healthcare: Promises, Opportunities and Challenges
Generative AI (artificial intelligence) refers to algorithms and models, such as OpenAI’s ChatGPT, that can be prompted to generate various types of content. In this narrative review, we present a selection of representative examples of generative AI applications in medicine and healthcare. We then briefly discuss some associated issues, such as trust, veracity, clinical safety and reliability, privacy, copyrights, ownership, and opportunities, e.g., AI-driven conversational user interfaces for friendlier human-computer interaction. We conclude that generative AI will play an increasingly important role in medicine and healthcare as it further evolves and gets better tailored to the unique settings and requirements of the medical domain and as the laws, policies and regulatory frameworks surrounding its use start taking shape.
Architecture & Planning• 2023• Multidisciplinary Digital Publishing Institute
Periodicals
A Survey on AI-Driven Digital Twins in Industry 4.0: Smart Manufacturing and Advanced Robotics
Digital twin (DT) and artificial intelligence (AI) technologies have grown rapidly in recent years and are considered by both academia and industry to be key enablers for Industry 4.0. As a digital replica of a physical entity, the basis of DT is the infrastructure and data, the core is the algorithm and model, and the application is the software and service. The grounding of DT and AI in industrial sectors is even more dependent on the systematic and in-depth integration of domain-specific expertise. This survey comprehensively reviews over 300 manuscripts on AI-driven DT technologies of Industry 4.0 used over the past five years and summarizes their general developments and the current state of AI-integration in the fields of smart manufacturing and advanced robotics. These cover conventional sophisticated metal machining and industrial automation as well as emerging techniques, such as 3D printing and human-robot interaction/cooperation. Furthermore, advantages of AI-driven DTs in the context of sustainable development are elaborated. Practical challenges and development prospects of AI-driven DTs are discussed with a respective focus on different levels. A route for AI-integration in multiscale/fidelity DTs with multiscale/fidelity data sources in Industry 4.0 is outlined.
Architecture & Planning• 2021• Multidisciplinary Digital Publishing Institute
Periodicals
C4MIP – The Coupled Climate–Carbon Cycle Model Intercomparison Project:experimental protocol for CMIP6
Abstract. Coordinated experimental design and implementation has become a cornerstone of global climate modelling. Model Intercomparison Projects (MIPs) enable systematic and robust analysis of results across many models, by reducing the influence of ad hoc differences in model set-up or experimental boundary conditions. As it enters its 6th phase, the Coupled Model Intercomparison Project (CMIP6) has grown significantly in scope with the design and documentation of individual simulations delegated to individual climate science communities. The Coupled Climate–Carbon Cycle Model Intercomparison Project (C4MIP) takes responsibility for design, documentation, and analysis of carbon cycle feedbacks and interactions in climate simulations. These feedbacks are potentially large and play a leading-order contribution in determining the atmospheric composition in response to human emissions of CO2 and in the setting of emissions targets to stabilize climate or avoid dangerous climate change. For over a decade, C4MIP has coordinated coupled climate–carbon cycle simulations, and in this paper we describe the C4MIP simulations that will be formally part of CMIP6. While the climate–carbon cycle community has created this experimental design, the simulations also fit within the wider CMIP activity, conform to some common standards including documentation and diagnostic requests, and are designed to complement the CMIP core experiments known as the Diagnostic, Evaluation and Characterization of Klima (DECK). C4MIP has three key strands of scientific motivation and the requested simulations are designed to satisfy their needs: (1) pre-industrial and historical simulations (formally part of the common set of CMIP6 experiments) to enable model evaluation, (2) idealized coupled and partially coupled simulations with 1 % per year increases in CO2 to enable diagnosis of feedback strength and its components, (3) future scenario simulations to project how the Earth system will respond to anthropogenic activity over the 21st century and beyond. This paper documents in detail these simulations, explains their rationale and planned analysis, and describes how to set up and run the simulations. Particular attention is paid to boundary conditions, input data, and requested output diagnostics. It is important that modelling groups participating in C4MIP adhere as closely as possible to this experimental design.
Architecture & Planning• 2016• Copernicus Publications
Periodicals
The cognitive cell: bacterial behavior reconsidered
Research on how bacteria adapt to changing environments underlies the contemporary biological understanding of signal transduction (ST), and ST provides the foundation of the information-processing approach that is the hallmark of the 'cognitive revolution,' which began in the mid-20th century. Yet cognitive scientists largely remain oblivious to research into microbial behavior that might provide insights into problems in their own domains, while microbiologists seem equally unaware of the potential importance of their work to understanding cognitive capacities in multicellular organisms, including vertebrates. Evidence in bacteria for capacities encompassed by the concept of cognition is reviewed. Parallels exist not only at the heuristic level of functional analogue, but also at the level of molecular mechanism, evolution and ecology, which is where fruitful cross-fertilization among disciplines might be found.
Architecture & Planning• 2015• Frontiers Media
Periodicals
Vestibular pathways involved in cognition
Recent discoveries have emphasized the role of the vestibular system in cognitive processes such as memory, spatial navigation and bodily self-consciousness. A precise understanding of the vestibular pathways involved is essential to understand the consequences of vestibular diseases for cognition, as well as develop therapeutic strategies to facilitate recovery. The knowledge of the "vestibular cortical projection areas", defined as the cortical areas activated by vestibular stimulation, has dramatically increased over the last several years from both anatomical and functional points of view. Four major pathways have been hypothesized to transmit vestibular information to the vestibular cortex: (1) the vestibulo-thalamo-cortical pathway, which probably transmits spatial information about the environment via the parietal, entorhinal and perirhinal cortices to the hippocampus and is associated with spatial representation and self-versus object motion distinctions; (2) the pathway from the dorsal tegmental nucleus via the lateral mammillary nucleus, the anterodorsal nucleus of the thalamus to the entorhinal cortex, which transmits information for estimations of head direction; (3) the pathway via the nucleus reticularis pontis oralis, the supramammillary nucleus and the medial septum to the hippocampus, which transmits information supporting hippocampal theta rhythm and memory; and (4) a possible pathway via the cerebellum, and the ventral lateral nucleus of the thalamus (perhaps to the parietal cortex), which transmits information for spatial learning. Finally a new pathway is hypothesized via the basal ganglia, potentially involved in spatial learning and spatial memory. From these pathways, progressively emerges the anatomical network of vestibular cognition.
Architecture & Planning• 2014• Frontiers Media
Periodicals
The role of language in emotion: predictions from psychological constructionism
Common sense suggests that emotions are physical types that have little to do with the words we use to label them. Yet recent psychological constructionist accounts reveal that language is a fundamental element in emotion that is constitutive of both emotion experiences and perceptions. According to the psychological constructionist Conceptual Act Theory (CAT), an instance of emotion occurs when information from one's body or other people's bodies is made meaningful in light of the present situation using concept knowledge about emotion. The CAT suggests that language plays a role in emotion because language supports the conceptual knowledge used to make meaning of sensations from the body and world in a given context. In the present paper, we review evidence from developmental and cognitive science to reveal that language scaffolds concept knowledge in humans, helping humans to acquire abstract concepts such as emotion categories across the lifespan. Critically, language later helps individuals use concepts to make meaning of on-going sensory perceptions. Building on this evidence, we outline predictions from a psychological constructionist model of emotion in which language serves as the "glue" for emotion concept knowledge, binding concepts to embodied experiences and in turn shaping the ongoing processing of sensory information from the body and world to create emotional experiences and perceptions.
Architecture & Planning• 2015• Frontiers Media
Periodicals
Proximal Remote Sensing Buggies and Potential Applications for Field-Based Phenotyping
The achievements made in genomic technology in recent decades are yet to be matched by fast and accurate crop phenotyping methods. Such crop phenotyping methods are required for crop improvement efforts to meet expected demand for food and fibre in the future. This review evaluates the role of proximal remote sensing buggies for field-based phenotyping with a particular focus on the application of currently available sensor technology for large-scale field phenotyping. To illustrate the potential for the development of high throughput phenotyping techniques, a case study is presented with sample data sets obtained from a ground-based proximal remote sensing buggy mounted with the following sensors: LiDAR, RGB camera, thermal infra-red camera and imaging spectroradiometer. The development of such techniques for routine deployment in commercial-scale breeding and pre-breeding operations will require a multidisciplinary approach to leverage the recent technological advances realised in computer science, image analysis, proximal remote sensing and robotics.
Architecture & Planning• 2014• Multidisciplinary Digital Publishing Institute
Periodicals
Transformer Network for Remaining Useful Life Prediction of Lithium-Ion Batteries
Accurately predicting the Remaining Useful Life (RUL) of a Li-ion battery plays an important role in managing the health and estimating the state of a battery. With the rapid development of electric vehicles, there is an increasing need to develop and improve the techniques for predicting RUL. To predict RUL, we designed a Transformer-based neural network. First, battery capacity data is always full of noise, especially during battery charge/discharge regeneration. To alleviate this problem, we applied a Denoising Auto-Encoder (DAE) to process raw data. Then, to capture temporal information and learn useful features, a reconstructed sequence was fed into a Transformer network. Finally, to bridge denoising and prediction tasks, we combined these two tasks into a unified framework. Results of extensive experiments conducted on two data sets and a comparison with some existing methods show that our proposed method performs better in predicting RUL. Our projects are all open source and are available athttps://github.com/XiuzeZhou/RUL.
Architecture & Planning• 2022• Institute of Electrical and Electronics Engineers
Periodicals
Design and Development of a Deep Learning-Based Model for Anomaly Detection in IoT Networks
The growing development of IoT (Internet of Things) devices creates a large attack surface for cybercriminals to conduct potentially more destructive cyberattacks; as a result, the security industry has seen an exponential increase in cyber-attacks. Many of these attacks have effectively accomplished their malicious goals because intruders conduct cyber-attacks using novel and innovative techniques. An anomaly-based IDS (Intrusion Detection System) uses machine learning techniques to detect and classify attacks in IoT networks. In the presence of unpredictable network technologies and various intrusion methods, traditional machine learning techniques appear inefficient. In many research areas, deep learning methods have shown their ability to identify anomalies accurately. Convolutional neural networks are an excellent alternative for anomaly detection and classification due to their ability to automatically categorize main characteristics in input data and their effectiveness in performing faster computations. In this paper, we design and develop a novel anomaly-based intrusion detection model for IoT networks. First, a convolutional neural network model is used to create a multiclass classification model. The proposed model is then implemented using convolutional neural networks in 1D, 2D, and 3D. The proposed convolutional neural network model is validated using the BoT-IoT, IoT Network Intrusion, MQTT-IoT-IDS2020, and IoT-23 intrusion detection datasets. Transfer learning is used to implement binary and multiclass classification using a convolutional neural network multiclass pre-trained model. Our proposed binary and multiclass classification models have achieved high accuracy, precision, recall, and F1 score compared to existing deep learning implementations.
Architecture & Planning• 2021• Institute of Electrical and Electronics Engineers
Periodicals
A Standard Model of the Mind: Toward a Common Computational Framework Across Artificial Intelligence, Cognitive Science, Neuroscience, and Robotics
A standard model captures a community consensus over a coherent region of science, serving as a cumulative reference point for the field that can provide guidance for both research and applications, while also focusing efforts to extend or revise it. Here we propose developing such a model for humanlike minds, computational entities whose structures and processes are substantially similar to those found in human cognition. Our hypothesis is that cognitive architectures provide the appropriate computational abstraction for defining a standard model, although the standard model is not itself such an architecture. The proposed standard model began as an initial consensus at the 2013 AAAI Fall Symposium on Integrated Cognition, but is extended here through a synthesis across three existing cognitive architectures: ACT‐R, Sigma, and Soar. The resulting standard model spans key aspects of structure and processing, memory and content, learning, and perception and motor, and highlights loci of architectural agreement as well as disagreement with the consensus while identifying potential areas of remaining incompleteness. The hope is that this work will provide an important step toward engaging the broader community in further development of the standard model of the mind.
Architecture & Planning• 2017• Association for the Advancement of Artificial Intelligence
Periodicals
Transcriptome profiling revealed multiple genes and ECM-receptor interaction pathways that may be associated with breast cancer
BACKGROUND: Exploration of the genes with abnormal expression during the development of breast cancer is essential to provide a deeper understanding of the mechanisms involved. Transcriptome sequencing and bioinformatics analysis of invasive ductal carcinoma and paracancerous tissues from the same patient were performed to identify the key genes and signaling pathways related to breast cancer development. METHODS: Samples of breast tumor tissue and paracancerous breast tissue were obtained from 6 patients. Sequencing used the Illumina HiSeq platform. All. Only perfectly matched clean reads were mapped to the reference genome database, further analyzed and annotated based on the reference genome information. Differentially expressed genes (DEGs) were identified using the DESeq R package (1.10.1) and DEGSeq R package (1.12.0). Using KOBAS software to execute the KEGG bioinformatics analyses, enriched signaling pathways of DEGs involved in the occurrence of breast cancer were determined. Subsequently, quantitative real time PCR was used to verify the accuracy of the expression profile of key DEGs from the RNA-seq result and to explore the expression patterns of novel cancer-related genes on 8 different clinical individuals. RESULTS: The transcriptomic sequencing results showed 937 DEGs, including 487 upregulated and 450 downregulated genes in the breast cancer specimens. Further quantitative gene expression analysis was performed and captured 252 DEGs (201 downregulated and 51 upregulated) that showed the same differential expression pattern in all libraries. Finally, 6 upregulated DEGs (CST2, DRP2, CLEC5A, SCD, KIAA1211, DTL) and 6 downregulated DEGs (STAC2, BTNL9, CA4, CD300LG, GPIHBP1 and PIGR), were confirmed in a quantitative real time PCR comparison of breast cancer and paracancerous breast tissues from 8 clinical specimens. KEGG analysis revealed various pathway changes, including 20 upregulated and 21 downregulated gene enrichment pathways. The extracellular matrix-receptor (ECM-receptor) interaction pathway was the most enriched pathway: all genes in this pathway were DEGs, including the THBS family, collagen and fibronectin. These DEGs and the ECM-receptor interaction pathway may perform important roles in breast cancer. CONCLUSION: Several potential breast cancer-related genes and pathways were captured, including 7 novel upregulated genes and 76 novel downregulated genes that were not found in other studies. These genes are related to cell proliferation, movement and adhesion. They may be important for research into breast cancer mechanisms, particularly CST2 and CA4. A key signaling pathway, the ECM-receptor interaction signal pathway, was also identified as possibly involved in the development of breast cancer.
Architecture & Planning• 2019• BioMed Central
Periodicals
Perfusion CT: a worthwhile enhancement?
Les tumeurs nasales chez le chien sont relativement rares (1-2%). Ce travail propose d'abord une revue bibliographique exhaustive sur ces tumeurs, en particulier les outils diagnostiques, et les approches thérapeutiques actuelles. Il explore ensuite l'utilisation de la séquence de perfusion au scanner pour le suivi de ces tumeurs, une pratique très peu réalisée en oncologie vétérinaire contrairement à la médecine humaine. Les critères de réponse aux traitements de l’OMS et du RECIST sont difficilement applicables aux tumeurs nasales canines en raison de leur forme irrégulière. Cela souligne le besoin de développer des indicateurs pronostiques plus adaptés. L'angiogenèse tumorale, associée à l'évolution de la tumeur, se révèle pertinente dans ce contexte. Les paramètres de perfusion, tels que le débit et le volume sanguin tumoral, servent de marqueurs pour évaluer la vascularisation tumorale. En oncologie humaine, des valeurs élevées de perfusion avant traitement sont associées à une meilleure réponse à la radiothérapie. Une étude prospective menée sur 8 chiens atteints de tumeurs nasales traités par radiothérapie montre que les sarcomes ont une perfusion initiale plus faible et une réduction de volume tumoral moindre par rapport aux carcinomes. Aucune corrélation significative n’a pu être établie entre le taux de réduction tumorale et la survie, ni entre les paramètres initiaux de perfusion et la survie. Ces résultats confirment les tendances observées dans les études antérieures, tout en soulignant la nécessité de cohortes plus larges pour valider pleinement le rôle des paramètres de perfusion comme indicateurs pronostiques et pour affiner les stratégies thérapeutiques.
Architecture & Planning• 2003• Wiley
Periodicals
A Survey on LiDAR Scanning Mechanisms
In recent years, light detection and ranging (LiDAR) technology has gained huge popularity in various applications such as navigation, robotics, remote sensing, and advanced driving assistance systems (ADAS). This popularity is mainly due to the improvements in LiDAR performance in terms of range detection, accuracy, power consumption, as well as physical features such as dimension and weight. Although a number of literatures on LiDAR technology have been published earlier, not many has been reported on the state-of-the-art LiDAR scanning mechanisms. The aim of this article is to review the scanning mechanisms employed in LiDAR technology from past research works to the current commercial products. The review highlights four commonly used mechanisms in LiDAR systems: Opto-mechanical, electromechanical, micro-electromechanical systems (MEMS), and solid-state scanning. The study reveals that electro-mechanical scanning is the most prominent technology in use today. The commercially available 1D time of flight (TOF) LiDAR instrument is currently the most attractive option for conversion from 1D to 3D LiDAR system, provided that low scanning rate is not an issue. As for applications with low size, weight, and power (SWaP) requirements, MEMS scanning is found to be the better alternative. MEMS scanning is by far the more matured technology compared to solid-state scanning and is currently given great emphasis to increase its robustness for fulfilling the requirements of ADAS applications. Finally, solid-state LiDAR systems are expected to fill in the gap in ADAS applications despite the low technology readiness in comparison to MEMS scanners. However, since solid-state scanning is believed to have superior robustness, field of view (FOV), and scanning rate potential, great efforts are given by both academics and industries to further develop this technology.
Architecture & Planning• 2020• Multidisciplinary Digital Publishing Institute
Periodicals
Hydrogen Fuel Cell Technology for the Sustainable Future of Stationary Applications
The climate changes that are becoming visible today are a challenge for the global research community. The stationary applications sector is one of the most important energy consumers. Harnessing the potential of renewable energy worldwide is currently being considered to find alternatives for obtaining energy by using technologies that offer maximum efficiency and minimum pollution. In this context, new energy generation technologies are needed to both generate low carbon emissions, as well as identifying, planning and implementing the directions for harnessing the potential of renewable energy sources. Hydrogen fuel cell technology represents one of the alternative solutions for future clean energy systems. This article reviews the specific characteristics of hydrogen energy, which recommends it as a clean energy to power stationary applications. The aim of review was to provide an overview of the sustainability elements and the potential of using hydrogen as an alternative energy source for stationary applications, and for identifying the possibilities of increasing the share of hydrogen energy in stationary applications, respectively. As a study method was applied a SWOT analysis, following which a series of strategies that could be adopted in order to increase the degree of use of hydrogen energy as an alternative to the classical energy for stationary applications were recommended. The SWOT analysis conducted in the present study highlights that the implementation of the hydrogen economy depends decisively on the following main factors: legislative framework, energy decision makers, information and interest from the end beneficiaries, potential investors, and existence of specialists in this field.
Architecture & Planning• 2019• Multidisciplinary Digital Publishing Institute
Periodicals
What Have We Learned from Market Design?
This article discusses some things we have learned about markets, in the process of designing marketplaces to fix market failures. To work well, marketplaces have to provide thickness, i.e. they need to attract a large enough proportion of the potential participants in the market; they have to overcome the congestion that thickness can bring, by making it possible to consider enough alternative transactions to arrive at good ones; and they need to make it safe and sufficiently simple to participate in the market, as opposed to transacting outside of the market, or having to engage in costly and risky strategic behaviour. I will draw on recent examples of market design ranging from labour markets for doctors and new economists, to kidney exchange, and school choice in New York City and Boston.
Architecture & Planning• 2008• Oxford University Press
Periodicals
Accounting, hybrids and the management of risk
[no abstract]
Architecture & Planning• 2007• Elsevier BV