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.

ACTIVE FILTERS:Dept: Architecture & Planning Clear All

Results 1,238

in Architecture & Planning
Periodicals

Exosomal DMBT1 from human urine-derived stem cells facilitates diabetic wound repair by promoting angiogenesis

Chronic non-healing wounds represent one of the most common complications of diabetes and need advanced treatment strategies. Exosomes are key mediators of cell paracrine action and can be directly utilized as therapeutic agents for tissue repair and regeneration. Here, we explored the effects of exosomes from human urine-derived stem cells (USC-Exos) on diabetic wound healing and the underlying mechanism. Methods: USCs were characterized by flow cytometry and multipotent differentiation potential analyses. USC-Exos were isolated from the conditioned media of USCs and identified by transmission electron microscopy and flow cytometry. A series of functional assays in vitro were performed to assess the effects of USC-Exos on the activities of wound healing-related cells. Protein profiles in USC-Exos and USCs were examined to screen the candidate molecules that mediate USC-Exos function. The effects of USC-Exos on wound healing in streptozotocin-induced diabetic mice were tested by measuring wound closure rates, histological and immunofluorescence analyses. Meanwhile, the role of the candidate protein in USC-Exos-induced regulation of angiogenic activities of endothelial cells and diabetic wound healing was assessed. Results: USCs were positive for CD29, CD44, CD73 and CD90, but negative for CD34 and CD45. USCs were able to differentiate into osteoblasts, adipocytes and chondrocytes. USC-Exos exhibited a cup-or sphere-shaped morphology with a mean diameter of 51.57 2.93 nm and positive for CD63 and TSG101. USC-Exos could augment the functional properties of wound healing-related cells including the angiogenic activities of endothelial cells. USC-Exos were enriched in the proteins that are involved in regulation of wound healing-related biological processes. Particularly, a pro-angiogenic protein called deleted in malignant brain tumors 1 (DMBT1) was highly expressed in USC-Exos. Further functional assays showed that DMBT1 protein was required for USC-Exos-induced promotion of angiogenic responses of cultured endothelial cells, as well as angiogenesis and wound healing in diabetic mice. Conclusion: Our findings suggest that USC-Exos may represent a promising strategy for diabetic soft tissue wound healing by promoting angiogenesis via transferring DMBT1 protein.

Architecture & Planning• 2018• Ivyspring International Publisher
Access Full TextView Details
Periodicals

Performance Analysis of IoT-Based Sensor, Big Data Processing, and Machine Learning Model for Real-Time Monitoring System in Automotive Manufacturing

With the increase in the amount of data captured during the manufacturing process, monitoring systems are becoming important factors in decision making for management. Current technologies such as Internet of Things (IoT)-based sensors can be considered a solution to provide efficient monitoring of the manufacturing process. In this study, a real-time monitoring system that utilizes IoT-based sensors, big data processing, and a hybrid prediction model is proposed. Firstly, an IoT-based sensor that collects temperature, humidity, accelerometer, and gyroscope data was developed. The characteristics of IoT-generated sensor data from the manufacturing process are: real-time, large amounts, and unstructured type. The proposed big data processing platform utilizes Apache Kafka as a message queue, Apache Storm as a real-time processing engine and MongoDB to store the sensor data from the manufacturing process. Secondly, for the proposed hybrid prediction model, Density-Based Spatial Clustering of Applications with Noise (DBSCAN)-based outlier detection and Random Forest classification were used to remove outlier sensor data and provide fault detection during the manufacturing process, respectively. The proposed model was evaluated and tested at an automotive manufacturing assembly line in Korea. The results showed that IoT-based sensors and the proposed big data processing system are sufficiently efficient to monitor the manufacturing process. Furthermore, the proposed hybrid prediction model has better fault prediction accuracy than other models given the sensor data as input. The proposed system is expected to support management by improving decision-making and will help prevent unexpected losses caused by faults during the manufacturing process.

Architecture & Planning• 2018• Multidisciplinary Digital Publishing Institute
Access Full TextView Details
Periodicals

The potential for tourism and hospitality experience research in human-robot interactions

Purpose The purpose of this study is to review recent work in the robotics literature and identify future opportunities for consumer/tourist experience research in human-robot interactions (HRIs). Design/methodology/approach The paper begins by covering the framework of robotic agent presence and embodiment that are relevant for HRI. Next, the paper identifies future opportunities for hospitality and tourism scholars to undertake consumer/tourist experience research in HRIs. Findings The result of this study provided potential directions for advancing theoretical, methodological and managerial implications for tourism experience research in HRI. Research limitations/implications Concepts from robotics research are diffusing into a range of disciplines, from engineering to social sciences. These advancements open many unique, yet urgent, opportunities for hospitality and tourism research. Practical implications This paper illustrates the speed at which robotics research is progressing. Moreover, the concepts reviewed in this research on robotic presence and embodiment are relevant for real-world applications in hospitality and tourism. Social implications Developments in robotics research will transform hospitality and tourism experiences in the future. Originality/value This research is one of the early papers in the field to review robotics research and provide innovative directions to broaden the interdisciplinary perspective for future hospitality and tourism research.

Architecture & Planning• 2017• Emerald Publishing Limited
Access Full TextView Details
Periodicals

ChatGPT as an Educational Tool: Opportunities, Challenges, and Recommendations for Communication, Business Writing, and Composition Courses

This empirical study examines ChatGPT as an educational and learning tool. It investigates the opportunities and chal-lenges that ChatGPT provides to the students and instruc-tors of communication, business writing, and composition courses. It also strives to provide recommendations. After conducting 30 theory-based and application-based ChatGPT tests, it is found that ChatGPT has the potential of replacing search engines as it provides accurate and relia-ble input to students. For opportunities, the study found that ChatGPT provides a platform for students to seek an-swers to theory-based questions and generate ideas for ap-plication-based questions. It also provides a platform for in-structors to integrate technology in classrooms and conduct workshops to discuss and evaluate generated responses. For challenges, the study found that ChatGPT, if unethically used by students, may lead to human unintelligence and un-learning. This may also present a challenge to instructors as the use of ChatGPT negatively affects their ability to dif-ferentiate between meticulous and automaton-dependent students, on the one hand, and measure the achievement of learning outcomes, on the other hand. Based on the out-come of the analysis, this study recommends communica-tion, business writing, and composition instructors to (1) re-frain from making theory-based questions as take-home as-sessments, (2) provide communication and business writing students with detailed case-based and scenario-based as-sessment tasks that call for personalized answers utilizing critical, creative, and imaginative thinking incorporating lec-tures and textbook material, (3) enforce submitting all take-home assessments on plagiarism detection software, espe-cially for composition courses, and (4) integrate ChatGPT generated responses in classes as examples to be discussed in workshops. Remarkably, this study found that ChatGPT skillfully paraphrases regenerated responses in a way that is not detected by similarity detection software. To maintain their effectiveness, similarity detection software providers need to upgrade their software to avoid such incidents from slipping unnoticed.

Architecture & Planning• 2023
Access Full TextView Details
Periodicals

Submergence and Waterlogging Stress in Plants: A Review Highlighting Research Opportunities and Understudied Aspects

Soil flooding creates composite and complex stress in plants known as either submergence or waterlogging stress depending on the depth of the water table. In nature, these stresses are important factors dictating the species composition of the ecosystem. On agricultural land, they cause economic damage associated with long-term social consequences. The understanding of the plant molecular responses to these two stresses has benefited from research studying individual components of the stress, in particular low-oxygen stress. To a lesser extent, other associated stresses and plant responses have been incorporated into the molecular framework, such as ion and ROS signaling, pathogen susceptibility, and organ-specific expression and development. In this review, we aim to highlight known or suspected components of submergence/waterlogging stress that have not yet been thoroughly studied at the molecular level in this context, such as miRNA and retrotransposon expression, the influence of light/dark cycles, protein isoforms, root architecture, sugar sensing and signaling, post-stress molecular events, heavy-metal and salinity stress, and mRNA dynamics (splicing, sequestering, and ribosome loading). Finally, we explore biotechnological strategies that have applied this molecular knowledge to develop cultivars resistant to flooding or to offer alternative uses of flooding-prone soils, like bioethanol and biomass production.

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

Strategic Planning Research: Toward a Theory-Driven Agenda

This review incorporates strategic planning research conducted over more than 30 years and ranges from the classical model of strategic planning to recent empirical work on intermediate outcomes, such as the reduction of managers’ position bias and the coordination of subunit activity. Prior reviews have not had the benefit of more socialized perspectives that developed in response to Mintzberg’s critique of planning, including research on planned emergence and strategy-as-practice approaches. To stimulate a resurgence of research interest on strategic planning, this review therefore draws on a diverse body of theory beyond the rational design and contingency approaches that characterized research in this domain until the mid-1990s. We develop a broad conceptualization of strategic planning and identify future research opportunities for improving our understanding of how strategic planning influences organizational outcomes. Our framework incorporates the role of strategic planning practitioners; the underlying routines, norms, and procedures of strategic planning (practices); and the concrete activities of planners (praxis).

Architecture & Planning• 2013• SAGE Publishing
Access Full TextView Details
Periodicals

An Overview of IoT Sensor Data Processing, Fusion, and Analysis Techniques

In the recent era of the Internet of Things, the dominant role of sensors and the Internet provides a solution to a wide variety of real-life problems. Such applications include smart city, smart healthcare systems, smart building, smart transport and smart environment. However, the real-time IoT sensor data include several challenges, such as a deluge of unclean sensor data and a high resource-consumption cost. As such, this paper addresses how to process IoT sensor data, fusion with other data sources, and analyses to produce knowledgeable insight into hidden data patterns for rapid decision-making. This paper addresses the data processing techniques such as data denoising, data outlier detection, missing data imputation and data aggregation. Further, it elaborates on the necessity of data fusion and various data fusion methods such as direct fusion, associated feature extraction, and identity declaration data fusion. This paper also aims to address data analysis integration with emerging technologies, such as cloud computing, fog computing and edge computing, towards various challenges in IoT sensor network and sensor data analysis. In summary, this paper is the first of its kind to present a complete overview of IoT sensor data processing, fusion and analysis techniques.

Architecture & Planning• 2020• Multidisciplinary Digital Publishing Institute
Access Full TextView Details
Periodicals

Non-Terrestrial Networks in 5G & Beyond: A Survey

Fifth-generation (5G) telecommunication systems are expected to meet the world market demands of accessing and delivering services anywhere and anytime. The Non-Terrestrial Network (NTN) systems are able to satisfy the requests of anywhere and anytime connections by offering wide-area coverage and ensuring service availability, continuity, and scalability. In this work, we review the 3GPP NTN features and their potential for satisfying the user expectations in 5G & beyond networks. The state of the art, current 3GPP research activities, and open issues are summarized to highlight the importance of NTN over the wireless communication landscape. Future research directions are also identified to assess the role of NTN in 5G and beyond systems.

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

Slums from Space—15 Years of Slum Mapping Using Remote Sensing

The body of scientific literature on slum mapping employing remote sensing methods has increased since the availability of more very-high-resolution (VHR) sensors. This improves the ability to produce information for pro-poor policy development and to build methods capable of supporting systematic global slum monitoring required for international policy development such as the Sustainable Development Goals. This review provides an overview of slum mapping-related remote sensing publications over the period of 2000–2015 regarding four dimensions: contextual factors, physical slum characteristics, data and requirements, and slum extraction methods. The review has shown the following results. First, our contextual knowledge on the diversity of slums across the globe is limited, and slum dynamics are not well captured. Second, a more systematic exploration of physical slum characteristics is required for the development of robust image-based proxies. Third, although the latest commercial sensor technologies provide image data of less than 0.5 m spatial resolution, thereby improving object recognition in slums, the complex and diverse morphology of slums makes extraction through standard methods difficult. Fourth, successful approaches show diversity in terms of extracted information levels (area or object based), implemented indicator sets (single or large sets) and methods employed (e.g., object-based image analysis (OBIA) or machine learning). In the context of a global slum inventory, texture-based methods show good robustness across cities and imagery. Machine-learning algorithms have the highest reported accuracies and allow working with large indicator sets in a computationally efficient manner, while the upscaling of pixel-level information requires further research. For local slum mapping, OBIA approaches show good capabilities of extracting both area- and object-based information. Ultimately, establishing a more systematic relationship between higher-level image elements and slum characteristics is essential to train algorithms able to analyze variations in slum morphologies to facilitate global slum monitoring.

Architecture & Planning• 2016• Multidisciplinary Digital Publishing Institute
Access Full TextView Details
Periodicals

Learning as immersive experiences: Using the four‐dimensional framework for designing and evaluating immersive learning experiences in a virtual world

Abstract Traditional approaches to learning have often focused upon knowledge transfer strategies that have centred on textually‐based engagements with learners, and dialogic methods of interaction with tutors. The use of virtual worlds, with text‐based, voice‐based and a feeling of ‘presence’ naturally is allowing for more complex social interactions and designed learning experiences and role plays, as well as encouraging learner empowerment through increased interactivity. To unpick these complex social interactions and more interactive designed experiences, this paper considers the use of virtual worlds in relation to structured learning activities for college and lifelong learners. This consideration necessarily has implications upon learning theories adopted and practices taken up, with real implications for tutors and learners alike. Alongside this is the notion of learning as an ongoing set of processes mediated via social interactions and experiential learning circumstances within designed virtual and hybrid spaces. This implies the need for new methodologies for evaluating the efficacy, benefits and challenges of learning in these new ways. Towards this aim, this paper proposes an evaluation methodology for supporting the development of specified learning activities in virtual worlds, based upon inductive methods and augmented by the four‐dimensional framework reported in a previous study. The study undertaken aimed to test the efficacy of the proposed evaluation methodology and framework, and to evaluate the broader uses of a virtual world for supporting lifelong learners specifically in their educational choices and career decisions. The paper presents the findings of the study and considers that virtual worlds are reorganising significantly how we relate to the design and delivery of learning. This is opening up a transition in learning predicated upon the notion of learning design through the lens of ‘immersive learning experiences’ rather than sets of knowledge to be transferred between tutor and learner. The challenges that remain for tutors rest with the design and delivery of these activities and experiences. The approach advocated here builds upon an incremental testing and evaluation of virtual world learning experiences.

Architecture & Planning• 2009• Wiley
Access Full TextView Details
Periodicals

Cloud-Assisted IoT-Based SCADA Systems Security: A Review of the State of the Art and Future Challenges

Industrial systems always prefer to reduce their operational expenses. To support such reductions, they need solutions that are capable of providing stability, fault tolerance, and flexibility. One such solution for industrial systems is cyber physical system (CPS) integration with the Internet of Things (IoT) utilizing cloud computing services. These CPSs can be considered as smart industrial systems, with their most prevalent applications in smart transportation, smart grids, smart medical and eHealthcare systems, and many more. These industrial CPSs mostly utilize supervisory control and data acquisition (SCADA) systems to control and monitor their critical infrastructure (CI). For example, WebSCADA is an application used for smart medical technologies, making improved patient monitoring and more timely decisions possible. The focus of the study presented in this paper is to highlight the security challenges that the industrial SCADA systems face in an IoT-cloud environment. Classical SCADA systems are already lacking in proper security measures; however, with the integration of complex new architectures for the future Internet based on the concepts of IoT, cloud computing, mobile wireless sensor networks, and so on, there are large issues at stakes in the security and deployment of these classical systems. Therefore, the integration of these future Internet concepts needs more research effort. This paper, along with highlighting the security challenges of these CI's, also provides the existing best practices and recommendations for improving and maintaining security. Finally, this paper briefly describes future research directions to secure these critical CPSs and help the research community in identifying the research gaps in this regard.

Architecture & Planning• 2016• Institute of Electrical and Electronics Engineers
Access Full TextView Details
Periodicals

Boundary Work among Groups, Occupations, and Organizations: From Cartography to Process

This article reviews scholarship dealing with the notion of “boundary work,” defined as purposeful individual and collective effort to influence the social, symbolic, material, or temporal boundaries, demarcations; and distinctions affecting groups, occupations, and organizations. We identify and explore the implications of three conceptually distinct but interrelated forms of boundary work emerging from the literature. Competitive boundary work involves mobilizing boundaries to establish some kind of advantage over others. In contrast, collaborative boundary work is concerned with aligning boundaries to enable collaboration. Finally, configurational boundary work involves manipulating patterns of differentiation and integration among groups to ensure that certain activities are brought together, whereas others are kept apart, orienting the domains of competition and collaboration. We argue that the notion of boundary work can contribute to the development of a uniquely processual view of organizational design as open-ended, and continually becoming, an orientation with significant future potential for understanding novel forms of organizing, and for integrating agency, power dynamics, materiality, and temporality into the study of organizing.

Architecture & Planning• 2019• Routledge
Access Full TextView Details
Periodicals

Bibliometric Analysis on Smart Cities Research

Smart cities have been a global concern in recent years, involving comprehensive scientific research. To obtain a structural overview and assist researchers in making insights into the characteristics of smart cities research, bibliometric analysis was carried out in this paper. With the application of the bibliometric analysis software VOSviewer and CiteSpace, 4409 smart cities were identified by the core collection of the Web of Science in publications between 1998 and 2019 and used in the analysis of this paper. Concretely, this research visually demonstrates a comprehensive overview of the field relating to smart cities in terms of the production of regular publications, main domain of smart cities researchers, most influential countries (institutions, sources and authors), and interesting research directions in the smart city researches. We also present the research collaboration among countries (regions), organizations and authors based on a series of cooperation analyses. The bibliometric analysis of the existing work provided a valuable and seminal reference for researchers and practitioners in smart cities-related research communities.

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

Interference Management for Cellular-Connected UAVs: A Deep Reinforcement Learning Approach

In this paper, an interference-aware path planning scheme for a network of cellular-connected unmanned aerial vehicles (UAVs) is proposed. In particular, each UAV aims at achieving a tradeoff between maximizing energy efficiency and minimizing both wireless latency and the interference caused on the ground network along its path. The problem is cast as a dynamic game among UAVs. To solve this game, a deep reinforcement learning algorithm, based on echo state network (ESN) cells, is proposed. The introduced deep ESN architecture is trained to allow each UAV to map each observation of the network state to an action, with the goal of minimizing a sequence of time-dependent utility functions. Each UAV uses the ESN to learn its optimal path, transmission power, and cell association vector at different locations along its path. The proposed algorithm is shown to reach a subgame perfect Nash equilibrium upon convergence. Moreover, an upper bound and a lower bound for the altitude of the UAVs are derived thus reducing the computational complexity of the proposed algorithm. The simulation results show that the proposed scheme achieves better wireless latency per UAV and rate per ground user (UE) while requiring a number of steps that are comparable to a heuristic baseline that considers moving via the shortest distance toward the corresponding destinations. The results also show that the optimal altitude of the UAVs varies based on the ground network density and the UE data rate requirements and plays a vital role in minimizing the interference level on the ground UEs as well as the wireless transmission delay of the UAV.

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

The neuromodulator of exploration: A unifying theory of the role of dopamine in personality

The neuromodulator dopamine is centrally involved in reward, approach behavior, exploration, and various aspects of cognition. Variations in dopaminergic function appear to be associated with variations in personality, but exactly which traits are influenced by dopamine remains an open question. This paper proposes a theory of the role of dopamine in personality that organizes and explains the diversity of findings, utilizing the division of the dopaminergic system into value coding and salience coding neurons (Bromberg-Martin et al., 2010). The value coding system is proposed to be related primarily to Extraversion and the salience coding system to Openness/Intellect. Global levels of dopamine influence the higher order personality factor, Plasticity, which comprises the shared variance of Extraversion and Openness/Intellect. All other traits related to dopamine are linked to Plasticity or its subtraits. The general function of dopamine is to promote exploration, by facilitating engagement with cues of specific reward (value) and cues of the reward value of information (salience). This theory constitutes an extension of the entropy model of uncertainty (EMU; Hirsh et al., 2012), enabling EMU to account for the fact that uncertainty is an innate incentive reward as well as an innate threat. The theory accounts for the association of dopamine with traits ranging from sensation and novelty seeking, to impulsivity and aggression, to achievement striving, creativity, and cognitive abilities, to the overinclusive thinking characteristic of schizotypy.

Architecture & Planning• 2013• Frontiers Media
Access Full TextView Details
Periodicals

The work of economics: how a discipline makes its world

What is the work of economics? How does it operate to establish facts and make them stable? Is it sometimes able to use the world as a laboratory? If so, what measures are necessary to organize the world as a laboratory for economic experiments? To what extent do these measures rely upon the efforts of nonacademic economists, and of other social agents and arrangements including think tanks, government policies, development programs, NGOs, and social movements? A recent “natural experiment” using the social world as a laboratory, carried out in Peru, produced remarkable results, enthusiastically received by economists in the United States and by international development agencies. The paper examines the work of organizing the socio-technical world required to produce this knowledge, the curious kind of facts that were produced, the connections among those involved in this work, in particular the organized work of the neoliberal movement, and the role of the new facts in making possible further efforts at economic experimentation.

Architecture & Planning• 2005• Cambridge University Press
Access Full TextView Details
Periodicals

A new stratospheric and tropospheric NO <sub>2</sub> retrieval algorithm for nadir-viewing satellite instruments: applications to OMI

Abstract. We describe a new algorithm for the retrieval of nitrogen dioxide (NO2) vertical columns from nadir-viewing satellite instruments. This algorithm (SP2) is the basis for the Version 2.1 OMI This algorithm (SP2) is the basis for the Version 2.1 Ozone Monitoring Instrument (OMI) NO2 Standard Product and features a novel method for separating the stratospheric and tropospheric columns. NO2 Standard Product and features a novel method for separating the stratospheric and tropospheric columns. The approach estimates the stratospheric NO2 directly from satellite data without using stratospheric chemical transport models or assuming any global zonal wave pattern. Tropospheric NO2 columns are retrieved using air mass factors derived from high-resolution radiative transfer calculations and a monthly climatology of NO2 profile shapes. We also present details of how uncertainties in the retrieved columns are estimated. The sensitivity of the retrieval to assumptions made in the stratosphere–troposphere separation is discussed and shown to be small, in an absolute sense, for most regions. We compare daily and monthly mean global OMI NO2 retrievals using the SP2 algorithm with those of the original Version 1 Standard Product (SP1) and the Dutch DOMINO product. The SP2 retrievals yield significantly smaller summertime tropospheric columns than SP1, particularly in polluted regions, and are more consistent with validation studies. SP2 retrievals are also relatively free of modeling artifacts and negative tropospheric NO2 values. In a reanalysis of an INTEX-B validation study, we show that SP2 largely eliminates an ~20% discrepancy that existed between OMI and independent in situ springtime NO2 SP1 measurements.

Architecture & Planning• 2013• Copernicus Publications
Access Full TextView Details
Periodicals

mHealth 2.0: Experiences, Possibilities, and Perspectives

With more than 1 billion users having access to mobile broadband Internet and a rapidly growing mobile app market, all stakeholders involved have high hopes that this technology may improve health care. Expectations range from overcoming structural barriers to access in low-income countries to more effective, interactive treatment of chronic conditions. Before medical health practice supported by mobile devices ("mHealth") can scale up, a number of challenges need to be adequately addressed. From a psychological perspective, high attrition rates, digital divide of society, and intellectual capabilities of the users are key issues when implementing such technologies. Furthermore, apps addressing behavior change often lack a comprehensive concept, which is essential for an ongoing impact. From a clinical point of view, there is insufficient evidence to allow scaling up of mHealth interventions. In addition, new concepts are required to assess the efficacy and efficiency of interventions. Regarding technology interoperability, open standards and low-energy wireless protocols appear to be vital for successful implementation. There is an ongoing discussion in how far health care-related apps require a conformity assessment and how to best communicate quality standards to consumers. "Apps Peer-Review" and standard reporting via an "App synopsis" appear to be promising approaches to increase transparency for end users. With respect to development, more emphasis must be placed on context analysis to identify what generic functions of mobile information technology best meet the needs of stakeholders involved. Hence, interdisciplinary alliances and collaborative strategies are vital to achieve sustainable growth for "mHealth 2.0," the next generation mobile technology to support patient care.

Architecture & Planning• 2014• JMIR Publications
Access Full TextView Details
Previous123456...52Next