- ترتیب محصولات: پیش فرض
A case study in early urban design: Toronto, 1966–۱۹۷۸0 تومان
This is a study in the practice of postwar urban design in Toronto, Canada, based on archival documents and interviews with participants. The narrative begins with the hiring of one British-trained architect/urban designer, Raymond Spaxman, by the City of Toronto Planning Board in 1966. Spaxman then set up a new division of staff that he filled with five or six other architect/urban designers of various national and institutional origins. The study describes the work carried out by these urban designers, identifies the principle themes apparent in it, and relates this to published literature on the founding principles of postwar urban design. In most ways, the study’s findings fit the current understanding of the early discipline – concern for pedestrians, sympathy for historical preservation – but in others not – it was different from but not antagonistic towards planning. The findings are then considered as an example of the international transfer of postwar planning ideas. The process of idea transfer in this case looks to have been more chaotic, and less definable, than existing paradigms suggest, but this might have been fairly common in second-rank, immigrant-receiving cities.
A conceptual framework to assess ecological quality of urban green space: a case study in Mashhad city, Iran0 تومان
This study evaluates the green space ecological quality with regard to its spatial properties. It investigates how the spatial properties of green space patches afect ecological aspects of municipal green spaces of Mashhad in Iran. The importance and necessity of this investigation is to develop a concept to evaluate the quality of urban green patches based on the perspective and method of landscape ecology. In accordance with our objectives, the quality concept is defned by quantitative (size, area, density) and qualitative (shape, complexity, connectivity) factors as referred to spatial confguration and composition of landscape structure. However, to have a better understanding of the quality concept, we explored the relationship between landscape variables and ecological quality by spatial analysis and correlation tests. We (1) drew the urban green space map by images processing, (2) quantifed landscape metrics for the green space patches, (3) analyzed and represented the metric value spatially, (4) calculated ecological quality and drew the grade map, (5) measured the Pearson correlation coefcients and linear regression between ecological quality and each landscape metric. Results of this study provided the evidence to study ecological quality by integrating metrics map and analyzing spatial heterogeneity in Mashhad city. Results showed that the extent and continuity of the green spaces were too low to efectively support some key ecological services. Additionally, the Pearson’s correlation coefcients and linear regression revealed strong relationships between ecological quality and most landscape metrics except LSI. Although it was expected that the qualitative variables of green space had higher infuence on the ecological quality, quantitative variables had the highest efect due to the origin and nature of the green patches.
A hybrid approach, Smart Street use case and future aspects for Internet of Things in smart cities0 تومان
Internet of Things (IoT) has led to the development of smart projects by connecting heterogeneous devices and hasaccelerated the global growth by providing digital services to the users. The Smart City Project is very complex concept and has many hurdles in its way and many of the hurdles (Digitization services) can easily be solved by IoT. Urban IoT, is designed to support the future vision of smart cities which supported the new hybrid technologies and provide the value added services to the citizens. In this Urban IoT framework the first layer is Data Layer. In Data layer, sensor platform uses the ptimized AODV-SPEED protocol (Hybrid Approach), proposed in this paper. Hybrid approach has shown improvement over delay, energy, miss ratio of the packet transmission and packet delivery rate ver traditional SPEED protocol which is suitable for IoT applications. This article also identifies the framework, challengesand trends of Smart city IoT and use case for the smart street highlights the importance of proposed structure. Furthermore, Smart City projects are discussed to recognize the importance of IoT in smart cities and its future.
A machine learning bayesian network for refrigerant charge faults of variable refrigerant flow air conditioning system0 تومان
An intelligent fault diagnosis network for variable refrigerant flow air conditioning system is proposed in this study. The network is developed under the foundation of bayesian belief network theory, which comprises two main elements: the structure and parameters. The structure obtained by machine learning and experts’ experiences illustrates the relationships among faults and physical variables from the qualitative prospective, and its parameters (including prior probability distribution and conditional distribution) describe the uncertainty between them quantitatively. Once the structure and parameters are determined, the posterior probability distribution which can be used to complete fault diagnosis and isolation will be calculated by some algorithms. In comparison with other fault diagnosis approaches, the proposed approach can make full use of performance information. Moreover, it is more reasonable and precise to express the relationship between faults and variables rather than Boolean variables. Evaluation was conducted on a variable refrigerant flow air conditioning system, which demonstrated that this strategy is effective and efficient.
A Novel Autonomous Taxi Model for Smart Cities0 تومان
Autonomous taxies are in high demand for smart city scenario. Such taxies have a well specified path to travel. Therefore, these vehicles only required two important parameters. One is detection parameter and other is control parameter. Further, detection parameters require turn detection and obstacle detection. The control parameters contain steering control and speed control. In this paper a novel autonomous taxi model has been proposed for smart city scenario. Deep learning has been used to model the human driver capabilities for the autonomous taxi. A hierarchical Deep Neural Network (DNN) architecture has been utilized to train various driving aspects. In first level, the proposed DNN architecture classifies the straight and turning of road. A parallel DNN is used to detect obstacle at level one. In second level, the DNN discriminates the turning i.e. left or right for steering and speed controls. Two multi layered DNNs have been used on Nvidia Tesla K 40 GPU based system with Core i-7 processor. The mean squared error (MSE) for the detection parameters viz. speed and steering angle were 0.018 and 0.0248 percent, respectively, with 15 milli seconds of realtime response delay.
A novel big data analytics framework for smart cities0 تومان
The emergence of smart cities aims at mitigating the challenges raised due to the continuous urbanization development and increasing population density in cities. To face these challenges, governments and decision makers undertake smart city projects targeting sustainable economic growth and better quality of life for both inhabitants and visitors. Information and Communication Technology (ICT) is a key enabling technology for city smartening. However, ICT artifacts and applications yield massive volumes of data known as big data. Extracting insights and hidden correlations from big data is a growing trend in information systems to provide better services to citizens and support the decision making processes. However, to extract valuable insights for developing city level smart information services, the generated datasets from various city domains need to be integrated and analyzed. This process usually referred to as big data analytics or big data value chain. Surveying the literature reveals an increasing interest in harnessing big data analytics applications in general and in the area of smart cities in particular. Yet, comprehensive discussions on the essential characteristics of big data analytics frameworks fitting smart cities requirements are still needed. This paper presents a novel big data analytics framework for smart cities called “Smart City Data Analytics Panel – SCDAP”. The design of SCDAP is based on answering the following research questions: what are the characteristics of big data analytics frameworks applied in smart cities in literature and what are the essential design principles that should guide the design of big data analytics frameworks have to serve smart cities purposes? In answering these questions, we adopted a systematic literature review on big data analytics frameworks in smart cities. The proposed framework introduces new functionalities to big data analytics frameworks represented in data model management and aggregation. The value of the proposed framework is discussed in comparison to traditional knowledge discovery approaches.
A novel ensemble method for k-nearest neighbor0 تومان
In this paper, to address the issue that ensembling k-nearest neighbor (kNN) classifiers with resampling approaches cannot generate component classifiers with a large diversity, we consider ensembling kNN through a multimodal perturbation-based method. Since kNN is sensitive to the input attributes, we propose a weighted heterogeneous distance Metric (WHDM). By using a WHDM and evidence theory, a progressive kNN classifier is developed. Based on a progressive kNN, the random subspace method, attribute reduction, and Bagging, a novelalgorithm termed RRSB (reduced random subspace-based Bagging) is proposed for construct ensemble classifier, which can increase the diversity of component classifiers without damagingthe accuracy of the component classifiers. In detail, RRSB adopts the perturbation on the learning parameter with a weighted heterogeneous distance metric, the perturbation on the input space with random subspace and attribute reduction, the perturbation on the training data with Bagging, and the perturbation on the output target of k neighbors with evidence theory. In the experimental stage, the value of k, the different perturbations on RRSB and the ensemble size are analyzed. In addition, RRSB is compared with other multimodal perturbation-based ensemble algorithms on multiple UCI data sets and a KDD data set. The results from the experiments demonstrate the effectiveness of RRSB for kNN ensembling.
A scientometric review of global research on sustainability and sustainable development0 تومان
The concept of sustainable development has gained worldwide attention in recent years which had enhanced its implementation. However, few studies have attempted to map the global research of sustainability. This study utilizes scientometric review of global trend and structure of sustainability research in 1991e2016 using techniques such as co-author, co-word, co-citation, clusters, and geospatial analyses. A total of 2094 bibliographic records from the Web of Science database were analyzed to generate the study’s research power networks and geospatial map. The findings reveal an evolution of the research field from the definition of its concepts in the Brundtland Commission report to the recent development of models and sustainability indicators. The most significant contributions in sustainability research have originated primarily from the United States, China, United Kingdom and Canada. Also, existing studies in sustainability research focus mainly on subject categories of environmental sciences, green & sustainable science technology, civil engineering, and construction & building technology. Emerging trends in sustainability research were sustainable urban development, sustainability indicators, water management, environmental assessment, public policy, etc.; while the study generated 21 co-citation clusters. This study provides its readers with an extensive understanding of the salient research themes, trends and pattern of sustainability research worldwide.
Accountability in urban regeneration partnerships: A role for design centers0 تومان
Partnerships in urban development reflect the ‘wicked’ nature of regeneration efforts, often requiring attention to a range of investment and programmatic interdependencies. “Taxpayer revolts, tax and expenditure limits, cutbacks in federal grants, a deep recession, and the pervasive pall of public opprobrium for things governmental”, to quote Peterson (1985, p. 34), are some of the challenges that have reinforced this trend. To this end, partnerships have achieved what Hodge and Greve (2007) describe as an ‘iconic status’ in urban administration. Partnerships in the context of the ‘entrepreneurial city’ have been associated with the delivery of large scale schemes, often involving significant attention to the civic design. Investments in waterfronts, streetscapes, and public plazas are some examples. As Goldstein and Mele (2016) have however recently pointed out, a large literature on partnerships focuses on questions of motivations and outcomes, while the ‘inner workings’ of hese arrangements are yet to be fully explored. This paper contributes to this scholarship by highlighting the utility of
analytic constructs derived from a broader literature on governance, most notably so from the field of public administration. In that literature, the study of approaches to task delegation and performance monitoring defines a research agenda on the relations between principals and their agents, and is particularly insightful of how the question of accountability should be approached in the design of regeneration partnerships. In a study of the redevelopment of the waterfront at ‘Canalside’ and a former industrial district at ‘Larkinville’ in Buffalo (NY), this paper argues that structuring a role for design centers reinforces social accountability in regeneration partnerships with an emphasis on civic design The next section presents an overview of partnerships and the question of accountability
An evaluation of participatory mapping methods to assess urban park benefits0 تومان
Traditional urban park research has used self-reported surveys and activity logs to examine relationships between health benefits, park use, and park features. An alternative approach uses participating mapping methods. This study sought to validate and expand on previous participatory mapping research methods and findings and address spatial scaling by applying these methods to a large urban park system. Key challenges for spatial scaling included ambiguity in park classification and achieving representative sampling for larger and spatially-disbursed urban residents. We designed an internet-based public participation GIS (PPGIS) survey and used household and volunteer sampling to identify the type and locations of urban park benefits. Study participants(n = 816) identified locations of physical activities and other urban park benefits (psychological, social, and environmental) which were analyzed by park type. Consistent with previous suburb-scale research, we found significant ssociations between urban park type and different urban park benefits. Linear parks were significantly associated with higher intensity physical activities; natural parks were associated with environmental benefits; and community parks were associated with benefits from social interaction. Neighborhood parks emerged as significantly associated with psychological benefits. The diversity of park activities and benefits were positively correlated with park size. Distance analysis confirmed that physical benefits of parks were closest toparticipant domicile, while social and environmental benefits were more distant. These results validate previous suburb-scale findings despite greater variability in park types and sample populations. Future urban park research using participatory mapping would benefit from greater effort to obtain participation from under-represented populations that can induce nonresponse bias, and analyses to determine whether system-wide results can be disaggregated by suburb or neighborhood to address social inequities in urban park benefits.
An intelligent decision computing paradigm for crowd monitoring in the smart city0 تومان
The ever-expanding urbanization and the advent of smart cities need better crowd management and security surveillance systems. Advanced systems are required to improve and automate the crowd management system. The aim of the closed circuit television and visual monitoring systems using multiple cameras faces many challenges like illumination variance, occlusion and small spatial-temporal resolution, person in sleep, shadows, dynamic backgrounds, and noises. Therefore, the crowd monitoring, prevention of stampedes and crowd-related emergencies in the smart cities are major challenging problems. In this paper, we propose an intelligent decision computing based paradigm for crowd monitoring in the smart city. In the intelligent computing based framework, the optimization algorithm is applied to compute the feature of crowd motion and measure the correlation between agents based motion model and the crowd data using extended Kalman filtering approach and KL-divergence technique. The proposed framework measures the correlation measure based on extracted novel distinctive feature, and holistic feature of crowd data represent and to classify the crowd motion of individual. Our experimental results demonstrate that the proposed approach yields 96.20% average precision in classifying real-world highly dense crowd scenes.
Blockchain based hybrid network architecture for the smart city0 تومان
Recently, the concept of “Smart Cities” has developed considerably with the rise and development of the Internet of Things as new form of sustainable development. Smart cities are based on autonomous and distributed infrastructure that includes intelligent information processing and control systems, heterogeneous network infrastructure, and ubiquitous sensing involving millions of information sources. Due to the continued growth of data volume and number of connected IoT devices, however, issues such as high latency, bandwidth bottlenecks, security and privacy, and scalability arise in the current smart city network architecture. Designing an efficient, secure, and scalable distributed architecture by bringing computational and storage resources closer to endpoints is needed to address the limitations of today’s smart city network. In this paper, we propose a novel hybrid network architecture for the smart city by leveraging the strength of emerging Software Defined Networking and lockchain technologies. To achieve efficiency and address the current limitations, our architecture is divided into two parts: core network and edge network. Through the design of a hybrid architecture, our proposed architecture inherits the strength of both centralized and distributed network architectures. We also propose a Proof-of-Work scheme in our model to ensure security and privacy. To evaluate the feasibility and performance of our proposed model, we simulate our model and evaluate it based on various performance metrics. The result of the evaluation shows the effectiveness of our proposed model.
Boundaries as an Enhancement Technique for Physical Layer Security0 تومان
In this paper, we study the receiver performance with physical layer security in a Poisson field of interferers. We compare the performance in two deployment scenarios: (i) the receiver is located at the corner of a quadrant, (ii) the receiver is located in the infinite plane. When the channel state information (CSI) of the eavesdropper is not available at the transmitter, we calculate the probability of secure connectivity using the Wyner coding scheme, and we show that hiding the receiver at the corner is beneficial at high rates of the transmitted codewords and detrimental at low transmission rates. When the CSI is available, we show that the average secrecy capacity is higher when thereceiver is located at the corner, even if the intensity of interferers in this case is four times higher than the intensity of interferers in the bulk. Therefore boundaries can also be used as a secrecy enhancement technique for high data rate applications.
Citizen Design Science: A strategy for crowd-creative urban design0 تومان
The last decades in urban design research are characterised by a focus on technological aspects of cities which is commonly known as the smart city strategy. The concerns and interests of citizens are coming to the forefront nowadays with the awareness that a liveable city does not only consist of good infrastructure and sustainable energy supply but also citizen input and feedback. In this paper, we present Citizen Design Science as a new strategy for cities to integrate citizens’ ideas and wishes in the urban planning process. The approach is to combine the opportunity of crowdsourcing opinions and thoughts by citizens through modern information and communication technology (ICT) with active design tools. The active design feedback from a city’s inhabitants is identified as a yet missing but essential way towards a responsive city. We therefore propose a system to merge Citizen Science and Citizen Design, which requires a structured evaluation process to integrate Design Science methods for urban design. We show examples of existing approaches of Citizen Design Science and present the Quick Urban Analysis Kit (qua-kit) as an application of this methodology. The toolkit allows users to move geometries in given environments and provides the opportunity for non-experts to express their ideas for their neighbourhood or city.