۶LowPSec: An End-to-End Security Protocol for 6LoWPAN0 تومان
6LoWPAN has radically changed the IoT (Internet of Things) landscape by seeking to extend the use of IPv6 to smart and tiny objects. Enabling efficient IPv6 communication over IEEE 802.15.4 LoWPAN radio links requires high end-to-end security rules. The IEEE 802.15.4 MAC layer implements several security features offering hardware hop-by-hop protection for exchanged frames. In order to provide end-to-end security, researchers focus on lightweighting variants of existing security solutions such as IPSecthat operates on the network layer. In this paper, we introduce a new security protocol referred to as ”6LowPSec”, providing a propitious end-to-end security solution but functioning at the adaptation layer. 6LowPSec employs existing hardware security features specified by the MAC security sublayer. A detailed campaign is presented that evaluates the performances of 6LowPSec compared with the ightweight IPSec. Results prove the feasibility of an end-to-end hardware security solution for IoT, that operates at the adaptation layer, without incurring much overhead.
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 Complete Internet of Things (IoT) Platform for Structural Health Monitoring (SHM)0 تومان
Structural Health Monitoring (SHM) is becoming a crucial research topic to improve the human safety and to reduce maintenance costs. However, most of the existing SHM systems face challenges performing at real-time due to environmental effects and different operational hazards. Furthermore, the remote and constant monitoring amenities are not established yet, properly. To overcome this, Internet of Things (IoT) can be used, which would provide flexibility to monitor structures (building, bridge) from anywhere. In this paper, a complete IoT SHM platform is proposed. The platform consists of a Raspberry Pi, an analog to digital converter (ADC) MCP3008, and a Wi-Fi module for wireless communication. Piezoelectric (PZT) sensors were used to collect the data from the structure. The MCP3008 is used as an interface between the PZT sensors and the Raspberry Pi. The raspberry pi performs the necessary calculations to determine the SHM status using a proposed mathematical model to determine the damage’s location and size if any. The All the data is pushed to the Internet filter using ThingWorx platform. The proposed platform is evaluated and tested successfully.
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 flexible multicriteria decision-making methodology to support the strategic management of Science, Technology and Innovation research funding programs0 تومان
Research funding programs are a policy instrument utilized by governments to influence the innovation process. They are usually elaborated, launched and managed by research funding agencies. In order to select the most adequate research projects, agencies often rely on the peer review process. This paper introduces a methodology to support funding decisions based on the peer review process. The methodology involves the use of a multicriteria decision model to support the assessment, evaluation, prioritization and selection of applications, under a multi-step decision-making process, which fits into a strategic management cycle within the agency. The Multiattribute Value Theory, being considered under a Value Focused Thinking approach, provides a basis for the construction of the multicriteria decision model. The good practices in peer review and also a logical framework for program management are considered by the methodology. A pilot study, presented in the paper, involved a retrospective implementation of a peer review process in the context of a program launched by the Ministry for Science, Technology, Innovations and Communications and the National Council of Technological and Scientific Development, in Brazil. The methodology allowed a clear distinction of roles. The agency staff in the role of decision-makers was responsible for making value judgments on behalf of the agency. The experts, in the role of committee members and ad hoc reviewers, contributed with their expertise by providing objective assessments. Such assessments served as a basis for evaluating the applications, characterizing the possible portfolios, and can be considered as data in future program evaluation studies.
A holistic evaluation of smart city performance in the context of China0 تومان
Development of smart city has been increasingly accepted as a new technology-based solution to itigate urban diseases. The Chinese government has been devoting good efforts to the promotion of smart city through introducing a series of policies. However, policies may have limited effectiveness in application if they do not respond to the practice. There is little study examining what results have been achieved in practice by applying policy measures. This study presents a holistic evaluation of smart city performance in the context of China. The evaluation indicators in this study are selected by applying a hybrid research methodology including literature review and semi structured interviews. Indicator data are collected from 44 sample smart cities. The evaluation was conducted by applying Entropy method and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) technique collectively. This study highlights that the overall smart city performance in China is at a relatively low level. There is also a significant unbalance in performance between five smart city dimensions including smart infrastructure, governance, people, economy and environment. The smart performance between cities varies significantly since cities implement smart city programs in different ways. These differences impede experience sharing between cities. Actions have been recommended in this study for promoting further development of smart city in the context of China, such as increasing the investment on smart infrastructure, providing training programs, and establishing evaluation mechanism.
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 Neural Network Based Expert System for the Diagnosis of Diabetes Mellitus0 تومان
Diabetes is a disease in which the blood glucose, or blood sugar levels in the body are too high. The damage caused by diabetes can be very severe and even more pronounced in pregnant women due to the tendency of transmitting the hereditary disease to the next generation. Expert systems are now used in medical diagnosis of diseases in patients so as to detect the ailment and help in providing a solution to it. This research developed and trained a neural network model for the diagnosis of diabetes mellitus in pregnant women. The model is a four-layer feed forward network, trained using back-propagation and Bayesian Regulation algorithm. The input layer has 8 neurons, two hidden layers have 10 neurons each, and the output layer has one neuron which is the diagnosis result. The developed model was also incorporated into a web-based application to facilitate its use. Validation by regression shows that the trained network is over 92% accurate.
A non-emulative moment connection for progressive collapse resistance in precast concrete building frames0 تومان
This paper documents the experimental development of a new spandrel-to-column moment connection detail for progressive collapse resistance in precast concrete building frames. This study focuses on a 10-story prototype precast concrete frame building with perimeter special moment frames (SMF) that are subjected to a groundfloor column removal. The experimental subassembly represents a spandrel-to-column connection on the perimeter SMF ear the middle of the building face (i.e. not at the corners). The connection is non-emulative and utilizes unbonded high-strength steel post-tensioning (PT) bars which pass through ducts in the column and are anchored to the spandrels via bearing plates. The proposed design strives for construction simplicity, avoids field welding and/or grouting, and maximizes ductility by allowing the high strength steel bars to act as structural “fuses” when yielding. A full-scale quasi-static pushdown test is performed on two variants of the proposed connection: one with higher moment-rotation capacity and limited ductility, and another with lower capacity and higher ductility. The results show that the connection can reliably achieve its design yield capacity, performs well under service level demands, and can achieve moderate-to-high ductility. The experimental results are then applied to a system-level computational model of the prototype building frame under a column removal scenario. The results of a nonlinear dynamic analysis demonstrate that the system can arrest progressive collapse in the event of a single column loss scenario when either variant of the proposed connection is considered.
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 Concatenated Coded Modulation Based on GFDM for Access Optical Networks0 تومان
In this paper, we proposed a novel concatenated coded modulation composed of adaptive turbo code with trellis-coded modulation (ATTCM) that is based on generalized frequency division multiplex (GFDM) system. The proposed scheme has low complexity and provides high spectrum efficiency and significant coding gain. An experiment with 4 Gbit/s novel concatenated coded modulation GFDM system is successfully demonstrated with the proposed method. It is shown that the novel concatenated coding modulation signal (ATTCM 32QAM) provides 2.3 dB coding gain over that of TCM32QAM signal at bit error rate of 1e–3.This paper indicates a prospect solution for the future fifth generation optical access system.
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 novel algorithm termed RRSB (reduced random subspace-based Bagging) is proposed for construct ensemble classifier, which can increase the diversity of component classifiers without damaging the accuracy of the component classifiers. In detail, RRSB adopts the perturbation on the learningparameter 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.
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