Search results for: urban network

Authors: Darshini Mahadevia, Kanika Gounder, Saumya Lathia

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Cities, an outcome of natural growth and migration, are ever-expanding due to urban sprawl. In the Global South, urban areas are experiencing a switch from public transport to private vehicles, coupled with intensified urban agglomeration, leading to frequent longer commutes by automobiles. This increase in travel distance and motorized vehicle kilometres lead to unsustainable cities. To achieve the nationally pledged GHG emission mitigation goal, the government is prioritizing a modal shift to low-carbon transport modes like mass transit and paratransit. Mixed land-use and urban densification are crucial for the economic viability of these projects. Informed by desktop assessment of mobility plans and in-person primary surveys, the paper explores the challenges around urban densification and travel patterns in two Indian cities of contrasting nature- Surat, a metropolitan industrial city with a 5.9 million population and a very compact urban form, and Udaipur, a heritage city attracting large international tourists’ footfall, with limited scope for further densification. Dense, mixed-use urban areas often improve access to basic services and economic opportunities by reducing distances and enabling people who don't own personal vehicles to reach them on foot/ cycle. But residents travelling on different modes end up contributing to similar trip lengths, highlighting the non-uniform distribution of land-uses and lack of planned transport infrastructure in the city and the urban-peri urban networks. Additionally, it is imperative to manage these densities to reduce negative externalities like congestion, air/noise pollution, lack of public spaces, loss of livelihood, etc. The study presents a comparison of the relationship between transport systems with the built form in both cities. The paper concludes with recommendations for managing densities in urban areas along with promoting low-carbon transport choices like improved non-motorized transport and public transport infrastructure and minimizing personal vehicle usage in the Global South.

Keywords: India, low-carbon transport, travel behaviour, trip length, urban densification

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Authors: Dalu Zhang, Xiang Jin, Dejiang Zhou, Jianpeng Wang, Haiying Jiang

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Traditional TCP/IP network is showing lots of shortages and research for future networks is becoming a hotspot. FIA (Future Internet Architecture) and FIA-NP (Next Phase) are supported by US NSF for future Internet designing. Moreover, virtual machine migration is a significant technique in cloud computing. As a network application, it should also be supported in XIA (expressive Internet Architecture), which is in both FIA and FIA-NP projects. This paper is an experimental study aims at verifying the feasibility of VM migration over XIA. We present three ways to maintain VM connectivity and communication states concerning DAG design and routing table modification. VM migration experiments are conducted intra-AD and inter-AD with KVM instances. The procedure is achieved by a migration control protocol which is suitable for the characters of XIA. Evaluation results show that our solutions can well supports full live VM migration over XIA network respectively, keeping services seamless.

Keywords: DAG, downtime, virtual machine migration, XIA

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Authors: A. Miškinytė, A. Dėdelė

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Road traffic is one of the main sources of air pollution in urban areas associated with adverse effects on human health and environment. Nitrogen dioxide (NO2) is considered as traffic-related air pollutant, which concentrations tend to be higher near highways, along busy roads and in city centres and exceedances are mainly observed in air quality monitoring stations located close to traffic. Atmospheric dispersion models can be used to examine emissions from many various sources and to predict the concentration of pollutants emitted from these sources into the atmosphere. The study aim was to compare modelled concentrations of nitrogen dioxide using ADMS-Urban dispersion model with air quality monitoring network in cold and warm seasons in Kaunas city. Modelled average seasonal concentrations of nitrogen dioxide for 2011 year have been verified with automatic air quality monitoring data from two stations in the city. Traffic station is located near high traffic street in industrial district and background station far away from the main sources of nitrogen dioxide pollution. The modelling results showed that the highest nitrogen dioxide concentration was modelled and measured in station located near intensive traffic street, both in cold and warm seasons. Modelled and measured nitrogen dioxide concentration was respectively 25.7 and 25.2 µg/m3 in cold season and 15.5 and 17.7 µg/m3 in warm season. While the lowest modelled and measured NO2 concentration was determined in background monitoring station, respectively 12.2 and 13.3 µg/m3 in cold season and 6.1 and 7.6 µg/m3 in warm season. The difference between monitoring station located near high traffic street and background monitoring station showed that better agreement between modelled and measured NO2 concentration was observed at traffic monitoring station.

Keywords: air pollution, nitrogen dioxide, modelling, ADMS-Urban model

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Authors: Amirreza Fazely Hamedani, Muzzamil Aziz, Philipp Wieder, Ramin Yahyapour

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Software-defined networking in recent years came into the sight of so many network designers as a successor to the traditional networking. Unlike traditional networks where control and data planes engage together within a single device in the network infrastructure such as switches and routers, the two planes are kept separated in software-defined networks (SDNs). All critical decisions about packet routing are made on the network controller, and the data level devices forward the packets based on these decisions. This type of network is vulnerable to DDoS attacks, degrading the overall functioning and performance of the network by continuously injecting the fake flows into it. This increases substantial burden on the controller side, and the result ultimately leads to the inaccessibility of the controller and the lack of network service to the legitimate users. Thus, the protection of this novel network architecture against denial of service attacks is essential. In the world of cybersecurity, attacks and new threats emerge every day. It is essential to have tools capable of managing and analyzing all this new information to detect possible attacks in real-time. These tools should provide a comprehensive solution to automatically detect, predict and prevent abnormalities in the network. Big data encompasses a wide range of studies, but it mainly refers to the massive amounts of structured and unstructured data that organizations deal with on a regular basis. On the other hand, it regards not only the volume of the data; but also that how data-driven information can be used to enhance decision-making processes, security, and the overall efficiency of a business. This paper presents an intelligent big data framework as a solution to handle illegitimate traffic burden on the SDN network created by the numerous DDoS attacks. The framework entails an efficient defence and monitoring mechanism against DDoS attacks by employing the state of the art machine learning techniques.

Keywords: apache spark, apache kafka, big data, DDoS attack, machine learning, SDN network

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Authors: Çağrı Özgün Kibiroğlu, Zeynep Turgut

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This paper considers a hub location problem where the network service area partitioned into predetermined zones (represented by node clusters is given) and potential hub nodes capacity levels are determined a priori as a selection criteria of hub to investigate congestion effect on network. The objective is to design hub network by determining all required hub locations in the node clusters and also allocate non-hub nodes to hubs such that the total cost including transportation cost, opening cost of hubs and penalty cost for exceed of capacity level at hubs is minimized. A mixed integer linear programming model is developed introducing additional constraints to the traditional model of capacitated multiple allocation hub location problem and empirically tested.

Keywords: hub location problem, p-hub median problem, clustering, congestion

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Authors: Cheng Fang, Lingwei Quan, Cunyue Lu

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Human pose estimation and tracking are to accurately identify and locate the positions of human joints in the video. It is a computer vision task which is of great significance for human motion recognition, behavior understanding and scene analysis. There has been remarkable progress on human pose estimation in recent years. However, more researches are needed for human pose tracking especially for online tracking. In this paper, a framework, called PoseSRPN, is proposed for online single-person pose estimation and tracking. We use Siamese network attaching a pose estimation branch to incorporate Single-person Pose Tracking (SPT) and Visual Object Tracking (VOT) into one framework. The pose estimation branch has a simple network structure that replaces the complex upsampling and convolution network structure with deconvolution. By augmenting the loss of fully convolutional Siamese network with the pose estimation task, pose estimation and tracking can be trained in one stage. Once trained, PoseSRPN only relies on a single bounding box initialization and producing human joints location. The experimental results show that while maintaining the good accuracy of pose estimation on COCO and PoseTrack datasets, the proposed method achieves a speed of 59 frame/s, which is superior to other pose tracking frameworks.

Keywords: computer vision, pose estimation, pose tracking, Siamese network

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Authors: Neeta Kumari, Gopal Pathak

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Artificial neural network has been proved to be an efficient tool for non-parametric modeling of data in various applications where output is non-linearly associated with input. It is a preferred tool for many predictive data mining applications because of its power , flexibility, and ease of use. A standard feed forward networks (FFN) is used to predict the groundwater fluoride content. The ANN model is trained using back propagated algorithm, Tansig and Logsig activation function having varying number of neurons. The models are evaluated on the basis of statistical performance criteria like Root Mean Squarred Error (RMSE) and Regression coefficient (R2), bias (mean error), Coefficient of variation (CV), Nash-Sutcliffe efficiency (NSE), and the index of agreement (IOA). The results of the study indicate that Artificial neural network (ANN) can be used for groundwater fluoride prediction in the limited data situation in the hard rock region like western parts of Jharkhand with sufficiently good accuracy.

Keywords: Artificial neural network (ANN), FFN (Feed-forward network), backpropagation algorithm, Levenberg-Marquardt algorithm, groundwater fluoride contamination

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Authors: Opal Giulianelli, Pegah Zamani

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Sustainable food has become a frequently debated topic in recent years due to a consumer push for environmentally sustainable food. While some research works on improving the monoculture farm systems that are currently in use, others focus on expanding the definition of sustainable food systems. This research looks at those concepts of alternative food systems applied to a more extensive city system. The goal is to create a theoretical site plan that could be implemented in emerging cities and other urban environments. This site plan combines the ideas of environmentally sustainable food development, such as food forests, urban farming, and community gardens. This would represent one part of a larger sustainable food system that can be altered depending on the environment or the people it is serving. However, this research is being carried out with the southeast United States in mind and, therefore, may prove difficult to apply to other regions, especially those of radically different climates.

Keywords: alternative food systems, urban design, food forests, aquaponics, hydroponics, food security, food system design

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Authors: Hassan Abubakar

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This paper will serve as a guide to good design and implementation of wireless networking for campus institutions in Nigeria. It can be implemented throughout the primary, secondary and tertiary institutions. This paper describe the some technical functions, standard configurations and layouts of the 802.11 wireless LAN(Local Area Network) that can be implemented across the campus network. The paper also touches upon the wireless infrastructure standards involved with enhanced services, such as voice over wireless and wireless guest hotspot. The paper also touch the benefits derived from implementing campus wireless network and share some lights on how to arrive at the success in increasing the performance of wireless and using the campus wireless to share resources like software applications, printer and documents.

Keywords: networking, standards, wireless local area network (WLAN), radio frequency (RF), campus

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Authors: Y. B. Kirankumar, J. D. Mallapur

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Wireless Sensor Network (WSN) is an emerging technology, which has great invention for various low cost applications both for mass public as well as for defence. The wireless sensor communication technology allows random participation of sensor nodes with particular applications to take part in the network, which results in most of the uncovered simulation area, where fewer nodes are located at far distances. The drawback of such network would be that the additional energy is spent by the nodes located in a pattern of dense location, using more number of nodes for a smaller distance of communication adversely in a region with less number of nodes and additional energy is again spent by the source node in order to transmit a packet to neighbours, thereby transmitting the packet to reach the destination. The proposed work is intended to develop Energy Efficient Node Placement Algorithm (EENPA) in order to place the sensor node efficiently in simulated area, where all the nodes are equally located on a radial path to cover maximum area at equidistance. The total energy consumed by each node compared to random placement of nodes is less by having equal burden on fewer nodes of far location, having distributed the nodes in whole of the simulation area. Calculating the network lifetime also proves to be efficient as compared to random placement of nodes, hence increasing the network lifetime, too. Simulation is been carried out in a qualnet simulator, results are obtained on par with random placement of nodes with EENP algorithm.

Keywords: energy, WSN, wireless sensor network, energy approach

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Authors: Sandra Rafael, Bruno Vicente, Vera Rodrigues, Carlos Borrego, Myriam Lopes

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Air pollution is an environmental and social issue at different spatial scales, especially in a climate change context, with an expected decrease of air quality. Air pollution is a combination of high emissions and unfavourable weather conditions, where wind speed and wind direction play a key role. The urban design (location and structure of buildings and trees) can both promote the air pollutants dispersion as well as promote their retention within the urban area. Today, most of the urban areas are applying measures to adapt to future extreme climatic events. Most of these measures are grounded on nature-based solutions, namely green roofs and green areas. In this sense, studies are required to evaluate how the implementation of these actions will influence the wind flow within the urban area and, consequently, how this will influence air pollutants' dispersion. The main goal of this study was to evaluate the influence of a set of urban morphologies in the wind conditions and in the dispersion of air pollutants, in a built-up area in Portugal. For that, two pollutants were analysed (NOx and PM10) and four scenarios were developed: i) a baseline scenario, which characterizes the current status of the study area, ii) an urban green scenario, which implies the implementation of a green area inside the domain, iii) a green roof scenario, which consists in the implementation of green roofs in a specific area of the domain; iv) a 'grey' scenario, which consists in a scenario with absence of vegetation. For that, two models were used, namely the Weather Research and Forecasting model (WRF) and the CFD model VADIS (pollutant dispersion in the atmosphere under variable wind conditions). The WRF model was used to initialize the CFD model, while the last was used to perform the set of numerical simulations, on an hourly basis. The implementation of the green urban area promoted a reduction of air pollutants' concentrations, 16% on average, related to the increase in the wind flow, which promotes air pollutants dispersion; while the application of green roofs showed an increase of concentrations (reaching 60% during specific time periods). Overall the results showed that a strategic placement of vegetation in cities has the potential to make an important contribution to increase air pollutants dispersion and so promote the improvement of air quality and sustainability of urban environments.

Keywords: air pollutants dispersion, wind conditions, urban morphologies, road traffic emissions

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Authors: Iacopo Testi, Diego Pajarito, Nicoletta Roberto, Carmen Greco

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Today, a consistent segment of the world’s population lives in urban areas, and this proportion will vastly increase in the next decades. Therefore, understanding the key trends in urbanization, likely to unfold over the coming years, is crucial to the implementation of sustainable urban strategies. In parallel, the daily amount of digital data produced will be expanding at an exponential rate during the following years. The analysis of various types of data sets and its derived applications have incredible potential across different crucial sectors such as healthcare, housing, transportation, energy, and education. Nevertheless, in city development, architects and urban planners appear to rely mostly on traditional and analogical techniques of data collection. This paper investigates the prospective of the data science field, appearing to be a formidable resource to assist city managers in identifying strategies to enhance the social, economic, and environmental sustainability of our urban areas. The collection of different new layers of information would definitely enhance planners' capabilities to comprehend more in-depth urban phenomena such as gentrification, land use definition, mobility, or critical infrastructural issues. Specifically, the research results correlate economic, commercial, demographic, and housing data with the purpose of defining the youth economic discomfort index. The statistical composite index provides insights regarding the economic disadvantage of citizens aged between 18 years and 29 years, and results clearly display that central urban zones and more disadvantaged than peripheral ones. The experimental set up selected the city of Rome as the testing ground of the whole investigation. The methodology aims at applying statistical and spatial analysis to construct a composite index supporting informed data-driven decisions for urban planning.

Keywords: data science, spatial analysis, composite index, Rome, urban planning, youth economic discomfort index

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Authors: Sai Siddharth S., Prasanna Kumar G. M., Alagarsamy R.

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This research introduces an alternative approach to urban road maintenance by utilizing Blended Wing Body (BWB) design and Vertical Takeoff and Landing (VTOL) drones. The integration of this aerospace innovation, combining blended wing efficiency with VTOL maneuverability, aims to optimize fuel consumption and explore versatile applications in solving urban problems. A few problems are discussed along with optimization of the design and comparative study with other drone configurations.

Keywords: design optimization, CFD, CAD, VTOL, blended wing body

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Authors: Peng Wang, Tigang Jiang

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The computer based lip reading method of different languages cannot be universal. At present, for the research of Chinese lip reading, whether the work on data sets or recognition algorithms, is far from mature. In this paper, we study the Chinese lipreading method based on machine learning, and propose a Chinese Sentence-level lip-reading network (CNLipNet) model which consists of spatio-temporal convolutional neural network(CNN), recurrent neural network(RNN) and Connectionist Temporal Classification (CTC) loss function. This model can map variable-length sequence of video frames to Chinese Pinyin sequence and is trained end-to-end. More over, We create CNLRS, a Chinese Lipreading Dataset, which contains 5948 samples and can be shared through github. The evaluation of CNLipNet on this dataset yielded a 41% word correct rate and a 70.6% character correct rate. This evaluation result is far superior to the professional human lip readers, indicating that CNLipNet performs well in lipreading.

Keywords: lipreading, machine learning, spatio-temporal, convolutional neural network, recurrent neural network

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Authors: Fariba Ebrahimi, Mehdi Ghorbani

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Achieving to integrated Water management fundamentally needs to effective relation, coordination, collaboration and synergy among various actors who have common but different responsibilities. In this sense, the foundation of comprehensive and integrated management is not compatible with centralization and top-down strategies. The aim of this paper is analysis institutional network of water relevant stakeholders and water policy monitoring in Shemiranat. In this study collaboration networks between informal and formal institutions co-management process have been investigated. Stakeholder network analysis as a quantitative method has been implicated in this research. The results of this study indicate that institutional cohesion is medium; sustainability of institutional network is about 40 percent (medium). Additionally the core-periphery index has measured in this study according to reciprocity index. Institutional capacities for integrated natural resource management in regional level are measured in this study. Furthermore, the necessity of centrality reduction and promote stakeholders relations and cohesion are emphasized to establish a collaborative natural resource governance.

Keywords: policy monitoring, water management, social network, stakeholder, shemiranat

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Authors: Lee Soo-Kyoung, Kim Young-Su

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This study established a network related to metabolic syndrome intervention by conducting a social network analysis of titles, keywords, and abstracts, and it identified emerging topics of research. It visualized an interconnection between critical keywords and investigated their frequency of appearance to construe the trends in metabolic syndrome intervention measures used in studies conducted over 38 years (1979–2017). It examined a collection of keywords from 8,285 studies using text rank analyzer, NetMiner 4.0. The analysis revealed 5 groups of newly emerging keywords in the research. By examining the relationship between keywords with reference to their betweenness centrality, the following clusters were identified. Thus if new researchers refer to existing trends to establish the subject of their study and the direction of the development of future research on metabolic syndrome intervention can be predicted.

Keywords: intervention, metabolic syndrome, network analysis, research, the trend

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Authors: Sanat Ramesh, Tarun Dutt, Abhilasha Aswal, Anushka Chandrababu, G. N. Srinivasa Prasanna

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Optimal Schedule Generation for a large national railway network operating thousands of passenger trains with tens of thousands of kilometers of track is a grand computational challenge in itself. We present heuristics based on a Mixed Integer Program (MIP) formulation for local optimization. These methods provide flexibility in scheduling new trains with varying speed and delays and improve utilization of infrastructure. We propose methods that provide a robust solution with hundreds of trains being scheduled over a portion of the railway network without significant increases in delay. We also provide techniques to validate the nominal schedules thus generated over global correlated variations in travel times thereby enabling us to detect conflicts arising due to delays. Our validation results which assume only the support of the arrival and departure time distributions takes an order of few minutes for a portion of the network and is computationally efficient to handle the entire network.

Keywords: mixed integer programming, optimization, railway network, train scheduling

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Authors: Chico Horacio Jose Sambo

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Recently neural network has gained popularity when come to solve complex nonlinear problems. Permeability is one of fundamental reservoir characteristics system that are anisotropic distributed and non-linear manner. For this reason, permeability prediction from well log data is well suited by using neural networks and other computer-based techniques. The main goal of this paper is to predict reservoir permeability from well logs data by using neural network approach. A multi-layered perceptron trained by back propagation algorithm was used to build the predictive model. The performance of the model on net results was measured by correlation coefficient. The correlation coefficient from testing, training, validation and all data sets was evaluated. The results show that neural network was capable of reproducing permeability with accuracy in all cases, so that the calculated correlation coefficients for training, testing and validation permeability were 0.96273, 0.89991 and 0.87858, respectively. The generalization of the results to other field can be made after examining new data, and a regional study might be possible to study reservoir properties with cheap and very fast constructed models.

Keywords: neural network, permeability, multilayer perceptron, well log

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Authors: Nopsarun Vannasirikul

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The purposes of this research paper were to study the current situations of community development, women’s potentials, women’s participation, network, and government policy as well as to study the factors influencing women’s potentials, women’s participation, network, and government policy that have on the community development. The population included the women age of 18 years old who were living in the communities of Bangkok areas. This study was a mix research method of quantitative and qualitative method. A simple random sampling method was utilized to obtain 400 sample groups from 50 districts of Bangkok and to perform data collection by using questionnaire. Also, a purposive sampling method was utilized to obtain 12 informants for an in-depth interview to gain an in-sight information for quantitative method.

Keywords: community development, participation, network, women’s right, management

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Authors: Hanbhin Ryu, Ilkwon Yun

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Automotive industry targets to provide an improvement in safety and convenience through realizing fully autonomous vehicle. For partially realizing fully automated driving, Current vehicles already feature varieties of advanced driver assistance system (ADAS) for safety and infotainment systems for the driver’s convenience. This paper presents Cloud Connected Vehicle (CCV) which connected vehicles with cloud data center via the access network to control the vehicle for achieving next autonomous driving form and describes its features. This paper also describes the shortcoming of the existing In-Vehicle Network (IVN) to be a next generation IVN of CCV and organize the 802.3 Ethernet, the next generation of IVN, related research issue to verify the feasibility of using Ethernet. At last, this paper refers to additional considerations to adopting Ethernet-based IVN for CCV.

Keywords: autonomous vehicle, cloud connected vehicle, ethernet, in-vehicle network

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Authors: Azadeh Bashiri

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Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

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Authors: Amrah Maryam

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The emergence of online social networks (OSNs) has transformed the way we pursue and share information. On the one hand, OSNs provide great ease for the spreading of positive information while, on the other hand, they may also become a channel for the spreading of malicious rumors and misinformation throughout the social network. Thus, to assure the trustworthiness of OSNs to its users, it is of vital importance to detect the misinformation propagation in the network by placing network monitors. In this paper, we aim to place monitors near the suspected nodes with the intent to limit the diffusion of misinformation in the social network, and then we also detect the most significant nodes in the network for propagating true information in order to minimize the effect of already diffused misinformation. Thus, we initiate two heuristic monitor placement using articulation points and truth propagation using eigenvector centrality. Furthermore, to provide real-time workings of the system, we integrate both the monitor placement and truth propagation entities as well. To signify the effectiveness of the approaches, we have carried out the experiment and evaluation of Stanford datasets of online social networks.

Keywords: online social networks, monitor placement, independent cascade model, spread of misinformation

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Authors: Tapan Jain, Davender Singh Saini

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Clustering is a useful mechanism in wireless sensor networks which helps to cope with scalability and data transmission problems. The basic aim of our research work is to provide efficient clustering using Hierarchical agglomerative clustering (HAC). If the distance between the sensing nodes is calculated using their location then it’s quantitative HAC. This paper compares the various agglomerative clustering techniques applied in a wireless sensor network using the quantitative data. The simulations are done in MATLAB and the comparisons are made between the different protocols using dendrograms.

Keywords: routing, hierarchical clustering, agglomerative, quantitative, wireless sensor network

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Authors: Richard Maguire

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This research evaluates the efficiency of using mobile HEPA filters to reduce localized Particulate Matter (PM), Total Volatile Organic Chemical (TVOC) and Formaldehyde (HCHO) Air Pollution. The research is being performed using a standard HEPA filter that is tube fitted and attached to a motor vehicle. The velocity of the vehicle is used to generate the pressure difference that allows the filter to remove PM, VOC and HCOC pollution from the localized atmosphere of a road transport traffic route. The testing has been performed on a sample of traffic routes in Non-Sparse and Sparse urban environments within the UK. Pre and Post filter measuring of the PM2.5 Air Quality has been carried out along with demographics of the climate environment, including live filming of the traffic conditions. This provides a base line for future national and international research. The effectiveness measurement is generated through evaluating the difference in PM2.5 Air Quality measured pre- and post- the mobile filter test equipment. A series of further research opportunities and future exploitation options are made based on the results of the research.

Keywords: high efficiency particulate air, HEPA filter, particulate matter, traffic pollution

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Authors: Diego A. Romero Espinosa

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Thermal simulations are used to evaluate comfort and energy consumption of buildings. However, the performance of different urban forms cannot be assessed precisely if an environmental control system and user schedules are considered. The outcome of such analysis would lead to conclusions that combine the building use, operation, services, envelope, orientation and density of the urban fabric. The influence of these factors varies during the life cycle of a building. The orientation, as well as the surroundings, can be considered a constant during the lifetime of a building. The structure impacts the thermal inertia and has the largest lifespan of all the building components. On the other hand, the building envelope is the most frequent renovated component of a building since it has a great impact on energy performance and comfort. Building services have a shorter lifespan and are replaced regularly. With the purpose of addressing the performance, an urban form, a specific orientation, and density, a thermal simulation method were developed. The solar irradiation is taken into consideration depending on the outdoor temperature. Incoming irradiation at low temperatures has a positive impact increasing the indoor temperature. Consequently, overheating would be the combination of high outdoor temperature and high irradiation at the façade. On this basis, the indoor temperature is simulated for a specific orientation of the evaluated urban form. Thermal inertia and building envelope performance are considered additionally as the materiality of the building. The results of different thermal zones are summarized using the 'Degree day method' for cooling and heating. During the early phase of a design process for a project, such as Masterplan, conclusions regarding urban form, density and materiality can be drawn by means of this analysis.

Keywords: building envelope, density, masterplanning, urban form

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Authors: Emejeamara Francis

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The future of potentials wind energy applications within suburban/urban areas are currently faced with various problems. These include insufficient assessment of urban wind resource, and the effectiveness of commercial gust control solutions as well as unavailability of effective and cheaper valuable tools for scoping the potentials of urban wind applications within built-up environments. In order to achieve effective assessment of the potentials of urban wind installations, an estimation of the total energy that would be available to them were effective control systems to be used, and evaluating the potential power to be generated by the wind system is required. This paper presents a methodology of predicting the power generated by a wind system operating within an urban wind resource. This method was developed by using high temporal resolution wind measurements from eight potential sites within the urban and suburban environment as inputs to a vertical axis wind turbine multiple stream tube model. A relationship between the unsteady performance coefficient obtained from the stream tube model results and turbulence intensity was demonstrated. Hence, an analytical methodology for estimating the unsteady power coefficient at a potential turbine site is proposed. This is combined with analytical models that were developed to predict the wind speed and the excess energy (EEC) available in estimating the potential power generated by wind systems at different heights within a built environment. Estimates of turbulence intensities, wind speed, EEC and turbine performance based on the current methodology allow a more complete assessment of available wind resource and potential urban wind projects. This methodology is applied to four major UK cities namely Leeds, Manchester, London and Edinburgh and the potential to map the turbine performance at different heights within a typical urban city is demonstrated.

Keywords: small-scale wind, turbine power, urban wind energy, turbulence intensity, excess energy content

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Authors: H. Gorine, M. Ramadan Elmezughi

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In this paper, we investigate security issues and challenges facing researchers in wireless sensor networks and countermeasures to resolve them. The broadcast nature of wireless communication makes Wireless Sensor Networks prone to various attacks. Due to resources limitation constraint in terms of limited energy, computation power and memory, security in wireless sensor networks creates different challenges than wired network security. We will discuss several attempts at addressing the issues of security in wireless sensor networks in an attempt to encourage more research into this area.

Keywords: wireless sensor networks, network security, light weight encryption, threats

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Authors: Poonam Sharma, Ankur Srivastav

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Cities are complex and dynamic systems that constitute a significant challenge to urban planning. The increasing size of the built-up area owing to growing population pressure and economic growth have lead to massive Landuse/Landcover change resulted in the loss of natural habitat and thus reducing the green covers in urban areas. Urban environmental quality is influenced by several aspects, including its geographical configuration, the scale, and nature of human activities occurring and environmental impacts generated. Cities have transformed into complex and dynamic systems that constitute a significant challenge to urban planning. Cities and their sustainability are often discussed together as the cities stand confronted with numerous environmental concerns as the world becoming increasingly urbanized, and the cities are situated in the mesh of global networks in multiple senses. A rapid transformed urban setting plays a crucial role to change the green area of natural habitats. To examine the pattern of urban growth and to measure the Landuse/Landcover change in Gurgoan in Haryana, India through the integration of Geospatial technique is attempted in the research paper. Satellite images are used to measure the spatiotemporal changes that have occurred in the land use and land cover resulting into a new cityscape. It has been observed from the analysis that drastically evident changes in land use has occurred with the massive rise in built up areas and the decrease in green cover and therefore causing the sustainability of the city an important area of concern. The massive increase in built-up area has influenced the localised temperatures and heat concentration. To enhance the decision-making process in urban planning, a detailed and real world depiction of these urban spaces is the need of the hour. Monitoring indicators of key processes in land use and economic development are essential for evaluating policy measures.

Keywords: cityscape, geospatial techniques, green cover index, urban environmental quality, urban planning

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Authors: Rhaptyalyani Herno Della, Nyimas Septi Rika Putri, Rika Nabila

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The growth of population and economic activities in urban areas needs support economic development, needs to be balanced with adequate environmental infrastructure development. Settlement can avoid from rundown condition and uninhabitable if the development of urban area accordance with healthy development. Identifying database of slum in this study reference to the Review of the Spatial Plan Development of Palembang City, Laws of Public Works Department about Technical Guidelines on the Quality Improvement Housing and Slum and Urban Spatial Global Report on Human Settlements 2003. A case study for identifying in Palembang riverbanks area are located in two districts; Ilir Timur I and Ilir Timur II. This study do the identification of slum areas based on several variables about physical and non physical aspect, then the result of identification are used to define a policy that can be used to improve the area.

Keywords: slum, riverbanks area, urban area, infrastructure

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Authors: Marie Madeleine Sarzi Inacio, Ligiane Carolina Leite Dauzacker, Rodrigo Henriques Lopes Da Silva

Abstract:

The climate changes resulting from human activity have increased interest in more sustainable production practices to reduce and offset pollutant emissions. Brazil, with its vast areas capable of carbon absorption, holds a significant advantage in this context. However, to optimize the country's sustainable potential, it is important to establish a robust carbon market with clear rules for the eligibility and validation of projects aimed at reducing and offsetting Greenhouse Gas (GHG) emissions. In this study, our objective is to conduct a feasibility analysis through a case study to evaluate the implementation of an urban forest credits standard in Brazil, using the Urban Forest Credits (UFC) model implemented in the United States as a reference. Thus, the city of Ribeirão Preto, located in Brazil, was selected to assess the availability of green areas. With the CO2 emissions value from the metalworking industry, it was possible to analyze information in the case study, considering the activity. The QGIS software was used to map potential urban forest areas, which can connect to various types of geospatial databases. Although the chosen municipality has little vegetative coverage, the mapping identified at least eight areas that fit the standard definitions within the delimited urban perimeter. The outlook was positive, and the implementation of projects like Urban Forest Credits (UFC) adapted to the Brazilian reality has great potential to benefit the country in the carbon market and contribute to achieving its Greenhouse Gas (GHG) emission reduction goals.

Keywords: carbon neutrality, metalworking industry, carbon credits, urban forestry credits

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