Search results for: spatial data analysis

Authors: M. M. Ali, Ahmed Al- Ani, Derek Eamus, Daniel K. Y. Tan

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In this glasshouse study, we developed the new image-based non-destructive technique for detecting leaf P status of different crops such as cotton, tomato and lettuce. Plants were allowed to grow on nutrient media containing different P concentrations, i.e. 0%, 50% and 100% of recommended P concentration (P0 = no P, L; P1 = 2.5 mL 10 L-1 of P and P2 = 5 mL 10 L-1 of P as NaH2PO4). After 10 weeks of growth, plants were harvested and data on leaf P contents were collected using the standard destructive laboratory method and at the same time leaf images were collected by a handheld crop image sensor. We calculated leaf area, leaf perimeter and RGB (red, green and blue) values of these images. This data was further used in the linear discriminant analysis (LDA) to estimate leaf P contents, which successfully classified these plants on the basis of leaf P contents. The data indicated that P deficiency in crop plants can be predicted using the image and morphological data. Our proposed non-destructive imaging method is precise in estimating P requirements of different crop species.

Keywords: image-based techniques, leaf area, leaf P contents, linear discriminant analysis

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Authors: Parul Bhalla, Sarvesh Palria

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Wetlands are areas of land that are either temporarily or permanently covered by water. Wetlands exhibit enormous diversity according to their genesis, geographical location, water regime and chemistry, dominant plants and soil or sediment characteristics. The spatial and temporal characteristics of wetland in terms of turbidity and aquatic vegetation could serve as guiding tool, in conservation prioritization of wetlands. The aquatic vegetation in the wetland is an indicator of the trophic status of the wetland which has a bearing on the water quality, the turbidity level in any wetland is indicative of the quality of the water in it. To conserve and manage wetland resources, it is important to have inventory of wetland and its catchment. Fateh Sagar wetland in Udaipur city is the one of the important wetland for tourism industry and other economic activities in the region. Realizing the importance of the wetland, the present study has been taken up with the specific objective of delineation and characterization of Fateh Sagar wetland in terms of turbidity and aquatic vegetation, using high resolution satellite data such as Cartosat and LISS IV multi-temporal data, which will efficiently bring out the changes in water spread and quality parameters. The catchment of wetland has been also characterized for various features. The study leads in to takes necessary steps to conserve the wetland and its resources.

Keywords: aquatic vegetation, catchment, turbidity status, wetland

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Authors: Mohit Kumar

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Natural fractures are classified in two broad categories of joints and faults on the basis of shear movement in the deposited strata. Natural fracture always has high structural relationship with extensional or non-extensional tectonics and sometimes the result is seen in the form of micro cracks. Geological evidences suggest that both large and small-scale fractures help in to analyze the seismic anisotropy which essentially contribute into characterization of petro physical properties behavior associated with directional migration of fluid. We generally question why basement study is much needed as historically it is being treated as non-productive and geoscientist had no interest in exploration of these basement rocks. Basement rock goes under high pressure and temperature, and seems to be highly fractured because of the tectonic stresses that are applied to the formation along with the other geological factors such as depositional trend, internal stress of the rock body, rock rheology, pore fluid and capillary pressure. Sometimes carbonate rocks also plays the role of basement and igneous body e.g basalt deposited over the carbonate rocks and fluid migrate from carbonate to igneous rock due to buoyancy force and adequate permeability generated by fracturing. So in order to analyze the complete petroleum system, FMC (Fluid Migration Characterization) is necessary through fractured media including fracture intensity, orientation and distribution both in basement rock and county rock. Thus good understanding of fractures can lead to project the correct wellbore trajectory or path which passes through potential permeable zone generated through intensified P-T and tectonic stress condition. This paper deals with the analysis of these fracture property such as intensity, orientation and distribution in basement rock as large scale fracture can be interpreted on seismic section, however, small scale fractures show ambiguity in interpretation because fracture in basement rock lies below the seismic wavelength and hence shows erroneous result in identification. Seismic attribute technique also helps us to delineate the seismic fracture and subtle changes in fracture zone and these can be inferred from azimuthal anisotropy in velocity and amplitude and spectral decomposition. Seismic azimuthal anisotropy derives fracture intensity and orientation from compressional wave and converted wave data and based on variation of amplitude or velocity with azimuth. Still detailed analysis of fractured basement required full isotropic and anisotropic analysis of fracture matrix and surrounding rock matrix in order to characterize the spatial variability of basement fracture which support the migration of fluid from basement to overlying rock.

Keywords: basement rock, natural fracture, reservoir characterization, seismic attribute

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Authors: U.V. Suryawanshi, S.S. Chowhan, U.V Kulkarni

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Accuracy of segmentation methods is of great importance in brain image analysis. Tissue classification in Magnetic Resonance brain images (MRI) is an important issue in the analysis of several brain dementias. This paper portraits performance of segmentation techniques that are used on Brain MRI. A large variety of algorithms for segmentation of Brain MRI has been developed. The objective of this paper is to perform a segmentation process on MR images of the human brain, using Fuzzy c-means (FCM), Kernel based Fuzzy c-means clustering (KFCM), Spatial Fuzzy c-means (SFCM) and Improved Fuzzy c-means (IFCM). The review covers imaging modalities, MRI and methods for noise reduction and segmentation approaches. All methods are applied on MRI brain images which are degraded by salt-pepper noise demonstrate that the IFCM algorithm performs more robust to noise than the standard FCM algorithm. We conclude with a discussion on the trend of future research in brain segmentation and changing norms in IFCM for better results.

Keywords: image segmentation, preprocessing, MRI, FCM, KFCM, SFCM, IFCM

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Authors: A. Elmethnani, A. Jroud

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This coastal crude oil refinery is situated north of a big city west of Tripoli; the city then could be highly prone to downwind refinery emissions where the NNE wind direction is prevailing through most seasons of the year. Furthermore, due to the absence of an air quality monitoring network and scarce emission data available for the neighboring community, nearby residents have serious worries about the impacts of the oil refining operations on local air quality. In responding to these concerns, a short term survey has performed for three consecutive days where a semi-continues mobile monitoring approach has developed effectively in this study; the monitoring station (Compact AQM 65 AeroQual) was mounted on a vehicle to move quickly between locations, measurements of 10 minutes averaging of 60 seconds then been taken at each fixed sampling point. The downwind ambient concentration of CO, H₂S, NOₓ, NO₂, SO₂, PM₁, PM₂.₅ PM₁₀, and TSP were measured at carefully chosen sampling locations, ranging from 200m nearby the fence-line passing through the city center up to 4.7 km east to attain best spatial coverage. Results showed worrying levels of PM₂.₅ PM₁₀, and TSP at one sampling location in the city center, southeast of the refinery site, with an average mean of 16.395μg/m³, 33.021μg/m³, and 42.426μg/m³ respectively, which could be attributed to road traffic. No significant concentrations have been detected for other pollutants of interest over the study area, as levels observed for CO, SO₂, H₂S, NOₓ, and NO₂ haven’t respectively exceeded 1.707 ppm, 0.021ppm, 0.134 ppm, 0.4582 ppm, and 0.0018 ppm, which was at the same sampling locations as well. Although it wasn’t possible to compare the results with the Libyan air quality standards due to the difference in the averaging time period, the technique was adequate for the baseline air quality screening procedure. Overall, findings primarily suggest modeling of dispersion of the refinery emissions to assess the likely impact and spatial-temporal distribution of air pollutants.

Keywords: air quality, mobil monitoring, oil refinery

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Authors: Gu Sihao

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The coordinated development of "ecology-production-life" in cities has been highly concerned by the country, and the transformation development and sustainable development of resource-based cities have become a hot research topic at present. As an important part of China's resource-based cities, coal resource-based cities have the characteristics of large number and wide distribution. However, due to the adjustment of national energy structure and the gradual exhaustion of urban coal resources, the development vitality of coal resource-based cities is gradually reduced. In many studies, the deterioration of ecological environment in coal resource-based cities has become the main problem restricting their urban transformation and sustainable development due to the "emphasis on economy and neglect of ecology". Since the 18th National Congress of the Communist Party of China (CPC), the Central Government has been deepening territorial space planning and development. On the premise of optimizing territorial space development pattern, it has completed the demarcation of ecological protection red lines, carried out ecological zoning and ecosystem evaluation, which have become an important basis and scientific guarantee for ecological modernization and ecological civilization construction. Grasp the regional multiple ecosystem services is the precondition of the ecosystem management, and the relationship between the multiple ecosystem services study, ecosystem services cluster can identify the interactions between multiple ecosystem services, and on the basis of the characteristics of the clusters on regional ecological function zoning, to better Social-Ecological system management. Based on this cognition, this study optimizes the spatial function zoning of Gujiao, a coal resource-based city, in order to provide a new theoretical basis for its sustainable development. This study is based on the detailed analysis of characteristics and utilization of Gujiao city land space, using SOFM neural networks to identify local ecosystem service clusters, according to the cluster scope and function of ecological function zoning of space partition balance and coordination between different ecosystem services strength, establish a relationship between clusters and land use, and adjust the functions of territorial space within each zone. Then, according to the characteristics of coal resources city and national spatial function zoning characteristics, as the driving factors of land change, by cellular automata simulation program, such as simulation under different restoration strategy situation of urban future development trend, and provides relevant theories and technical methods for the "third-line" demarcations of Gujiao's territorial space planning, optimizes territorial space functions, and puts forward targeted strategies for the promotion of regional ecosystem services, providing theoretical support for the improvement of human well-being and sustainable development of resource-based cities.

Keywords: coal resource-based city, territorial spatial planning, ecosystem service cluster, gmop model, geosos-FLUS model, functional zoning optimization and upgrading

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Authors: Yan Wang, Yasushi Asami, Yukio Sadahiro

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In urban area, several landmarks may affect housing price and rents, hedonic analysis should employ distance variables corresponding to each landmarks. Unfortunately, the effects of distances to landmarks on housing prices are generally not consistent with the true price. These distance variables may cause magnitude error in regression, pointing a problem of spatial multicollinearity. In this paper, we provided some approaches for getting the samples with less bias and method on locating the specific sampling area to avoid the multicollinerity problem in two specific landmarks case.

Keywords: landmarks, hedonic regression, distance variables, collinearity, multicollinerity

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Authors: Argaw T. Gurmu, Muhammad N. Mahmood

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The objective of this research is to identify the architecture and construction management students’ learning challenges of the building measurement. This research used the survey data obtained collected from the students who completed the building measurement unit. NVivo qualitative data analysis software was used to identify relevant themes. The analysis of the qualitative data revealed the major learning difficulties such as inadequacy of practice questions for the examination, inability to work as a team, lack of detailed understanding of the prerequisite units, insufficiency of the time allocated for tutorials and incompatibility of lecture and tutorial schedules. The output of this research can be used as a basis for improving the teaching and learning activities in construction measurement units.

Keywords: building measurement, construction management, learning challenges, evaluate survey

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Authors: Fathi M. O. Hamed, Salma F. Elkofhaifee

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The aim of this work is to detect geometrical shape objects in an image. In this paper, the object is considered to be as a circle shape. The identification requires find three characteristics, which are number, size, and location of the object. To achieve the goal of this work, this paper presents an algorithm that combines from some of statistical approaches and image analysis techniques. This algorithm has been implemented to arrive at the major objectives in this paper. The algorithm has been evaluated by using simulated data, and yields good results, and then it has been applied to real data.

Keywords: image processing, median filter, projection, scale-space, segmentation, threshold

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Authors: Sergio Paez Moncaleano, Alvaro Mauricio Montenegro

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This paper presents a novel statistical methodology for measuring and founding constructs in Latent Regression Analysis. This approach uses the qualities of Factor Analysis in binary data with interpretations on Item Response Theory (IRT). In addition, based on the fundamentals of submodel theory and with a convergence of many ideas of IRT, we propose an algorithm not just to solve the dimensionality problem (nowadays an open discussion) but a new research field that promises more fear and realistic qualifications for examiners and a revolution on IRT and educational research. In the end, the methodology is applied to a set of real data set presenting impressive results for the coherence, speed and precision. Acknowledgments: This research was financed by Colciencias through the project: 'Multidimensional Item Response Theory Models for Practical Application in Large Test Designed to Measure Multiple Constructs' and both authors belong to SICS Research Group from Universidad Nacional de Colombia.

Keywords: item response theory, dimensionality, submodel theory, factorial analysis

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Authors: Seyed Vahid Kamal Alavi

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Italy has experienced a notable quantity and impact of disasters due to natural hazards and technological accidents caused by diverse risk sources on its physical, technological, and human/sociological infrastructures during past decade. This study discusses the frequency and impacts of the most three physical devastating natural hazards in Italy for the period 2000–2013. The approach examines the reliability of a range of open source WebGIS techniques versus a proposed multi-hazard risk management methodology. Spatial and attribute data which include USGS publically available hazard data and thirteen years Munich RE recorded data for Italy with different severities have been processed, visualized in a GIS (Geographic Information System) framework. Comparison of results from the study showed that the multi-hazard risk maps generated using open source techniques do not provide a reliable system to analyze the infrastructures losses in respect to national risk sources while they can be adopted for general international risk management purposes. Additionally, this study establishes the possibility to critically examine and calibrate different integrated techniques in evaluating what better protection measures can be taken in an area.

Keywords: multi-hazard risk mapping, risk management, GIS, Italy

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Authors: Masilonyane Mokhele

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Across the world, different planning models of the so-called airport-led developments are becoming bandwagons hailed as key to the future of cities. However, in the existing knowledge, there is paucity of empirically informed description and explanation of the economic fundamentals driving the forces of attraction of airports. This void is arguably a result of the absence of an appropriate theoretical framework to guide the analyses. Given this paucity, the aim of the paper is to contribute towards a theoretical framework that could be used to describe and explain forces that drive the location and mix of airport-centric developments. Towards achieving this aim, the objectives of the paper are: one, to establish the type of economic activities that are located on and around O.R. Tambo International Airport (ORTIA), and analyse the reasons for locating there; two, to establish changes that have occurred over time in the form of the airport-centric development of ORTIA; three, to identify the propulsive economic qualities of ORTIA; four, to analyse the spatial, economic and structural linkages within the airport-centric development of ORTIA, between the airport-centric development and the airport, as well as the airport-centric development’s linkages with their metropolitan area and other regional, national and international airport-centric developments and locations. To address the objectives above, the study adopted a case study approach, centred on ORTIA in South Africa: Africa’s busiest airport in terms of passengers and airfreight handled. Using a lens of location theory, a survey was adopted as a main research method, wherein telephonic interviews were conducted with a representative number of firms on and around ORTIA. Other data collection methods encompassed in-depth qualitative interviews (to augment the information obtained through the survey) and analysis of secondary information, particularly as regards establishing changes that have occurred in the form of ORTIA and surrounds. From the empirical findings, ORTIA was discovered to have propulsive economic qualities that act as significant forces of attraction in the clustering of firms. Together with its airport-centric development, ORTIA was discovered to have growth pole properties because of the linkages that occur within the study area, and the linkages that exist between the airport-centric firms and the airport. It was noted that the transport-oriented firms (typified by couriers and freight carriers) act as anchors in some fellow airport-centric firms making use of elements of urbanisation economies, particularly as regards the use of the airport for airfreight services. The empirical findings presented in the paper (in conjunction with results from other airport-centric development case studies) could be used as contribution towards extending theory that describes and explains forces that drive the location and mix of airport-centric developments.

Keywords: airports, airport-centric development, O. R. Tambo international airport, South Africa

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Authors: Oussama Hafferssas, Hiba Benyahia, Amina Madani, Nassima Zeriri

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Although data nowadays has multiple forms; from text to images, and from audio to videos, yet text is still the most used one at a public level. At an academical and research level, and unlike other forms, text can be considered as the easiest form to process. Therefore, a brunch of Data Mining researches has been always under its shadow, called "Text Mining". Its concept is just like data mining’s, finding valuable patterns in data, from large collections and tremendous volumes of data, in this case: Text. Named entity recognition (NER) is one of Text Mining’s disciplines, it aims to extract and classify references such as proper names, locations, expressions of time and dates, organizations and more in a given text. Our approach "Octopub" does not aim to find new ways to improve named entity recognition process, rather than that it’s about finding a new, and yet smart way, to use NER in a way that we can extract sentiments of millions of people using Social Networks as a limitless information source, and Marketing for product promotion as the main domain of application.

Keywords: textmining, named entity recognition(NER), sentiment analysis, social media networks (SN, SMN), business intelligence(BI), marketing

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Authors: Basma Khelfa, Antoine Tordeux, Ibrahima Ba

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We present a descriptive analysis data of lane-changing events in multi-lane roads. The data are provided from The Highway Drone Dataset (HighD), which are microscopic trajectories in highway. This paper describes and analyses the role of the different parameters and their significance. Thanks to HighD data, we aim to find the most frequent reasons that motivate drivers to change lanes. We used the programming language R for the processing of these data. We analyze the involvement and relationship of different variables of each parameter of the ego vehicle and the four vehicles surrounding it, i.e., distance, speed difference, time gap, and acceleration. This was studied according to the class of the vehicle (car or truck), and according to the maneuver it undertook (overtaking or falling back).

Keywords: autonomous driving, physical traffic model, prediction model, statistical learning process

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Authors: Fathi Ali Swaid

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The CBR test is widely used in the assessment of granular materials in base, subbase and subgrade layers of road and airfield pavements. Despite the success of this method, but it depends on a limited numbers of soil samples. This limitation do not adequately account for the spatial variability of soil properties. Thus, assessment is derived using these cursory soil data are likely to contain errors and thus make interpretation and soil characterization difficult. On the other hand quantitative methods of soil inventory at the field scale involve the design and adoption of sampling regimes and laboratory analysis that are time consuming and costly. In the latter case new technologies are required to efficiently sample and observe the soil in the field. This is particularly the case where soil bearing capacity is prevalent, and detailed quantitative information for determining its cause is required. In this paper, an electrical resistivity method DC is described and its application in Elg'deem Dirt road, located in Gasser Ahmad - Misurata, Libya. Results from the DC instrument were found to be correlated with the CBR values (r2 = 0.89). Finally, it is noticed that, the correlation can be used with experience for determining CBR value using basic soil electrical resistivity measurements and checked by few CBR test representing a similar range of CBR.

Keywords: California bearing ratio, basic soil electrical resistivity, CBR, soil, subgrade, new technologies

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Authors: Ioan Corneliu Salisteanu, Valentin Dogaru Ulieru, Mihaita Nicolae Ardeleanu, Alin Pohoata, Bogdan Salisteanu, Stefan Broscareanu

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Creating a personalized statistic for an individual within the population using IT systems, based on the searches and intercepted spheres of interest they manifest, is just one 'atom' of the artificial intelligence analysis network. However, having the ability to generate statistics based on individual data intercepted from large demographic areas leads to reasoning like that issued by a human mind with global strategic ambitions. The DiaMOTO device is a technical sensory system that allows the interception of car events caused by a driver, positioning them in time and space. The device's connection to the vehicle allows the creation of a source of data whose analysis can create psychological, behavioural profiles of the drivers involved. The SiaMOTO system collects data from many vehicles equipped with DiaMOTO, driven by many different drivers with a unique fingerprint in their approach to driving. In this paper, we aimed to explain the software infrastructure of the SiaMOTO system, a system designed to monitor and improve driver driving behaviour, as well as the criteria and algorithms underlying the intelligent analysis process.

Keywords: artificial intelligence, data processing, driver behaviour, driver monitoring, SiaMOTO

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Authors: Dražen Cvitanić, Biljana Maljković

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This paper presents models for predicting operating speeds on tangent sections of two-lane rural roads developed on continuous speed data. The data corresponds to 20 drivers of different ages and driving experiences, driving their own cars along an 18 km long section of a state road. The data were first used for determination of maximum operating speeds on tangents and their comparison with speeds in the middle of tangents i.e. speed data used in most of operating speed studies. Analysis of continuous speed data indicated that the spot speed data are not reliable indicators of relevant speeds. After that, operating speed models for tangent sections were developed. There was no significant difference between models developed using speed data in the middle of tangent sections and models developed using maximum operating speeds on tangent sections. All developed models have higher coefficient of determination then models developed on spot speed data. Thus, it can be concluded that the method of measuring has more significant impact on the quality of operating speed model than the location of measurement.

Keywords: operating speed, continuous speed data, tangent sections, spot speed, consistency

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Authors: Mesbaholdin Salami, Farzad Movahedi Sobhani, Mohammad Sadegh Ghazizadeh

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Evaluation of organizational performance is among the most important measures that help organizations and entities continuously improve their efficiency. Organizations can use the existing data and results from the comparison of units under investigation to obtain an estimation of their performance. The Malmquist Productivity Index (MPI) is an important index in the evaluation of overall productivity, which considers technological developments and technical efficiency at the same time. This article proposed a model based on the multistage MPI, considering limited data (Grey’s theory). This model can evaluate the performance of units using limited and uncertain data in a multistage process. It was applied by the electricity market manager to Iran’s electric power supply chain (EPSC), which contains uncertain data, to evaluate the performance of its actors. Results from solving the model showed an improvement in the accuracy of future performance of the units under investigation, using the Grey’s system theory. This model can be used in all case studies, in which MPI is used and there are limited or uncertain data.

Keywords: Malmquist Index, Grey's Theory, CCR Model, network data envelopment analysis, Iran electricity power chain

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Authors: Sophy Joseph

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The study uses the concept of ‘Settler city’ to understand the nature of peripheralization that a neoliberal city initiates. The settler city designs powerless communities without inherent rights, title and sovereignty. Kathputli Colony, home to generations of artists/craftsmen, who have kept heritage of arts/crafts alive, has undergone eviction of its population from urban space. The proposed study, ‘Neoliberal Settler City: Socio-spatial segregation and livelihood of artists/craftsmen in Delhi’ would problematize the settler city as a colonial technology. The colonial regime has ‘erased’ the ‘unwanted’ as primitive and swept them to peripheries in the city. This study would also highlight how structural change in political economy has undermined their crafts/arts by depriving them from practicing/performing it with dignity in urban space. The interconnections between citizenship and In-Situ Private Public Partnership in Kathputli rehabilitation has become part of academic exercise. However, a comprehensive study connecting inherent characteristics of neoliberal settler city, trajectory of political economy of unorganized workers - artists/craftsmen and legal containment and exclusion leading to dispossession and marginalization of communities from the city site, is relevant to contextualize the trauma of spatial segregation. This study would deal with political, cultural, social and economic dominant behavior of the structure in the state formation, accumulation of property and design of urban space, fueled by segregation of marginalized/unorganized communities and disowning the ‘footloose proletariat’, the migrant workforce. The methodology of study involves qualitative research amongst communities and the field work-oral testimonies and personal accounts- becomes the primary material to theorize the realities. The secondary materials in the forms of archival materials about historical evolution of Delhi as a planned city from various archives, would be used. As the study also adopt ‘narrative approach’ in qualitative study, the life experiences of craftsmen/artists as performers and emotional trauma of losing their livelihood and space forms an important record to understand the instability and insecurity that marginalization and development attributes on urban poor. The study attempts to prove that though there was a change in political tradition from colonialism to constitutional democracy, new state still follows the policy of segregation and dispossession of the communities. It is this dispossession from the space, deprivation of livelihood and non-consultative process in rehabilitation that reflects the neoliberal approach of the state and also critical findings in the study. This study would entail critical spatial lens analyzing ethnographic and sociological data, representational practices and development debates to understand ‘urban otherization’ against craftsmen/artists. This seeks to develop a conceptual framework for understanding the resistance of communities against primitivity attached with them and to decolonize the city. This would help to contextualize the demand for declaring Kathputli Colony as ‘heritage artists village’. The conceptualization and contextualization would help to argue for right to city of the communities, collective rights to property, services and self-determination. The aspirations of the communities also help to draw normative orientation towards decolonization. It is important to study this site as part of the framework, ‘inclusive cities’ because cities are rarely noted as important sites of ‘community struggles’.

Keywords: neoliberal settler city, socio-spatial segregation, the livelihood of artists/craftsmen, dispossession of indigenous communities, urban planning and cultural uprooting

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Authors: V. Vicente E. Mujica, Gustavo Gonzalez

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The global coverage of broadband multimedia and internet-based services in terrestrial-satellite networks demand particular interests for satellite providers in order to enhance services with low latencies and high signal quality to diverse users. In particular, the delay of on-board processing is an inherent source of latency in a satellite communication that sometimes is discarded for the end-to-end delay of the satellite link. The frame work for this paper includes modelling of an on-orbit satellite payload using an agent model that can reproduce the properties of processing delays. In essence, a comparison of different spatial interpolation methods is carried out to evaluate physical data obtained by an GEO satellite in order to define a discretization function for determining that delay. Furthermore, the performance of the proposed agent and the development of a delay discretization function are together validated by simulating an hybrid satellite and terrestrial network. Simulation results show high accuracy according to the characteristics of initial data points of processing delay for Ku bands.

Keywords: terrestrial-satellite networks, latency, on-orbit satellite payload, simulation

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Authors: S. Nickolas, Shobha K.

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The treatment of incomplete data is an important step in the data pre-processing. Missing values creates a noisy environment in all applications and it is an unavoidable problem in big data management and analysis. Numerous techniques likes discarding rows with missing values, mean imputation, expectation maximization, neural networks with evolutionary algorithms or optimized techniques and hot deck imputation have been introduced by researchers for handling missing data. Among these, imputation techniques plays a positive role in filling missing values when it is necessary to use all records in the data and not to discard records with missing values. In this paper we propose a novel artificial neural network based clustering algorithm, Adaptive Resonance Theory-2(ART2) for imputation of missing values in mixed attribute data sets. The process of ART2 can recognize learned models fast and be adapted to new objects rapidly. It carries out model-based clustering by using competitive learning and self-steady mechanism in dynamic environment without supervision. The proposed approach not only imputes the missing values but also provides information about handling the outliers.

Keywords: ART2, data imputation, clustering, missing data, neural network, pre-processing

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Authors: Jelena R. Pejović, Nina N. Serdar

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This paper presents an analysis of the “Performance-Based” seismic design method, in order to overcome the perceived disadvantages and limitations of the existing seismic design approach based on force, in engineering practice. Bearing in mind, the specificity of the earthquake as a load and the fact that the seismic resistance of the structures solely depends on its behaviour in the nonlinear field, traditional seismic design approach based on force and linear analysis is not adequate. “Performance-Based” seismic design method is based on nonlinear analysis and can be used in everyday engineering practice. This paper presents the application of this method to eight-story high reinforced concrete building with combined structural system (reinforced concrete frame structural system in one direction and reinforced concrete ductile wall system in other direction). The nonlinear time-history analysis is performed on the spatial model of the structure using program Perform 3D, where the structure is exposed to forty real earthquake records. For considered building, large number of results were obtained. It was concluded that using this method we could, with a high degree of reliability, evaluate structural behavior under earthquake. It is obtained significant differences in the response of structures to various earthquake records. Also analysis showed that frame structural system had not performed well at the effect of earthquake records on soil like sand and gravel, while a ductile wall system had a satisfactory behavior on different types of soils.

Keywords: ductile wall, frame system, nonlinear time-history analysis, performance-based methodology, RC building

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Authors: Junaid Asimiyu Mohammed, Olakunle Docas Tosin

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The housing environment in many developing countries is fraught with risks that have potential negative impacts on the lives of the residents. The study examined the risk factors in residential areas of two neighborhoods in Bosso Local Government Areas of Minna in Nigeria with a view to determining the level of their potential impacts. A sample of 378 households was drawn from the estimated population of 22,751 household heads. The questionnaire and direct observation were used as instruments for data collection. The data collected were analyzed using the Relative Importance Index (RII) rule to determine the level of the potential impact of the risk factors while ArcGIS was used for mapping the spatial distribution of the risks. The study established that the housing environment of Angwan Biri and El-Waziri areas of Bosso is poor and vulnerable as 26% of the houses were not habitable and 57% were only fairly habitable. The risks of epidemics, building collapse and rainstorms were evident in the area as 53% of the houses had poor ventilation; 20% of residents had no access to toilets; 47% practiced open waste dumping; 46% of the houses had cracked walls while 52% of the roofs were weak and sagging. The results of the analysis of the potential impact of the risk factors indicate a RII score of 0.528 for building collapse, 0.758 for rainstorms and 0.830 for epidemics, indicating a moderate to very high level of potential impacts. The mean RII score of 0.639 shows a significant potential impact of the risk factors. The study recommends the implementation of sanitation measures, provision of basic urban facilities and neighborhood revitalization through housing infrastructure retrofitting as measures to mitigate the risks of disasters and improve the living conditions of the residents of the study area.

Keywords: assessment, risk, residential, Nigeria

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Authors: Volkan Kaya, Ersin Elbasi

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Watermarking and stenography are getting importance recently because of copyright protection and authentication. In watermarking we embed stamp, logo, noise or image to multimedia elements such as image, video, audio, animation and text. There are several works have been done in watermarking for different purposes. In this research work, we used watermarking techniques to embed patient information into the medical magnetic resonance (MR) images. There are two methods have been used; frequency domain (Digital Wavelet Transform-DWT, Digital Cosine Transform-DCT, and Digital Fourier Transform-DFT) and spatial domain (Least Significant Bits-LSB) domain. Experimental results show that embedding in frequency domains resist against one type of attacks, and embedding in spatial domain is resist against another group of attacks. Peak Signal Noise Ratio (PSNR) and Similarity Ratio (SR) values are two measurement values for testing. These two values give very promising result for information hiding in medical MR images.

Keywords: watermarking, medical image, frequency domain, least significant bits, security

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Authors: Brian Ceh, Alison Jackson-Holland

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Food deserts are a reality in some cities. These deserts can be described as a shortage of healthy food options within close proximity of consumers. The shortage in this case is typically facilitated by a lack of stores in an urban area that provide adequate fruit and vegetable choices. This study explores new avenues to better understand food deserts by examining modes of transportation that are available to shoppers or consumers, e.g. walking, automobile, or public transit. Further, this study is unique in that it not only explores the location of large grocery stores, but small grocery and convenience stores too. In this study, the relationship between some socio-economic indicators, such as personal income, are also explored to determine any possible association with food deserts. In addition, to help facilitate our understanding of food deserts, complex network spatial models that are built on adequate algorithms are used to investigate the possibility of food deserts in the city of Hamilton, Canada. It is found that Hamilton, Canada is adequate serviced by retailers who provide healthy food choices and that the food desert phenomena is almost absent.

Keywords: Canada, desert, food, Hamilton, store

Procedia PDF Downloads 223

Authors: Abbas Raza Ali

Abstract:

Big Data technology is gradually becoming a dire need of large enterprises. These enterprises are generating massively large amount of off-line and streaming data in both structured and unstructured formats on daily basis. It is a challenging task to effectively extract useful insights from the large scale datasets, even though sometimes it becomes a technology constraint to manage transactional data history of more than a few months. This paper presents a framework to efficiently manage massively large and complex datasets. The framework has been tested on a communication service provider producing massively large complex streaming data in binary format. The communication industry is bound by the regulators to manage history of their subscribers’ call records where every action of a subscriber generates a record. Also, managing and analyzing transactional data allows service providers to better understand their customers’ behavior, for example, deep packet inspection requires transactional internet usage data to explain internet usage behaviour of the subscribers. However, current relational database systems limit service providers to only maintain history at semantic level which is aggregated at subscriber level. The framework addresses these challenges by leveraging Big Data technology which optimally manages and allows deep analysis of complex datasets. The framework has been applied to offload existing Intelligent Network Mediation and relational Data Warehouse of the service provider on Big Data. The service provider has 50+ million subscriber-base with yearly growth of 7-10%. The end-to-end process takes not more than 10 minutes which involves binary to ASCII decoding of call detail records, stitching of all the interrogations against a call (transformations) and aggregations of all the call records of a subscriber.

Keywords: big data, communication service providers, enterprise data warehouse, stream computing, Telco IN Mediation

Procedia PDF Downloads 155

Authors: M. Goodarzi, M. Mohammadi, A. Gharib

Abstract:

Solar energy is a renewable energy which has attracted special attention in many countries. Solar cathodic protectionsystems harness the sun’senergy to protect underground pipelinesand tanks from galvanic corrosion. The object of this study is to design and the economic analysis a cathodic protection system by impressed current supplied with solar energy panels applied to underground pipelines. In the present study, the technical and economic analysis of using solar energy for cathodic protection system in southwestern of Iran (Khuzestan province) is investigated. For this purpose, the ecological conditions such as the weather data, air clearness and sunshine hours are analyzed. The economic analyses were done using computer code to investigate the feasibility analysis from the using of various energy sources in order to cathodic protection system. The overall research methodology is divided into four components: Data collection, design of elements, techno economical evaluation, and output analysis. According to the results, solar renewable energy systems can supply adequate power for cathodic protection system purposes.

Keywords: renewable energy, solar energy, solar cathodic protection station, lifecycle cost method

Procedia PDF Downloads 519

Authors: Armin Rahimi

Abstract:

In this study, we reveal co-seismic signals of two combined earthquakes, the 2006 Mw8.3 thrust and 2007 Mw8.1 normal fault earthquakes of the central Kuril Islands from GRACE observations. We compute monthly full gravitational gradient tensor in the local north-east-down frame for Kuril Islands earthquakes without spatial averaging and de-striping filters. Some of the gravitational gradient components (e.g. ΔVxx, ΔVxz) enhance high frequency components of the earth gravity field and reveal more details in spatial and temporal domain. Therefore that preseismic activity can be better illustrated. We show that the positive-negative-positive co-seismic ΔVxx due to the Kuril Islands earthquakes ranges from − 0.13 to + 0.11 milli Eötvös, and ΔVxz shows a positive-negative-positive pattern ranges from − 0.16 to + 0.13 milli Eötvös, agree well with seismic model predictions.

Keywords: GRACE observation, gravitational gradient changes, Kuril island earthquakes, PSGRN/PSCMP

Procedia PDF Downloads 256

Authors: David Ming Liu, Benjamin Hirsch, Bashir Aden

Abstract:

Syndromic surveillance is to detect or predict disease outbreaks through the analysis of medical sources of data. Using social media data like tweets to do syndromic surveillance becomes more and more popular with the aid of open platform to collect data and the advantage of microblogging text and mobile geographic location features. In this paper, a Syndromic Surveillance Framework is presented with machine learning kernel using tweets data analytics. Influenza and the three cities Abu Dhabi, Al Ain and Dubai of United Arabic Emirates are used as the test disease and trial areas. Hospital cases data provided by the Health Authority of Abu Dhabi (HAAD) are used for the correlation purpose. In our model, Latent Dirichlet allocation (LDA) engine is adapted to do supervised learning classification and N-Fold cross validation confusion matrix are given as the simulation results with overall system recall 85.595% performance achieved.

Keywords: Syndromic surveillance, Tweets, Machine Learning, data mining, Latent Dirichlet allocation (LDA), Influenza

Procedia PDF Downloads 96

Authors: Jefriza, Habibah Lateh, Saumi Syahreza

Abstract:

The 2016 Mw 6.5 Pidie Jaya earthquake is one of the biggest disasters that has occurred in Aceh within the last five years. This earthquake has caused severe damage to many infrastructures such as schools, hospitals, mosques, and houses in the district of Pidie Jaya and surrounding areas. Earthquakes commonly occur in Aceh Province due to the Aceh-Sumatra is located in the convergent boundaries of the Sunda Plate subducted beneath the Indo-Australian Plate. This convergence is responsible for the intensification of seismicity in this region. The plates are tilted at a speed of 63 mm per year and the right lateral component is accommodated by strike- slip faulting within Sumatra, mainly along the great Sumatran fault. This paper presents preliminary findings of InSAR study aimed at investigating the co-seismic surface deformation pattern in Pidie Jaya, Aceh-Indonesia. Coseismic surface deformation is rapid displacement that occurs at the time of an earthquake. Coseismic displacement mapping is required to study the behavior of seismic faults. InSAR is a powerful tool for measuring Earth surface deformation to a precision of a few centimetres. In this study, two radar images of the same area but at two different times are required to detect changes in the Earth’s surface. The ascending and descending Sentinel-1A (S1A) synthetic aperture radar (SAR) data and Sentinels application platform (SNAP) toolbox were used to generate SAR interferogram image. In order to visualize the InSAR interferometric, the S1A from both master (26 Nov 2016) and slave data-sets (26 Dec 2016) were utilized as the main data source for mapping the coseismic surface deformation. The results show that the fringes of phase difference have appeared in the border region as a result of the movement that was detected with interferometric technique. On the other hand, the dominant fringes pattern also appears near the coastal area, this is consistent with the field investigations two days after the earthquake. However, the study has also limitations of resolution and atmospheric artefacts in SAR interferograms. The atmospheric artefacts are caused by changes in the atmospheric refractive index of the medium, as a result, has limitation to produce coherence image. Low coherence will be affected the result in creating fringes (movement can be detected by fringes). The spatial resolution of the Sentinel satellite has not been sufficient for studying land surface deformation in this area. Further studies will also be investigated using both ALOS and TerraSAR-X. ALOS and TerraSAR-X improved the spatial resolution of SAR satellite.

Keywords: earthquake, InSAR, interferometric, Sentinel-1A

Procedia PDF Downloads 180