Search results for: spatial features
4887 A Bayesian Hierarchical Poisson Model with an Underlying Cluster Structure for the Analysis of Measles in Colombia
Authors: Ana Corberan-Vallet, Karen C. Florez, Ingrid C. Marino, Jose D. Bermudez
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In 2016, the Region of the Americas was declared free of measles, a viral disease that can cause severe health problems. However, since 2017, measles has reemerged in Venezuela and has subsequently reached neighboring countries. In 2018, twelve American countries reported confirmed cases of measles. Governmental and health authorities in Colombia, a country that shares the longest land boundary with Venezuela, are aware of the need for a strong response to restrict the expanse of the epidemic. In this work, we apply a Bayesian hierarchical Poisson model with an underlying cluster structure to describe disease incidence in Colombia. Concretely, the proposed methodology provides relative risk estimates at the department level and identifies clusters of disease, which facilitates the implementation of targeted public health interventions. Socio-demographic factors, such as the percentage of migrants, gross domestic product, and entry routes, are included in the model to better describe the incidence of disease. Since the model does not impose any spatial correlation at any level of the model hierarchy, it avoids the spatial confounding problem and provides a suitable framework to estimate the fixed-effect coefficients associated with spatially-structured covariates.Keywords: Bayesian analysis, cluster identification, disease mapping, risk estimation
Procedia PDF Downloads 1474886 Novel Fluorescent High Density Polyethylene Composites for Fused Deposition Modeling 3D Printing in Packaging Security Features
Authors: Youssef R. Hassan, Mohamed S. Hasanin, Reda M. Abdelhameed
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Recently, innovations in packaging security features become more important to see the originality of packaging in industrial application. Luminescent 3d printing materials have been a promising property which can provides a unique opportunity for the design and application of 3D printing. Lack emission of terbium ions, as a source of green emission, in salt form prevent its uses in industrial applications, so searching about stable and highly emitter material become essential. Nowadays, metal organic frameworks (MOFs) play an important role in designing light emitter material. In this work, fluorescent high density polyethylene (FHDPE) composite filament with Tb-benzene 1,3,5-tricarboxylate (Tb-BTC) MOFs for 3D printing have been successfully developed.HDPE pellets were mixed with Tb-BTC and melting extrustion with single screw extruders. It was found that Tb-BTCuniformly dispersed in the HDPE matrix and significantly increased the crystallinity of PE, which not only maintained the good thermal property but also improved the mechanical properties of Tb-BTC@HDPE composites. Notably, the composite filaments emitted ultra-bright green light under UV lamp, and the fluorescence intensity increased as the content of Tb-BTC increased. Finally, several brightly luminescent exquisite articles could be manufactured by fused deposition modeling (FDM) 3D printer with these new fluorescent filaments. In this context, the development of novel fluorescent Tb-BTC@HDPE composites was combined with 3D printing technology to amplified the packaging Security Features.Keywords: 3D printing, fluorescent, packaging, security
Procedia PDF Downloads 924885 Stream Extraction from 1m-DTM Using ArcGIS
Authors: Jerald Ruta, Ricardo Villar, Jojemar Bantugan, Nycel Barbadillo, Jigg Pelayo
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Streams are important in providing water supply for industrial, agricultural and human consumption, In short when there are streams there are lives. Identifying streams are essential since many developed cities are situated in the vicinity of these bodies of water and in flood management, it serves as basin for surface runoff within the area. This study aims to process and generate features from high-resolution digital terrain model (DTM) with 1-meter resolution using Hydrology Tools of ArcGIS. The raster was then filled, processed flow direction and accumulation, then raster calculate and provide stream order, converted to vector, and clearing undesirable features using the ancillary or google earth. In field validation streams were classified whether perennial, intermittent or ephemeral. Results show more than 90% of the extracted feature were accurate in assessment through field validation.Keywords: digital terrain models, hydrology tools, strahler method, stream classification
Procedia PDF Downloads 2644884 Simulation and Experimental Study on Dual Dense Medium Fluidization Features of Air Dense Medium Fluidized Bed
Authors: Cheng Sheng, Yuemin Zhao, Chenlong Duan
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Air dense medium fluidized bed is a typical application of fluidization techniques for coal particle separation in arid areas, where it is costly to implement wet coal preparation technologies. In the last three decades, air dense medium fluidized bed, as an efficient dry coal separation technique, has been studied in many aspects, including energy and mass transfer, hydrodynamics, bubbling behaviors, etc. Despite numerous researches have been published, the fluidization features, especially dual dense medium fluidization features have been rarely reported. In dual dense medium fluidized beds, different combinations of different dense mediums play a significant role in fluidization quality variation, thus influencing coal separation efficiency. Moreover, to what extent different dense mediums mix and to what extent the two-component particulate mixture affects the fluidization performance and quality have been in suspense. The proposed work attempts to reveal underlying mechanisms of generation and evolution of two-component particulate mixture in the fluidization process. Based on computational fluid dynamics methods and discrete particle modelling, movement and evolution of dual dense mediums in air dense medium fluidized bed have been simulated. Dual dense medium fluidization experiments have been conducted. Electrical capacitance tomography was employed to investigate the distribution of two-component mixture in experiments. Underlying mechanisms involving two-component particulate fluidization are projected to be demonstrated with the analysis and comparison of simulation and experimental results.Keywords: air dense medium fluidized bed, particle separation, computational fluid dynamics, discrete particle modelling
Procedia PDF Downloads 3744883 Learning Dynamic Representations of Nodes in Temporally Variant Graphs
Authors: Sandra Mitrovic, Gaurav Singh
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In many industries, including telecommunications, churn prediction has been a topic of active research. A lot of attention has been drawn on devising the most informative features, and this area of research has gained even more focus with spread of (social) network analytics. The call detail records (CDRs) have been used to construct customer networks and extract potentially useful features. However, to the best of our knowledge, no studies including network features have yet proposed a generic way of representing network information. Instead, ad-hoc and dataset dependent solutions have been suggested. In this work, we build upon a recently presented method (node2vec) to obtain representations for nodes in observed network. The proposed approach is generic and applicable to any network and domain. Unlike node2vec, which assumes a static network, we consider a dynamic and time-evolving network. To account for this, we propose an approach that constructs the feature representation of each node by generating its node2vec representations at different timestamps, concatenating them and finally compressing using an auto-encoder-like method in order to retain reasonably long and informative feature vectors. We test the proposed method on churn prediction task in telco domain. To predict churners at timestamp ts+1, we construct training and testing datasets consisting of feature vectors from time intervals [t1, ts-1] and [t2, ts] respectively, and use traditional supervised classification models like SVM and Logistic Regression. Observed results show the effectiveness of proposed approach as compared to ad-hoc feature selection based approaches and static node2vec.Keywords: churn prediction, dynamic networks, node2vec, auto-encoders
Procedia PDF Downloads 3064882 Tempo-Spatial Pattern of Progress and Disparity in Child Health in Uttar Pradesh, India
Authors: Gudakesh Yadav
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Uttar Pradesh is one of the poorest performing states of India in terms of child health. Using data from the three round of NFHS and two rounds of DLHS, this paper attempts to examine tempo-spatial change in child health and care practices in Uttar Pradesh and its regions. Rate-ratio, CI, multivariate, and decomposition analysis has been used for the study. Findings demonstrate that child health care practices have improved over the time in all regions of the state. However; western and southern region registered the lowest progress in child immunization. Nevertheless, there is no decline in prevalence of diarrhea and ARI over the period, and it remains critically high in the western and southern region. These regions also poorly performed in giving ORS, diarrhoea and ARI treatment. Public health services are least preferred for diarrhoea and ARI treatment. Results from decomposition analysis reveal that rural area, mother’s illiteracy and wealth contributed highest to the low utilization of the child health care practices consistently over the period of time. The study calls for targeted intervention for vulnerable children to accelerate child health care service utilization. Poor performing regions should be targeted and routinely monitored on poor child health indicators.Keywords: Acute Respiratory Infection (ARI), decomposition, diarrhea, inequality, immunization
Procedia PDF Downloads 2914881 Spatial Variability of Soil Metal Contamination to Detect Cancer Risk Zones in Coimbatore Region of India
Authors: Aarthi Mariappan, Janani Selvaraj, P. B. Harathi, M. Prashanthi Devi
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Anthropogenic modification of the urban environment has largely increased in the recent years in order to sustain the growing human population. Intense industrial activity, permanent and high traffic on the roads, a developed subterranean infrastructure network, land use patterns are just some specific characteristics. Every day, the urban environment is polluted by more or less toxic emissions, organic or metals wastes discharged from specific activities such as industrial, commercial, municipal. When these eventually deposit into the soil, the physical and chemical properties of the surrounding soil is changed, transforming it into a human exposure indicator. Metals are non-degradable and occur cumulative in soil due to regular deposits are a result of permanent human activity. Due to this, metals are a contaminant factor for soil when persistent over a long period of time and a possible danger for inhabitant’s health on prolonged exposure. Metals accumulated in contaminated soil may be transferred to humans directly, by inhaling the dust raised from top soil, or by ingesting, or by dermal contact and indirectly, through plants and animals grown on contaminated soil and used for food. Some metals, like Cu, Mn, Zn, are beneficial for human’s health and represent a danger only if their concentration is above permissible levels, but other metals, like Pb, As, Cd, Hg, are toxic even at trace level causing gastrointestinal and lung cancers. In urban areas, metals can be emitted from a wide variety of sources like industrial, residential, commercial activities. Our study interrogates the spatial distribution of heavy metals in soil in relation to their permissible levels and their association with the health risk to the urban population in Coimbatore, India. Coimbatore region is a high cancer risk zone and case records of gastro intestinal and respiratory cancer patients were collected from hospitals and geocoded in ArcGIS10.1. The data of patients pertaining to the urban limits were retained and checked for their diseases history based on their diagnosis and treatment. A disease map of cancer was prepared to show the disease distribution. It has been observed that in our study area Cr, Pb, As, Fe and Mg exceeded their permissible levels in the soil. Using spatial overlay analysis a relationship between environmental exposure to these potentially toxic elements in soil and cancer distribution in Coimbatore district was established to show areas of cancer risk. Through this, our study throws light on the impact of prolonged exposure to soil contamination in soil in the urban zones, thereby exploring the possibility to detect cancer risk zones and to create awareness among the exposed groups on cancer risk.Keywords: soil contamination, cancer risk, spatial analysis, India
Procedia PDF Downloads 3974880 The Involvement of Visual and Verbal Representations Within a Quantitative and Qualitative Visual Change Detection Paradigm
Authors: Laura Jenkins, Tim Eschle, Joanne Ciafone, Colin Hamilton
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An original working memory model suggested the separation of visual and verbal systems in working memory architecture, in which only visual working memory components were used during visual working memory tasks. It was later suggested that the visuo spatial sketch pad was the only memory component at use during visual working memory tasks, and components such as the phonological loop were not considered. In more recent years, a contrasting approach has been developed with the use of an executive resource to incorporate both visual and verbal representations in visual working memory paradigms. This was supported using research demonstrating the use of verbal representations and an executive resource in a visual matrix patterns task. The aim of the current research is to investigate the working memory architecture during both a quantitative and a qualitative visual working memory task. A dual task method will be used. Three secondary tasks will be used which are designed to hit specific components within the working memory architecture – Dynamic Visual Noise (visual components), Visual Attention (spatial components) and Verbal Attention (verbal components). A comparison of the visual working memory tasks will be made to discover if verbal representations are at use, as the previous literature suggested. This direct comparison has not been made so far in the literature. Considerations will be made as to whether a domain specific approach should be employed when discussing visual working memory tasks, or whether a more domain general approach could be used instead.Keywords: semantic organisation, visual memory, change detection
Procedia PDF Downloads 5854879 AS-Geo: Arbitrary-Sized Image Geolocalization with Learnable Geometric Enhancement Resizer
Authors: Huayuan Lu, Chunfang Yang, Ma Zhu, Baojun Qi, Yaqiong Qiao, Jiangqian Xu
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Image geolocalization has great application prospects in fields such as autonomous driving and virtual/augmented reality. In practical application scenarios, the size of the image to be located is not fixed; it is impractical to train different networks for all possible sizes. When its size does not match the size of the input of the descriptor extraction model, existing image geolocalization methods usually directly scale or crop the image in some common ways. This will result in the loss of some information important to the geolocalization task, thus affecting the performance of the image geolocalization method. For example, excessive down-sampling can lead to blurred building contour, and inappropriate cropping can lead to the loss of key semantic elements, resulting in incorrect geolocation results. To address this problem, this paper designs a learnable image resizer and proposes an arbitrary-sized image geolocation method. (1) The designed learnable image resizer employs the self-attention mechanism to enhance the geometric features of the resized image. Firstly, it applies bilinear interpolation to the input image and its feature maps to obtain the initial resized image and the resized feature maps. Then, SKNet (selective kernel net) is used to approximate the best receptive field, thus keeping the geometric shapes as the original image. And SENet (squeeze and extraction net) is used to automatically select the feature maps with strong contour information, enhancing the geometric features. Finally, the enhanced geometric features are fused with the initial resized image, to obtain the final resized images. (2) The proposed image geolocalization method embeds the above image resizer as a fronting layer of the descriptor extraction network. It not only enables the network to be compatible with arbitrary-sized input images but also enhances the geometric features that are crucial to the image geolocalization task. Moreover, the triplet attention mechanism is added after the first convolutional layer of the backbone network to optimize the utilization of geometric elements extracted by the first convolutional layer. Finally, the local features extracted by the backbone network are aggregated to form image descriptors for image geolocalization. The proposed method was evaluated on several mainstream datasets, such as Pittsburgh30K, Tokyo24/7, and Places365. The results show that the proposed method has excellent size compatibility and compares favorably to recently mainstream geolocalization methods.Keywords: image geolocalization, self-attention mechanism, image resizer, geometric feature
Procedia PDF Downloads 2074878 Solventless C−C Coupling of Low Carbon Furanics to High Carbon Fuel Precursors Using an Improved Graphene Oxide Carbocatalyst
Authors: Ashish Bohre, Blaž Likozar, Saikat Dutta, Dionisios G. Vlachos, Basudeb Saha
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Graphene oxide, decorated with surface oxygen functionalities, has emerged as a sustainable alternative to precious metal catalysts for many reactions. Herein, we report for the first time that graphene oxide becomes super active for C-C coupling upon incorporation of multilayer crystalline features, highly oxidized surface, Brønsted acidic functionalities and defect sites on the surface and edges via modified oxidation. The resulting improved graphene oxide (IGO) demonstrates superior activity to commonly used framework zeolites for upgrading of low carbon biomass furanics to long carbon chain aviation fuel precursors. A maximum 95% yield of C15 fuel precursor with high selectivity is obtained at low temperature (60 C) and neat conditions via hydroxyalkylation/alkylation (HAA) of 2-methylfuran (2-MF) and furfural. The coupling of 2-MF with carbonyl molecules ranging from C3 to C6 produced the precursors of carbon numbers 12 to 21. The catalyst becomes inactive in the 4th cycle due to the loss of oxygen functionalities, defect sites and multilayer features; however, regains comparable activity upon regeneration. Extensive microscopic and spectroscopic characterization of the fresh and reused IGO is presented to elucidate high activity of IGO and to establish a correlation between activity and surface and structural properties. Kinetic Monte Carlo (KMC) and density functional theory (DFT) calculations are presented to further illustrate the surface features and the reaction mechanism.Keywords: methacrylic acid, itaconic acid, biomass, monomer, solid base catalyst
Procedia PDF Downloads 1664877 Identifying Environmental Adaptive Genetic Loci in Caloteropis Procera (Estabragh): Population Genetics and Landscape Genetic Analyses
Authors: Masoud Sheidaei, Mohammad-Reza Kordasti, Fahimeh Koohdar
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Calotropis procera (Aiton) W.T.Aiton, (Apocynaceae), is an economically and medicinally important plant species which is an evergreen, perennial shrub growing in arid and semi-arid climates, and can tolerate very low annual rainfall (150 mm) and a dry season. The plant can also tolerate temperature ran off 20 to30°C and is not frost tolerant. This plant species prefers free-draining sandy soils but can grow also in alkaline and saline soils.It is found at a range of altitudes from exposed coastal sites to medium elevations up to 1300 m. Due to morpho-physiological adaptations of C. procera and its ability to tolerate various abiotic stresses. This taxa can compete with desirable pasture species and forms dense thickets that interfere with stock management, particularly mustering activities. Caloteropis procera grows only in southern part of Iran where in comprises a limited number of geographical populations. We used different population genetics and r landscape analysis to produce data on geographical populations of C. procera based on molecular genetic study using SCoT molecular markers. First, we used spatial principal components (sPCA), as it can analyze data in a reduced space and can be used for co-dominant markers as well as presence / absence data as is the case in SCoT molecular markers. This method also carries out Moran I and Mantel tests to reveal spatial autocorrelation and test for the occurrence of Isolation by distance (IBD). We also performed Random Forest analysis to identify the importance of spatial and geographical variables on genetic diversity. Moreover, we used both RDA (Redundency analysis), and LFMM (Latent factor mixed model), to identify the genetic loci significantly associated with geographical variables. A niche modellng analysis was carried our to predict present potential area for distribution of these plants and also the area present by the year 2050. The results obtained will be discussed in this paper.Keywords: population genetics, landscape genetic, Calotreropis procera, niche modeling, SCoT markers
Procedia PDF Downloads 864876 Orthosis and Finite Elements: A Study for Development of New Designs through Additive Manufacturing
Authors: M. Volpini, D. Alves, A. Horta, M. Borges, P. Reis
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The gait pattern in people that present motor limitations foment the demand for auxiliary locomotion devices. These artifacts for movement assistance vary according to its shape, size and functional features, following the clinical applications desired. Among the ortheses of lower limbs, the ankle-foot orthesis aims to improve the ability to walk in people with different neuromuscular limitations, although they do not always answer patients' expectations for their aesthetic and functional characteristics. The purpose of this study is to explore the possibility of using new design in additive manufacturer to reproduce the shape and functional features of a ankle-foot orthesis in an efficient and modern way. Therefore, this work presents a study about the performance of the mechanical forces through the analysis of finite elements in an ankle-foot orthesis. It will be demonstrated a study of distribution of the stress on the orthopedic device in orthostatism and during the movement in the course of patient's walk.Keywords: additive manufacture, new designs, orthoses, finite elements
Procedia PDF Downloads 2034875 Spatial Assessment of Creek Habitats of Marine Fish Stock in Sindh Province
Authors: Syed Jamil H. Kazmi, Faiza Sarwar
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The Indus delta of Sindh Province forms the largest creeks zone of Pakistan. The Sindh coast starts from the mouth of Hab River and terminates at Sir Creek area. In this paper, we have considered the major creeks from the site of Bin Qasim Port in Karachi to Jetty of Keti Bunder in Thatta District. A general decline in the mangrove forest has been observed that within a span of last 25 years. The unprecedented human interventions damage the creeks habitat badly which includes haphazard urban development, industrial and sewage disposal, illegal cutting of mangroves forest, reduced and inconsistent fresh water flow mainly from Jhang and Indus rivers. These activities not only harm the creeks habitat but affected the fish stock substantially. Fishing is the main livelihood of coastal people but with the above-mentioned threats, it is also under enormous pressure by fish catches resulted in unchecked overutilization of the fish resources. This pressure is almost unbearable when it joins with deleterious fishing methods, uncontrolled fleet size, increase trash and by-catch of juvenile and illegal mesh size. Along with these anthropogenic interventions study area is under the red zone of tropical cyclones and active seismicity causing floods, sea intrusion, damage mangroves forests and devastation of fish stock. In order to sustain the natural resources of the Indus Creeks, this study was initiated with the support of FAO, WWF and NIO, the main purpose was to develop a Geo-Spatial dataset for fish stock assessment. The study has been spread over a year (2013-14) on monthly basis which mainly includes detailed fish stock survey, water analysis and few other environmental analyses. Environmental analysis also includes the habitat classification of study area which has done through remote sensing techniques for 22 years’ time series (1992-2014). Furthermore, out of 252 species collected, fifteen species from estuarine and marine groups were short-listed to measure the weight, health and growth of fish species at each creek under GIS data through SPSS system. Furthermore, habitat suitability analysis has been conducted by assessing the surface topographic and aspect derivation through different GIS techniques. The output variables then overlaid in GIS system to measure the creeks productivity. Which provided the results in terms of subsequent classes: extremely productive, highly productive, productive, moderately productive and less productive. This study has revealed the Geospatial tools utilization along with the evaluation of the fisheries resources and creeks habitat risk zone mapping. It has also been identified that the geo-spatial technologies are highly beneficial to identify the areas of high environmental risk in Sindh Creeks. This has been clearly discovered from this study that creeks with high rugosity are more productive than the creeks with low levels of rugosity. The study area has the immense potential to boost the economy of Pakistan in terms of fish export, if geo-spatial techniques are implemented instead of conventional techniques.Keywords: fish stock, geo-spatial, productivity analysis, risk
Procedia PDF Downloads 2414874 Feature Selection for Production Schedule Optimization in Transition Mines
Authors: Angelina Anani, Ignacio Ortiz Flores, Haitao Li
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The use of underground mining methods have increased significantly over the past decades. This increase has also been spared on by several mines transitioning from surface to underground mining. However, determining the transition depth can be a challenging task, especially when coupled with production schedule optimization. Several researchers have simplified the problem by excluding operational features relevant to production schedule optimization. Our research objective is to investigate the extent to which operational features of transition mines accounted for affect the optimal production schedule. We also provide a framework for factors to consider in production schedule optimization for transition mines. An integrated mixed-integer linear programming (MILP) model is developed that maximizes the NPV as a function of production schedule and transition depth. A case study is performed to validate the model, with a comparative sensitivity analysis to obtain operational insights.Keywords: underground mining, transition mines, mixed-integer linear programming, production schedule
Procedia PDF Downloads 1624873 Cervical Cell Classification Using Random Forests
Authors: Dalwinder Singh, Amandeep Verma, Manpreet Kaur, Birmohan Singh
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The detection of pre-cancerous changes using a Pap smear test of cervical cell is the important step for the early diagnosis of cervical cancer. The Pap smear test consists of a sample of human cells taken from the cervix which are analysed to detect cancerous and pre-cancerous stage of the given subject. The manual analysis of these cells is labor intensive and time consuming process which relies on expert cytotechnologist. In this paper, a computer assisted system for the automated analysis of the cervical cells has been proposed. We propose a morphology based approach to the nucleus detection and segmentation of the cytoplasmic region of the given single or multiple overlapped cell. Further, various texture and region based features are calculated from these cells to classify these into normal and abnormal cell. Experimental results on public available dataset show that our system has achieved satisfactory success rate.Keywords: cervical cancer, cervical tissue, mathematical morphology, texture features
Procedia PDF Downloads 5174872 Time-Frequency Modelling and Analysis of Faulty Rotor
Authors: B. X. Tchomeni, A. A. Alugongo, T. B. Tengen
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In this paper, de Laval rotor system has been characterized by a hinge model and its transient response numerically treated for a dynamic solution. The effect of the ensuing non-linear disturbances namely rub and breathing crack is numerically simulated. Subsequently, three analysis methods: Orbit Analysis, Fast Fourier Transform (FFT) and Wavelet Transform (WT) are employed to extract features of the vibration signal of the faulty system. An analysis of the system response orbits clearly indicates the perturbations due to the rotor-to-stator contact. The sensitivities of WT to the variation in system speed have been investigated by Continuous Wavelet Transform (CWT). The analysis reveals that features of crack, rubs and unbalance in vibration response can be useful for condition monitoring. WT reveals its ability to detect non-linear signal, and obtained results provide a useful tool method for detecting machinery faults.Keywords: Continuous wavelet, crack, discrete wavelet, high acceleration, low acceleration, nonlinear, rotor-stator, rub
Procedia PDF Downloads 3424871 Mathematical Study of CO₂ Dispersion in Carbonated Water Injection Enhanced Oil Recovery Using Non-Equilibrium 2D Simulator
Authors: Ahmed Abdulrahman, Jalal Foroozesh
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CO₂ based enhanced oil recovery (EOR) techniques have gained massive attention from major oil firms since they resolve the industry's two main concerns of CO₂ contribution to the greenhouse effect and the declined oil production. Carbonated water injection (CWI) is a promising EOR technique that promotes safe and economic CO₂ storage; moreover, it mitigates the pitfalls of CO₂ injection, which include low sweep efficiency, early CO₂ breakthrough, and the risk of CO₂ leakage in fractured formations. One of the main challenges that hinder the wide adoption of this EOR technique is the complexity of accurate modeling of the kinetics of CO₂ mass transfer. The mechanisms of CO₂ mass transfer during CWI include the slow and gradual cross-phase CO₂ diffusion from carbonated water (CW) to the oil phase and the CO₂ dispersion (within phase diffusion and mechanical mixing), which affects the oil physical properties and the spatial spreading of CO₂ inside the reservoir. A 2D non-equilibrium compositional simulator has been developed using a fully implicit finite difference approximation. The material balance term (k) was added to the governing equation to account for the slow cross-phase diffusion of CO₂ from CW to the oil within the gird cell. Also, longitudinal and transverse dispersion coefficients have been added to account for CO₂ spatial distribution inside the oil phase. The CO₂-oil diffusion coefficient was calculated using the Sigmund correlation, while a scale-dependent dispersivity was used to calculate CO₂ mechanical mixing. It was found that the CO₂-oil diffusion mechanism has a minor impact on oil recovery, but it tends to increase the amount of CO₂ stored inside the formation and slightly alters the residual oil properties. On the other hand, the mechanical mixing mechanism has a huge impact on CO₂ spatial spreading (accurate prediction of CO₂ production) and the noticeable change in oil physical properties tends to increase the recovery factor. A sensitivity analysis has been done to investigate the effect of formation heterogeneity (porosity, permeability) and injection rate, it was found that the formation heterogeneity tends to increase CO₂ dispersion coefficients, and a low injection rate should be implemented during CWI.Keywords: CO₂ mass transfer, carbonated water injection, CO₂ dispersion, CO₂ diffusion, cross phase CO₂ diffusion, within phase CO2 diffusion, CO₂ mechanical mixing, non-equilibrium simulation
Procedia PDF Downloads 1624870 Assessment of Spatial and Vertical Distribution of Heavy Metals in the Mid Sand Bars of Brahmaputra River in Assam, India
Authors: Vijay Meena, Arup Kumar Sarma, Chandan Mahanta
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The environment has been getting contaminated by anthropogenic processes including those that discharge heavy metals to air, soil and water. The present work emphasizes the spatial distribution and vertical profile of six heavy metals (Cu, Zn, Mn, Ni, Fe, Cr) in three layers of mid sand bars (bed surface layer, 50 cm and 100 cm depth) at 42 sampling stations covering around 600 km stretch of the Brahmaputra River, India. Heavy metal analysis was conducted on the sample collected from mid-sand bars in the river stretch to examine the impact of dredging for various hydrological operations in the future. Sediment quality was assessed by calculating six different indices viz., EF, CF, CD, PLI, Igeo, and PERI. In all sediment layers, heavy metal concentrations have been observed to be the same as listed, Fe > Mn > Zn > Ni > Cr > Cu in μg/g. The average concentration of Cu, Mn, and Fe was found in the middle layer while Zn, Ni, and Cr were in the Surface layer. EF indicates higher enrichment in reach 2 which is likely to be due to anthropogenic sources of industrial and urbanized effluents. The sediment of the mid-sand bar was generally found moderately polluted possessing low risk to aquatic lives and the environment. Suggesting, Dredging can be possible in the future. An examination of correlation matrices, principal components analysis, and cluster analyses indicated that these heavy metals possess similar anthropogenic origins for their enrichment.Keywords: heavy metal contamination, risk assessment, anthropogenic impacts, sediment
Procedia PDF Downloads 904869 Territorialisation and Elections: Land and Politics in Benin
Authors: Kamal Donko
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In the frontier zone of Benin Republic, land seems to be a fundamental political resource as it is used as a tool for socio-political mobilization, blackmail, inclusion and exclusion, conquest and political control. This paper seeks to examine the complex and intriguing interlinks between land, identity and politics in central Benin. It aims to investigate what roles territorialisation and land ownership are playing in the electioneering process in central Benin. It employs ethnographic multi-sited approach to data collections including observations, interviews and focused group discussions. Research findings reveal a complex and intriguing relationship between land ownership and politics in central Benin. Land is found to be playing a key role in the electioneering process in the region. The study has also discovered many emerging socio-spatial patterns of controlling and maintaining political power in the zone which are tied to land politics. These include identity reconstruction and integration mechanism through intermarriages, socio-political initiatives and construction of infrastructure of sovereignty. It was also found that ‘Diaspora organizations’ and identity issues; strategic creation of administrative units; alliance building strategy; gerrymandering local political field, etc. These emerging socio-spatial patterns of territorialisation for maintaining political power affect migrant and native communities’ relationships. It was also found that ‘Diaspora organizations’ and identity issues; strategic creation of administrative units; alliance building strategy; gerrymandering local political field, etc. are currently affecting migrant’s and natives’ relationships. The study argues that territorialisation is not only about national boundaries and the demarcation between different nation states, but more importantly, it serves as a powerful tool of domination and political control at the grass root level. Furthermore, this study seems to provide another perspective from which the political situation in Africa can be studied. Investigating how the dynamics of land ownership is influencing politics at the grass root or micro level, this study is fundamental to understanding spatial issues in the frontier zone.Keywords: land, migration, politics, territorialisation
Procedia PDF Downloads 3524868 Pattern of Valvular Involvement and Demographic Features of Patients on Benzathine Penicillin at Dhulikhel Hospital
Authors: Sanjaya Humagain, Rajendra Koju
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Background: Rheumatic heart disease (RHD) is the most common cardiovascular disease in children and young adults. Though declined and almost non-existent in developed nations, RHD is still one of the leading cause for premature death and disability in developing countries. Prevalence of RHD is high in both rural as well as urban area of Nepal. Present study is designed to look at the pattern of valvular involvement and demographic features in RHD. Methods: 326 patients indicated for inj. Benzathine penicillin were selected and echocardiograph performed to see the pattern of vavular involvement. Data analysis was done using SPSS 17. Result: The most common type of lesion was mixed type with mitral valve involvement. MR was the most common isolated lesion. MS was more commonly seen in females whereas AS was more common in males. Secondary prophylaxis was more common than primary prophylaxis. Conclusion: RHD still being a major problem and a preventable disease so extensive screening program is required to identify them early and prevent the complication.Keywords: acute rheumatic fever, RHD, MS, MR, AS, AR, Inj benzathine penicillin
Procedia PDF Downloads 3114867 Potential of Detailed Environmental Data, Produced by Information and Communication Technology Tools, for Better Consideration of Microclimatology Issues in Urban Planning to Promote Active Mobility
Authors: Živa Ravnikar, Alfonso Bahillo Martinez, Barbara Goličnik Marušić
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Climate change mitigation has been formally adopted and announced by countries over the globe, where cities are targeting carbon neutrality through various more or less successful, systematic, and fragmentary actions. The article is based on the fact that environmental conditions affect human comfort and the usage of space. Urban planning can, with its sustainable solutions, not only support climate mitigation in terms of a planet reduction of global warming but as well enabling natural processes that in the immediate vicinity produce environmental conditions that encourage people to walk or cycle. However, the article draws attention to the importance of integrating climate consideration into urban planning, where detailed environmental data play a key role, enabling urban planners to improve or monitor environmental conditions on cycle paths. In a practical aspect, this paper tests a particular ICT tool, a prototype used for environmental data. Data gathering was performed along the cycling lanes in Ljubljana (Slovenia), where the main objective was to assess the tool's data applicable value within the planning of comfortable cycling lanes. The results suggest that such transportable devices for in-situ measurements can help a researcher interpret detailed environmental information, characterized by fine granularity and precise data spatial and temporal resolution. Data can be interpreted within human comfort zones, where graphical representation is in the form of a map, enabling the link of the environmental conditions with a spatial context. The paper also provides preliminary results in terms of the potential of such tools for identifying the correlations between environmental conditions and different spatial settings, which can help urban planners to prioritize interventions in places. The paper contributes to multidisciplinary approaches as it demonstrates the usefulness of such fine-grained data for better consideration of microclimatology in urban planning, which is a prerequisite for creating climate-comfortable cycling lanes promoting active mobility.Keywords: information and communication technology tools, urban planning, human comfort, microclimate, cycling lanes
Procedia PDF Downloads 1284866 Machine Learning Approach for Anomaly Detection in the Simulated Iec-60870-5-104 Traffic
Authors: Stepan Grebeniuk, Ersi Hodo, Henri Ruotsalainen, Paul Tavolato
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Substation security plays an important role in the power delivery system. During the past years, there has been an increase in number of attacks on automation networks of the substations. In spite of that, there hasn’t been enough focus dedicated to the protection of such networks. Aiming to design a specialized anomaly detection system based on machine learning, in this paper we will discuss the IEC 60870-5-104 protocol that is used for communication between substation and control station and focus on the simulation of the substation traffic. Firstly, we will simulate the communication between substation slave and server. Secondly, we will compare the system's normal behavior and its behavior under the attack, in order to extract the right features which will be needed for building an anomaly detection system. Lastly, based on the features we will suggest the anomaly detection system for the asynchronous protocol IEC 60870-5-104.Keywords: Anomaly detection, IEC-60870-5-104, Machine learning, Man-in-the-Middle attacks, Substation security
Procedia PDF Downloads 3564865 Urban Planning Patterns after (COVID-19): An Assessment toward Resiliency
Authors: Mohammed AL-Hasani
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The Pandemic COVID-19 altered the daily habits and affected the functional performance of the cities after this crisis leaving remarkable impacts on many metropolises worldwide. It is so obvious that having more densification in the city leads to more threats altering this main approach that was called for achieving sustainable development. The main goal to achieve resiliency in the cities, especially in forcing risks, is to deal with a planning system that is able to resist, absorb, accommodate and recover from the impacts that had been affected. Many Cities in London, Wuhan, New York, and others worldwide carried different planning approaches and varied in reaction to safeguard the impacts of the pandemic. The cities globally varied from the radiant pattern predicted by Le Corbusier, or having multi urban centers more like the approach of Frank Lloyd Wright’s Broadacre City, or having linear growth or gridiron expansion that was common by Doxiadis, compact pattern, and many other hygiene patterns. These urban patterns shape the spatial distribution and Identify both open and natural spaces with gentrified and gentrifying areas. This crisis paid attention to reassess many planning approaches and examine the existing urban patterns focusing more on the aim of continuity and resiliency in managing the crises within the rapid transformation and the power of market forces. According to that, this paper hypothesized that those urban planning patterns determine the method of reaction in assuring quarantine for the inhabitance and the performance of public services and need to be updated through carrying out an innovative urban management system and adopt further resilience patterns in prospective urban planning approaches. This paper investigates the adaptivity and resiliency of variant urban planning patterns regarding selected cities worldwide that affected by COVID-19 and their role in applying certain management strategies in controlling the pandemic spread, finding out the main potentials that should be included in prospective planning approaches. The examination encompasses the spatial arrangement, blocks definition, plots arrangement, and urban space typologies. This paper aims to investigate the urban patterns to deliberate also the debate between densification as one of the more sustainable planning approaches and disaggregation tendency that was followed after the pandemic by restructuring and managing its application according to the assessment of the spatial distribution and urban patterns. The biggest long-term threat to dense cities proves the need to shift to online working and telecommuting, creating a mixture between using cyber and urban spaces to remobilize the city. Reassessing spatial design and growth, open spaces, urban population density, and public awareness are the main solutions that should be carried out to face the outbreak in our current cities that should be managed from global to tertiary levels and could develop criteria for designing the prospective citiesKeywords: COVID-19, densification, resiliency, urban patterns
Procedia PDF Downloads 1234864 2D Surface Flow Model in The Biebrza Floodplain
Authors: Dorota Miroslaw-Swiatek, Mateusz Grygoruk, Sylwia Szporak
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We applied a two-dimensional surface water flow model with irregular wet boundaries. In this model, flow equations are in the form of a 2-D, non-linear diffusion equations which allows to account spatial variations in flow resistance and topography. Calculation domain to simulate the flow pattern in the floodplain is congruent with a Digital Elevation Model (DEM) grid. The rate and direction of sheet flow in wetlands is affected by vegetation type and density, therefore the developed model take into account spatial distribution vegetation resistance to the water flow. The model was tested in a part of the Biebrza Valley, of an outstanding heterogeneity in the elevation and flow resistance distributions due to various ecohydrological conditions and management measures. In our approach we used the highest-possible quality of the DEM in order to obtain hydraulic slopes and vegetation distribution parameters for the modelling. The DEM was created from the cloud of points measured in the LiDAR technology. The LiDAR reflects both the land surface as well as all objects on top of it such as vegetation. Depending on the density of vegetation cover the ability of laser penetration is variable. Therefore to obtain accurate land surface model the “vegetation effect” was corrected using data collected in the field (mostly the vegetation height) and satellite imagery such as Ikonos (to distinguish different vegetation types of the floodplain and represent them spatially). Model simulation was performed for the spring thaw flood in 2009.Keywords: floodplain flow, Biebrza valley, model simulation, 2D surface flow model
Procedia PDF Downloads 4934863 Analysis of Composite Health Risk Indicators Built at a Regional Scale and Fine Resolution to Detect Hotspot Areas
Authors: Julien Caudeville, Muriel Ismert
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Analyzing the relationship between environment and health has become a major preoccupation for public health as evidenced by the emergence of the French national plans for health and environment. These plans have identified the following two priorities: (1) to identify and manage geographic areas, where hotspot exposures are suspected to generate a potential hazard to human health; (2) to reduce exposure inequalities. At a regional scale and fine resolution of exposure outcome prerequisite, environmental monitoring networks are not sufficient to characterize the multidimensionality of the exposure concept. In an attempt to increase representativeness of spatial exposure assessment approaches, risk composite indicators could be built using additional available databases and theoretical framework approaches to combine factor risks. To achieve those objectives, combining data process and transfer modeling with a spatial approach is a fundamental prerequisite that implies the need to first overcome different scientific limitations: to define interest variables and indicators that could be built to associate and describe the global source-effect chain; to link and process data from different sources and different spatial supports; to develop adapted methods in order to improve spatial data representativeness and resolution. A GIS-based modeling platform for quantifying human exposure to chemical substances (PLAINE: environmental inequalities analysis platform) was used to build health risk indicators within the Lorraine region (France). Those indicators combined chemical substances (in soil, air and water) and noise risk factors. Tools have been developed using modeling, spatial analysis and geostatistic methods to build and discretize interest variables from different supports and resolutions on a 1 km2 regular grid within the Lorraine region. By example, surface soil concentrations have been estimated by developing a Kriging method able to integrate surface and point spatial supports. Then, an exposure model developed by INERIS was used to assess the transfer from soil to individual exposure through ingestion pathways. We used distance from polluted soil site to build a proxy for contaminated site. Air indicator combined modeled concentrations and estimated emissions to take in account 30 polluants in the analysis. For water, drinking water concentrations were compared to drinking water standards to build a score spatialized using a distribution unit serve map. The Lden (day-evening-night) indicator was used to map noise around road infrastructures. Aggregation of the different factor risks was made using different methodologies to discuss weighting and aggregation procedures impact on the effectiveness of risk maps to take decisions for safeguarding citizen health. Results permit to identify pollutant sources, determinants of exposure, and potential hotspots areas. A diagnostic tool was developed for stakeholders to visualize and analyze the composite indicators in an operational and accurate manner. The designed support system will be used in many applications and contexts: (1) mapping environmental disparities throughout the Lorraine region; (2) identifying vulnerable population and determinants of exposure to set priorities and target for pollution prevention, regulation and remediation; (3) providing exposure database to quantify relationships between environmental indicators and cancer mortality data provided by French Regional Health Observatories.Keywords: health risk, environment, composite indicator, hotspot areas
Procedia PDF Downloads 2434862 Modeling Activity Pattern Using XGBoost for Mining Smart Card Data
Authors: Eui-Jin Kim, Hasik Lee, Su-Jin Park, Dong-Kyu Kim
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Smart-card data are expected to provide information on activity pattern as an alternative to conventional person trip surveys. The focus of this study is to propose a method for training the person trip surveys to supplement the smart-card data that does not contain the purpose of each trip. We selected only available features from smart card data such as spatiotemporal information on the trip and geographic information system (GIS) data near the stations to train the survey data. XGboost, which is state-of-the-art tree-based ensemble classifier, was used to train data from multiple sources. This classifier uses a more regularized model formalization to control the over-fitting and show very fast execution time with well-performance. The validation results showed that proposed method efficiently estimated the trip purpose. GIS data of station and duration of stay at the destination were significant features in modeling trip purpose.Keywords: activity pattern, data fusion, smart-card, XGboost
Procedia PDF Downloads 2364861 A Context-Sensitive Algorithm for Media Similarity Search
Authors: Guang-Ho Cha
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This paper presents a context-sensitive media similarity search algorithm. One of the central problems regarding media search is the semantic gap between the low-level features computed automatically from media data and the human interpretation of them. This is because the notion of similarity is usually based on high-level abstraction but the low-level features do not sometimes reflect the human perception. Many media search algorithms have used the Minkowski metric to measure similarity between image pairs. However those functions cannot adequately capture the aspects of the characteristics of the human visual system as well as the nonlinear relationships in contextual information given by images in a collection. Our search algorithm tackles this problem by employing a similarity measure and a ranking strategy that reflect the nonlinearity of human perception and contextual information in a dataset. Similarity search in an image database based on this contextual information shows encouraging experimental results.Keywords: context-sensitive search, image search, similarity ranking, similarity search
Procedia PDF Downloads 3534860 Making New Theoretical Insights into Violence: The Temporal and Spatial Relevance of Blood Spatter Crime Scene Investigations
Authors: Simone Jane Dennis
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This paper leverages the spatial and temporal investigative strategy utilized by crime scene investigators – blood spatter work– to engage with the real and metaphorical memorialization of blood-soaked places. It uses this key trope with phenomenological sensibility, to trace the physical and temporal movement of blood outbound from the human body to sites beyond. Working backward, as crime scene investigators do, this paper traces the importance of both space and time and their confluence, to developing a comprehensive theory of violence. To do this work, the paper engages a range of geo-violent scales, from murder scenes to genocides, to both engage an extraordinarily replete literature of bloodshed across history and to move beyond analyses of how significance is assigned to the sites in which blood comes to rest to instead consider the importance of space and time to the structure of violence itself. It is in this regard that the kind of investigative work upon which blood spatter analysis depends is crucial: it engages time and space in reverse to understand the microscopic relations between bodies, places, and numerous (biological, clock, and seasonal) temporalities. Considering the circumstances under which blood escaped a body, the details of its destination in place, and the temporal circumstances of corporal departure, is crucial to making new knowledge about the peculiar temporality and spatiality of violence itself.Keywords: blood, crime scenes, temporality, violence
Procedia PDF Downloads 614859 A Constructivist Grounded Theory Study on the Impact of Automation on People and Gardening
Authors: Hamilton V. Niculescu
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Following a three year study conducted on eighteen Irish people that are involved in growing vegetables in various community gardens around Dublin, Republic of Ireland, it was revealed that addition of some automated features aimed at improving agricultural practices represented a process which was regarded as potentially beneficial, and as a great tool to closely monitor climate conditions inside the greenhouses. The participants were provided with a free custom-built mobile app through which they could remotely monitor and control features such as irrigation, air ventilation, and windows to ensure optimal growing conditions for vegetables growing inside purpose-built greenhouses. While the initial interest was generally high, within weeks, the participants' level of interaction with the enclosures slowly declined. By employing a constructivist grounded theory methodology, following focus group discussions, in-depth semi-structured interviews, and observations, it was revealed that participants' trust in newer technologies, and renewables, in particular, was low. There are various reasons for this, but because the participants in this study consist of mainly working-class people, it can be argued that lack of education and knowledge are the main barriers acting against the adoption of innovations. Consequently, it was revealed that most participants eventually decided to "set and forget" the systems in automatic working mode, indicating that the immediate effect of introducing people to assisting technologies also introduced some unintended consequences into their lifestyle. It is argued that this occurrence also indicates the fact that people initially "read" newer technologies and only adopt those features that they find useful and less intrusive in regards to their current lifestyle.Keywords: automation, communication, greenhouse, sustainable
Procedia PDF Downloads 1154858 Computer Aide Discrimination of Benign and Malignant Thyroid Nodules by Ultrasound Imaging
Authors: Akbar Gharbali, Ali Abbasian Ardekani, Afshin Mohammadi
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Introduction: Thyroid nodules have an incidence of 33-68% in the general population. More than 5-15% of these nodules are malignant. Early detection and treatment of thyroid nodules increase the cure rate and provide optimal treatment. Between the medical imaging methods, Ultrasound is the chosen imaging technique for assessment of thyroid nodules. The confirming of the diagnosis usually demands repeated fine-needle aspiration biopsy (FNAB). So, current management has morbidity and non-zero mortality. Objective: To explore diagnostic potential of automatic texture analysis (TA) methods in differentiation benign and malignant thyroid nodules by ultrasound imaging in order to help for reliable diagnosis and monitoring of the thyroid nodules in their early stages with no need biopsy. Material and Methods: The thyroid US image database consists of 70 patients (26 benign and 44 malignant) which were reported by Radiologist and proven by the biopsy. Two slices per patient were loaded in Mazda Software version 4.6 for automatic texture analysis. Regions of interests (ROIs) were defined within the abnormal part of the thyroid nodules ultrasound images. Gray levels within an ROI normalized according to three normalization schemes: N1: default or original gray levels, N2: +/- 3 Sigma or dynamic intensity limited to µ+/- 3σ, and N3: present intensity limited to 1% - 99%. Up to 270 multiscale texture features parameters per ROIs per each normalization schemes were computed from well-known statistical methods employed in Mazda software. From the statistical point of view, all calculated texture features parameters are not useful for texture analysis. So, the features based on maximum Fisher coefficient and the minimum probability of classification error and average correlation coefficients (POE+ACC) eliminated to 10 best and most effective features per normalization schemes. We analyze this feature under two standardization states (standard (S) and non-standard (NS)) with Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Non-Linear Discriminant Analysis (NDA). The 1NN classifier was performed to distinguish between benign and malignant tumors. The confusion matrix and Receiver operating characteristic (ROC) curve analysis were used for the formulation of more reliable criteria of the performance of employed texture analysis methods. Results: The results demonstrated the influence of the normalization schemes and reduction methods on the effectiveness of the obtained features as a descriptor on discrimination power and classification results. The selected subset features under 1%-99% normalization, POE+ACC reduction and NDA texture analysis yielded a high discrimination performance with the area under the ROC curve (Az) of 0.9722, in distinguishing Benign from Malignant Thyroid Nodules which correspond to sensitivity of 94.45%, specificity of 100%, and accuracy of 97.14%. Conclusions: Our results indicate computer-aided diagnosis is a reliable method, and can provide useful information to help radiologists in the detection and classification of benign and malignant thyroid nodules.Keywords: ultrasound imaging, thyroid nodules, computer aided diagnosis, texture analysis, PCA, LDA, NDA
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