Search results for: panel data method
36781 Degradation of Polycyclic Aromatic Hydrocarbons-Contaminated Soil by Proxy-Acid Method
Authors: Reza Samsami
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The aim of the study was to degradation of polycyclic aromatic hydrocarbons (PAHs) by proxy-acid method. The amounts of PAHs were determined in a silty-clay soil sample of an aged oil refinery field in Abadan, Iran. Proxy-acid treatment method was investigated. The results have shown that the proxy-acid system is an effective method for degradation of PAHs. The results also demonstrated that the number of fused aromatic rings have not significant effects on PAH removal by proxy-acid method. The results also demonstrated that the number of fused aromatic rings have not significant effects on PAH removal by proxy-acid method.Keywords: proxy-acid treatment, silty-clay soil, PAHs, degradation
Procedia PDF Downloads 26736780 Experimental Monitoring of the Parameters of the Ionosphere in the Local Area Using the Results of Multifrequency GNSS-Measurements
Authors: Andrey Kupriyanov
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In recent years, much attention has been paid to the problems of ionospheric disturbances and their influence on the signals of global navigation satellite systems (GNSS) around the world. This is due to the increase in solar activity, the expansion of the scope of GNSS, the emergence of new satellite systems, the introduction of new frequencies and many others. The influence of the Earth's ionosphere on the propagation of radio signals is an important factor in many applied fields of science and technology. The paper considers the application of the method of transionospheric sounding using measurements from signals from Global Navigation Satellite Systems to determine the TEC distribution and scintillations of the ionospheric layers. To calculate these parameters, the International Reference Ionosphere (IRI) model of the ionosphere, refined in the local area, is used. The organization of operational monitoring of ionospheric parameters is analyzed using several NovAtel GPStation6 base stations. It allows performing primary processing of GNSS measurement data, calculating TEC and fixing scintillation moments, modeling the ionosphere using the obtained data, storing data and performing ionospheric correction in measurements. As a result of the study, it was proved that the use of the transionospheric sounding method for reconstructing the altitude distribution of electron concentration in different altitude range and would provide operational information about the ionosphere, which is necessary for solving a number of practical problems in the field of many applications. Also, the use of multi-frequency multisystem GNSS equipment and special software will allow achieving the specified accuracy and volume of measurements.Keywords: global navigation satellite systems (GNSS), GPstation6, international reference ionosphere (IRI), ionosphere, scintillations, total electron content (TEC)
Procedia PDF Downloads 18136779 Classification of Land Cover Usage from Satellite Images Using Deep Learning Algorithms
Authors: Shaik Ayesha Fathima, Shaik Noor Jahan, Duvvada Rajeswara Rao
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Earth's environment and its evolution can be seen through satellite images in near real-time. Through satellite imagery, remote sensing data provide crucial information that can be used for a variety of applications, including image fusion, change detection, land cover classification, agriculture, mining, disaster mitigation, and monitoring climate change. The objective of this project is to propose a method for classifying satellite images according to multiple predefined land cover classes. The proposed approach involves collecting data in image format. The data is then pre-processed using data pre-processing techniques. The processed data is fed into the proposed algorithm and the obtained result is analyzed. Some of the algorithms used in satellite imagery classification are U-Net, Random Forest, Deep Labv3, CNN, ANN, Resnet etc. In this project, we are using the DeepLabv3 (Atrous convolution) algorithm for land cover classification. The dataset used is the deep globe land cover classification dataset. DeepLabv3 is a semantic segmentation system that uses atrous convolution to capture multi-scale context by adopting multiple atrous rates in cascade or in parallel to determine the scale of segments.Keywords: area calculation, atrous convolution, deep globe land cover classification, deepLabv3, land cover classification, resnet 50
Procedia PDF Downloads 13936778 Difference Expansion Based Reversible Data Hiding Scheme Using Edge Directions
Authors: Toshanlal Meenpal, Ankita Meenpal
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A very important technique in reversible data hiding field is Difference expansion. Secret message as well as the cover image may be completely recovered without any distortion after data extraction process due to reversibility feature. In general, in any difference expansion scheme embedding is performed by integer transform in the difference image acquired by grouping two neighboring pixel values. This paper proposes an improved reversible difference expansion embedding scheme. We mainly consider edge direction for embedding by modifying the difference of two neighboring pixels values. In general, the larger difference tends to bring a degraded stego image quality than the smaller difference. Image quality in the range of 0.5 to 3.7 dB in average is achieved by the proposed scheme, which is shown through the experimental results. However payload wise it achieves almost similar capacity in comparisons with previous method.Keywords: information hiding, wedge direction, difference expansion, integer transform
Procedia PDF Downloads 48436777 A Clustering-Based Approach for Weblog Data Cleaning
Authors: Amine Ganibardi, Cherif Arab Ali
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This paper addresses the data cleaning issue as a part of web usage data preprocessing within the scope of Web Usage Mining. Weblog data recorded by web servers within log files reflect usage activity, i.e., End-users’ clicks and underlying user-agents’ hits. As Web Usage Mining is interested in End-users’ behavior, user-agents’ hits are referred to as noise to be cleaned-off before mining. Filtering hits from clicks is not trivial for two reasons, i.e., a server records requests interlaced in sequential order regardless of their source or type, website resources may be set up as requestable interchangeably by end-users and user-agents. The current methods are content-centric based on filtering heuristics of relevant/irrelevant items in terms of some cleaning attributes, i.e., website’s resources filetype extensions, website’s resources pointed by hyperlinks/URIs, http methods, user-agents, etc. These methods need exhaustive extra-weblog data and prior knowledge on the relevant and/or irrelevant items to be assumed as clicks or hits within the filtering heuristics. Such methods are not appropriate for dynamic/responsive Web for three reasons, i.e., resources may be set up to as clickable by end-users regardless of their type, website’s resources are indexed by frame names without filetype extensions, web contents are generated and cancelled differently from an end-user to another. In order to overcome these constraints, a clustering-based cleaning method centered on the logging structure is proposed. This method focuses on the statistical properties of the logging structure at the requested and referring resources attributes levels. It is insensitive to logging content and does not need extra-weblog data. The used statistical property takes on the structure of the generated logging feature by webpage requests in terms of clicks and hits. Since a webpage consists of its single URI and several components, these feature results in a single click to multiple hits ratio in terms of the requested and referring resources. Thus, the clustering-based method is meant to identify two clusters based on the application of the appropriate distance to the frequency matrix of the requested and referring resources levels. As the ratio clicks to hits is single to multiple, the clicks’ cluster is the smallest one in requests number. Hierarchical Agglomerative Clustering based on a pairwise distance (Gower) and average linkage has been applied to four logfiles of dynamic/responsive websites whose click to hits ratio range from 1/2 to 1/15. The optimal clustering set on the basis of average linkage and maximum inter-cluster inertia results always in two clusters. The evaluation of the smallest cluster referred to as clicks cluster under the terms of confusion matrix indicators results in 97% of true positive rate. The content-centric cleaning methods, i.e., conventional and advanced cleaning, resulted in a lower rate 91%. Thus, the proposed clustering-based cleaning outperforms the content-centric methods within dynamic and responsive web design without the need of any extra-weblog. Such an improvement in cleaning quality is likely to refine dependent analysis.Keywords: clustering approach, data cleaning, data preprocessing, weblog data, web usage data
Procedia PDF Downloads 17036776 Patterns Obtained by Using Knitting Technique in Textile Crafts
Authors: Özlem Erzurumlu, Nazan Oskay, Ece Melek
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Knitting which is one of the textile manufacturing techniques is manufactured by using the system of single yarn. Knitting wares consisting of loops structurally have flexible structures. Knitting can be shaped and given volume easily due to increasing or decreasing the number of loops, being manufactured in circular form and its flexible structure. While the knitting wares are basically being manufactured to meet the requirements, it takes its place in the art field overflowing outside of industrial production later. Textile artist ensures his ideas to convert into artistic product by using textiles and non-textiles with aesthetic concerns and creative impulses. When textile crafts are observed at the present time we see that knitting technique has an extensive area of use such as sculpture, panel, installation art and performing art. It is examined how the knitting technique is used in textile crafts observing patterns obtained by this technique in textile crafts in this study.Keywords: art, textile, knitting art, textile crafts
Procedia PDF Downloads 70736775 Long-Baseline Single-epoch RTK Positioning Method Based on BDS-3 and Galileo Penta-Frequency Ionosphere-Reduced Combinations
Authors: Liwei Liu, Shuguo Pan, Wang Gao
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In order to take full advantages of the BDS-3 penta-frequency signals in the long-baseline RTK positioning, a long-baseline RTK positioning method based on the BDS-3 penta-frequency ionospheric-reduced (IR) combinations is proposed. First, the low noise and weak ionospheric delay characteristics of the multi-frequency combined observations of BDS-3is analyzed. Second, the multi-frequency extra-wide-lane (EWL)/ wide-lane (WL) combinations with long-wavelengths are constructed. Third, the fixed IR EWL combinations are used to constrain the IR WL, then constrain narrow-lane (NL)ambiguityies and start multi-epoch filtering. There is no need to consider the influence of ionospheric parameters in the third step. Compared with the estimated ionospheric model, the proposed method reduces the number of parameters by half, so it is suitable for the use of multi-frequency and multi-system real-time RTK. The results using real data show that the stepwise fixed model of the IR EWL/WL/NL combinations can realize long-baseline instantaneous cimeter-level positioning.Keywords: penta-frequency, ionospheric-reduced (IR), RTK positioning, long-baseline
Procedia PDF Downloads 16836774 Critical Activity Effect on Project Duration in Precedence Diagram Method
Authors: Salman Ali Nisar, Koshi Suzuki
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Precedence Diagram Method (PDM) with its additional relationships i.e., start-to-start, finish-to-finish, and start-to-finish, between activities provides more flexible schedule than traditional Critical Path Method (CPM). But, changing the duration of critical activities in PDM network will have anomalous effect on critical path. Researchers have proposed some classification of critical activity effects. In this paper, we do further study on classifications of critical activity effect and provide more information in detailed. Furthermore, we determine the maximum amount of time for each class of critical activity effect by which the project managers can control the dynamic feature (shortening/lengthening) of critical activities and project duration more efficiently.Keywords: construction project management, critical path method, project scheduling, precedence diagram method
Procedia PDF Downloads 51136773 Design and Development of a Computerized Medical Record System for Hospitals in Remote Areas
Authors: Grace Omowunmi Soyebi
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A computerized medical record system is a collection of medical information about a person that is stored on a computer. One principal problem of most hospitals in rural areas is using the file management system for keeping records. A lot of time is wasted when a patient visits the hospital, probably in an emergency, and the nurse or attendant has to search through voluminous files before the patient's file can be retrieved; this may cause an unexpected to happen to the patient. This data mining application is to be designed using a structured system analysis and design method which will help in a well-articulated analysis of the existing file management system, feasibility study, and proper documentation of the design and implementation of a computerized medical record system. This computerized system will replace the file management system and help to quickly retrieve a patient's record with increased data security, access clinical records for decision-making, and reduce the time range at which a patient gets attended to.Keywords: programming, data, software development, innovation
Procedia PDF Downloads 8736772 Availability of TB Infection Control Plans at Rural Hospitals of South Africa
Authors: Takalani Tshitangano
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Background: In Limpopo province the rate of new tuberculosis (TB) cases increase daily. The Infection Control (IC) plan is one of the essential actions for TB IC. This study aimed to establish the availability of these plans at health care facilities. Objectives: The objectives were to explore and describe the awareness and knowledge of health care workers (HCWs) of the availability and content of TB IC plan; and to identity the role of infection control committees from the perspective of HCWs. Method: A qualitative approach using a cross-sectional descriptive design was adopted. The target population was all HCWs from the seven hospitals of Vhembe district. A purposive sampling approach was used to select 57 participants. The approval to conduct this study was obtained from the relevant authorities and participants. Data were collected through seven focus group discussions comprising five to 10 members. An unstructured discussion guide was used to collect data, and an open-coding method was used to analyse the data. Lincoln and Guba’s criteria ensured trustworthiness of the study findings. Results: Findings revealed that HCWs were not aware of the availability and the information contained in the TB IC plans. No person was designated as TB IC officer at hospital level. There was lack of a TB IC Committee and teams as well as ineffective utilisation of those that did exist. Conclusions: It was concluded that if the TB IC plans are not available at health care facilities, then the TB IC practices implemented by HCWs vary, resulting in TB nosocomial infection transmission. It was recommended that the World Health Organisation’s TB IC plans be adopted and implemented in Vhembe district.Keywords: health care workers' awareness, health care workers' knowledge, availability of TB infection control plans, rural hospitals
Procedia PDF Downloads 22036771 Feature Selection Approach for the Classification of Hydraulic Leakages in Hydraulic Final Inspection using Machine Learning
Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter
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Manufacturing companies are facing global competition and enormous cost pressure. The use of machine learning applications can help reduce production costs and create added value. Predictive quality enables the securing of product quality through data-supported predictions using machine learning models as a basis for decisions on test results. Furthermore, machine learning methods are able to process large amounts of data, deal with unfavourable row-column ratios and detect dependencies between the covariates and the given target as well as assess the multidimensional influence of all input variables on the target. Real production data are often subject to highly fluctuating boundary conditions and unbalanced data sets. Changes in production data manifest themselves in trends, systematic shifts, and seasonal effects. Thus, Machine learning applications require intensive pre-processing and feature selection. Data preprocessing includes rule-based data cleaning, the application of dimensionality reduction techniques, and the identification of comparable data subsets. Within the used real data set of Bosch hydraulic valves, the comparability of the same production conditions in the production of hydraulic valves within certain time periods can be identified by applying the concept drift method. Furthermore, a classification model is developed to evaluate the feature importance in different subsets within the identified time periods. By selecting comparable and stable features, the number of features used can be significantly reduced without a strong decrease in predictive power. The use of cross-process production data along the value chain of hydraulic valves is a promising approach to predict the quality characteristics of workpieces. In this research, the ada boosting classifier is used to predict the leakage of hydraulic valves based on geometric gauge blocks from machining, mating data from the assembly, and hydraulic measurement data from end-of-line testing. In addition, the most suitable methods are selected and accurate quality predictions are achieved.Keywords: classification, achine learning, predictive quality, feature selection
Procedia PDF Downloads 16236770 Study on Two Way Reinforced Concrete Slab Using ANSYS with Different Boundary Conditions and Loading
Authors: A. Gherbi, L. Dahmani, A. Boudjemia
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This paper presents the Finite Element Method (FEM) for analyzing the failure pattern of rectangular slab with various edge conditions. Non-Linear static analysis is carried out using ANSYS 15 Software. Using SOLID65 solid elements, the compressive crushing of concrete is facilitated using plasticity algorithm, while the concrete cracking in tension zone is accommodated by the nonlinear material model. Smeared reinforcement is used and introduced as a percentage of steel embedded in concrete slab. The behavior of the analyzed concrete slab has been observed in terms of the crack pattern and displacement for various loading and boundary conditions. The finite element results are also compared with the experimental data. One of the other objectives of the present study is to show how similar the crack path found by ANSYS program to those observed for the yield line analysis. The smeared reinforcement method is found to be more practical especially for the layered elements like concrete slabs. The value of this method is that it does not require explicit modeling of the rebar, and thus a much coarser mesh can be defined.Keywords: ANSYS, cracking pattern, displacements, reinforced concrete slab, smeared reinforcements
Procedia PDF Downloads 19936769 Determination and Evaluation of the Need of Land Consolidation for Nationalization Purpose with the Survey Results
Authors: Turgut Ayten, Tayfun Çay, Demet Ayten
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In this research, nationalization method for obtaining land on the destination of Ankara-Konya High Speed Train in Turkey; Land consolidation for nationalization purpose as an alternative solution on obtaining land; a survey prepared for land owners whose lands were nationalized and institution officials who carries out the nationalization and land consolidation was applied, were investigated and the need for land consolidation for nationalization purpose is tried to be put forth. Study area is located in the Konya city- Kadınhanı district-Kolukısa and Sarikaya neighbourhood in Turkey and land consolidation results of the selected field which is on the destination of the high-speed train route were obtained. The data obtained was shared with the landowners in the research area, their choice between the nationalization method and land consolidation for nationalization method was questioned. In addition, the organization and institution officials who are accepted to used primarily by the state for obtaining land that are needed for the investments of state, and institution officials who make land consolidation were investigated on the issues of the efficiency of the methods they used and if they tried different methods.Keywords: nationalization, land consolidation, land consolidation for nationalization
Procedia PDF Downloads 32436768 A Measuring Industrial Resiliency by Using Data Envelopment Analysis Approach
Authors: Ida Bagus Made Putra Jandhana, Teuku Yuri M. Zagloel, Rahmat Nurchayo
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Having several crises that affect industrial sector performance in the past decades, decision makers should utilize measurement application that enables them to measure industrial resiliency more precisely. It provides not only a framework for the development of resilience measurement application, but also several theories for the concept building blocks, such as performance measurement management, and resilience engineering in real world environment. This research is a continuation of previously published paper on performance measurement in the industrial sector. Finally, this paper contributes an alternative performance measurement method in industrial sector based on resilience concept. Moreover, this research demonstrates how applicable the concept of resilience engineering is and its method of measurement.Keywords: industrial, measurement, resilience, sector
Procedia PDF Downloads 27736767 Lee-Carter Mortality Forecasting Method with Dynamic Normal Inverse Gaussian Mortality Index
Authors: Funda Kul, İsmail Gür
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Pension scheme providers have to price mortality risk by accurate mortality forecasting method. There are many mortality-forecasting methods constructed and used in literature. The Lee-Carter model is the first model to consider stochastic improvement trends in life expectancy. It is still precisely used. Mortality forecasting is done by mortality index in the Lee-Carter model. It is assumed that mortality index fits ARIMA time series model. In this paper, we propose and use dynamic normal inverse gaussian distribution to modeling mortality indes in the Lee-Carter model. Using population mortality data for Italy, France, and Turkey, the model is forecasting capability is investigated, and a comparative analysis with other models is ensured by some well-known benchmarking criterions.Keywords: mortality, forecasting, lee-carter model, normal inverse gaussian distribution
Procedia PDF Downloads 36036766 A Decision Tree Approach to Estimate Permanent Residents Using Remote Sensing Data in Lebanese Municipalities
Authors: K. Allaw, J. Adjizian Gerard, M. Chehayeb, A. Raad, W. Fahs, A. Badran, A. Fakherdin, H. Madi, N. Badaro Saliba
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Population estimation using Geographic Information System (GIS) and remote sensing faces many obstacles such as the determination of permanent residents. A permanent resident is an individual who stays and works during all four seasons in his village. So, all those who move towards other cities or villages are excluded from this category. The aim of this study is to identify the factors affecting the percentage of permanent residents in a village and to determine the attributed weight to each factor. To do so, six factors have been chosen (slope, precipitation, temperature, number of services, time to Central Business District (CBD) and the proximity to conflict zones) and each one of those factors has been evaluated using one of the following data: the contour lines map of 50 m, the precipitation map, four temperature maps and data collected through surveys. The weighting procedure has been done using decision tree method. As a result of this procedure, temperature (50.8%) and percentage of precipitation (46.5%) are the most influencing factors.Keywords: remote sensing, GIS, permanent residence, decision tree, Lebanon
Procedia PDF Downloads 13336765 Determinants of Pastoral Women's Demand for Credit: Evidence from Northern Kenya
Authors: Anne Gesare Timu, Megan Sheahan, Andrew Gache Mude, Rupsha Banerjee
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Women headed households are among the most vulnerable to negative climatic shocks and are often left poorer as a result. Credit provision has been recognized as one way of alleviating rural poverty and developing poor rural households’ resilience to shocks. Much has been documented about credit demand in small-holder agriculture settings in Kenya. However, little is known about demand for credit among pastoral women. This paper analyzes the determinants of demand for credit in the pastoral regions of Marsabit District of Northern Kenya. Using a five wave balanced panel data set of 820 households, a double hurdle model is employed to analyze if shocks, financial literacy and risk aversion affect credit demand among female and male headed households differently. The results show that borrowing goods on credit and monetary credit from informal market segments are the most common sources of credit in the study area. The impact of livestock loss and financial literacy on the decision to borrow and how much to borrow vary with gender. While the paper suggests that provision of credit is particularly valuable in the aftermath of a negative shock and more so for female-headed households, it also explores alternatives to the provision of credit where credit access is a constraint. It recommends further understanding of systems and institutions which could enhance access to credit, and particularly during times of stress, to enable households in the study area in particular and Northern Kenya in general to invest, engage in meaningful development and growth, and be resilient to persistent shocks.Keywords: female headed households, pastoralism, rural financing, double hurdle model
Procedia PDF Downloads 26936764 The Effect of Global Value Chain Participation on Environment
Authors: Piyaphan Changwatchai
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Global value chain is important for current world economy through foreign direct investment. Multinational enterprises' efficient location seeking for each stage of production lead to global production network and more global value chain participation of several countries. Global value chain participation has several effects on participating countries in several aspects including the environment. The effect of global value chain participation on the environment is ambiguous. As a result, this research aims to study the effect of global value chain participation on countries' CO₂ emission and methane emission by using quantitative analysis with secondary panel data of sixty countries. The analysis is divided into two types of global value chain participation, which are forward global value chain participation and backward global value chain participation. The results show that, for forward global value chain participation, GDP per capita affects two types of pollutants in downward bell curve shape. Forward global value chain participation negatively affects CO₂ emission and methane emission. As for backward global value chain participation, GDP per capita affects two types of pollutants in downward bell curve shape. Backward global value chain participation negatively affects methane emission only. However, when considering Asian countries, forward global value chain participation positively affects CO₂ emission. The recommendations of this research are that countries participating in global value chain should promote production with effective environmental management in each stage of value chain. The examples of policies are providing incentives to private sectors, including domestic producers and MNEs, for green production technology and efficient environment management and engaging in international agreements in terms of green production. Furthermore, government should regulate each stage of production in value chain toward green production, especially for Asia countries.Keywords: CO₂ emission, environment, global value chain participation, methane emission
Procedia PDF Downloads 19136763 Suitable Site Selection of Small Dams Using Geo-Spatial Technique: A Case Study of Dadu Tehsil, Sindh
Authors: Zahid Khalil, Saad Ul Haque, Asif Khan
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Decision making about identifying suitable sites for any project by considering different parameters is difficult. Using GIS and Multi-Criteria Analysis (MCA) can make it easy for those projects. This technology has proved to be an efficient and adequate in acquiring the desired information. In this study, GIS and MCA were employed to identify the suitable sites for small dams in Dadu Tehsil, Sindh. The GIS software is used to create all the spatial parameters for the analysis. The parameters that derived are slope, drainage density, rainfall, land use / land cover, soil groups, Curve Number (CN) and runoff index with a spatial resolution of 30m. The data used for deriving above layers include 30-meter resolution SRTM DEM, Landsat 8 imagery, and rainfall from National Centre of Environment Prediction (NCEP) and soil data from World Harmonized Soil Data (WHSD). Land use/Land cover map is derived from Landsat 8 using supervised classification. Slope, drainage network and watershed are delineated by terrain processing of DEM. The Soil Conservation Services (SCS) method is implemented to estimate the surface runoff from the rainfall. Prior to this, SCS-CN grid is developed by integrating the soil and land use/land cover raster. These layers with some technical and ecological constraints are assigned weights on the basis of suitability criteria. The pairwise comparison method, also known as Analytical Hierarchy Process (AHP) is taken into account as MCA for assigning weights on each decision element. All the parameters and group of parameters are integrated using weighted overlay in GIS environment to produce suitable sites for the Dams. The resultant layer is then classified into four classes namely, best suitable, suitable, moderate and less suitable. This study reveals a contribution to decision-making about suitable sites analysis for small dams using geospatial data with minimal amount of ground data. This suitability maps can be helpful for water resource management organizations in determination of feasible rainwater harvesting structures (RWH).Keywords: Remote sensing, GIS, AHP, RWH
Procedia PDF Downloads 38936762 Potential of Mineral Composition Reconstruction for Monitoring the Performance of an Iron Ore Concentration Plant
Authors: Maryam Sadeghi, Claude Bazin, Daniel Hodouin, Laura Perez Barnuevo
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The performance of a separation process is usually evaluated using performance indices calculated from elemental assays readily available from the chemical analysis laboratory. However, the separation process performance is essentially related to the properties of the minerals that carry the elements and not those of the elements. Since elements or metals can be carried by valuable and gangue minerals in the ore and that each mineral responds differently to a mineral processing method, the use of only elemental assays could lead to erroneous or uncertain conclusions on the process performance. This paper discusses the advantages of using performance indices calculated from minerals content, such as minerals recovery, for process performance assessments. A method is presented that uses elemental assays to estimate the minerals content of the solids in various process streams. The method combines the stoichiometric composition of the minerals and constraints of mass conservation for the minerals through the concentration process to estimate the minerals content from elemental assays. The advantage of assessing a concentration process using mineral based performance indices is illustrated for an iron ore concentration circuit.Keywords: data reconciliation, iron ore concentration, mineral composition, process performance assessment
Procedia PDF Downloads 21836761 Globalization and Women's Social Identity in Iran: A Case Study of Educated Women in the 'World City' of Yazd
Authors: Mohammad Tefagh
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The process of globalization has transformed many social and cultural phenomena and has entered the world into a new era and arena. This phenomenon has introduced new methods, ideas, and identity interactions to human beings and has caused great changes in individual and social identity. Women have also been affected by globalization. Globalization has made the presence of women more and more effective and has caused identity changes and changes in the dimensions of identity in them. The purpose of this study is to investigate the impact of globalization of culture on changes in the social identity of educated women in the global city of Yazd. This study will discuss identity change and identity reconstruction due to globalization. The method of this study is qualitative, and the research data is obtained through in-depth interviews with 15 Yazdi-educated women at the Ph.D. level. The method of data analysis is thematic analysis. Findings of the research show that educated Yazdi women have changed their identity due to new communication processes and globalization, including faster, easier, and cheaper communication with other women in the world near and far. Women's social identity has also changed in the face of elements of globalization in various dimensions such as national, gender, religious, and group identities. The analysis of the interviews revealed the confronting elements such as using new cultural goods and communication technologies, membership in social networks, and increasing awareness of environmental change.Keywords: globalization, social identity, educated women, Yazd
Procedia PDF Downloads 33236760 Political Regimes, Political Stability and Debt Dependence in African Countries of Franc Zone: A Logistic Modeling
Authors: Nounamo Nguedie Yann Harold
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The factors behind the debt have been the subject of several studies in the literature. Pioneering studies based on the 'double deficit' approach linked indebtedness to the imbalance between savings and investment, the budget deficit and the current account deficit. Most studies on identifying factors that may stimulate or reduce the level of external public debt agree that the following variables are important explanatory variables in leveraging debt: the budget deficit, trade opening, current account and exchange rate, import, export, interest rate, term variation exchange rate, economic growth rate and debt service, capital flight, and over-indebtedness. Few studies addressed the impact of political factors on the level of external debt. In general, however, the IMF's stabilization programs in developing countries following the debt crisis have resulted in economic recession and the advent of political crises that have resulted in changes in governments. In this sense, political institutions are recognised as factors of accumulation of external debt in most developing countries. This paper assesses the role of political factors on the external debt level of African countries in the Franc Zone over the period 1985-2016. Data used come from World Bank and ICRG. Using a logit in panel, the results show that the more a country is politically stable, the lower the external debt compared to the gross domestic product. Political stability multiplies 1.18% the chances of being in the sustainable debt zone. For example, countries with good political institutions experience less severe external debt burdens than countries with bad political institutions.Keywords: African countries, external debt, Franc Zone, political factors
Procedia PDF Downloads 21936759 Development of Electroencephalograph Collection System in Language-Learning Self-Study System That Can Detect Learning State of the Learner
Authors: Katsuyuki Umezawa, Makoto Nakazawa, Manabu Kobayashi, Yutaka Ishii, Michiko Nakano, Shigeichi Hirasawa
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This research aims to develop a self-study system equipped with an artificial teacher who gives advice to students by detecting the learners and to evaluate language learning in a unified framework. 'Detecting the learners' means that the system understands the learners' learning conditions, such as each learner’s degree of understanding, the difference in each learner’s thinking process, the degree of concentration or boredom in learning, and problem solving for each learner, which can be interpreted from learning behavior. In this paper, we propose a system to efficiently collect brain waves from learners by focusing on only the brain waves among the biological information for 'detecting the learners'. The conventional Electroencephalograph (EEG) measurement method during learning using a simple EEG has the following disadvantages. (1) The start and end of EEG measurement must be done manually by the experiment participant or staff. (2) Even when the EEG signal is weak, it may not be noticed, and the data may not be obtained. (3) Since the acquired EEG data is stored in each PC, there is a possibility that the time of data acquisition will be different in each PC. This time, we developed a system to collect brain wave data on the server side. This system overcame the above disadvantages.Keywords: artificial teacher, e-learning, self-study system, simple EEG
Procedia PDF Downloads 14336758 Mobile Platform’s Attitude Determination Based on Smoothed GPS Code Data and Carrier-Phase Measurements
Authors: Mohamed Ramdani, Hassen Abdellaoui, Abdenour Boudrassen
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Mobile platform’s attitude estimation approaches mainly based on combined positioning techniques and developed algorithms; which aim to reach a fast and accurate solution. In this work, we describe the design and the implementation of an attitude determination (AD) process, using only measurements from GPS sensors. The major issue is based on smoothed GPS code data using Hatch filter and raw carrier-phase measurements integrated into attitude algorithm based on vectors measurement using least squares (LSQ) estimation method. GPS dataset from a static experiment is used to investigate the effectiveness of the presented approach and consequently to check the accuracy of the attitude estimation algorithm. Attitude results from GPS multi-antenna over short baselines are introduced and analyzed. The 3D accuracy of estimated attitude parameters using smoothed measurements is over 0.27°.Keywords: attitude determination, GPS code data smoothing, hatch filter, carrier-phase measurements, least-squares attitude estimation
Procedia PDF Downloads 15536757 Reinforcing Fibre Reinforced Polymer (FRP) Bridge Decks with Steel Plates
Authors: M. Alpaslan Koroglu
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Fibre reinforced polymer (FRP) bridge decks have become an innovative alternative, and they have offered many advantages, and this has been increasing attention for applications in not only reinforcement of existing bridges decks but also construction of new bridges decks. The advantages of these FRP decks are; lightweight, high-strength FRP materials, corrosion resistance. However, this high strength deck is not ductile. In this study, the behaviour of hybrid FRP-steel decks are investigated. All FRP decks was analysed with the commercial package ABAQUS. In the FE model, the webs and flanges were discretised by 4 nodes shell elements. A full composite action between the steel and the FRP composite was assumed in the FE analysis because the bond-slip behaviour was unknown at that time. The performance of the proposed hybrid FRP deck panel with steel plates was evaluated by means of FE analysis.Keywords: FRP, deck, bridge, finite element
Procedia PDF Downloads 47536756 A Novel Computer-Generated Hologram (CGH) Achieved Scheme Generated from Point Cloud by Using a Lens Array
Authors: Wei-Na Li, Mei-Lan Piao, Nam Kim
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We proposed a novel computer-generated hologram (CGH) achieved scheme, wherein the CGH is generated from a point cloud which is transformed by a mapping relationship of a series of elemental images captured from a real three-dimensional (3D) object by using a lens array. This scheme is composed of three procedures: mapping from elemental images to point cloud, hologram generation, and hologram display. A mapping method is figured out to achieve a virtual volume date (point cloud) from a series of elemental images. This mapping method consists of two steps. Firstly, the coordinate (x, y) pairs and its appearing number are calculated from the series of sub-images, which are generated from the elemental images. Secondly, a series of corresponding coordinates (x, y, z) are calculated from the elemental images. Then a hologram is generated from the volume data that is calculated by the previous two steps. Eventually, a spatial light modulator (SLM) and a green laser beam are utilized to display this hologram and reconstruct the original 3D object. In this paper, in order to show a more auto stereoscopic display of a real 3D object, we successfully obtained the actual depth data of every discrete point of the real 3D object, and overcame the inherent drawbacks of the depth camera by obtaining point cloud from the elemental images.Keywords: elemental image, point cloud, computer-generated hologram (CGH), autostereoscopic display
Procedia PDF Downloads 58436755 Fault Detection and Diagnosis of Broken Bar Problem in Induction Motors Base Wavelet Analysis and EMD Method: Case Study of Mobarakeh Steel Company in Iran
Authors: M. Ahmadi, M. Kafil, H. Ebrahimi
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Nowadays, induction motors have a significant role in industries. Condition monitoring (CM) of this equipment has gained a remarkable importance during recent years due to huge production losses, substantial imposed costs and increases in vulnerability, risk, and uncertainty levels. Motor current signature analysis (MCSA) is one of the most important techniques in CM. This method can be used for rotor broken bars detection. Signal processing methods such as Fast Fourier transformation (FFT), Wavelet transformation and Empirical Mode Decomposition (EMD) are used for analyzing MCSA output data. In this study, these signal processing methods are used for broken bar problem detection of Mobarakeh steel company induction motors. Based on wavelet transformation method, an index for fault detection, CF, is introduced which is the variation of maximum to the mean of wavelet transformation coefficients. We find that, in the broken bar condition, the amount of CF factor is greater than the healthy condition. Based on EMD method, the energy of intrinsic mode functions (IMF) is calculated and finds that when motor bars become broken the energy of IMFs increases.Keywords: broken bar, condition monitoring, diagnostics, empirical mode decomposition, fourier transform, wavelet transform
Procedia PDF Downloads 15036754 A General Framework for Knowledge Discovery from Echocardiographic and Natural Images
Authors: S. Nandagopalan, N. Pradeep
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The aim of this paper is to propose a general framework for storing, analyzing, and extracting knowledge from two-dimensional echocardiographic images, color Doppler images, non-medical images, and general data sets. A number of high performance data mining algorithms have been used to carry out this task. Our framework encompasses four layers namely physical storage, object identification, knowledge discovery, user level. Techniques such as active contour model to identify the cardiac chambers, pixel classification to segment the color Doppler echo image, universal model for image retrieval, Bayesian method for classification, parallel algorithms for image segmentation, etc., were employed. Using the feature vector database that have been efficiently constructed, one can perform various data mining tasks like clustering, classification, etc. with efficient algorithms along with image mining given a query image. All these facilities are included in the framework that is supported by state-of-the-art user interface (UI). The algorithms were tested with actual patient data and Coral image database and the results show that their performance is better than the results reported already.Keywords: active contour, Bayesian, echocardiographic image, feature vector
Procedia PDF Downloads 44536753 Gender Stereotype, Leadership Behavior and Job Performance of Sports Council Personnel in Lagos State
Authors: R. A. Moronfolu, I. M. Ndaks, O. E. Ifekoya
Abstract:
This study investigated Gender Stereotypes in Leadership Behaviour and its consequent effect on Job Performance of Sports Council Personnel in Lagos State. The descriptive research method was adapted in conducting the study, while eighty sports personnel of Lagos State sports council, Lagos, Nigeria were drawn as respondents using the stratified random sampling technique. A self-structured questionnaire titled “ Gender- Leader Performance Questionnaire (GLPQ) ”was used for data collection. The GLPQ was face validated by three experts in sports management and was subjected to a pilot test using the test retest method for reliability. A total of eighty copies of the validated GLPQ were administered on selected respondents and retrieved on the spot. The descriptive statistics of frequency counts and percentages were used in describing the demographic data collected, while the inferential statistics of Chi-square (X2) and Analysis of Variance (ANOVA) were used in drawing inferences at a level of significance of 0.05. It was observed that gender stereotypes and behaviours of leaders in Lagos State Sports Council, significantly differ. In addition, gender stereotypes and leadership behavior were observed to significantly influence the job performance of sports council personnel in Lagos State.Keywords: gender, leadership, stereotype, performance
Procedia PDF Downloads 54636752 Polarimetric Synthetic Aperture Radar Data Classification Using Support Vector Machine and Mahalanobis Distance
Authors: Najoua El Hajjaji El Idrissi, Necip Gokhan Kasapoglu
Abstract:
Polarimetric Synthetic Aperture Radar-based imaging is a powerful technique used for earth observation and classification of surfaces. Forest evolution has been one of the vital areas of attention for the remote sensing experts. The information about forest areas can be achieved by remote sensing, whether by using active radars or optical instruments. However, due to several weather constraints, such as cloud cover, limited information can be recovered using optical data and for that reason, Polarimetric Synthetic Aperture Radar (PolSAR) is used as a powerful tool for forestry inventory. In this [14paper, we applied support vector machine (SVM) and Mahalanobis distance to the fully polarimetric AIRSAR P, L, C-bands data from the Nezer forest areas, the classification is based in the separation of different tree ages. The classification results were evaluated and the results show that the SVM performs better than the Mahalanobis distance and SVM achieves approximately 75% accuracy. This result proves that SVM classification can be used as a useful method to evaluate fully polarimetric SAR data with sufficient value of accuracy.Keywords: classification, synthetic aperture radar, SAR polarimetry, support vector machine, mahalanobis distance
Procedia PDF Downloads 133