Search results for: higher dimensional pmf estimation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 14391

Search results for: higher dimensional pmf estimation

13581 Parametric Study of 3D Micro-Fin Tubes on Heat Transfer and Friction Factor

Authors: Shima Soleimani, Steven Eckels

Abstract:

One area of special importance for the surface-level study of heat exchangers is tubes with internal micro-fins (< 0.5 mm tall). Micro-finned surfaces are a kind of extended solid surface in which energy is exchanged with water that acts as the source or sink of energy. Significant performance gains are possible for either shell, tube, or double pipe heat exchangers if the best surfaces are identified. The parametric studies of micro-finned tubes that have appeared in the literature left some key parameters unexplored. Specifically, they ignored three-dimensional (3D) micro-fin configurations, conduction heat transfer in the fins, and conduction in the solid surface below the micro-fins. Thus, this study aimed at implementing a parametric study of 3D micro-finned tubes that considered micro-fine height and discontinuity features. A 3D conductive and convective heat-transfer simulation through coupled solid and periodic fluid domains is applied in a commercial package, ANSYS Fluent 19.1. The simulation is steady-state with turbulent water flow cooling the inner wall of a tube with micro-fins. The simulation utilizes a constant and uniform temperature on the tube outer wall. Performance is mapped for 18 different simulation cases, including a smooth tube using a realizable k-ε turbulence model at a Reynolds number of 48,928. Results compared the performance of 3D tubes with results for the similar two-dimensional (2D) one. Results showed that the micro-fine height has a greater impact on performance factors than discontinuity features in 3D micro-fin tubes. A transformed 3D micro-fin tube can enhance heat transfer, and pressure drops up to 21% and 56% compared to a 2D one, respectfully.

Keywords: three-dimensional micro-fin tube, heat transfer, friction factor, heat exchanger

Procedia PDF Downloads 98
13580 Comparison of Petrophysical Relationship for Soil Water Content Estimation at Peat Soil Area Using GPR Common-Offset Measurements

Authors: Nurul Izzati Abd Karim, Samira Albati Kamaruddin, Rozaimi Che Hasan

Abstract:

The appropriate petrophysical relationship is needed for Soil Water Content (SWC) estimation especially when using Ground Penetrating Radar (GPR). Ground penetrating radar is a geophysical tool that provides indirectly the parameter of SWC. This paper examines the performance of few published petrophysical relationships to obtain SWC estimates from in-situ GPR common- offset survey measurements with gravimetric measurements at peat soil area. Gravimetric measurements were conducted to support of GPR measurements for the accuracy assessment. Further, GPR with dual frequencies (250MHhz and 700MHz) were used in the survey measurements to obtain the dielectric permittivity. Three empirical equations (i.e., Roth’s equation, Schaap’s equation and Idi’s equation) were selected for the study, used to compute the soil water content from dielectric permittivity of the GPR profile. The results indicate that Schaap’s equation provides strong correlation with SWC as measured by GPR data sets and gravimetric measurements.

Keywords: common-offset measurements, ground penetrating radar, petrophysical relationship, soil water content

Procedia PDF Downloads 235
13579 Estimation of Mobility Parameters and Threshold Voltage of an Organic Thin Film Transistor Using an Asymmetric Capacitive Test Structure

Authors: Rajesh Agarwal

Abstract:

Carrier mobility at the organic/insulator interface is essential to the performance of organic thin film transistors (OTFT). The present work describes estimation of field dependent mobility (FDM) parameters and the threshold voltage of an OTFT using a simple, easy to fabricate two terminal asymmetric capacitive test structure using admittance measurements. Conventionally, transfer characteristics are used to estimate the threshold voltage in an OTFT with field independent mobility (FIDM). Yet, this technique breaks down to give accurate results for devices with high contact resistance and having field dependent mobility. In this work, a new technique is presented for characterization of long channel organic capacitor (LCOC). The proposed technique helps in the accurate estimation of mobility enhancement factor (γ), the threshold voltage (V_th) and band mobility (µ₀) using capacitance-voltage (C-V) measurement in OTFT. This technique also helps to get rid of making short channel OTFT or metal-insulator-metal (MIM) structures for making C-V measurements. To understand the behavior of devices and ease of analysis, transmission line compact model is developed. The 2-D numerical simulation was carried out to illustrate the correctness of the model. Results show that proposed technique estimates device parameters accurately even in the presence of contact resistance and field dependent mobility. Pentacene/Poly (4-vinyl phenol) based top contact bottom-gate OTFT’s are fabricated to illustrate the operation and advantages of the proposed technique. Small signal of frequency varying from 1 kHz to 5 kHz and gate potential ranging from +40 V to -40 V have been applied to the devices for measurement.

Keywords: capacitance, mobility, organic, thin film transistor

Procedia PDF Downloads 148
13578 A Targeted Maximum Likelihood Estimation for a Non-Binary Causal Variable: An Application

Authors: Mohamed Raouf Benmakrelouf, Joseph Rynkiewicz

Abstract:

Targeted maximum likelihood estimation (TMLE) is well-established method for causal effect estimation with desirable statistical properties. TMLE is a doubly robust maximum likelihood based approach that includes a secondary targeting step that optimizes the target statistical parameter. A causal interpretation of the statistical parameter requires assumptions of the Rubin causal framework. The causal effect of binary variable, E, on outcomes, Y, is defined in terms of comparisons between two potential outcomes as E[YE=1 − YE=0]. Our aim in this paper is to present an adaptation of TMLE methodology to estimate the causal effect of a non-binary categorical variable, providing a large application. We propose coding on the initial data in order to operate a binarization of the interest variable. For each category, we get a transformation of the non-binary interest variable into a binary variable, taking value 1 to indicate the presence of category (or group of categories) for an individual, 0 otherwise. Such a dummy variable makes it possible to have a pair of potential outcomes and oppose a category (or a group of categories) to another category (or a group of categories). Let E be a non-binary interest variable. We propose a complete disjunctive coding of our variable E. We transform the initial variable to obtain a set of binary vectors (dummy variables), E = (Ee : e ∈ {1, ..., |E|}), where each vector (variable), Ee, takes the value of 0 when its category is not present, and the value of 1 when its category is present, which allows to compute a pairwise-TMLE comparing difference in the outcome between one category and all remaining categories. In order to illustrate the application of our strategy, first, we present the implementation of TMLE to estimate the causal effect of non-binary variable on outcome using simulated data. Secondly, we apply our TMLE adaptation to survey data from the French Political Barometer (CEVIPOF), to estimate the causal effect of education level (A five-level variable) on a potential vote in favor of the French extreme right candidate Jean-Marie Le Pen. Counterfactual reasoning requires us to consider some causal questions (additional causal assumptions). Leading to different coding of E, as a set of binary vectors, E = (Ee : e ∈ {2, ..., |E|}), where each vector (variable), Ee, takes the value of 0 when the first category (reference category) is present, and the value of 1 when its category is present, which allows to apply a pairwise-TMLE comparing difference in the outcome between the first level (fixed) and each remaining level. We confirmed that the increase in the level of education decreases the voting rate for the extreme right party.

Keywords: statistical inference, causal inference, super learning, targeted maximum likelihood estimation

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13577 A Corpus-Assisted Discourse Analysis of Adjectival Collocation of the Word 'Education' in the American Context

Authors: Ngan Nguyen

Abstract:

The study analyses adjectives collocating with the word ‘education’ in the American language of the Corpus of Global Web-based English using a combination of corpus linguistic and discourse analytical methods to examine not only language patterns but also social political ideologies around the topic. Significant conclusions are deduced: (1) there are a large number of adjectival collocates of the word education which have been identified and classified into four categories representing four different aspects of education: level, quality, forms and types of education; (2) education, as in combination with three first categories, carries the meaning as the act and process of teaching and learning while with the last category having the meaning of a particular kind of teaching or training; (3) higher education is the topic that gains most concerns from the American public; (4) five most significant ideologies are discovered from the corpus: higher education associates with financial affairs, higher education is an industry, monetary policy of the government on higher education, people require greater accessibility to higher education and people value higher education. The study contributes to the field of developing meanings of words through corpus analysis and the field of discourse analysis.

Keywords: adjectival collocation, American context, corpus linguistics, discourse analysis, education

Procedia PDF Downloads 315
13576 Flow Links Curiosity and Creativity: The Mediating Role of Flow

Authors: Nicola S. Schutte, John M. Malouff

Abstract:

Introduction: Curiosity is a positive emotion and motivational state that consists of the desire to know. Curiosity consists of several related dimensions, including a desire for exploration, deprivation sensitivity, and stress tolerance. Creativity involves generating novel and valuable ideas or products. How curiosity may prompt greater creativity remains to be investigated. The phenomena of flow may link curiosity and creativity. Flow is characterized by intense concentration and absorption and gives rise to optimal performance. Objective of Study: The objective of the present study was to investigate whether the phenomenon of flow may link curiosity with creativity. Methods and Design: Fifty-seven individuals from Australia (45 women and 12 men, mean age of 35.33, SD=9.4) participated. Participants were asked to design a program encouraging residents in a local community to conserve water and to record the elements of their program in writing. Participants were then asked to rate their experience as they developed and wrote about their program. Participants rated their experience on the Dimensional Curiosity Measure sub-scales assessing the exploration, deprivation sensitivity, and stress tolerance facets of curiosity, and the Flow Short Scale. Reliability of the measures as assessed by Cronbach's alpha was as follows: Exploration Curiosity =.92, Deprivation Sensitivity Curiosity =.66, Stress Tolerance Curiosity =.93, and Flow=.96. Two raters independently coded each participant’s water conservation program description on creativity. The mixed-model intraclass correlation coefficient for the two sets of ratings was .73. The mean of the two ratings produced the final creativity score for each participant. Results: During the experience of designing the program, all three types of curiosity were significantly associated with the flow. Pearson r correlations were as follows: Exploration Curiosity and flow, r =.68 (higher Exploration Curiosity was associated with more flow); Deprivation Sensitivity Curiosity and flow, r =.39 (higher Deprivation Sensitivity Curiosity was associated with more flow); and Stress Tolerance Curiosity and flow, r = .44 (more stress tolerance in relation to novelty and exploration was associated with more flow). Greater experience of flow was significantly associated with greater creativity in designing the water conservation program, r =.39. The associations between dimensions of curiosity and creativity did not reach significance. Even though the direct relationships between dimensions of curiosity and creativity were not significant, indirect relationships through the mediating effect of the experience of flow between dimensions of curiosity and creativity were significant. Mediation analysis using PROCESS showed that flow linked Exploration Curiosity with creativity, standardized beta=.23, 95%CI [.02,.25] for the indirect effect; Deprivation Sensitivity Curiosity with creativity, standardized beta=.14, 95%CI [.04,.29] for the indirect effect; and Stress Tolerance Curiosity with creativity, standardized beta=.13, 95%CI [.02,.27] for the indirect effect. Conclusions: When engaging in an activity, higher levels of curiosity are associated with greater flow. More flow is associated with higher levels of creativity. Programs intended to increase flow or creativity might build on these findings and also explore causal relationships.

Keywords: creativity, curiosity, flow, motivation

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13575 Effects of Daily Temperature Changes on Transient Heat and Moisture Transport in Unsaturated Soils

Authors: Davood Yazdani Cherati, Ali Pak, Mehrdad Jafarzadeh

Abstract:

This research contains the formulation of a two-dimensional analytical solution to transient heat, and moisture flow in a semi-infinite unsaturated soil environment under the influence of daily temperature changes. For this purpose, coupled energy conservation and mass fluid continuity equations governing hydrothermal behavior of unsaturated soil media are presented in terms of temperature and volumetric moisture content. In consideration of the soil environment as an infinite half-space and by linearization of the governing equations, Laplace–Fourier transformation is conducted to convert differential equations with partial derivatives (PDEs) to ordinary differential equations (ODEs). The obtained ODEs are solved, and the inverse transformations are calculated to determine the solution to the system of equations. Results indicate that heat variation induces moisture transport in both horizontal and vertical directions.

Keywords: analytical solution, heat conduction, hydrothermal analysis, laplace–fourier transformation, two-dimensional

Procedia PDF Downloads 200
13574 Study of Photonic Crystal Band Gap and Hexagonal Microcavity Based on Elliptical Shaped Holes

Authors: A. Benmerkhi, A. Bounouioua, M. Bouchemat, T. Bouchemat

Abstract:

In this paper, we present a numerical optical properties of a triangular periodic lattice of elliptical air holes. We report the influence of the ratio (semi-major axis length of elliptical hole to the filling ratio) on the photonic band gap. Then by using the finite difference time domain (FDTD) algorithm, the resonant wavelength of the point defect microcavities in a two-dimensional photonic crystal (PC) shifts towards the low wavelengths with significantly increased filing ratio. It can be noted that the Q factor is gradually changed to higher when the filling ratio increases. It is due to an increase in reflectivity of the PC mirror. Also we theoretically investigate the H1 cavity, where the value of semi-major axis (Rx) of the six holes surrounding the cavity are fixed at 0.5a and the Rx of the two edge air holes are fixed at the optimum value of 0.52a. The highest Q factor of 4.1359 × 106 is achieved at the resonant mode located at λ = 1.4970 µm.

Keywords: photonic crystal, microcavity, filling ratio, elliptical holes

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13573 Role of Spatial Variability in the Service Life Prediction of Reinforced Concrete Bridges Affected by Corrosion

Authors: Omran M. Kenshel, Alan J. O'Connor

Abstract:

Estimating the service life of Reinforced Concrete (RC) bridge structures located in corrosive marine environments of a great importance to their owners/engineers. Traditionally, bridge owners/engineers relied more on subjective engineering judgment, e.g. visual inspection, in their estimation approach. However, because financial resources are often limited, rational calculation methods of estimation are needed to aid in making reliable and more accurate predictions for the service life of RC structures. This is in order to direct funds to bridges found to be the most critical. Criticality of the structure can be considered either form the Structural Capacity (i.e. Ultimate Limit State) or from Serviceability viewpoint whichever is adopted. This paper considers the service life of the structure only from the Structural Capacity viewpoint. Considering the great variability associated with the parameters involved in the estimation process, the probabilistic approach is most suited. The probabilistic modelling adopted here used Monte Carlo simulation technique to estimate the Reliability (i.e. Probability of Failure) of the structure under consideration. In this paper the authors used their own experimental data for the Correlation Length (CL) for the most important deterioration parameters. The CL is a parameter of the Correlation Function (CF) by which the spatial fluctuation of a certain deterioration parameter is described. The CL data used here were produced by analyzing 45 chloride profiles obtained from a 30 years old RC bridge located in a marine environment. The service life of the structure were predicted in terms of the load carrying capacity of an RC bridge beam girder. The analysis showed that the influence of SV is only evident if the reliability of the structure is governed by the Flexure failure rather than by the Shear failure.

Keywords: Chloride-induced corrosion, Monte-Carlo simulation, reinforced concrete, spatial variability

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13572 Parameter Estimation of Additive Genetic and Unique Environment (AE) Model on Diabetes Mellitus Type 2 Using Bayesian Method

Authors: Andi Darmawan, Dewi Retno Sari Saputro, Purnami Widyaningsih

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Diabetes mellitus (DM) is a chronic disease in human that occurred if pancreas cannot produce enough of insulin hormone or the body uses ineffectively insulin hormone which causes increasing level of glucose in the blood, or it was called hyperglycemia. In Indonesia, DM is a serious disease on health because it can cause blindness, kidney disease, diabetic feet (gangrene), and stroke. The type of DM criteria can also be divided based on the main causes; they are DM type 1, type 2, and gestational. Diabetes type 1 or previously known as insulin-independent diabetes is due to a lack of production of insulin hormone. Diabetes type 2 or previously known as non-insulin dependent diabetes is due to ineffective use of insulin while gestational diabetes is a hyperglycemia that found during pregnancy. The most one type commonly found in patient is DM type 2. The main factors of this disease are genetic (A) and life style (E). Those disease with 2 factors can be constructed with additive genetic and unique environment (AE) model. In this article was discussed parameter estimation of AE model using Bayesian method and the inheritance character simulation on parent-offspring. On the AE model, there are response variable, predictor variables, and parameters were capable of representing the number of population on research. The population can be measured through a taken random sample. The response and predictor variables can be determined by sample while the parameters are unknown, so it was required to estimate the parameters based on the sample. Estimation of AE model parameters was obtained based on a joint posterior distribution. The simulation was conducted to get the value of genetic variance and life style variance. The results of simulation are 0.3600 for genetic variance and 0.0899 for life style variance. Therefore, the variance of genetic factor in DM type 2 is greater than life style.

Keywords: AE model, Bayesian method, diabetes mellitus type 2, genetic, life style

Procedia PDF Downloads 261
13571 Digital Reconstruction of Museum's Statue Using 3D Scanner for Cultural Preservation in Indonesia

Authors: Ahmad Zaini, F. Muhammad Reza Hadafi, Surya Sumpeno, Muhtadin, Mochamad Hariadi

Abstract:

The lack of information about museum’s collection reduces the number of visits of museum. Museum’s revitalization is an urgent activity to increase the number of visits. The research's roadmap is building a web-based application that visualizes museum in the virtual form including museum's statue reconstruction in the form of 3D. This paper describes implementation of three-dimensional model reconstruction method based on light-strip pattern on the museum statue using 3D scanner. Noise removal, alignment, meshing and refinement model's processes is implemented to get a better 3D object reconstruction. Model’s texture derives from surface texture mapping between object's images with reconstructed 3D model. Accuracy test of dimension of the model is measured by calculating relative error of virtual model dimension compared against the original object. The result is realistic three-dimensional model textured with relative error around 4.3% to 5.8%.

Keywords: 3D reconstruction, light pattern structure, texture mapping, museum

Procedia PDF Downloads 445
13570 Numerical Study of Nonlinear Guided Waves in Composite Laminates with Delaminations

Authors: Reza Soleimanpour, Ching Tai Ng

Abstract:

Fibre-composites are widely used in various structures due to their attractive properties such as higher stiffness to mass ratio and better corrosion resistance compared to metallic materials. However, one serious weakness of this composite material is delamination, which is a subsurface separation of laminae. A low level of this barely visible damage can cause a significant reduction in residual compressive strength. In the last decade, the application of guided waves for damage detection has been a topic of significant interest for many researches. Among all guided wave techniques, nonlinear guided wave has shown outstanding sensitivity and capability for detecting different types of damages, e.g. cracks and delaminations. So far, most of researches on applications of nonlinear guided wave have been dedicated to isotropic material, such as aluminium and steel, while only a few works have been done on applications of nonlinear characteristics of guided waves in anisotropic materials. This study investigates the nonlinear interactions of the fundamental antisymmetric lamb wave (A0) with delamination in composite laminates using three-dimensional (3D) explicit finite element (FE) simulations. The nonlinearity considered in this study arises from interactions of two interfaces of sub-laminates at the delamination region, which generates contact acoustic nonlinearity (CAN). The aim of this research is to investigate the phenomena of CAN in composite laminated beams by a series of numerical case studies. In this study interaction of fundamental antisymmetric lamb wave with delamination of different sizes are studied in detail. The results show that the A0 lamb wave interacts with the delaminations generating CAN in the form of higher harmonics, which is a good indicator for determining the existence of delaminations in composite laminates.

Keywords: contact acoustic nonlinearity, delamination, fibre reinforced composite beam, finite element, nonlinear guided waves

Procedia PDF Downloads 187
13569 Efficient Monolithic FEM for Compressible Flow and Conjugate Heat Transfer

Authors: Santhosh A. K.

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This work presents an efficient monolithic finite element strategy for solving thermo-fluid-structure interaction problems involving compressible fluids and linear-elastic structure. This formulation uses displacement variables for structure and velocity variables for the fluid, with no additional variables required to ensure traction, velocity, temperature, and heat flux continuity at the fluid-structure interface. Rate of convergence in each time step is quadratic, which is achieved in this formulation by deriving an exact tangent stiffness matrix. The robustness and good performance of the method is ascertained by applying the proposed strategy on a wide spectrum of problems taken from the literature pertaining to steady, transient, two dimensional, axisymmetric, and three dimensional fluid flow and conjugate heat transfer. It is shown that the current formulation gives excellent results on all the case studies conducted, which includes problems involving compressibility effects as well as problems where fluid can be treated as incompressible.

Keywords: linear thermoelasticity, compressible flow, conjugate heat transfer, monolithic FEM

Procedia PDF Downloads 179
13568 The Impact of Board Characteristics on Firm Performance: Evidence from Banking Industry in India

Authors: Manmeet Kaur, Madhu Vij

Abstract:

The Board of Directors in a firm performs the primary role of an internal control mechanism. This Study seeks to understand the relationship between internal governance and performance of banks in India. The research paper investigates the effect of board structure (proportion of nonexecutive directors, gender diversity, board size and meetings per year) on the firm performance. This paper evaluates the impact of corporate governance mechanisms on bank’s financial performance using panel data for 28 listed banks in National Stock Exchange of India for the period of 2008-2014. Returns on Asset, Return on Equity, Tobin’s Q and Net Interest Margin were used as the financial performance indicators. To estimate the relationship among governance and bank performance initially the Study uses Pooled Ordinary Least Square (OLS) Estimation and Generalized Least Square (GLS) Estimation. Then a well-developed panel Generalized Method of Moments (GMM) Estimator is developed to investigate the dynamic nature of performance and governance relationship. The Study empirically confirms that two-step system GMM approach controls the problem of unobserved heterogeneity and endogeneity as compared to the OLS and GLS approach. The result suggests that banks with small board, boards with female members, and boards that meet more frequently tend to be more efficient and subsequently have a positive impact on performance of banks. The study offers insights to policy makers interested in enhancing the quality of governance of banks in India. Also, the findings suggest that board structure plays a vital role in the improvement of corporate governance mechanism for financial institutions. There is a need to have efficient boards in banks to improve the overall health of the financial institutions and the economic development of the country.

Keywords: board of directors, corporate governance, GMM estimation, Indian banking

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13567 Vehicle Timing Motion Detection Based on Multi-Dimensional Dynamic Detection Network

Authors: Jia Li, Xing Wei, Yuchen Hong, Yang Lu

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Detecting vehicle behavior has always been the focus of intelligent transportation, but with the explosive growth of the number of vehicles and the complexity of the road environment, the vehicle behavior videos captured by traditional surveillance have been unable to satisfy the study of vehicle behavior. The traditional method of manually labeling vehicle behavior is too time-consuming and labor-intensive, but the existing object detection and tracking algorithms have poor practicability and low behavioral location detection rate. This paper proposes a vehicle behavior detection algorithm based on the dual-stream convolution network and the multi-dimensional video dynamic detection network. In the videos, the straight-line behavior of the vehicle will default to the background behavior. The Changing lanes, turning and turning around are set as target behaviors. The purpose of this model is to automatically mark the target behavior of the vehicle from the untrimmed videos. First, the target behavior proposals in the long video are extracted through the dual-stream convolution network. The model uses a dual-stream convolutional network to generate a one-dimensional action score waveform, and then extract segments with scores above a given threshold M into preliminary vehicle behavior proposals. Second, the preliminary proposals are pruned and identified using the multi-dimensional video dynamic detection network. Referring to the hierarchical reinforcement learning, the multi-dimensional network includes a Timer module and a Spacer module, where the Timer module mines time information in the video stream and the Spacer module extracts spatial information in the video frame. The Timer and Spacer module are implemented by Long Short-Term Memory (LSTM) and start from an all-zero hidden state. The Timer module uses the Transformer mechanism to extract timing information from the video stream and extract features by linear mapping and other methods. Finally, the model fuses time information and spatial information and obtains the location and category of the behavior through the softmax layer. This paper uses recall and precision to measure the performance of the model. Extensive experiments show that based on the dataset of this paper, the proposed model has obvious advantages compared with the existing state-of-the-art behavior detection algorithms. When the Time Intersection over Union (TIoU) threshold is 0.5, the Average-Precision (MP) reaches 36.3% (the MP of baselines is 21.5%). In summary, this paper proposes a vehicle behavior detection model based on multi-dimensional dynamic detection network. This paper introduces spatial information and temporal information to extract vehicle behaviors in long videos. Experiments show that the proposed algorithm is advanced and accurate in-vehicle timing behavior detection. In the future, the focus will be on simultaneously detecting the timing behavior of multiple vehicles in complex traffic scenes (such as a busy street) while ensuring accuracy.

Keywords: vehicle behavior detection, convolutional neural network, long short-term memory, deep learning

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13566 Study of Interaction between Ascorbic Acid and Bovine Hemoglobin by Multispectroscopic Methods

Authors: Krishnamoorthy Shanmugaraj, Malaichamy Ilanchelian

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Ascorbic acid is an essential component in the diet of humans, and also is a typical long used pharmaceutical agent. In the present contribution, we have carried out a detailed study on the binding interaction of ascorbic acid (AA) with bovine hemoglobin (BHb) using steady state emission, time resolved fluorescence, UV-Vis absorption, circular dichroism (CD), Fourier transform infra-red (FT-IR) and three dimensional emission (3D) spectral studies. The results from the emission spectral studies unveiled that the quenching of BHb emission by AA is attributed to the formation of a complex in the ground state (static in nature) after correcting for inner filter effect. The binding parameters calculated from corrected emission quenching data revealed that BHb exhibited a significant binding affinity towards AA. Moreover, AA induced tertiary and secondary conformational changes of BHb were monitored by UV-Vis absorption, CD, FT-IR and 3D emission spectral studies. The results presented here will help to further understand the credible mechanism of BHb-AA system which is expected to provide insights into conformational and microenvironmental changes of BHb.

Keywords: ascorbic acid, bovine hemoglobin, circular dichroism, three dimensional emission spectral studies

Procedia PDF Downloads 949
13565 Insecticide Efficacy against Jassids in Egg Plants

Authors: Zunnu Raen Akhtar, Farhan Ali, Muhammad Saeed-Ur-Rehman

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Jassids are considered as serious sucking pests in eggplants. Jassids can be controlled using imidacloprid, but it can also result in non-target ecological impacts on eco-system. It can also result in reduced population of predators of jassids in the field. An experiment was conducted on jassids, Amrasca sp. reared on eggplant leaves were treated with insecticide imidacloprid at lower, recommended and higher doses including 1L, 2L, 3L respectively. 3rd instar larvae and adults of jassids were exposed to lower, recommended, higher doses. Mortality tests were repeated three times for each dose and insect growth stage. Imidacloprid was sprayed on the leaves followed by drying. Data was recorded for 4, 8, 12, 16, 20, 24 hours after spraying insecticide on the leaves. Results showed that higher mortality was observed in higher and recommended doses, while slow mortality was observed in the case of lower dose. It can be asserted that higher and recommended doses causing immediate mortality of insects are better to control Amrasca sp. in the field, it will not cause immediate resistance development in insects against imidacloprid.

Keywords: Amrasca sp., imidacloprid, egg plant, efficacy

Procedia PDF Downloads 201
13564 Wind Energy Resources Assessment and Micrositting on Different Areas of Libya: The Case Study in Darnah

Authors: F. Ahwide, Y. Bouker, K. Hatem

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This paper presents long term wind data analysis in terms of annual and diurnal variations at different areas of Libya. The data of the wind speed and direction are taken each ten minutes for a period, at least two years, are used in the analysis. ‘WindPRO’ software and Excel workbook were used for the wind statistics and energy calculations. As for Derna, average speeds are 10 m, 20 m, and 40 m, and respectively 6.57 m/s, 7.18 m/s, and 8.09 m/s. Highest wind speeds are observed at SSW, followed by S, WNW and NW sectors. Lowest wind speeds are observed between N and E sectors. Most frequent wind directions are NW and NNW. Hence, wind turbines can be installed against these directions. The most powerful sector is NW (29.4 % of total expected wind energy), followed by 19.9 % SSW, 11.9% NNW, 8.6% WNW and 8.2% S. Furthermore in Al-Maqrun: the most powerful sector is W (26.8 % of total expected wind energy), followed by 12.3 % WSW and 9.5% WNW. While in Goterria: the most powerful sector is S (14.8 % of total expected wind energy), followed by SSE, SE, and WSW. And Misalatha: the most powerful sector is S, by far represents 28.5% of the expected power, followed by SSE and SE. As for Tarhuna, it is by far SSE and SE, representing each one two times the expected energy of the third powerful sector (NW). In Al-Asaaba: it is SSE by far represents 50% of the expected power, followed by S. It can to be noted that the high frequency of the south direction winds, that come from the desert could cause a high frequency of dust episodes. This fact then, should be taken into account in order to take appropriate measures to prevent wind turbine deterioration. In Excel workbook, an estimation of annual energy yield at position of Derna, Al-Maqrun, Tarhuna, and Al-Asaaba meteorological mast has been done, considering a generic wind turbine of 1.65 MW. (mtORRES, TWT 82-1.65MW) in position of meteorological mast. Three other turbines have been tested. At 80 m, the estimation of energy yield for Derna, Al-Maqrun, Tarhuna, and Asaaba is 6.78 GWh or 3390 equivalent hours, 5.80 GWh or 2900 equivalent hours, 4.91 GWh or 2454 equivalent hours and 5.08 GWh or 2541 equivalent hours respectively. It seems a fair value in the context of a possible development of a wind energy project in the areas, considering a value of 2400 equivalent hours as an approximate limit to consider a wind warm economically profitable. Furthermore, an estimation of annual energy yield at positions of Misalatha, Azizyah and Goterria meteorological mast has been done, considering a generic wind turbine of 2 MW. We found that, at 80 m, the estimation of energy yield is 3.12 GWh or 1557 equivalent hours, 4.47 GWh or 2235 equivalent hours and 4.07GWh or 2033 respectively . It seems a very poor value in the context of possible development of a wind energy project in the areas, considering a value of 2400 equivalent hours as an approximate limit to consider a wind warm economically profitable. Anyway, more data and a detailed wind farm study would be necessary to draw conclusions.

Keywords: wind turbines, wind data, energy yield, micrositting

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13563 Application of Generalized Autoregressive Score Model to Stock Returns

Authors: Katleho Daniel Makatjane, Diteboho Lawrence Xaba, Ntebogang Dinah Moroke

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The current study investigates the behaviour of time-varying parameters that are based on the score function of the predictive model density at time t. The mechanism to update the parameters over time is the scaled score of the likelihood function. The results revealed that there is high persistence of time-varying, as the location parameter is higher and the skewness parameter implied the departure of scale parameter from the normality with the unconditional parameter as 1.5. The results also revealed that there is a perseverance of the leptokurtic behaviour in stock returns which implies the returns are heavily tailed. Prior to model estimation, the White Neural Network test exposed that the stock price can be modelled by a GAS model. Finally, we proposed further researches specifically to model the existence of time-varying parameters with a more detailed model that encounters the heavy tail distribution of the series and computes the risk measure associated with the returns.

Keywords: generalized autoregressive score model, South Africa, stock returns, time-varying

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13562 Bio-Estimation of Selected Heavy Metals in Shellfish and Their Surrounding Environmental Media

Authors: Ebeed A. Saleh, Kadry M. Sadek, Safaa H. Ghorbal

Abstract:

Due to the determination of the pollution status of fresh resources in the Egyptian territorial waters is very important for public health, this study was carried out to reveal the levels of heavy metals in the shellfish and their environment and its relation to the highly developed industrial activities in those areas. A total of 100 shellfish samples from the Rosetta, Edku, El-Maadiya, Abo-Kir and El-Max coasts [10 crustaceans (shrimp) and 10 mollusks (oysters)] were randomly collected from each coast. Additionally, 10 samples from both the water and the sediment were collected from each coast. Each collected sample was analyzed for cadmium, chromium, copper, lead and zinc residues using a Perkin Elmer atomic absorption spectrophotometer (AAS). The results showed that the levels of heavy metals were higher in the water and sediment from Abo-Kir. The heavy metal levels decreased successively for the Rosetta, Edku, El-Maadiya, and El-Max coasts, and the concentrations of heavy metals, except copper and zinc, in shellfish exhibited the same pattern. For the concentration of heavy metals in shellfish tissue, the highest was zinc and the concentrations decreased successively for copper, lead, chromium and cadmium for all coasts, except the Abo-Kir coast, where the chromium level was highest and the other metals decreased successively for zinc, copper, lead and cadmium. In Rosetta, chromium was higher only in the mollusks, while the level of this metal was lower in the crustaceans; this trend was observed at the Edku, El-Maadiya and El-Max coasts as well. Herein, we discuss the importance of such contamination for public health and the sources of shellfish contamination with heavy metals. We suggest measures to minimize and prevent these pollutants in the aquatic environment and, furthermore, how to protect humans from excessive intake.

Keywords: atomic absorption, heavy metals, sediment, shellfish, water

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13561 Dynamic Relaxation and Isogeometric Analysis for Finite Deformation Elastic Sheets with Combined Bending and Stretching

Authors: Nikhil Padhye, Ellen Kintz, Dan Dorci

Abstract:

Recent years have seen a rising interest in study and applications of materially uniform thin-structures (plates/shells) subject to finite-bending and stretching deformations. We introduce a well-posed 2D-model involving finite-bending and stretching of thin-structures to approximate the three-dimensional equilibria. Key features of this approach include: Non-Uniform Rational B-Spline (NURBS)-based spatial discretization for finite elements, method of dynamic relaxation to predict stable equilibria, and no a priori kinematic assumption on the deformation fields. The approach is validated against the benchmark problems,and the use of NURBS for spatial discretization facilitates exact spatial representation and computation of curvatures (due to C1-continuity of interpolated displacements) for this higher-order accuracy 2D-model.

Keywords: Isogeometric Analysis, Plates/Shells , Finite Element Methods, Dynamic Relaxation

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13560 In vitro Estimation of Genotoxic Lesions in Peripheral Blood Lymphocytes of Rat Exposed to Organophosphate Pesticides

Authors: A. Ojha, Y. K. Gupta

Abstract:

Organophosphate (OP) pesticides are among the most widely used synthetic chemicals for controlling a wide variety of pests throughout the world. Chlorpyrifos (CPF), methyl parathion (MPT), and malathion (MLT) are among the most extensively used OP pesticides in India. DNA strand breaks and DNA-protein crosslinks (DPC) are toxic lesions associated with the mechanisms of toxicity of genotoxic compounds. In the present study, we have examined the potential of CPF, MPT, and MLT individually and in combination, to cause DNA strand breakage and DPC formation. Peripheral blood lymphocytes of rat were exposed to 1/4 and 1/10 LC50 dose of CPF, MPT, and MLT for 2, 4, 8, and 12h. The DNA strand break was measured by the comet assay and expressed as DNA damage index while DPC estimation was done by fluorescence emission. There was significantly marked increase in DNA damage and DNA-protein crosslink formation in time and dose dependent manner. It was also observed that MPT caused the highest level of DNA damage as compared to other studied OP compounds. Thus, from present study, we can conclude that studied pesticides have genotoxic potential. The pesticides mixture does not potentiate the toxicity of each other. Nonetheless, additional in vivo data are required before a definitive conclusion can be drawn regarding hazard prediction to humans.

Keywords: organophosphate, pesticides, DNA damage, DNA protein crosslink, genotoxic

Procedia PDF Downloads 336
13559 Parameter Estimation for the Oral Minimal Model and Parameter Distinctions Between Obese and Non-obese Type 2 Diabetes

Authors: Manoja Rajalakshmi Aravindakshana, Devleena Ghosha, Chittaranjan Mandala, K. V. Venkateshb, Jit Sarkarc, Partha Chakrabartic, Sujay K. Maity

Abstract:

Oral Glucose Tolerance Test (OGTT) is the primary test used to diagnose type 2 diabetes mellitus (T2DM) in a clinical setting. Analysis of OGTT data using the Oral Minimal Model (OMM) along with the rate of appearance of ingested glucose (Ra) is performed to study differences in model parameters for control and T2DM groups. The differentiation of parameters of the model gives insight into the behaviour and physiology of T2DM. The model is also studied to find parameter differences among obese and non-obese T2DM subjects and the sensitive parameters were co-related to the known physiological findings. Sensitivity analysis is performed to understand changes in parameter values with model output and to support the findings, appropriate statistical tests are done. This seems to be the first preliminary application of the OMM with obesity as a distinguishing factor in understanding T2DM from estimated parameters of insulin-glucose model and relating the statistical differences in parameters to diabetes pathophysiology.

Keywords: oral minimal model, OGTT, obese and non-obese T2DM, mathematical modeling, parameter estimation

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13558 An Application of Sinc Function to Approximate Quadrature Integrals in Generalized Linear Mixed Models

Authors: Altaf H. Khan, Frank Stenger, Mohammed A. Hussein, Reaz A. Chaudhuri, Sameera Asif

Abstract:

This paper discusses a novel approach to approximate quadrature integrals that arise in the estimation of likelihood parameters for the generalized linear mixed models (GLMM) as well as Bayesian methodology also requires computation of multidimensional integrals with respect to the posterior distributions in which computation are not only tedious and cumbersome rather in some situations impossible to find solutions because of singularities, irregular domains, etc. An attempt has been made in this work to apply Sinc function based quadrature rules to approximate intractable integrals, as there are several advantages of using Sinc based methods, for example: order of convergence is exponential, works very well in the neighborhood of singularities, in general quite stable and provide high accurate and double precisions estimates. The Sinc function based approach seems to be utilized first time in statistical domain to our knowledge, and it's viability and future scopes have been discussed to apply in the estimation of parameters for GLMM models as well as some other statistical areas.

Keywords: generalized linear mixed model, likelihood parameters, qudarature, Sinc function

Procedia PDF Downloads 379
13557 Structuring and Visualizing Healthcare Claims Data Using Systems Architecture Methodology

Authors: Inas S. Khayal, Weiping Zhou, Jonathan Skinner

Abstract:

Healthcare delivery systems around the world are in crisis. The need to improve health outcomes while decreasing healthcare costs have led to an imminent call to action to transform the healthcare delivery system. While Bioinformatics and Biomedical Engineering have primarily focused on biological level data and biomedical technology, there is clear evidence of the importance of the delivery of care on patient outcomes. Classic singular decomposition approaches from reductionist science are not capable of explaining complex systems. Approaches and methods from systems science and systems engineering are utilized to structure healthcare delivery system data. Specifically, systems architecture is used to develop a multi-scale and multi-dimensional characterization of the healthcare delivery system, defined here as the Healthcare Delivery System Knowledge Base. This paper is the first to contribute a new method of structuring and visualizing a multi-dimensional and multi-scale healthcare delivery system using systems architecture in order to better understand healthcare delivery.

Keywords: health informatics, systems thinking, systems architecture, healthcare delivery system, data analytics

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13556 Acculturation Profiles of Syrian Refugees in Turkey

Authors: Abdurrahim Guler

Abstract:

Immigrants who came to a new country experience some socio-cultural difficulties which are different from theirs. The study aims to investigate how Syrian Refugees manage their life in Turkey and the relationship between acculturation profiles and demographic background of Syrian refugees who came to Turkey after civil war has intensified in Syria. Data are collected from 280 adult Syrian refugees who were born in Syria. The study adopts bi-dimensional acculturation approach stating that both heritage and dominant host cultures can live together. Results suggest that demographic backgrounds, religion, and religiosity are significantly linked to both heritage and dominant host culture. Syrian refugees who are not affiliated with Islam are found to significantly preserve their ethnic/heritage culture. Generally, Syrian refugees are more willing to integrate Turkish society but not to assimilate. The results also confirmed acculturation process as a bi-dimensional, not a zero-sum game since we found a significant positive correlation between the heritage and the dominant host cultures which assume the independence and orthogonal of involvements in the dominant host and heritage cultures.

Keywords: acculturation, demographic backgrounds, heritage culture, religion, Syrian refugees

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13555 A Quantitative Study Identifying the Prevalence of Anxiety in Dyslexic Students in Higher Education

Authors: Amanda Abbott-Jones

Abstract:

Adult students with dyslexia in higher education can receive support for their cognitive needs but may also experience negative emotion such as anxiety due to their dyslexia in connection with their studies. This paper aims to test the hypothesis that adult dyslexic learners have a higher prevalence of academic and social anxiety than their non-dyslexic peers. A quantitative approach was used to measure differences in academic and social anxiety between 102 students with a formal diagnosis of dyslexia compared to 72 students with no history of learning difficulties. Academic and social anxiety was measured in a questionnaire based on the State-Trait Anxiety Inventory. Findings showed that dyslexic students showed statistically significant higher levels of academic, but not social anxiety in comparison to the non-dyslexic sample. Dyslexic students in higher education show academic anxiety levels that are well above what is shown by students without dyslexia. The implications of this for the dyslexia practitioner is that delivery of strategies to deal with anxiety should be seen equally as important, if not more so, than interventions to deal with cognitive difficulties.

Keywords: Academic, Anxiety, Dyslexia, Quantitative

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13554 Deep Learning Based Fall Detection Using Simplified Human Posture

Authors: Kripesh Adhikari, Hamid Bouchachia, Hammadi Nait-Charif

Abstract:

Falls are one of the major causes of injury and death among elderly people aged 65 and above. A support system to identify such kind of abnormal activities have become extremely important with the increase in ageing population. Pose estimation is a challenging task and to add more to this, it is even more challenging when pose estimations are performed on challenging poses that may occur during fall. Location of the body provides a clue where the person is at the time of fall. This paper presents a vision-based tracking strategy where available joints are grouped into three different feature points depending upon the section they are located in the body. The three feature points derived from different joints combinations represents the upper region or head region, mid-region or torso and lower region or leg region. Tracking is always challenging when a motion is involved. Hence the idea is to locate the regions in the body in every frame and consider it as the tracking strategy. Grouping these joints can be beneficial to achieve a stable region for tracking. The location of the body parts provides a crucial information to distinguish normal activities from falls.

Keywords: fall detection, machine learning, deep learning, pose estimation, tracking

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13553 One Dimensional Unsteady Boundary Layer Flow in an Inclined Wavy Wall of a Nanofluid with Convective Boundary Condition

Authors: Abdulhakeem Yusuf, Yomi Monday Aiyesimi, Mohammed Jiya

Abstract:

The failure in an ordinary heat transfer fluid to meet up with today’s industrial cooling rate has resulted in the development of high thermal conductivity fluid which nanofluids belongs. In this work, the problem of unsteady one dimensional laminar flow of an incompressible fluid within a parallel wall is considered with one wall assumed to be wavy. The model is presented in its rectangular coordinate system and incorporates the effects of thermophoresis and Brownian motion. The local similarity solutions were also obtained which depends on Soret number, Dufour number, Biot number, Lewis number, and heat generation parameter. The analytical solution is obtained in a closed form via the Adomian decomposition method. It was found that the method has a good agreement with the numerical method, and it is also established that the heat generation parameter has to be kept low so that heat energy are easily evacuated from the system.

Keywords: Adomian decomposition method, Biot number, Dufour number, nanofluid

Procedia PDF Downloads 312
13552 A Comparative Psychological Interventional Study of Nicotine Dependence in Schizophrenic Patients

Authors: S. Madhusudhan, G. V. Vaniprabha

Abstract:

Worldwide statistics have shown that smoking contributes significantly to mortality, with nicotine, being more addictive. Smoking causes more than 7,00,000 deaths/year in India. Compared to the general population, the prevalence of smoking is found to be much higher among people with psychotic disorders and, more so in schizophrenia. Schizophrenic patients who smoke tend to have higher frequency of heavy smoking, with rates ranging from 60% to as high as 80%. Hence, smokers with psychiatric disorders suffer higher rates of morbidity and mortality secondary to smoking related illnesses.

Keywords: brief intervention, nicotine dependence, schizophrenia

Procedia PDF Downloads 365