Search results for: exploratory factors analysis

Authors: Brianna Douglas

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A literary Meta-Analysis was conducted in order to form a proactive solution to the systematic issue of international human trafficking stemming from the Asia-Pacific region. This approach seeks to resolve the low economic prospect for women in the region, along with other identified drivers, to mitigate human trafficking before it begins. Through the reallocation of aid in agriculture, implementation of an education-for-education model, and provision of access to market information to the women in rural regions, the retraction of both the supply and international demand curves of trafficked humans is possible; resulting in the shutdown of the market as a whole. This report provides a basic and adaptable proposal to mitigation the selling of Asia Pacific women within international trafficking schemes with byproduct effects of increasing food, sustainability and decreasing government spending.

Keywords: human trafficking, agricultural development, Asia Pacific, women's empowerment

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Authors: Barbora Chmelíková

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Making sound financial decisions is an essential skill which can have an impact on life of each consumer of financial products. The aim of this paper is to examine decision-making concerning financial matters and personal finance. The selected target group was university students majoring in finance related fields. The study was conducted in the Czech Republic at Masaryk University in 2015. In order to analyze financial decision-making questions related to basic finance decisions were developed to address the research objective. The results of the study suggest gaps in detecting best solutions to given financial decision-making questions among finance students. The analysis results indicate relation between financial decision-making and own experience with holding and using concrete financial products.

Keywords: financial decision-making, financial literacy, personal finance, university students

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Authors: Qasim Zaheer, Jehanzeb Masud

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The understanding of entrainment and mixing phenomenon in the ejector pump is of pivotal importance for designing and performance estimation. In this paper, the existence of turbulent vortical structures due to Kelvin-Helmholtz instability at the free surface between the motive and the entrained fluids streams are simulated using Embedded LES methodology. The efficacy of Embedded LES for simulation of complex flow field of ejector pump is evaluated using ANSYS Fluent®. The enhanced mixing and entrainment process due to breaking down of larger eddies into smaller ones as a consequence of Vortex Stretching phenomenon is captured in this study. Moreover, the flow field characteristics of ejector pump like pressure velocity fields and mass flow rates are analyzed and validated against the experimental results.

Keywords: Kelvin Helmholtz instability, embedded LES, complex flow field, ejector pump

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Authors: Hayder H. Kareem, Shunqi Pan

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Groundwater is a vital water resource in many areas in the world, particularly in the Middle-East region where the water resources become scarce and depleting. Sustainable management and planning of the groundwater resources become essential and urgent given the impact of the global climate change. In the recent years, numerical models have been widely used to predict the flow pattern and assess the water resources security, as well as the groundwater quality affected by the contaminants transported. In this study, MODFLOW is used to study the current status of groundwater resources and the risk of water resource security in the region centred at Al-Najaf City, which is located in the mid-west of Iraq and adjacent to the Euphrates River. In this study, a conceptual model is built using the geologic and hydrogeologic collected for the region, together with the Digital Elevation Model (DEM) data obtained from the "Global Land Cover Facility" (GLCF) and "United State Geological Survey" (USGS) for the study area. The computer model is also implemented with the distributions of 69 wells in the area with the steady pro-defined hydraulic head along its boundaries. The model is then applied with the recharge rate (from precipitation) of 7.55 mm/year, given from the analysis of the field data in the study area for the period of 1980-2014. The hydraulic conductivity from the measurements at the locations of wells is interpolated for model use. The model is calibrated with the measured hydraulic heads at the locations of 50 of 69 wells in the domain and results show a good agreement. The standard-error-of-estimate (SEE), root-mean-square errors (RMSE), Normalized RMSE and correlation coefficient are 0.297 m, 2.087 m, 6.899% and 0.971 respectively. Sensitivity analysis is also carried out, and it is found that the model is sensitive to recharge, particularly when the rate is greater than (15mm/year). Hydraulic conductivity is found to be another parameter which can affect the results significantly, therefore it requires high quality field data. The results show that there is a general flow pattern from the west to east of the study area, which agrees well with the observations and the gradient of the ground surface. It is found that with the current operational pumping rates of the wells in the area, a dry area is resulted in Al-Najaf City due to the large quantity of groundwater withdrawn. The computed water balance with the current operational pumping quantity shows that the Euphrates River supplies water into the groundwater of approximately 11759 m3/day, instead of gaining water of 11178 m3/day from the groundwater if no pumping from the wells. It is expected that the results obtained from the study can provide important information for the sustainable and effective planning and management of the regional groundwater resources for Al-Najaf City.

Keywords: Al-Najaf city, conceptual modelling, groundwater, unconfined aquifer, visual MODFLOW

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Authors: Jolanta Tamošaitienė

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The article focuses on a developed comprehensive model to be used in an agile environment for the risk assessment and selection based on multi-attribute methods. The model is based on a multi-attribute evaluation of risk in construction, and the determination of their optimality criterion values are calculated using complex Multiple Criteria Decision-Making methods. The model may be further applied to risk assessment in an agile construction environment. The attributes of risk in a construction project are selected by applying the risk assessment condition to the construction sector, and the construction process efficiency in the construction industry accounts for the agile environment. The paper presents the comprehensive risk assessment model in an agile construction environment. It provides a background and a description of the proposed model and the developed analysis of the comprehensive risk assessment model in an agile construction environment with the criteria.

Keywords: assessment, environment, agile, model, risk

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Authors: Hong Dongchen, Chen Qiuxiao, Wu Shuang

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Systematic science reveals the complex nonlinear mechanisms of behaviour in urban system. However, in China, when the current city planners face with the system, most of them are still taking simple linear thinking to consider the open complex giant system. This paper introduces the hyper-cycle theory, which is one of the basis theories of systematic science, based on the analysis of the reasons why the current urban planning failed, and proposals for optimization ideas that urban planning compilation should change, from controlling quantitative to the changes of relationship, from blueprint planning to progressive planning based on the nonlinear characteristics and from management control to dynamically monitor feedback.

Keywords: systematic science, hyper-cycle theory, urban planning, urban management

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Authors: Naser Zourikalatehsamad, Seyed Abdorreza Payambarpour, Ibrahim Alwashali, Zahra Abdolkarimi

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The paper aims to evaluate the effect of online advertising on consumer purchase behavior in Malaysian organizations. The paper has potential to extend and refine theory. A survey was distributed among Students of UTM university during the winter 2014 and 160 responses were collected. Regression analysis was used to test the hypothesized relationships of the model. Result shows that the predictors (cost saving factor, convenience factor and customized product or services) have positive impact on intention to continue seeking online advertising.

Keywords: consumer purchase, convenience, customized product, cost saving, customization, flow theory, mass communication, online advertising ads, online advertising measurement, online advertising mechanism, online intelligence system, self-confidence, willingness to purchase

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Authors: I. Ruzaina, A. B. Rashid, M. S. Halimahton Zahrah, C. S. Cheow, M. S. Adi

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This study was conducted to determine the potential of palm stearin (PS) as edible coating materials for fruits. The palm stearin was blended with 20-80% palm kernel olein (PKOo) and the properties of the blends were evaluated in terms of the slip melting point (SMP), solid fat content (SFC), fatty acid and triacylglycerol compositions (TAG), and polymorphism. Blending of PS with PKOo reduced the SMP, SFC, altered the FAC and TAG composition and changed the crystal polymorphism from β to mixture of β and β′. The changes in the physicochemical properties of PS were due to the replacement of the high melting TAG in PS with medium chain TAG in PKOo. From the analysis, 1:1 and 3:2 were the better PSPKOo blend formulations in slowing down the weight loss, respiration gases and gave better appearance when compared to other PSPKOo blends formulations.

Keywords: guava, palm stearin, palm kernel olein, physicochemical

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Authors: Ritika Chaturvedi

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Introduction: Sexual objectification, characterized by the reduction of an individual to a mere object of sexual desire, remains a pervasive societal issue with profound repercussions on individual well-being. Such experiences, often rooted in systemic and cultural norms, have long-lasting implications for mental and emotional health. This study aims to explore the intricate relationship between experiences of sexual objectification and insidious trauma, further investigating the potential moderating effects of overexcitabilities as proposed by Dabrowski's theory of positive disintegration. Methodology: The research involved a comprehensive cohort of 204 women, spanning ages from 18 to 65 years. Participants were tasked with completing self-administered questionnaires designed to capture their experiences with sexual objectification. Additionally, the questionnaire assessed symptoms indicative of insidious trauma and explored overexcitabilities across five distinct domains: emotional, intellectual, psychomotor, sensory, and imaginational. Employing advanced statistical techniques, including multiple regression and moderation analysis, the study sought to decipher the intricate interplay among these variables. Findings: The study's results revealed a compelling positive correlation between experiences of sexual objectification and the onset of symptoms indicative of insidious trauma. This correlation underscores the profound and detrimental effects of sexual objectification on an individual's psychological well-being. Interestingly, the moderation analyses introduced a nuanced understanding, highlighting the differential roles of various overexcitabilities. Specifically, emotional, intellectual, and sensual overexcitabilities were found to exacerbate trauma symptomatology. In contrast, psychomotor overexcitability emerged as a protective factor, demonstrating a mitigating influence on the relationship between sexual objectification and trauma. Implications: The study's findings hold significant implications for a diverse array of stakeholders, encompassing mental health practitioners, educators, policymakers, and advocacy groups. The identified moderating effects of overexcitabilities emphasize the need for tailored interventions that consider individual differences in coping and resilience mechanisms. By recognizing the pivotal role of overexcitabilities in modulating the traumatic consequences of sexual objectification, this research advocates for the development of more nuanced and targeted support frameworks. Moreover, the study underscores the importance of continued research endeavors to unravel the intricate mechanisms and dynamics underpinning these relationships. Such endeavors are crucial for fostering the evolution of informed, evidence-based interventions and strategies aimed at mitigating the adverse effects of sexual objectification and promoting holistic well-being.

Keywords: sexual objectification, insidious trauma, emotional overexcitability, intellectual overexcitability, sensual overexcitability, psychomotor overexcitability, imaginational overexcitability

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Authors: U. K. Sahin, N. Erdumlu, C. Saricam, I. Gocek, M. H. Arslan, H. Acikgoz-Tufan, B. Kalav

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Finishing is an important part of fabric processing with which a wide range of features are imparted to greige or colored fabrics for various end-uses. Especially, by the addition or impartation of nano-scaled particles to the fabric structure composite fabrics, a kind of composite materials can be acquired. Composite materials, generally shortened as composites or in other words composition materials, are engineered or naturally occurring materials made from two or more component materials with significantly different physical, mechanical or chemical characteristics remaining separate and distinctive at the macroscopic or microscopic scale within the end product structure. Therefore, the technique finishing which is one of the fundamental methods to be applied on fabrics for obtainment of composite fabrics with many functionalities was used in the current study with the same purpose. However, regardless of the finishing materials applied, the efficient life of finished product on offering desired feature is low, since the durability of finishes on the material is limited. Any increase in durability of these finishes on textiles would enhance the life of use for textiles, which will result in happier users. Therefore, in this study, since higher durability was desired for the finishing materials fixed on the fabrics, nano-scaled hollow structured cyclodextrins were chemically imparted by grafting to the structure of conventional cotton fabrics by the help of finishing technique in order to be fixed permanently. By this way, a processed and functionalized base fabric having potential to be treated in the subsequent processes with many different finishing agents and nanomaterials could be obtained. Henceforth, this fabric can be used as a multi-functional fabric due to the encapturing ability of cyclodextrins to molecules/particles via physical/chemical means. In this study, scoured and rinsed woven bleached plain weave 100% cotton fabrics were utilized because textiles made of cotton are the most demanded textile products in the textile market by the textile consumers in daily life. Cotton fabric samples were immersed in treating baths containing β-cyclodextrin and 1,2,3,4-butanetetracarboxylic acid and to reduce the curing temperature the catalyst sodium hypophosphite monohydrate was used. All impregnated fabric samples were pre-dried. The reaction of grafting was performed in dry state. The treated and cured fabric samples were rinsed with warm distilled water and dried. The samples were dried for 4 h and weighed before and after finishing and rinsing. Stability and durability of β-cyclodextrins on fabric surface against external factors such as washing as well as strength of functionalized fabric in terms of tensile and tear strength were tested. Presence and homogeneity of distribution of β-cyclodextrins on fabric surface were characterized.

Keywords: cotton fabric, cyclodextrine, improved durability, multifunctional composite textile

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Authors: Nirjhar Dhang, S. Vinay Kumar

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Concrete is a non-homogeneous mix of coarse aggregates, sand, cement, air-voids and interfacial transition zone (ITZ) around aggregates. Adoption of these complex structures and material properties in numerical simulation would lead us to better understanding and design of concrete. In this work, the mesoscale model of concrete has been prepared from X-ray computerized tomography (CT) image. These images are converted into computer model and numerically simulated using commercially available finite element software. The mesoscale models are simulated under the influence of compressive displacement. The effect of shape and distribution of aggregates, continuous and discrete ITZ thickness, voids, and variation of mortar strength has been investigated. The CT scan of concrete cube consists of series of two dimensional slices. Total 49 slices are obtained from a cube of 150mm and the interval of slices comes approximately 3mm. In CT scan images, the same cube can be CT scanned in a non-destructive manner and later the compression test can be carried out in a universal testing machine (UTM) for finding its strength. The image processing and extraction of mortar and aggregates from CT scan slices are performed by programming in Python. The digital colour image consists of red, green and blue (RGB) pixels. The conversion of RGB image to black and white image (BW) is carried out, and identification of mesoscale constituents is made by putting value between 0-255. The pixel matrix is created for modeling of mortar, aggregates, and ITZ. Pixels are normalized to 0-9 scale considering the relative strength. Here, zero is assigned to voids, 4-6 for mortar and 7-9 for aggregates. The value between 1-3 identifies boundary between aggregates and mortar. In the next step, triangular and quadrilateral elements for plane stress and plane strain models are generated depending on option given. Properties of materials, boundary conditions, and analysis scheme are specified in this module. The responses like displacement, stresses, and damages are evaluated by ABAQUS importing the input file. This simulation evaluates compressive strengths of 49 slices of the cube. The model is meshed with more than sixty thousand elements. The effect of shape and distribution of aggregates, inclusion of voids and variation of thickness of ITZ layer with relation to load carrying capacity, stress-strain response and strain localizations of concrete have been studied. The plane strain condition carried more load than plane stress condition due to confinement. The CT scan technique can be used to get slices from concrete cores taken from the actual structure, and the digital image processing can be used for finding the shape and contents of aggregates in concrete. This may be further compared with test results of concrete cores and can be used as an important tool for strength evaluation of concrete.

Keywords: concrete, image processing, plane strain, interfacial transition zone

Procedia PDF Downloads 237

Authors: Precious Ehiomogue, Ifechukwude Israel Ahuchaogu, Isiguzo Edwin Ahaneku

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Vermicompost is the product of the decomposition process using various species of worms, to create a mixture of decomposing vegetable or food waste, bedding materials, and vemicast. This process is called vermicomposting, while the rearing of worms for this purpose is called vermiculture. Several works have verified the adsorption of toxic metals using vermicompost but the application is still scarce for the retention of organic compounds. This research brings to knowledge the effectiveness of earthworm waste (vermicompost) for the remediation of crude oil contaminated soils. The remediation methods adopted in this study were two soil washing methods namely, batch and column process which represent laboratory and in-situ remediation. Characterization of the vermicompost and crude oil contaminated soil were performed before and after the soil washing using Fourier transform infrared (FTIR), scanning electron microscopy (SEM), X-ray fluorescence (XRF), X-ray diffraction (XRD) and Atomic adsorption spectrometry (AAS). The optimization of washing parameters, using response surface methodology (RSM) based on Box-Behnken Design was performed on the response from the laboratory experimental results. This study also investigated the application of machine learning models [Artificial neural network (ANN), Adaptive neuro fuzzy inference system (ANFIS). ANN and ANFIS were evaluated using the coefficient of determination (R²) and mean square error (MSE)]. Removal efficiency obtained from the Box-Behnken design experiment ranged from 29% to 98.9% for batch process remediation. Optimization of the experimental factors carried out using numerical optimization techniques by applying desirability function method of the response surface methodology (RSM) produce the highest removal efficiency of 98.9% at absorbent dosage of 34.53 grams, adsorbate concentration of 69.11 (g/ml), contact time of 25.96 (min), and pH value of 7.71, respectively. Removal efficiency obtained from the multilevel general factorial design experiment ranged from 56% to 92% for column process remediation. The coefficient of determination (R²) for ANN was (0.9974) and (0.9852) for batch and column process, respectively, showing the agreement between experimental and predicted results. For batch and column precess, respectively, the coefficient of determination (R²) for RSM was (0.9712) and (0.9614), which also demonstrates agreement between experimental and projected findings. For the batch and column processes, the ANFIS coefficient of determination was (0.7115) and (0.9978), respectively. It can be concluded that machine learning models can predict the removal of crude oil from polluted soil using vermicompost. Therefore, it is recommended to use machines learning models to predict the removal of crude oil from contaminated soil using vermicompost.

Keywords: ANFIS, ANN, crude-oil, contaminated soil, remediation and vermicompost

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Authors: Ghada A. Alfattni

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Analysing unbalanced datasets is one of the challenges that practitioners in machine learning field face. However, many researches have been carried out to determine the effectiveness of the use of the synthetic minority over-sampling technique (SMOTE) to address this issue. The aim of this study was therefore to compare the effectiveness of the SMOTE over different models on unbalanced datasets. Three classification models (Logistic Regression, Support Vector Machine and Nearest Neighbour) were tested with multiple datasets, then the same datasets were oversampled by using SMOTE and applied again to the three models to compare the differences in the performances. Results of experiments show that the highest number of nearest neighbours gives lower values of error rates. 

Keywords: imbalanced datasets, SMOTE, machine learning, logistic regression, support vector machine, nearest neighbour

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Authors: Arjun, A. D. Singh

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Concrete the basic material using in construction across the global these days. The purpose of this special concrete is to provide extra strength and stability for irregular structure where the center of gravity is disturbed. In this paper an effort has been made to use different type of material aggregates has been discussed. We named As "STAR Aggregates" which has qualities to resist Shear, tension and compression forces. We have been divided into coarse aggregates and fine aggregates according to their sizes. Star Aggregates has interlocking behavior and cutting edge technology. Star aggregates had been draft and deign in Auto CAD and then analysis in ANSYS software. by using special aggregates we deign concrete grade of M40 for mega structures and irregular structure. This special concrete with STAR aggregates use in construction for irregular structure like Bridges, Skyscrapers or in deigned buildings.

Keywords: star aggregates, high performance concrete, material aggregates, interlocking

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Authors: Mohd Asrul Affedi, Nyi Nyi Naing

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Overdispersion is present in count data, and basically when a phenomenon happened, a Negative Binomial (NB) is commonly used to replace a standard Poisson model. Analysis of count data event, such as mortality cases basically Poisson regression model is appropriate. Hence, the model is not appropriate when existing a zero values. The zero-inflated negative binomial model is appropriate. In this article, we modelled the mortality cases as a dependent variable by age categorical. The objective of this study to determine existing overdispersion in mortality data of AIDS co-infection patients in Kelantan.

Keywords: negative binomial death rate, overdispersion, zero-inflation negative binomial death rate, AIDS

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Authors: L. Ramirez, E. Guillén, J. Sánchez

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Some of the main goals about telecare such as monitoring, treatment, telediagnostic are deployed with the integration of applications with specific appliances. In order to achieve a coherent model to integrate software, hardware, and healthcare systems, different telehealth models with Internet of Things (IoT), cloud computing, artificial intelligence, etc. have been implemented, and their advantages are still under analysis. In this paper, we propose an integrated model based on IoT architecture and cloud computing telehealth center. Analytics module is presented as a solution to control an ideal diagnostic about some diseases. Specific features are then compared with the recently deployed conventional models in telemedicine. The main advantage of this model is the availability of controlling the security and privacy about patient information and the optimization on processing and acquiring clinical parameters according to technical characteristics.

Keywords: analytics, telemedicine, internet of things, cloud computing

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Authors: Sh. Minapoor, S. Ajeli, M. Javadi Toghchi

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Non-crimp 3D orthogonal fabric composite is one of the textile-based composite materials that are rapidly developing light-weight engineering materials. The present paper focuses on geometric and micro mechanical modeling of non-crimp 3D orthogonal carbon fabric and composites reinforced with it for aerospace applications. In this research meso-finite element (FE) modeling employs for stress analysis in different load conditions. Since mechanical testing of expensive textile carbon composites with specific application isn't affordable, simulation composite in a virtual environment is a helpful way to investigate its mechanical properties in different conditions.

Keywords: woven composite, aerospace applications, finite element method, mechanical properties

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Authors: Jon Cobb, Nasir

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Due to higher switching frequencies, the conducted Electromagnetic interference (EMI) noise is generated in a converter. It degrades the performance of a switching converter. Therefore, it is an essential requirement to mitigate EMI noise of high performance converter. Moreover, it includes two types of emission such as common mode (CM) and differential mode (DM) noise. CM noise is due to parasitic capacitance present in a converter and DM noise is caused by switching current. However, there is dire need to understand the main cause of EMI noise. Hence, we propose a novel method to predict conducted EMI noise of different converter topologies during early stage. This paper also presents the comparison of conducted electromagnetic interference (EMI) noise due to different SMPS topologies. We also make an attempt to develop an EMI noise model for a converter which allows detailed performance analysis. The proposed method is applied to different converter, as an example, and experimental results are verified the novel prediction technique.

Keywords: EMI, electromagnetic interference, SMPS, switch-mode power supply, common mode, CM, differential mode, DM, noise

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Authors: Henry Gonzalo Acurio Flores, Alvaro Nicolas Corral Naveda, Juan Francisco Fonseca Palacios

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In Ecuador, subventions on fossil fuels for the road transportation sector have always been part of its economy throughout time, mainly because of demagogy and populism from political leaders. It is clearly seen that the government cannot maintain the subsidies anymore due to its commercial balance and its general state budget; subsidies are a key barrier to implementing the use of cleaner technologies. However, during the last few months, the elimination of subsidies has been done gradually with the purpose of reaching international prices. It is expected that with this measure, the population will opt for other means of transportation, and in a certain way, it will promote the use of private electric vehicles and public, e.g., taxis and buses (urban transport). Considering the three main elements of sustainable development, an analysis of the social, economic, and environmental impacts of eliminating subsidies will be generated at the country level. To achieve this, four scenarios will be developed in order to determine how the subsidies will contribute to the promotion of electro-mobility. 1) A Business as Usual BAU scenario; 2) the introduction of 10 000 electric vehicles by 2025; 3) the introduction of 100 000 electric vehicles by 2030; 4) the introduction of 750 000 electric vehicles by 2040 (for all the scenarios buses, taxis, lightweight duty vehicles, and private vehicles will be introduced, as it is established in the National Electro Mobility Strategy for Ecuador). The Low Emissions Analysis Platform (LEAP) will be used, and it will be suitable to determine the cost for the government in terms of importing derivatives for fossil fuels and the cost of electricity to power the electric fleet that can be changed. The elimination of subventions generates fiscal resources for the state that can be used to develop other kinds of projects that will benefit Ecuadorian society. It will definitely change the energy matrix, and it will provide energy security for the country; it will be an opportunity for the government to incentivize a greater introduction of renewable energies, e.g., solar, wind, and geothermal. At the same time, it will also reduce greenhouse gas emissions (GHG) from the transportation sector, considering its mitigation potential, which as a result, will ameliorate the inhabitant quality of life by improving the quality of air, therefore reducing respiratory diseases associated with exhaust emissions, consequently, achieving sustainability, the Sustainable Development Goals (SDGs), and complying with the agreements established in the Paris Agreement COP 21 in 2015. Electro mobility in Latin America and the Caribbean can only be achieved by the implementation of the right policies at the central government, which need to be accompanied by a National Urban Mobility Policy (NUMP) and can encompass a greater vision to develop holistic, sustainable transport systems at local governments.

Keywords: electro mobility, energy, policy, sustainable transportation

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Authors: Jasmeet Kaur, Anup Singh, Shashikant Iyengar, Arun Kumar, Ira Sahay

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Latent autoimmune diabetes in adults (LADA) is an irreversible autoimmune disease that affects insulin production. LADA is characterized by the production of Glutamic acid decarboxylase (GAD) antibodies, which is similar to type 1 diabetes. Individuals with LADA may eventually develop overt diabetes and require insulin. In this condition, the pancreas produces little or no insulin, which is a hormone used by the body to allow glucose to enter cells and produce energy. While type 1 diabetes was traditionally associated with children and teenagers, its prevalence has increased in adults as well. LADA is frequently misdiagnosed as type 2 diabetes, especially in adulthood when type 2 diabetes is more common. LADA develops in adulthood, usually after age 30. Managing LADA involves metabolic control with exogenous insulin and prolonging the life of surviving beta cells, thereby slowing the disease's progression. This case study examines the impact of approximately 3 months of low-carbohydrate dietary intervention in a 42-year-old woman with LADA who was initially misdiagnosed as having type 2 diabetes. Her c-peptide was 0.13 and her HbA1c was 9.3% when this trial began. Low-carbohydrate interventions have been shown to improve blood sugar levels, including fasting, post-meal, and random blood sugar levels, as well as haemoglobin levels, blood pressure, energy levels, sleep quality, and satiety levels. The use of low-carbohydrate dietary intervention significantly reduces both hypo- and hyperglycaemia events. During the 3 months of the study, there were 2 to 3 hyperglycaemic events owing to physical stress and a single hypoglycaemic event. Low-carbohydrate dietary therapies lessen insulin dose inaccuracy, which explains why there were fewer hyperglycaemic and hypoglycaemic events. In three months, the glycated haemoglobin (HbA1c) level was reduced from 9.3% to 6.3%. These improvements occur without the need for caloric restriction or physical activity. Stress management was crucial aspect of the treatment plan as stress-induced neuroendocrine hormones can cause immunological dysregulation. Additionally, supplements that support immune system and reduce inflammation were used as part of the treatment during the trial. Long-term studies are needed to track disease development and corroborate the claim that such dietary treatments can prolong the honeymoon phase in LADA. Various factors can contribute to additional autoimmune attacks, so measuring c-peptide is crucial on a regular basis to determine whether insulin levels need to be adjusted.

Keywords: autoimmune, diabetes, LADA, low_carb, nutrition

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Authors: Shreya Thusoo, Karan Modi, Rajesh Kumar, Hitesh Madahar

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Over the years, it has been extensively established that the practice of assuming a structure being fixed at base, leads to gross errors in evaluation of its overall response due to dynamic loadings and overestimations in design. The extent of these errors depends on a number of variables; soil type being one of the major factor. This paper studies the effect of Soil Structure Interaction (SSI) on multi-storey buildings with varying under-laying soil types after proper validation of the effect of SSI. Analysis for soft, stiff and very stiff base soils has been carried out, using a powerful Finite Element Method (FEM) software package ANSYS v14.5. Results lead to some very important conclusions regarding time period, deflection and acceleration responses.

Keywords: dynamic response, multi-storey building, soil-structure interaction, varying soil types

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Authors: Larbi Hammadi, Abdellatif El Bari Tidjani

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In order to reduce the flow of pollutants in the wastewater of the urban agglomerations of the city of Oran, a preliminary study was carried out at the El-Karma wastewater treatment plant. The primary objective of this study was to estimate the overall physicochemical pollution in the effluents of the El-Karma sewage treatment plant wastewater. It was found that the effluent of El-Karma wastewater treatment plant contains a significant amount of insoluble. Total suspended soli TSS concentrations ranged from 112 to 475 mg/l, with an average of 220.5 mg/l. The chemical oxygen demand (COD) and biochemical oxygen demand (BOD₅) values remain within the reference range for domestic wastewater with an average value of COD < 125 and BOD₅ < 25. The COD/BOD₅ ratio of raw water entering the treatment plant is less than 2. This ratio would predict that the raw sewage from the El-Karma treatment plant is polluted by inorganic pollution strong enough.

Keywords: El-Karma wastewater, TSS concentrations, COD and BOD5, COD/BOD5 ratio, treatment

Procedia PDF Downloads 255

Authors: E. Popov, N. Yorino, Y. Zoka, Y. Sasaki, H. Sugihara

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This paper discusses the performance of critical trajectory method (CTrj) for power system transient stability analysis under various loading settings and heavy fault condition. The method obtains Controlling Unstable Equilibrium Point (CUEP) which is essential for estimation of power system stability margins. The CUEP is computed by applying the CTrjto the boundary controlling unstable equilibrium point (BCU) method. The Proposed method computes a trajectory on the stability boundary that starts from the exit point and reaches CUEP under certain assumptions. The robustness and effectiveness of the method are demonstrated via six power system models and five loading conditions. As benchmark is used conventional simulation method whereas the performance is compared with and BCU Shadowing method.

Keywords: power system, transient stability, critical trajectory method, energy function method

Procedia PDF Downloads 378

Authors: Klaus Peter Scherer, Daniel Knöll, Constantin Rieder

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Problem and Purpose: Intelligent systems are available and helpful to support the human being decision process, especially when complex surgical eye interventions are necessary and must be performed. Normally, such a decision support system consists of a knowledge-based module, which is responsible for the real assistance power, given by an explanation and logical reasoning processes. The interview based acquisition and generation of the complex knowledge itself is very crucial, because there are different correlations between the complex parameters. So, in this project (semi)automated self-learning methods are researched and developed for an enhancement of the quality of such a decision support system. Methods: For ophthalmic data sets of real patients in a hospital, advanced data mining procedures seem to be very helpful. Especially subgroup analysis methods are developed, extended and used to analyze and find out the correlations and conditional dependencies between the structured patient data. After finding causal dependencies, a ranking must be performed for the generation of rule-based representations. For this, anonymous patient data are transformed into a special machine language format. The imported data are used as input for algorithms of conditioned probability methods to calculate the parameter distributions concerning a special given goal parameter. Results: In the field of knowledge discovery advanced methods and applications could be performed to produce operation and patient related correlations. So, new knowledge was generated by finding causal relations between the operational equipment, the medical instances and patient specific history by a dependency ranking process. After transformation in association rules logically based representations were available for the clinical experts to evaluate the new knowledge. The structured data sets take account of about 80 parameters as special characteristic features per patient. For different extended patient groups (100, 300, 500), as well one target value as well multi-target values were set for the subgroup analysis. So the newly generated hypotheses could be interpreted regarding the dependency or independency of patient number. Conclusions: The aim and the advantage of such a semi-automatically self-learning process are the extensions of the knowledge base by finding new parameter correlations. The discovered knowledge is transformed into association rules and serves as rule-based representation of the knowledge in the knowledge base. Even more, than one goal parameter of interest can be considered by the semi-automated learning process. With ranking procedures, the most strong premises and also conjunctive associated conditions can be found to conclude the interested goal parameter. So the knowledge, hidden in structured tables or lists can be extracted as rule-based representation. This is a real assistance power for the communication with the clinical experts.

Keywords: an expert system, knowledge-based support, ophthalmic decision support, self-learning methods

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Authors: Zhi-Jun Lu, Qi Lu, Meng Wu, Qian Xiang, Jun Gu

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The analysis of perforated steel members is a 3D problem in nature, therefore the traditional analytical expressions for the ultimate load of thin-walled steel sections cannot be used for the perforated steel member design. In this study, finite element method (FEM) and artificial neural network (ANN) were used to simulate the process of stub column tests based on specific codes. Results show that compared with those of the FEM model, the ultimate load predictions obtained from ANN technique were much closer to those obtained from the physical experiments. The ANN model for the solving the hard problem of complex steel perforated sections is very promising.

Keywords: artificial neural network (ANN), finite element method (FEM), perforated sections, thin-walled Steel, ultimate load

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Authors: Mara Simons

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There are many ways to define what 'diaspora' is in a global world as the term has become more and more fluid in the way it is understood and implemented. The main focus of the research has been on the definition of diaspora – arguments against and for the wider and inclusive definition versus the narrower and excluding one. Who can belong and who are supposed to be left out, who is 'ours' and who is 'other' – those struggles have been observed and researched in the content analysis of Latvia’s mass media, audio recordings from the Foreign Affairs Commission of the parliament of Latvia and official letters from the Ministries, deputies and NGO’s. Latvia’s case is interesting from the point of view of cultural studies as it has been a real struggle to define the term 'diaspora' and it's content in Latvia’s Diaspora law. Those in favour of a narrow definition warned of political risks for Latvia (such as voting demographics). The side arguing for a wide definition argued that anyone with a felt ‘connection’ should be eligible. This identity-based debate is still on-going in spite of the inclusive definition of diaspora being integrated into the law.

Keywords: belonging, cultural studies, diaspora, Latvia

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Authors: Helen J. Spray, Karina J. Linnell

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Local-global bias in adulthood is strongly dependent on environmental factors and a global bias is not the universal characteristic of adult perception it was once thought to be: whilst Western adults typically demonstrate a global bias, Namibian adults living in traditional villages possess a strong local bias. Furthermore, environmental effects on local-global bias have been shown to be highly gender-specific; whereas urbanisation promoted a global bias in urbanised Namibian women but not men, education promoted a global bias in urbanised Namibian men but not women. Adult populations, however, provide only a snapshot of the gene-environment interactions which shape perceptual bias. Yet, to date, there has been little work on the development of local-global bias across environmental settings. In the current study, local-global bias was assessed using a similarity-matching task with Navon figures in children aged between 4 and 15 years from across three populations: traditional Namibians, urban Namibians, and urban British. For the two Namibian groups, measures of urbanisation and education were obtained. Data were subjected to both between-group and within-group analyses. Between-group analyses compared developmental trajectories across population and gender. These analyses revealed a global bias from even as early as 4 in the British sample, and showed that the developmental onset of a global bias is not fixed. Urbanised Namibian children ultimately developed a global bias that was indistinguishable from British children; however, a global bias did not emerge until much later in development. For all populations, the greatest developmental effects were observed directly following the onset of formal education. No overall gender effects were observed; however, there was a significant gender by age interaction which was difficult to reconcile with existing biological-level accounts of gender differences in the development of local-global bias. Within-group analyses compared the effects of urbanisation and education on local-global bias for traditional and urban Namibian boys and girls separately. For both traditional and urban boys, education mediated all effects of age and urbanisation; however, this was not the case for girls. Traditional Namibian girls retained a local bias regardless of age, education, or urbanisation, and in urbanised girls, the development of a global bias was not attributable to any one factor specifically. These results are broadly consistent with aforementioned findings that education promoted a global bias in urbanised Namibian men but not women. The development of local-global bias does not follow a fixed trajectory but is subject to environmental control. Understanding how variability in the development of local-global bias might arise, particularly in the context of gender, may have far-reaching implications. For example, a number of educationally important cognitive functions (e.g., spatial ability) are known to show consistent gender differences in childhood and local-global bias may mediate some of these effects. With education becoming an increasingly prevalent force across much of the developing world it will be important to understand the processes that underpin its effects and their implications.

Keywords: cross-cultural, development, education, gender, local-global bias, perception, urbanisation, urbanization

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Authors: Dana Pugach, Michal Tamir

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Most criminal cases end with a plea agreement, an issue whose many aspects have been discussed extensively in legal literature. One important feature, however, has gained little notice, and that is crime victims’ place in plea agreements following the federal Crime Victims Rights Act of 2004. This law has provided victims some meaningful and potentially revolutionary rights, including the right to be heard in the proceeding and a right to appeal against a decision made while ignoring the victim’s rights. While victims’ rights literature has always emphasized the importance of such right, references to this provision in the general literature about plea agreements are sparse, if existing at all. Furthermore, there are a few cases only mentioning this right. This article purports to bridge between these two bodies of legal thinking – the vast literature concerning plea agreements and victims’ rights research– by using behavioral economics. The article will, firstly, trace the possible structural reasons for the failure of this right to be materialized. Relevant incentives of all actors involved will be identified as well as their inherent consequential processes that lead to the victims’ rights malfunction. Secondly, the article will use nudge theory in order to suggest solutions that will enhance incentives for the repeat players in the system (prosecution, judges, defense attorneys) and lead to the strengthening of weaker group’s interests – the crime victims. Behavioral psychology literature recognizes that the framework in which an individual confronts a decision can significantly influence his decision. Richard Thaler and Cass Sunstein developed the idea of ‘choice architecture’ - ‘the context in which people make decisions’ - which can be manipulated to make particular decisions more likely. Choice architectures can be changed by adjusting ‘nudges,’ influential factors that help shape human behavior, without negating their free choice. The nudges require decision makers to make choices instead of providing a familiar default option. In accordance with this theory, we suggest a rule, whereby a judge should inquire the victim’s view prior to accepting the plea. This suggestion leaves the judge’s discretion intact; while at the same time nudges her not to go directly to the default decision, i.e. automatically accepting the plea. Creating nudges that force actors to make choices is particularly significant when an actor intends to deviate from routine behaviors but experiences significant time constraints, as in the case of judges and plea bargains. The article finally recognizes some far reaching possible results of the suggestion. These include meaningful changes to the earlier stages of criminal process even before reaching court, in line with the current criticism of the plea agreements machinery.

Keywords: plea agreements, victims' rights, nudge theory, criminal justice

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Authors: Amin Salighehdar, Ziwen Ye, Mingzhe Liu, Ionut Florescu, Alan F. Blumberg

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Storm surge is an abnormal water level caused by a storm. Accurate prediction of a storm surge is a challenging problem. Researchers developed various ensemble modeling techniques to combine several individual forecasts to produce an overall presumably better forecast. There exist some simple ensemble modeling techniques in literature. For instance, Model Output Statistics (MOS), and running mean-bias removal are widely used techniques in storm surge prediction domain. However, these methods have some drawbacks. For instance, MOS is based on multiple linear regression and it needs a long period of training data. To overcome the shortcomings of these simple methods, researchers propose some advanced methods. For instance, ENSURF (Ensemble SURge Forecast) is a multi-model application for sea level forecast. This application creates a better forecast of sea level using a combination of several instances of the Bayesian Model Averaging (BMA). An ensemble dressing method is based on identifying best member forecast and using it for prediction. Our contribution in this paper can be summarized as follows. First, we investigate whether the ensemble models perform better than any single forecast. Therefore, we need to identify the single best forecast. We present a methodology based on a simple Bayesian selection method to select the best single forecast. Second, we present several new and simple ways to construct ensemble models. We use correlation and standard deviation as weights in combining different forecast models. Third, we use these ensembles and compare with several existing models in literature to forecast storm surge level. We then investigate whether developing a complex ensemble model is indeed needed. To achieve this goal, we use a simple average (one of the simplest and widely used ensemble model) as benchmark. Predicting the peak level of Surge during a storm as well as the precise time at which this peak level takes place is crucial, thus we develop a statistical platform to compare the performance of various ensemble methods. This statistical analysis is based on root mean square error of the ensemble forecast during the testing period and on the magnitude and timing of the forecasted peak surge compared to the actual time and peak. In this work, we analyze four hurricanes: hurricanes Irene and Lee in 2011, hurricane Sandy in 2012, and hurricane Joaquin in 2015. Since hurricane Irene developed at the end of August 2011 and hurricane Lee started just after Irene at the beginning of September 2011, in this study we consider them as a single contiguous hurricane event. The data set used for this study is generated by the New York Harbor Observing and Prediction System (NYHOPS). We find that even the simplest possible way of creating an ensemble produces results superior to any single forecast. We also show that the ensemble models we propose generally have better performance compared to the simple average ensemble technique.

Keywords: Bayesian learning, ensemble model, statistical analysis, storm surge prediction

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Authors: F. Dabir, R. Sarraf-Mamoory, N. Riahi-Noori

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In this work, a nanostructured TiO2 layer was coated onto a FTO-less glass substrate using screen printing technique for back contact DSSC application. Then, titanium nitride thin film was applied on TiO2 layer by plasma assisted chemical vapor deposition (PACVD) as charge collector layer. The microstructure of prepared TiO2 layer was characterized by SEM. The sheet resistance, microstructure and elemental composition of titanium nitride thin films were analysed by four point probe, SEM, and EDS, respectively. TiO2 layer had porous nanostructure. The EDS analysis of TiN thin film showed presence of chlorine impurity. Sheet resistance of TiN thin film was 30 Ω/sq. With respect to the results, PACVD TiN can be a good candidate as a charge collector layer in back contacts DSSC.

Keywords: TiO2, TiN, charge collector, DSSC

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