Search results for: electrical network frequency stability

Authors: Ahmet Koyuncu, Abdullah Berkan Erdogmus, Orkun Dogu, Sinan Uygur

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Thermoelectric modules are integrated to electronic components to keep their temperature in specific values in electronic cooling applications. They can be used in different ambient temperatures. The cold side temperatures of thermoelectric modules depend on their hot side temperatures, operation currents, and heat loads. Performance curves of thermoelectric modules are given at most two different hot surface temperatures in product catalogs. Characteristic properties are required to select appropriate thermoelectric modules in thermal design phase of projects. Generally, manufacturers do not provide characteristic material property values of thermoelectric modules to customers for confidentiality. Common commercial software applied like ANSYS ICEPAK, FloEFD, etc., include thermoelectric modules in their libraries. Therefore, they can be easily used to predict the effect of thermoelectric usage in thermal design. Some software requires only the performance values in different temperatures. However, others like ICEPAK require three temperature-dependent equations for material properties (Seebeck coefficient (α), electrical resistivity (β), and thermal conductivity (γ)). Since the number and the variety of thermoelectric modules are limited in this software, definitions of characteristic material properties of thermoelectric modules could be required. In this manuscript, the method of derivation of characteristic material properties from the datasheet of thermoelectric modules is presented. Material characteristics were estimated from two different performance curves by experimentally and numerically in this study. Numerical calculations are accomplished in ICEPAK by using a thermoelectric module exists in the ICEPAK library. A new experimental setup was established to perform experimental study. Because of similar results of numerical and experimental studies, it can be said that proposed equations are approved. This approximation can be suggested for the analysis includes different type or brand of TEC modules.

Keywords: electrical resistivity, material characteristics, thermal conductivity, thermoelectric coolers, seebeck coefficient

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Authors: Evgeniya Y. Yuzbasheva, Tigran V. Yuzbashev, Natalia I. Perkovskaya, Elizaveta B. Mostova

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Cell-surface display of lipase is of great interest as it has many applications in the field of biotechnology owing to its unique advantages: simplified product purification, and cost-effective downstream processing. One promising area of application for whole-cell biocatalysts with surface displayed lipase is biodiesel synthesis. Biodiesel is biodegradable, renewable, and nontoxic alternative fuel for diesel engines. Although the alkaline catalysis method has been widely used for biodiesel production, it has a number of limitations, such as rigorous feedstock specifications, complicated downstream processes, including removal of inorganic salts from the product, recovery of the salt-containing by-product glycerol, and treatment of alkaline wastewater. Enzymatic synthesis of biodiesel can overcome these drawbacks. In this study, Lip2p lipase was displayed on Yarrowia lipolytica cells via C- and N-terminal fusion variant. The active site of lipase is located near the C-terminus, therefore to prevent the activity loosing the insertion of glycine-serine linker between Lip2p and C-domains was performed. The hydrolytic activity of the displayed lipase reached 12,000–18,000 U/g of dry weight. However, leakage of enzyme from the cell wall was observed. In case of C-terminal fusion variant, the leakage was occurred due to the proteolytic cleavage within the linker peptide. In case of N-terminal fusion variant, the leaking enzyme was presented as three proteins, one of which corresponded to the whole hybrid protein. The calculated number of recombinant enzyme displayed on the cell surface is approximately 6–9 × 105 molecules per cell, which is close to the theoretical maximum (2 × 106 molecules/cell). Thus, we attribute the enzyme leakage to the limited space available on the cell surface. Nevertheless, cell-bound lipase exhibited greater stability to short-term and long-term temperature treatment than the native enzyme. It retained 74% of original activity at 60°C for 5 min of incubation, and 83% of original activity after incubation at 50°C during 5 h. Cell-bound lipase had also higher stability in organic solvents and detergents. The developed whole-cell biocatalyst was used for recycling biodiesel synthesis. Two repeated cycles of methanolysis yielded 84.1–% and 71.0–% methyl esters after 33–h and 45–h reactions, respectively.

Keywords: biodiesel, cell-surface display, lipase, whole-cell biocatalyst

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Authors: Meysam Saidi

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While the specific externalities and required regulatory measures in relation to Islamic banking are fairly uncertain, the business is growing across the world. Unofficial data indicate that the Islamic Finance market is growing with annual rate of 15% and it has reached 1.3 $ trillion size. This trend is associated with inherent systematic connection of Islamic financial institutions to other entities and different sectors of economies. Islamic banking has been subject of market development policies in major economies, most notably the UK. This trend highlights the need for identification of distinct risk features of Islamic banking and crafting customized regulatory measures. So far there has not been a significant systemic crisis in this market which can be attributed to its distinct nature. However, the significant growth and spread of its products worldwide necessitate an in depth study of its nature for customized congruent regulatory measures. In the post financial crisis era some market analysis and reports suggested that the Islamic banks fairly weathered the crisis. As far as heavily blamed conventional financial products such as subprime mortgage backed securities and speculative credit default swaps were concerned the immunity claim can be considered true, as Islamic financial institutions were not directly exposed to such products. Nevertheless, similar to the experience of the conventional banking industry, it can be only a matter of time for Islamic banks to face failures that can be specific to the nature of their business. Using the experience of conventional banking regulations and identifying those peculiarities of Islamic banking that need customized regulatory approach can aid to prevent major failures. Frank Knight has stated that “We perceive the world before we react to it, and we react not to what we perceive, but always to what we infer”. The debate over congruent Islamic banking regulations might not be an exception to Frank Knight’s statement but I will try to base my discussion on concrete evidences. This paper first analyzes both theoretical and actual features of Islamic banking in order to ascertain to its peculiarities in terms of market stability and other externalities. Next, the paper discusses distinct features of Islamic financial transactions and banking which might require customized regulatory measures. Finally, the paper explores how a more transparent path for the Islamic banking regulations can be drawn.

Keywords: Islamic banking, regulation, risks, capital requirements, customer protection, financial stability

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Authors: N. H. Z. Abidin, N. F. M. Mokhtar, S. S. A. Gani

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The influence of diffusion of the thermal or known as Soret effect in a heated Binary fluid model with Coriolis force is investigated theoretically. The linear stability analysis is used, and the eigenvalue is obtained using the Galerkin method. The impact of the Soret and Coriolis force on the onset of stationary convection in a system is analysed with respect to various Binary fluid parameters and presented graphically. It is found that an increase of the Soret values, destabilize the Binary fluid layer system. However, elevating the values of the Coriolis force helps to lag the onset of convection in a system.

Keywords: Benard convection, binary fluid, Coriolis, Soret

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Authors: Teles de Sales Bezerra, Saulo Aislan da Silva Eleuterio, José Anderson Rodrigues de Souza, Jeronimo Silva Rocha

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Propagation in radio frequency is a constant concern in the application of Wireless Sensor Networks (WSN), the behavior of an environment determines how good the quality of signal reception. The objective of this paper is to analyze the behavior of a WSN in an environment for agriculture where environmental variables are present and correlate the capture of values received signal strength (RSSI) with a propagation model.

Keywords: propagation, WSN, agriculture, quality

Procedia PDF Downloads 739

Authors: Biruhi Tesfaye, Avinash M. Potdar

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The laboratory test process to determine the California bearing ratio (CBR) of black cotton soils is not only overpriced but also time-consuming as well. Hence advanced prediction of CBR plays a significant role as it is applicable In pavement design. The prediction of CBR of treated soil was executed by Artificial Neural Networks (ANNs) which is a Computational tool based on the properties of the biological neural system. To observe CBR values, combined eggshell and waste glass was added to soil as 4, 8, 12, and 16 % of the weights of the soil samples. Accordingly, the laboratory related tests were conducted to get the required best model. The maximum CBR value found at 5.8 at 8 % of eggshell waste glass powder addition. The model was developed using CBR as an output layer variable. CBR was considered as a function of the joint effect of liquid limit, plastic limit, and plastic index, optimum moisture content and maximum dry density. The best model that has been found was ANN with 5, 6 and 1 neurons in the input, hidden and output layer correspondingly. The performance of selected ANN has been 0.99996, 4.44E-05, 0.00353 and 0.0067 which are correlation coefficient (R), mean square error (MSE), mean absolute error (MAE) and root mean square error (RMSE) respectively. The research presented or summarized above throws light on future scope on stabilization with waste glass combined with different percentages of eggshell that leads to the economical design of CBR acceptable to pavement sub-base or base, as desired.

Keywords: CBR, artificial neural network, liquid limit, plastic limit, maximum dry density, OMC

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Authors: D. Rama Krishna, Y. Pandu Rangaiah

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This paper presents the design of multiband reconfigurable antenna using PIN diodes for four iterations and all the four iterations have been validated by measuring return loss and pattern measurements of developed prototype antenna. The simulated and experimental data have demonstrated the concepts of a multiband reconfigurable antenna by switching OFF and ON of PIN diodes for multiple band frequencies. The technique has taken the advantage of a different number of radiating lengths with the use of PIN diode switches, each configuration resonating at multiband frequencies.

Keywords: frequency reconfigurable, meandered line multiband antenna, PIN diode, multiband frequencies

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Authors: Lalanthica Yogendran, Manassa Hany, Saira Pasha, Benjamin Chaucer, Simarpreet Kaur, Christopher Janusz

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Children and adolescent patients visit the Psychiatric Emergency Department (ED) for multiple reasons. Visiting the Psychiatric ED itself can be a traumatic experience that can affect an adolescents mental well-being, regardless of a history of mental illness. Despite this, limited research exists in this domain. Prospective studies have correlated adverse psychosocial determinants among adolescents to risk factors for poor well-being and unfavorable behavior outcomes. Studies have also shown that physiological stress is a contributor in the development of health problems and an increase in substance abuse in adolescents. This study aimed to retrospectively determine which psychosocial factors are associated with an increase in psychiatric ED visits. 600 charts of patients who had a psychiatric ED and inpatient admission visit from January 2014 through December 2014 were reviewed. Sociodemographics, diagnoses, ED visits and inpatient admissions were collected. Descriptive statistics, chi-square tests and independent t-test analyses were utilized to examine differences in the sample to determine which factors affected ED visits and admissions. The sample was 50% female, 35.2% self-identified black, and had a mean age of 13 years. The majority, 85%, went to public school and 17% were in special education. Attention Deficit Hyperactivity Disorder was the most common admitting diagnosis, found in 132(23%) responders. Most patients came from single parent household 305 (53%). The mean ages of patients that were sexually active, with legal issues, and reporting marijuana substance abuse were 15, 14.35, and 15 years respectively. Patients from two biological parent households had significantly fewer ED visits (1.2 vs. 1.7, p < 0.01) and admissions (0.09 vs. 0.26, p < 0.01). Among social factors, those who reported sexual, physical or emotional abuse had a significantly greater number of ED visits (2.1 vs. 1.5, p < 0.01) and admissions (0.61 vs. 0.14, p < 0.01) than those who did not. Patients that were sexually active or had legal issues or substance abuse with marijuana had a significantly greater number of admissions (0.43 vs. 0.17, p < 0.01), (0.54 vs. .18, p < 0.01) and (0.46 vs. 0.18, p < 0.01) respectively. This data supports the theory of the stability of a two parent home. Dual parenting plays a role in creating a safe space where a child can develop; this is shown by subsequent decreases in psychiatric ED visits and admissions. This may highlight the psychological protective role of a two parent household. Abuse can exacerbate existing psychiatric illness or initiate the onset of new disease. Substance abuse and legal issues result in early induction to the criminal system. Results show that this causes an increase in frequency of visits and severity of symptoms. Only marijuana, but not other illicit substances, correlated with higher incidence of psychiatric ED visits. This may speak to the psychotropic nature of tetrahydrocannabinols and their role in mental illness. This study demonstrates the array of psychosocial factors that lead to increased ED visits and admissions in children and adolescents.

Keywords: adolescent, child psychiatry, emergency department, substance abuse

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Authors: Meng-Jou Chien, Jheng-Cheng Chen, Chang-Hsiung Tsai

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Let maxζG(m) denote the maximum number of edges in a subgraph of graph G induced by m nodes. The n-dimensional augmented cube, denoted as AQn, a variation of the hypercube, possesses some properties superior to those of the hypercube. We study the cases when G is the augmented cube AQn.

Keywords: interconnection network, augmented cube, induced subgraph, bisection width

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Authors: Xinyu Wang

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In the context of the rapid development of Internet technology and the increasing prevalence of online social media, this study investigates the impact of digital communication on social learning. Through three behavioral experiments, we explore both affective and cognitive social learning in online environments. Experiment 1 manipulates the content of experimental materials and two forms of feedback, emotional valence, sociability, and repetition, to verify whether individuals can achieve online emotional social learning through reinforcement using two social learning strategies. Results reveal that both social learning strategies can assist individuals in affective, social learning through reinforcement, with feedback-based learning strategies outperforming frequency-dependent strategies. Experiment 2 similarly manipulates the content of experimental materials and two forms of feedback to verify whether individuals can achieve online knowledge social learning through reinforcement using two social learning strategies. Results show that similar to online affective social learning, individuals adopt both social learning strategies to achieve cognitive social learning through reinforcement, with feedback-based learning strategies outperforming frequency-dependent strategies. Experiment 3 simultaneously observes online affective and cognitive social learning by manipulating the content of experimental materials and feedback at different levels of social pressure. Results indicate that online affective social learning exhibits different learning effects under different levels of social pressure, whereas online cognitive social learning remains unaffected by social pressure, demonstrating more stable learning effects. Additionally, to explore the sustained effects of online social learning and differences in duration among different types of online social learning, all three experiments incorporate two test time points. Results reveal significant differences in pre-post-test scores for online social learning in Experiments 2 and 3, whereas differences are less apparent in Experiment 1. To accurately measure the sustained effects of online social learning, the researchers conducted a mini-meta-analysis of all effect sizes of online social learning duration. Results indicate that although the overall effect size is small, the effect of online social learning weakens over time.

Keywords: online social learning, affective social learning, cognitive social learning, social learning strategies, social reinforcement, social pressure, duration

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Authors: M. Riazat, H. Abdolvand, M. Baniassadi

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In this present work, 3D reconstruction of cathode of SOFC is developed with various volume fractions and porosity. Three Phase Boundary (TPB) of construction of such derived micro structures is calculated. The neural network is used to optimize the porosity and volume fraction of each phase to reach a structure with maximum TPB.

Keywords: fuel cell, solid oxide, TPB, 3D reconstruction

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Authors: Anny Zambrano, German Gonzalez, Yair Quintero

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The continuum damage concept is used to study the interaction between hydraulic fractures and natural fractures, the objective is representing the path and relation among this two fractures types and predict its complex behavior without the need to pre-define their direction as occurs in other finite element applications, providing results more consistent with the physical behavior of the phenomenon. The approach uses finite element simulations through Abaqus software to model damage fracturing, the fracturing process by damage propagation in a rock. The modeling the phenomenon develops in two dimensional (2D) so that the fracture will be represented by a line and the crack front by a point. It considers nonlinear constitutive behavior, finite strain, time-dependent deformation, complex boundary conditions, strain hardening and softening, and strain based damage evolution in compression and tension. The complete governing equations are provided and the method is described in detail to permit readers to replicate all results. The model is compared to models that are published and available. Comparisons are focused in five interactions between natural fractures (NF) and hydraulic fractures: Fractured arrested at NF, crossing NF with or without offset, branching at intersecting NFs, branching at end of NF and NF dilation due to shear slippage. The most significant new finding is, that is not necessary to use pre-defined addresses propagation and stress condition can be evaluated as a dominant factor in the process. This is important because it can model in a more real way the generated complex hydraulic fractures, and be a valuable tool to predict potential problems and different geometries of the fracture network in the process of fracturing due to fluid injection.

Keywords: continuum damage, hydraulic fractures, natural fractures, complex fracture network, stiffness

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Authors: Yi Hu, Chun-Chi Lin, Shau-En Yeh, Shin Lee

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In this study, p–n heterojunctions with La0.5Sr0.5CoO3 (LSCO) and W-doped VO2 thin films were fabricated by the radio frequency (r.f.) magnetron sputtering technique and sol-gel process, respectively. The thickness of VO2 and LSCO thin films are about 40 nm and 400 nm, respectively. Good crystalline match between LSCO and VO2 films was observed from the SEM. The built-in voltages for the junction are about 1.1 V and 2.3 V for the sample in the metallic and insulating state, respectively. The sample can undergo the current induced MIT during applying field when the sample was heated at 40 and 50ºC. This is in agreement with the value obtained from the difference in the work functions of LSCO and VO2. The band structure of the heterojunction was proposed based on the results of analysis.

Keywords: hetrojection, Mott transition, switching , VO2

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Authors: Abrar Almutairi, Alyaa Farouk, Amal Gouda

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Background: Social capital is a factor that helps in bonding in a social network. The individual and the neighborhood social capital affect the health status of members of a particular society. In addition, to the influence of social health on the health of the population, social health has a significant effect on women, especially those with pregnancy. Study objective was to assess the impact of the social capital on the health status of pregnant women Design: A descriptive crosssectional correlational design was utilized in this study. Methods: A convenient sample of 210 pregnant women who attended the outpatient antenatal clinicsfor follow-up in King Fahad hospital (Ministry of National Guard Health Affairs/Riyadh) and King Abdullah bin Abdelaziz University Hospital (KAAUH, Ministry of Education /Riyadh) were included in the study. Data was collected using a self-administered questionnaire that was developed by the researchers based on the “World Bank Social Capital Assessment Tool” and SF-36 questionnaire (Short Form Health Survey). The questionnaire consists of 4 parts to collect information regarding socio-demographic data, obstetric and gynecological history, general scale of health status and social activity during pregnancy and the social capital of the study participants, with different types of questions such as multiple-choice questions, polar questions, and Likert scales. Data analysis was carried out by using Statistical Package for the Social Sciences version 23. Descriptive statistic as frequency, percentage, mean, and standard deviation was used to describe the sample characteristics, and the simple linear regression test was used to assess the relationship between the different variables, with level of significance P≤0.005. Result: This study revealed that only 31.1% of the study participants perceived that they have good general health status. About two thirds (62.8%) of the participants have moderate social capital, more than one ten (11.2٪) have high social capital and more than a quarter (26%) of them have low social capital. All dimensions of social capital except for empowerment and political action had positive significant correlations with the health status of pregnant women with P value ranging from 0.001 to 0.010in all dimensions. In general, the social capital showed high statistically significant association with the health status of the pregnant (P=0.002). Conclusion: Less than one third of the study participants had good perceived health status, and the majority of the study participants have moderate social capital, with only about one ten of them perceived that they have high social capital. Finally, neighborhood residency area, family size, sufficiency of income, past medical and surgical history and parity of the study participants were all significantly impacting the assessed health domains of the pregnant women.

Keywords: impact, social capital, health status, pregnant women

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Authors: Sema Kayapinar, Ismail Karaoglan, Turan Paksoy, Hadi Gokcen

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Green Supply Chain Management is gaining growing interest among researchers and supply chain management. The concept of Green Supply Chain Management is to integrate environmental thinking into the Supply Chain Management. It is the systematic concept emphasis on environmental problems such as reduction of greenhouse gas emissions, energy efficiency, recycling end of life products, generation of solid and hazardous waste. This study is to present a green supply chain network model integrated Internet of Things applications. Internet of Things provides to get precise and accurate information of end-of-life product with sensors and systems devices. The forward direction consists of suppliers, plants, distributions centres and sales and collect centres while, the reverse flow includes the sales and collects centres, disassembled centre, recycling and disposal centre. The sales and collection centre sells the new products are transhipped from factory via distribution centre and also receive the end-of life product according their value level. We describe green logistics activities by presenting specific examples including “recycling of the returned products and “reduction of CO2 gas emissions”. The different transportation choices are illustrated between echelons according to their CO2 gas emissions. This problem is formulated as a mixed integer linear programming model to solve the green supply chain problems which are emerged from the environmental awareness and responsibilities. This model is solved by using Gams package program. Numerical examples are suggested to illustrate the efficiency of the proposed model.

Keywords: green supply chain optimization, internet of things, greenhouse gas emission, recycling

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Authors: Taju Abdela Mohammed

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Introduction: There has been a rise in awareness of violence against young women and girls, particularly when it occurs in educational environments. Gender-based violence in schools is a significant barrier. Therefore, it would be a threat to the achievement of the sustainable development goals, strive for gender equality in all our programs, right from the planning stages, to make sure we are as equitable as possible. Research on the causes, attitudes, and perceptions of gender-based violence was scant. Furthermore, there aren't many studies done on female students attending private colleges. Thus, the purpose of this study is to evaluate the frequency of gender-based violence and related variables among female students attending private colleges in Harar City, Ethiopia. Methodology: A facility-based mixed method concurrent triangulation study design was conducted among 500 randomly selected Private college female students in Harar City. Self-administered questionnaire and an in-depth interview were used to collect the data. The collected data were cleaned and analyzed using a statistical package for social science. Descriptive statistics were conducted and the results were reported using frequency, and percentile. Bivariate logistic regression was performed to identify associated factors. Adjusted odds ratios with 95% confidence intervals and p values < 0.05 were used to explain statistically significant associations. Thematic analysis was used to manually translate, transcribe, and analyze qualitative data. Result: The study showed the prevalence of gender-based violence was 338 (67.6%) (CI 0.432–0.721) Private college female students in Harar city Administration. Age less than 20 years and 20–24 years, [AOR = 0.21, 95% CI (0.03–0.81)] and [AOR = 0.12, 95% CI (0.03–0.51)], tight family control, [AOR = 5.12, 95% CI (1.43–6.9)], Witnessed father abuse mother at childhood; [AOR = 4.04, 95% CI (1.36–12.1)], had drunkenness female or boyfriend; [AOR = 2.12, 95% CI (1.60–14.05)] had significant association with gender-based violence. Conclusion: Our study shows the prevalence of gender-based violence among Private college female students is significant. This is due to the fact that gender-based violence, such as school dropout, unintended pregnancy, abortion, STDs, and psychological disorders, is abandoning young girls' lives and lowering their productivity.

Keywords: female students, gender-violence, harar, Ethiopia

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Authors: N. Ben Si Ali, N. Benalia, N. Zerzouri

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Many electronic drivers for the induction motor control are based on sensorless technologies. Speed and torque control is usually attained by application of a speed or position sensor which requires the additional mounting space, reduce the reliability and increase the cost. This paper seeks to analyze dynamical performances and sensitivity to motor parameter changes of reactive power based technique used in sensorless control of induction motors. Validity of theoretical results is verified by simulation.

Keywords: adaptive observers, model reference adaptive system, RP-based estimator, sensorless control, stability analysis

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Authors: Amin Hamrahi

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Near Field Communication (NFC) is one of the latest wireless communication technologies. NFC enables electronic devices to communicate in short range using the radio waves. NFC offers safe yet simple communication between electronic devices. This technology provides the fastest way to communicate two device with in a fraction of second. With NFC technology, communication occurs when an NFC-compatible device is brought within a few centimeters of another NFC device. NFC is an open-platform technology that is being standardized in the NFC Forum. NFC is based on and extends on RFID. It operates on 13.56 MHz frequency.

Keywords: near field communication, NFC technology, wireless communication technologies, NFC-compatible device, NFC, communication

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Authors: Gabriela Rivadeneyra-Romero, Claudia del C. Gutierrez Torres, Sergio A. Martinez-Delgadillo, Victor X. Mendoza-Escamilla, Alejandro Alonzo-Garcia

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Ultrasonic degradation is currently being used in sonochemical reactors to degrade pollutant compounds from aqueous media, as emerging contaminants (e.g. pharmaceuticals, drugs and personal care products.) because they can produce possible ecological impacts on the environment. For this reason, it is important to develop appropriate water and wastewater treatments able to reduce pollution and increase reuse. Pollutants such as textile dyes, aromatic and phenolic compounds, cholorobenzene, bisphenol-A and carboxylic acid and other organic pollutants, can be removed from wastewaters by sonochemical oxidation. The effect on the removal of pollutants depends on the type of the ultrasonic frequency used; however, not much studies have been done related to the behavior of the fluid into the sonoreactors operated at different ultrasonic frequencies. Based on the above, it is necessary to study the hydrodynamic behavior of the liquid generated by the ultrasonic irradiation to design efficient sonoreactors to reduce treatment times and costs. In this work, it was studied the hydrodynamic behavior of the fluid in sonochemical reactors at different frequencies (250 kHz, 500 kHz and 1000 kHz). The performances of the sonoreactors at those frequencies were simulated using computational fluid dynamics (CFD). Due to there is great sound speed gradient between piezoelectric and fluid, k-e models were used. Piezoelectric was defined as a vibration surface, to evaluate the different frequencies effect on the fluid into sonochemical reactor. Structured hexahedral cells were used to mesh the computational liquid domain, and fine triangular cells were used to mesh the piezoelectric transducers. Unsteady state conditions were used in the solver. Estimation of the dissipation rate, flow field velocities, Reynolds stress and turbulent quantities were evaluated by CFD and 2D-PIV measurements. Test results show that there is no necessary correlation between an increase of the ultrasonic frequency and the pollutant degradation, moreover, the reactor geometry and power density are important factors that should be considered in the sonochemical reactor design.

Keywords: CFD, reactor, ultrasound, wastewater

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Authors: Leonard Tiong, Sonit Singh, Kevin Ho Shon, Sarah Lewis

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Investigation into the use of artificial intelligence in radiology continues to develop at a rapid rate. During the coronavirus pandemic, the combination of an exponential increase in chest x-rays and unpredictable staff shortages resulted in a huge strain on the department's workload. There is a World Health Organisation estimate that two-thirds of the global population does not have access to diagnostic radiology. Therefore, there could be demand for a program that could detect acute changes in imaging compatible with infection to assist with screening. We generated a conventional neural network and tested its efficacy in recognizing changes compatible with coronavirus infection. Following ethics approval, a deidentified set of 77 normal and 77 abnormal chest x-rays in patients with confirmed coronavirus infection were used to generate an algorithm that could train, validate and then test itself. DICOM and PNG image formats were selected due to their lossless file format. The model was trained with 100 images (50 positive, 50 negative), validated against 28 samples (14 positive, 14 negative), and tested against 26 samples (13 positive, 13 negative). The initial training of the model involved training a conventional neural network in what constituted a normal study and changes on the x-rays compatible with coronavirus infection. The weightings were then modified, and the model was executed again. The training samples were in batch sizes of 8 and underwent 25 epochs of training. The results trended towards an 85.71% true positive/true negative detection rate and an area under the curve trending towards 0.95, indicating approximately 95% accuracy in detecting changes on chest X-rays compatible with coronavirus infection. Study limitations include access to only a small dataset and no specificity in the diagnosis. Following a discussion with our programmer, there are areas where modifications in the weighting of the algorithm can be made in order to improve the detection rates. Given the high detection rate of the program, and the potential ease of implementation, this would be effective in assisting staff that is not trained in radiology in detecting otherwise subtle changes that might not be appreciated on imaging. Limitations include the lack of a differential diagnosis and application of the appropriate clinical history, although this may be less of a problem in day-to-day clinical practice. It is nonetheless our belief that implementing this program and widening its scope to detecting multiple pathologies such as lung masses will greatly assist both the radiology department and our colleagues in increasing workflow and detection rate.

Keywords: artificial intelligence, COVID, neural network, machine learning

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Authors: Alessandra Panico, Francesco Bagordo, Tiziana Grassi, Adele Idolo, Marcello Guido, Francesca Serio, Mattia De Giorgi, Antonella De Donno

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In the Province of Lecce (Southeastern Italy) an area with unusual high incidence of chronic respiratory diseases, including lung cancer, was recently identified. The causes of this health emergency are still not entirely clear. In order to determine the risk profile of children living in five municipalities included in this area an epidemiological-molecular study was performed in the years 2014-2016: the IMP.AIR. (Impact of air quality on health of residents in the Municipalities of Sternatia, Galatina, Cutrofiano, Sogliano Cavour and Soleto) study. 122 children aged 6-8 years attending primary school in the study area were enrolled to evaluate the frequency of micronuclei (MNs) in their buccal exfoliated cells. The samples were collected in May 2015 by rubbing the oral mucosa with a soft bristle disposable toothbrush. At the same time, a validated questionnaire was administered to parents to obtain information about health, lifestyle and eating habits of the children. In addition, information on airborne pollutants, routinely detected by the Regional Environmental Agency (ARPA Puglia) in the study area, was acquired. A multivariate analysis was performed to detect any significant association between frequency of MNs (dependent variable) and behavioral factors (independent variables). The presence of MNs was highlighted in the buccal exfoliated cells of about 42% of recruited children with a mean frequency of 0.49 MN/1000 cells, greater than in other areas of Salento. The survey on individual characteristics and lifestyles showed that one in three children was overweight and that most of them had unhealthy eating habits with frequent consumption of foods considered ‘risky’. Moreover many parents (40% of fathers and 12% of mothers) were smokers and about 20% of them admitted to smoking in the house where the children lived. Information regarding atmospheric contaminants was poor. Of the few substances routinely detected by the only one monitoring station located in the study area (PM2.5, SO2, NO2, CO, O3) only ozone showed high concentrations exceeding the limits set by the legislation for 67 times in the year 2015. The study showed that the level of early biological effect markers in children was not negligible. This critical condition could be related to some individual factors and lifestyles such as overweight, unhealthy eating habits and exposure to passive smoking. At present, no relationship with airborne pollutants can be established due to the lack of information on many substances. Therefore, it would be advisable to modify incorrect behaviors and to intensify the monitoring of airborne pollutants (e.g. including detection of PM10, heavy metals, aromatic polycyclic hydrocarbons, benzene) given the epidemiology of chronic respiratory diseases registered in this area.

Keywords: chronic respiratory diseases, environmental pollution, lifestyle, micronuclei

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Authors: Jennifer A. Kowalkowski

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Production agriculture (farming) is a physically, emotionally, and cognitively stressful occupation, where workers have little control over the stressors that impact both their work and their lives. In an occupation already rife with hazards, these occupational-related stressors have been shown to increase farm workers’ risks for illness, injury, disability, and death associated with their work. Despite efforts to mitigate the negative health effects from occupational-related stress (ORS) and to promote health and well-being (HWB) among farmers in the US, marked improvements have not been attained. Social support accessed through social networks has been shown to buffer against the negative health effects from stress, yet no studies have directly examined these relationships among farmers. The purpose of this study was to use social network analysis to explore the social networks of farm owner-operators and the social supports available to them for mitigating the negative health effects of ORS. A convenience sample of 71 farm owner-operators from a Midwestern County in the US completed and returned a mailed survey (55.5% response rate) that solicited information about their social networks related to ORS. Farmers reported an average of 2.4 individuals in their personal networks and higher levels of comfort discussing ORS with female network members. Farmers also identified few connections (3.4% density) and indicated low comfort with members of affiliation networks specific to ORS. Findings from this study highlighted that farmers accessed different social networks and resources for their personal HWB than for issues related to occupational(farm-related) health and safety. In addition, farmers’ social networks for personal HWB were smaller, with different relational characteristics than reported in studies of farmers’ social networks related to occupational health and safety. Collectively, these findings suggest that farmers conceptualize personal HWB differently than farm health and safety. Therefore, the same research approaches and targets that guide occupational health and safety research may not be appropriate for personal HWB for farmers. Interventions and programming targeting ORS and HWB have largely been offered through the same platforms or mechanisms as occupational health and safety programs. This may be attributed to the significant overlap between the farm as a family business and place of residence, or that ORS stems from farm-related issues. However, these assumptions translated to health research of farmers and farm families from the occupational health and safety literature have not been directly studied or challenged. Thismay explain why past interventions have not been effective at improving health outcomes for farmers and farm families. A close examination of findings from this study raises important questions for researchers who study agricultural health. Findings from this study have significant implications for future research agendas focused on addressing ORS, HWB, and health disparities for farmersand farm families.

Keywords: agricultural health, occupational-related stress, social networks, well-being

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Authors: Prajna Paramita Mohapatra, Pamu Dobbidi

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Lithium ferrite (LiFe5O8) has potential applications as a component of microwave magnetic devices such as circulators and monolithic integrated circuits. For efficient device applications, spinel ferrites in the form of thin films are highly required. It is necessary to improve their magnetic and dielectric behavior by optimizing the processing parameters during deposition. The lithium ferrite thin films are deposited on Pt/Si substrate using the pulsed laser deposition technique (PLD). As controlling the film thickness is the easiest parameter to tailor the strain, we deposited the thin films having different film thicknesses (160 nm, 200 nm, 240 nm) at oxygen partial pressure of 0.001 mbar. The formation of single phase with spinel structure (space group - P4132) is confirmed by the XRD pattern and the Rietveld analysis. The optical bandgap is decreased with the increase in thickness. FESEM confirmed the formation of uniform grains having well separated grain boundaries. Further, the film growth and the roughness are analyzed by AFM. The root-mean-square (RMS) surface roughness is decreased from 13.52 nm (160 nm) to 9.34 nm (240 nm). The room temperature magnetization is measured with a maximum field of 10 kOe. The saturation magnetization is enhanced monotonically with an increase in thickness. The magnetic resonance linewidth is obtained in the range of 450 – 780 Oe. The dielectric response is measured in the frequency range of 104 – 106 Hz and in the temperature range of 303 – 473 K. With an increase in frequency, the dielectric constant and the loss tangent of all the samples decreased continuously, which is a typical behavior of conventional dielectric material. The real part of the dielectric constant and the dielectric loss is increased with an increase in thickness. The contribution of grain and grain boundaries is also analyzed by employing the equivalent circuit model. The highest dielectric constant is obtained for the film having a thickness of 240 nm at 104 Hz. The obtained results demonstrate that desired response can be obtained by tailoring the film thickness for the microwave magnetic devices.

Keywords: PLD, optical response, thin films, magnetic response, dielectric response

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Authors: N. W. I. A. Jayawardana, W. A. T. A. Jayalath, W. M. T. Madhujith, U. Ralapanawa, R. S. Jayasekera, S. A. S. B. Alagiyawanna, A. M. K. R. Bandara, N. S. Kalupahana

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There is mounting evidence to the effect that dietary and lifestyle changes affect the incidence of non-communicable diseases (NCDs). This study was conducted to investigate the association of diet, physical activity, smoking, alcohol consumption and duration of sleep with overweight, obesity, hypertension and diabetes in a cohort of males from the Central Province of Sri Lanka. A total of 2694 individuals aged between 17 – 68 years (Mean = 31) were included in the study. Body Mass Index cutoff values for Asians were used to categorize the participants as normal, overweight and obese. The dietary data were collected using a food frequency questionnaire [FFQ] and data on the level of physical activity, smoking, alcohol consumption and sleeping hours were obtained using a self-administered validated questionnaire. Systolic and diastolic blood pressure, random blood glucose levels were measured to determine the incidence of hypertension and diabetes. Among the individuals, the prevalence of overweight and obesity were 34% and 16.4% respectively. Approximately 37% of the participants suffered from hypertension. Overweight and obesity were associated with older age men (P<0.0001), frequency of smoking (P=0.0434), alcohol consumption level (P=0.0287) and the quantity of lipid intake (P=0.0081). Consumption of fish (P=0.6983) and salty snacks (P=0.8327), sleeping hours (P=0.6847) and the level of physical activity were not significantly (P=0.3301) associated with the incidence of overweight and obesity. Based on the fitted model, only age was significantly associated with hypertension (P < 0.001). Further, age (P < 0.0001), sleeping hours (P=0.0953) and consumption of fatty foods (P=0.0930) were significantly associated with diabetes. Age was associated with higher odds of pre diabetes (OR:1.089;95% CI:1.053,1.127) and diabetes (OR:1.077;95% CI:1.055,1.1) whereas 7-8 hrs. of sleep per day was associated with lesser odds of diabetes (OR:0.403;95% CI:0.184,0.884). High prevalence of overweight, obesity and hypertension in working-age males is a threatening sign for this area. As this population ages in the future and urbanization continues, the prevalence of above risk factors will likely to escalate.

Keywords: age, males, non-communicable diseases, obesity

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Authors: A. Dinelka Panagoda, Bathiya Bandara, Chamod Wijetunga, Chathura Malinda, Lakmal Rupasinghe, Chethana Liyanapathirana

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This research takes us forward with the concepts of Federated Learning and Software-Defined Networking (SDN) to introduce an efficient malware detection technique and provide a mitigation mechanism to give birth to a resilient and automated healthcare sector network system by also adding the feature of extended privacy preservation. Due to the daily transformation of new malware attacks on hospital Integrated Clinical Environment (ICEs), the healthcare industry is at an undefinable peak of never knowing its continuity direction. The state of blindness by the array of indispensable opportunities that new medical device inventions and their connected coordination offer daily, a factor that should be focused driven is not yet entirely understood by most healthcare operators and patients. This solution has the involvement of four clients in the form of hospital networks to build up the federated learning experimentation architectural structure with different geographical participation to reach the most reasonable accuracy rate with privacy preservation. While the logistic regression with cross-entropy conveys the detection, SDN comes in handy in the second half of the research to stack up the initial development phases of the system with malware mitigation based on policy implementation. The overall evaluation sums up with a system that proves the accuracy with the added privacy. It is no longer needed to continue with traditional centralized systems that offer almost everything but not privacy.

Keywords: software-defined network, federated learning, privacy, integrated clinical environment, decentralized learning, malware detection, malware mitigation

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Authors: Rafat Rob, Khaled Alotaibi, Dana Nour, Abdullah Albadrani, Abdulmohsen Mulhim

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Power systems digitization solutions provides a comprehensive smart, cohesive, interconnected network, extensive connectivity between digital assets, physical power plants, and resources to form digital economies. However, digitization has exposed the classical air gapped power plants to the rapid spread of cyber threats and attacks in the process delaying and forcing many organizations to rethink their cyber security policies and standards before they can augment their operation the new advanced digital devices. Cyber Security requirements for power systems (and industry control systems therein) demand a new approach, unique methodology, and design process that is completely different to Cyber Security measures designed for the IT systems. In practice, Cyber Security strategy, as applied to power systems, tends to be closely aligned to those measures applied for IT system purposes. The differentiator for Cyber Security in terms of power systems are the physical assets and applications used, alongside the ever-growing rate of expansion within the industry controls sector (in comparison to the relatively saturated growth observed for corporate IT systems). These factors increase the magnitude of the cyber security risk within such systems. The introduction of smart devices and sensors along the grid initiate vulnerable entry points to the systems. Every installed Smart Meter is a target; the way these devices communicate with each other may instigate a Denial of Service (DoS) and Distributed Denial of Service (DDoS) attack. Attacking one sensor or meter has the potential to propagate itself throughout the power grid reaching the IT network, where it may manifest itself as a malware infiltration.

Keywords: supply chain, cybersecurity, maturity model, risk, smart grid

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Authors: Nibal Al-Batsh, Issam A. Al-Khatib, Subha Ghannam

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Yatta is a town in the Governorate of Hebron, located 9 km south of Hebron City in the West Bank. The town houses over 100,000 people, 49% of which are females; a population that doubles every 15 years. Yatta has been connected to a water network since 1974 serving nearly 85% of the households. The water network is old and inadequate to meet the needs of the population. The water supply made available to the area is also very limited, estimated to be around 20 l/c/d. Residents are thus forced to rely on water vendors which supply water with a lower quality compared to municipal water while being 400% more expensive. As a cheaper and more reliable alternative, rainwater harvesting is a common practice in the area, with the majority of the households owning at least one cistern. Rainwater harvesting is of great socioeconomic importance in areas where water sources are scarce or polluted. In this research, the quality of harvested rainwater used for drinking and domestic purposes in the Yatta area was assessed throughout a year. A total of 100 samples, were collected from (cisterns) with an average capacity of 69 m3, which are adjacent to cement-roof catchment areas with an average area of 145 m2. Samples were analyzed for a number of parameters including: pH, alkalinity, hardness, turbidity, Total Dissolved Solids (TDS), NO3, NH4, chloride and salinity. Biological and microbiological contents such as Total Coliforms (TCC) and Fecal Coliforms (FC) bacteria were also tested. Results showed that most of the rainwater samples were within WHO and EPA guidelines set for chemical parameters. The research also addressed the impact of different socioeconomic attributes on rainwater harvesting through questionnaire that was pre-tested before the actual statically sample is collected.

Keywords: rainwater, harvesting, water quality, socio-economic aspects

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Authors: M. Hadji, N. Chiker, Y. Hadji, A. Haddad

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In this paper, we report for the first time on the synthesis and characterization of novel MAX phases (Ti3SiC2, Ti2AlC) reinforced Ni-matrix and Ti2AlC reinforced Al-matrix. The stability of MAX phases in Al-matrix and Ni-matrix at a temperature of 985°C has been investigated. All the composites were cold pressed and sintered at a temperature of 985°C for 20min in H2 environment, except (Ni/Ti3SiC2) who was sintered at 1100°C for 1h.Microstructure analysis by scanning electron microscopy and phase analysis by X-Ray diffraction confirmed that there was minimal interfacial reaction between MAX particles and Ni, thus Al/MAX samples shown that MAX phases was totally decomposed at 985°C.The Addition of MAX enhanced the Al-matrix and Ni-matrix.

Keywords: MAX phase, microstructures, composites, hardness, SEM

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Authors: Xiaolei Hu, Enrico Ferrera, Riccardo Tomasi, Claudio Pastrone

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Load Forecasting plays a key role in making today's and future's Smart Energy Grids sustainable and reliable. Accurate power consumption prediction allows utilities to organize in advance their resources or to execute Demand Response strategies more effectively, which enables several features such as higher sustainability, better quality of service, and affordable electricity tariffs. It is easy yet effective to apply Load Forecasting at larger geographic scale, i.e. Smart Micro Grids, wherein the lower available grid flexibility makes accurate prediction more critical in Demand Response applications. This paper analyses the application of short-term load forecasting in a concrete scenario, proposed within the EU-funded GreenCom project, which collect load data from single loads and households belonging to a Smart Micro Grid. Three short-term load forecasting techniques, i.e. linear regression, artificial neural networks, and radial basis function network, are considered, compared, and evaluated through absolute forecast errors and training time. The influence of weather conditions in Load Forecasting is also evaluated. A new definition of Gain is introduced in this paper, which innovatively serves as an indicator of short-term prediction capabilities of time spam consistency. Two models, 24- and 1-hour-ahead forecasting, are built to comprehensively compare these three techniques.

Keywords: short-term load forecasting, smart micro grid, linear regression, artificial neural networks, radial basis function network, gain

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Authors: Fares Senouci, Bachir Imine

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This document provides numerical and experimental optimization of the aerodynamic performance of a drone equipped with three types of horizontal stabilizer. To build this optimal configuration, an experimental and numerical study was conducted on three parameters: the geometry of the stabilizer (horizontal form or reverse V form), the position of the horizontal stabilizer (up or down), and the landing gear position (closed or open). The results show that up-stabilizer position with respect to the horizontal plane of the fuselage provides better aerodynamic performance, and that the landing gear increases the lift in the zone of stability, that is to say where the flow is not separated.

Keywords: aerodynamics, drag, lift, turbulence model, wind tunnel

Procedia PDF Downloads 240