Search results for: elderly care service model

Authors: Taehyun Kim, Hyunjoo Park, Taehyun Kim

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Since the rapid economic development, Korea has recently entered a period of low growth due to population decline and aging. Due to the urbanization around the metropolitan area and the hollowing of local cities, the ecological capacity of a city is decreasing while ecological footprints are increasing, requiring a compact space plan for maintaining urban functions. The purpose of this study is to analyze the relationship between urban spatial structure and residents' ecological footprints for sustainable spatial planning. To do this, we try to analyze the relationship between intra-urban spatial structure, such as net/gross density and service accessibility, and resident ecological footprints of food, housing, transportation, goods and services through survey and structural equation modeling. The results of the study will be useful in establishing an implementation plan for sustainable development goals (SDGs), especially for sustainable cities and communities (SDG 11) and responsible consumption and production (SDG 12) in the future.

Keywords: ecological footprint, structural equation modeling, survey, sustainability, urban spatial structure

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Authors: Daniel Olshansky, Ramiro Rodrıguez Colmeiro

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Relay Mining presents a scalable solution employing probabilistic mechanisms and crypto-economic incentives to estimate RPC volume usage, facilitating decentralized multitenant rate limiting. Network traffic from individual applications can be concurrently serviced by multiple RPC service providers, with costs, rewards, and rate limiting governed by a native cryptocurrency on a distributed ledger. Building upon established research in token bucket algorithms and distributed rate-limiting penalty models, our approach harnesses a feedback loop control mechanism to adjust the difficulty of mining relay rewards, dynamically scaling with network usage growth. By leveraging crypto-economic incentives, we reduce coordination overhead costs and introduce a mechanism for providing RPC services that are both geopolitically and geographically distributed.

Keywords: remote procedure call, crypto-economic, commit-reveal, decentralization, scalability, blockchain, rate limiting, token bucket

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Authors: Anita Setianingrum, Oki S. Jaya, Zuherman Rustam

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Forecasting stock price is a challenging task due to the complex time series of the data. The complexity arises from many variables that affect the stock market. Many time series models have been proposed before, but those previous models still have some problems: 1) put the subjectivity of choosing the technical indicators, and 2) rely upon some assumptions about the variables, so it is limited to be applied to all datasets. Therefore, this paper studied a novel Adaptive Neuro-Fuzzy Inference System (ANFIS) time series model based on Support Vector Regression (SVR) for forecasting the stock market. In order to evaluate the performance of proposed models, stock market transaction data of TAIEX and HIS from January to December 2015 is collected as experimental datasets. As a result, the method has outperformed its counterparts in terms of accuracy.

Keywords: ANFIS, fuzzy time series, stock forecasting, SVR

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Authors: Luisa Windhagen, Atsumi Hirose, Alex Bottle

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Global urbanization has resulted in the expansion of slums, leaving over 10 million Tanzanians in urban poverty and at risk of poor health. Whilst rural residence has historically been associated with an increased risk of adverse pregnancy outcomes, recent studies found higher perinatal mortality rates in urban Tanzania. This study aims to understand to what extent slum neighborhoods may account for the spatial disparities seen in Tanzania. We generated a slum indicator based on UN-HABITAT criteria to identify slum clusters within the 2015-2016 Tanzania Demographic and Health Survey. Descriptive statistics, disaggregated by urban slum, urban non-slum, and rural areas, were produced. Simple and multivariable logistic regression examined the association between cluster residence type and neonatal mortality and stillbirth. For neonatal mortality, we additionally built a multilevel logistic regression model, adjusting for confounding and clustering. The neonatal mortality ratio was highest in slums (38.3 deaths per 1000 live births); the stillbirth rate was three times higher in slums (32.4 deaths per 1000 births) than in urban non-slums. Neonatal death was more likely to occur in slums than in urban non-slums (aOR=2.15, 95% CI=1.02-4.56) and rural areas (aOR=1.78, 95% CI=1.15-2.77). Odds of stillbirth were over five times higher among rural than urban non-slum residents (aOR=5.25, 95% CI=1.31-20.96). The results suggest that slums contribute to the urban disadvantage in Tanzanian neonatal health. Higher neonatal mortality in slums may be attributable to lack of education, lower socioeconomic status, poor healthcare access, and environmental factors, including indoor and outdoor air pollution and unsanitary conditions from inadequate housing. However, further research is required to ascertain specific causalities as well as significant associations between residence type and other pregnancy outcomes. The high neonatal mortality, stillbirth, and slum formation rates in Tanzania signify that considerable change is necessary to achieve international goals for health and human settlements. Disparities in access to adequate housing, safe water and sanitation, high standard antenatal, intrapartum, and neonatal care, and maternal education need to urgently be addressed. This study highlights the spatial neonatal mortality shift from rural settings to urban informal settlements in Tanzania. Importantly, other low- and middle-income countries experiencing overwhelming urbanization and slum expansion may also be at risk of a reversing trend in residential neonatal health differences.

Keywords: urban health, slum residence, neonatal mortality, stillbirth, global urbanisation

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Authors: Kari Huhtala, Iiro Jussila

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The supervisory board is assumed to use power in the governance of a firm, but the actual use of power has been scantly investigated. The research question of the paper is “How does the supervisory board use power in the selection of the board of directors”. The data stem from 11 large Finnish agricultural cooperatives. The research approach was qualitative including semi-structured interviews of the board of directors and supervisory board chairpersons. The results were analyzed and interpreted against theories of social power. As a result, the use of power is approached from two perspectives: (1) formal position-based authority and (2) informal power. Central elements of power were the mandate of the supervisory board, the role of the supervisory board, the supervisory board chair, the nomination committee, collaboration between the supervisory board and the board of directors, the role of regions and the role of the board of directors. The study contributes to the academic discussion on corporate governance in cooperatives and on the supervisory board in the context of the two-tier model. Additional research of the model in other countries and of other types of cooperatives would further academic understanding of supervisory boards.

Keywords: board, co-operative, supervisory board, selection, director

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Authors: Saad M. Alshehri, Tansir Ahamad

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Thiourea-Formaldehyde Pre-Polymer (TUF) was prepared by the reaction thiourea and formaldehyde in basic medium and used as a coating materials for magnetite Fe3O4. The synthesized polymer coated microspheres (TUF@Fe3O4) was characterized using FTIR, TGA SEM and TEM. Its BET surface area was up to 1680 m2 g_1. The adsorption capacity of this ACF product was evaluated in its adsorption of Methylene Blue (MB) in water under different pH values and different temperature. We found that the adsorption process was well described both by the Langmuir and Freundlich isotherm model. The kinetic processes of MB adsorption onto TUF@Fe3O4 were described in order to provide a more clear interpretation of the adsorption rate and uptake mechanism. The overall kinetic data was acceptably explained by a pseudo second-order rate model. Evaluated ∆Go and ∆Ho specify the spontaneous and exothermic nature of the reaction. The adsorption takes place with a decrease in entropy (∆So is negative). The monolayer capacity for MB was up to 450 mg g_1 and was one of the highest among similar polymeric products. It was due to its large BET surface area.

Keywords: TGA, FTIR, magentite, thiourea formaldehyde resin, methylene blue, adsorption

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Authors: Redouane Lombarkia

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To apply a new material model developed and validated for plain weave fabric CFRP composites usually used in stanchions in sub-cargo section in aircrafts. This work deals with the development of a numerical model of the fuselage section of commercial aircraft based on the pure explicit finite element method FEM within Abaqus/Explicit commercial code. The aim of this work is the evaluation of the energy absorption capabilities of a full-scale composite fuselage section, including sub-cargo stanchions, Drop tests were carried out from a free fall height of about 5 m and impact velocity of about 6 m∕s. To asses, the prediction efficiency of the proposed numerical modeling procedure, a comparison with literature existed experimental results was performed. We demonstrate the efficiency of the proposed methodology to well capture crash damage mechanisms compared to experimental results

Keywords: crashworthiness, fuselage section, finite elements method (FEM), stanchions, specific energy absorption SEA

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Authors: Kambiz Rasoulkhani, Jeanne Cole, Sybil Sharvelle, Ali Mostafavi

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Dual water distribution systems have been proposed as solutions to enhance the sustainability and resilience of urban water systems by improving performance and decreasing energy consumption. The objective of this study was to evaluate the long-term resilience and robustness of dual water distribution systems versus singular water distribution systems under various stressors such as demand fluctuation, aging infrastructure, and funding constraints. To this end, the long-term dynamics of these infrastructure systems was captured using a simulation model that integrates institutional agency decision-making processes with physical infrastructure degradation to evaluate the long-term transformation of water infrastructure. A set of model parameters that varies for dual and singular distribution infrastructure based on the system attributes, such as pipes length and material, energy intensity, water demand, water price, average pressure and flow rate, as well as operational expenditures, were considered and input in the simulation model. Accordingly, the model was used to simulate various scenarios of demand changes, funding levels, water price growth, and renewal strategies. The long-term resilience and robustness of each distribution infrastructure were evaluated based on various performance measures including network average condition, break frequency, network leakage, and energy use. An ecologically-based resilience approach was used to examine regime shifts and tipping points in the long-term performance of the systems under different stressors. Also, Classification and Regression Tree analysis was adopted to assess the robustness of each system under various scenarios. Using data from the City of Fort Collins, the long-term resilience and robustness of the dual and singular water distribution systems were evaluated over a 100-year analysis horizon for various scenarios. The results of the analysis enabled: (i) comparison between dual and singular water distribution systems in terms of long-term performance, resilience, and robustness; (ii) identification of renewal strategies and decision factors that enhance the long-term resiliency and robustness of dual and singular water distribution systems under different stressors.

Keywords: complex systems, dual water distribution systems, long-term resilience performance, multi-agent modeling, sustainable and resilient water systems

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Authors: Wenlong Feng, Zhenchun Du, Jianguo Yang

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To decrease the grating scale thermal expansion error, a novel method which based on multiple temperature detections is proposed. Several temperature sensors are installed on the grating scale and the temperatures of these sensors are recorded. The temperatures of every point on the grating scale are calculated by interpolating between adjacent sensors. According to the thermal expansion principle, the grating scale thermal expansion error model can be established by doing the integral for the variations of position and temperature. A novel compensation method is proposed in this paper. By applying the established error model, the grating scale thermal expansion error is decreased by 90% compared with no compensation. The residual positioning error of the grating scale is less than 15um/10m and the accuracy of the machine tool is significant improved.

Keywords: thermal expansion error of grating scale, error compensation, machine tools, integral method

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Authors: M. I. Youssef, A. E. Emam, M. Abd Elghany

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The performance of wireless communication systems is affected mainly by the environment of its associated channel, which is characterized by dynamic and unpredictable behavior. In this paper, different statistical earth-satellite channel models are studied with emphasize on two main models, first is the Rice-Log normal model, due to its representation for the environment including shadowing and multi-path components that affect the propagated signal along its path, and a three-state model that take into account different fading conditions (clear area, moderate shadow and heavy shadowing). The provided models are based on AWGN, Rician, Rayleigh, and log-normal distributions were their Probability Density Functions (PDFs) are presented. The transmission system Bit Error Rate (BER), Peak-Average-Power Ratio (PAPR), and the channel capacity vs. fading models are measured and analyzed. These simulations are implemented using MATLAB tool, and the results had shown the performance of transmission system over different channel models.

Keywords: fading channels, MIMO communication, RNS scheme, statistical modeling

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Authors: Romulo D. C. Santos, Silvio M. A. Gama, Ramiro G. R. Camacho

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In this present paper, the thermos-fluid dynamics considering the mixed convection (natural and forced convections) and the principles of turbulence flow around complex geometries have been studied. In these applications, it was necessary to analyze the influence between the flow field and the heated immersed body with constant temperature on its surface. This paper presents a study about the Newtonian incompressible two-dimensional fluid around isothermal geometry using the immersed boundary method (IBM) with the virtual physical model (VPM). The numerical code proposed for all simulations satisfy the calculation of temperature considering Dirichlet boundary conditions. Important dimensionless numbers such as Strouhal number is calculated using the Fast Fourier Transform (FFT), Nusselt number, drag and lift coefficients, velocity and pressure. Streamlines and isothermal lines are presented for each simulation showing the flow dynamics and patterns. The Navier-Stokes and energy equations for mixed convection were discretized using the finite difference method for space and a second order Adams-Bashforth and Runge-Kuta 4th order methods for time considering the fractional step method to couple the calculation of pressure, velocity, and temperature. This work used for simulation of turbulence, the Smagorinsky, and Spalart-Allmaras models. The first model is based on the local equilibrium hypothesis for small scales and hypothesis of Boussinesq, such that the energy is injected into spectrum of the turbulence, being equal to the energy dissipated by the convective effects. The Spalart-Allmaras model, use only one transport equation for turbulent viscosity. The results were compared with numerical data, validating the effect of heat-transfer together with turbulence models. The IBM/VPM is a powerful tool to simulate flow around complex geometries. The results showed a good numerical convergence in relation the references adopted.

Keywords: immersed boundary method, mixed convection, turbulence methods, virtual physical model

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Authors: Bharatendra Rai

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Predictive data analysis and modeling involving machine learning techniques become challenging in presence of too many explanatory variables or features. Presence of too many features in machine learning is known to not only cause algorithms to slow down, but they can also lead to decrease in model prediction accuracy. This study involves housing dataset with 79 quantitative and qualitative features that describe various aspects people consider while buying a new house. Boruta algorithm that supports feature selection using a wrapper approach build around random forest is used in this study. This feature selection process leads to 49 confirmed features which are then used for developing predictive random forest models. The study also explores five different data partitioning ratios and their impact on model accuracy are captured using coefficient of determination (r-square) and root mean square error (rsme).

Keywords: housing data, feature selection, random forest, Boruta algorithm, root mean square error

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Authors: Bandreddy Anand Babu, Srinivasa Rao Mandadi, C. Pradeep Reddy, N. Ramesh Babu

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In this paper quickly illustrate the correlation investigation of Auto-Regressive Integrated Moving and Average (ARIMA) and daptive Network Based Fuzzy Inference System (ANFIS) models done by climate estimating. The climate determining is taken from University of Waterloo. The information is taken as Relative Humidity, Ambient Air Temperature, Barometric Pressure and Wind Direction utilized within this paper. The paper is carried out by analyzing the exhibitions are seen by demonstrating of ARIMA and ANIFIS model like with Sum of average of errors. Versatile Network Based Fuzzy Inference System (ANFIS) demonstrating is carried out by Mat lab programming and Auto-Regressive Integrated Moving and Average (ARIMA) displaying is produced by utilizing XLSTAT programming. ANFIS is carried out in Fuzzy Logic Toolbox in Mat Lab programming.

Keywords: ARIMA, ANFIS, fuzzy surmising tool stash, weather forecasting, MATLAB

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Authors: Eva L. Suarez, Daniel E. Meeroff, Yan Yong

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Current flooding risk modeling focuses on resilience, defined as the probability of recovery from a severe flooding event. However, the long-term damage to property and well-being by nuisance flooding and its long-term effects on communities are not typically included in risk assessments. An approach was developed to address the probability of recovering from a severe flooding event combined with the probability of community performance during a nuisance event. A consolidated model, namely the conflation flooding recovery (&FR) model, evaluates risk-coping mitigation strategies for communities based on the recovery time from catastrophic events, such as hurricanes or extreme surges, and from everyday nuisance flooding events. The &FR model assesses the variation contribution of each independent input and generates a weighted output that favors the distribution with minimum variation. This approach is especially useful if the input distributions have dissimilar variances. The &FR is defined as a single distribution resulting from the product of the individual probability density functions. The resulting conflated distribution resides between the parent distributions, and it infers the recovery time required by a community to return to basic functions, such as power, utilities, transportation, and civil order, after a flooding event. The &FR model is more accurate than averaging individual observations before calculating the mean and variance or averaging the probabilities evaluated at the input values, which assigns the same weighted variation to each input distribution. The main disadvantage of these traditional methods is that the resulting measure of central tendency is exactly equal to the average of the input distribution’s means without the additional information provided by each individual distribution variance. When dealing with exponential distributions, such as resilience from severe flooding events and from nuisance flooding events, conflation results are equivalent to the weighted least squares method or best linear unbiased estimation. The combination of severe flooding risk with nuisance flooding improves flood risk management for highly populated coastal communities, such as in South Florida, USA, and provides a method to estimate community flood recovery time more accurately from two different sources, severe flooding events and nuisance flooding events.

Keywords: community resilience, conflation, flood risk, nuisance flooding

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Authors: Alsaidi M. Altaher, Mohd Tahir Ismail

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Wavelet thresholding has been a power tool in curve estimation and data analysis. In the presence of outliers this non parametric estimator can not suppress the outliers involved. This study proposes a new two-stage combined method based on the use of the median filter as primary step before applying wavelet thresholding. After suppressing the outliers in a signal through the median filter, the classical wavelet thresholding is then applied for removing the remaining noise. We use automatic boundary corrections; using a low order polynomial model or local polynomial model as a more realistic rule to correct the bias at the boundary region; instead of using the classical assumptions such periodic or symmetric. A simulation experiment has been conducted to evaluate the numerical performance of the proposed method. Results show strong evidences that the proposed method is extremely effective in terms of correcting the boundary bias and eliminating outlier’s sensitivity.

Keywords: boundary correction, median filter, simulation, wavelet thresholding

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Authors: Katharina Eberhardt, Florian Klaus Kaiser, Frank Schultmann

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Last-mile distribution is one of the most critical parts of a disaster relief operation. Various uncertainties, such as infrastructure conditions, resource availability, and fluctuating beneficiary demand, render last-mile distribution challenging in disaster relief operations. The need to balance critical performance criteria like response time, meeting demand and cost-effectiveness further complicates the task. The occurrence of disasters cannot be controlled, and the magnitude is often challenging to assess. In summary, these uncertainties create a need for additional flexibility, agility, and preparedness in logistics operations. As a result, strategic planning and efficient network design are critical for an effective and efficient response. Furthermore, the increasing frequency of disasters and the rising cost of logistical operations amplify the need to provide robust and resilient solutions in this area. Therefore, we formulate a scenario-based bi-objective optimization model that integrates pre-positioning, allocation, and distribution of relief supplies extending the general form of a covering location problem. The proposed model aims to minimize underlying logistics costs while maximizing demand coverage. Using a set of disruption scenarios, the model allows decision-makers to identify optimal network solutions to address the risk of disruptions. We provide an empirical case study of the public authorities’ emergency food storage strategy in Germany to illustrate the potential applicability of the model and provide implications for decision-makers in a real-world setting. Also, we conduct a sensitivity analysis focusing on the impact of varying stockpile capacities, single-site outages, and limited transportation capacities on the objective value. The results show that the stockpiling strategy needs to be consistent with the optimal number of depots and inventory based on minimizing costs and maximizing demand satisfaction. The strategy has the potential for optimization, as network coverage is insufficient and relies on very high transportation and personnel capacity levels. As such, the model provides decision support for public authorities to determine an efficient stockpiling strategy and distribution network and provides recommendations for increased resilience. However, certain factors have yet to be considered in this study and should be addressed in future works, such as additional network constraints and heuristic algorithms.

Keywords: humanitarian logistics, bi-objective optimization, pre-positioning, last mile distribution, decision support, disaster relief networks

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Authors: Lule Basha, Eralda Gjika

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This study is focused on analyzing climate change in Albania and its potential effects on cereal yields. Initially, monthly temperature and rainfalls in Albania were studied for the period 1960-2021. Climacteric variables are important variables when trying to model cereal yield behavior, especially when significant changes in weather conditions are observed. For this purpose, in the second part of the study, linear and nonlinear models explaining cereal yield are constructed for the same period, 1960-2021. The multiple linear regression analysis and lasso regression method are applied to the data between cereal yield and each independent variable: average temperature, average rainfall, fertilizer consumption, arable land, land under cereal production, and nitrous oxide emissions. In our regression model, heteroscedasticity is not observed, data follow a normal distribution, and there is a low correlation between factors, so we do not have the problem of multicollinearity. Machine-learning methods, such as random forest, are used to predict cereal yield responses to climacteric and other variables. Random Forest showed high accuracy compared to the other statistical models in the prediction of cereal yield. We found that changes in average temperature negatively affect cereal yield. The coefficients of fertilizer consumption, arable land, and land under cereal production are positively affecting production. Our results show that the Random Forest method is an effective and versatile machine-learning method for cereal yield prediction compared to the other two methods.

Keywords: cereal yield, climate change, machine learning, multiple regression model, random forest

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Authors: I. N. Nwafia, U. C. Ozumba, M. E. Ohanu, S. O. Ebede

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Antibiotic resistance is increasing globally and has become a major health challenge. Extended-spectrum beta-lactamase is clinically important because the ESBL gene are mostly plasmid encoded and these plasmids frequently carry genes encoding resistance to other classes of antimicrobials thereby limiting antibiotic options in the treatment of infections caused by these organisms. The specific objectives of this study were to determine the prevalence of ESBLs production in Escherichia coli, to determine the antibiotic susceptibility pattern of ESBLs producing Escherichia coli, to detect TEM, SHV and CTX-M genes and the risk factors to acquisition of ESBL producing Escherichia coli. The protocol of the study was approved by Health Research and Ethics committee of the University of Nigeria Teaching Hospital (UNTH), Enugu. It was a descriptive cross-sectional study that involved all hospitalized patients in UNTH from whose specimens Escherichia coli was isolated during the period of the study. The samples analysed were urine, wound swabs, blood and cerebrospinal fluid. These samples were cultured in 5% sheep Blood agar and MacConkey agar (Oxoid Laboratories, Cambridge UK) and incubated at 35-370C for 24 hours. Escherichia coli was identified with standard biochemical tests and confirmed using API 20E auxanogram (bioMerieux, Marcy 1'Etoile, France). The antibiotic susceptibility testing was done by disc diffusion method and interpreted according to the Clinical and Laboratory Standard Institute guideline. ESBL production was confirmed using ESBL Epsilometer test strips (Liofilchem srl, Italy). The ESBL bla genes were detected with polymerase chain reaction, after extraction of DNA with plasmid mini-prep kit (Jena Bioscience, Jena, Germany). Data analysis was with appropriate descriptive and inferential statistics. One hundred and six isolates (53.00%) out of the 200 were from urine, followed by isolates from different swabs specimens 53(26.50%) and the least number of the isolates 4(2.00) were from blood (P value = 0.096). Seventy (35.00%) out of the 200 isolates, were confirmed positive for ESBL production. Forty-two (60.00%) of the isolates were from female patients while 28(40.00%) were from male patients (P value = 0.13). Sixty-eight (97.14%) of the isolates were susceptible to imipenem while all of the isolates were resistant to ampicillin, chloramphenicol and tetracycline. From the 70 positive isolates the ESBL genes detected with polymerase chain reaction were blaCTX-M (n=26; 37.14%), blaTEM (n=7; 10.00%), blaSHV (n=2; 2.86%), blaCTX-M/TEM (n=7; 10.0%), blaCTX-M/SHV (n=14; 20.0%) and blaCTX-M/TEM/SHV (n=10; 14.29%). There was no gene detected in 4(5.71%) of the isolates. The most associated risk factors to infections caused by ESBL producing Escherichia coli was previous antibiotics use for the past 3 months followed by admission in the intensive care unit, recent surgery, and urinary catheterization. In conclusion, ESBLs was detected in 4 of every 10 Escherichia coli with the predominant gene detected being CTX-M. This knowledge will enable appropriate measures towards improvement of patient health care, antibiotic stewardship, research and infection control in the hospital.

Keywords: antimicrobial, Escherichia coli, extended spectrum beta lactamase, resistance

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Authors: Michel Wakim, Rodrigo Rivera Tinoco

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Supersonic ejector is an economical device that use high pressure vapor to compress a low pressure vapor without any rotating parts or external power sources. Entrainment ratio is a major characteristic of the ejector performance, so the ejector performance is highly dependent on its geometry. The aim of this paper is to design ejector geometry, based on pre-specified operating conditions, and to study the flow behavior inside the ejector by using computational fluid dynamics ‘CFD’ by using ‘ANSYS FLUENT 15.0’ software. In the first section; 1-D mathematical model is carried out to predict the ejector geometry. The second part describes the flow behavior inside the designed model. CFD is the most reliable tool to reveal the mixing process at different parts of the supersonic turbulent flow and to study the effect of the geometry on the effective ejector area. Finally, the results show the effect of the geometry on the entrainment ratio.

Keywords: computational fluids dynamics, ejector, entrainment ratio, geometry optimization, performance

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Authors: Luqman Shah

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The myopic gender discrimination is now a well-documented and recognized fact. However, gender is only one facet of an individual’s multiple identities. The aim of this work is to investigate gender discrimination highlighted in print media in the subcontinent with a specific focus on Pakistan and India. In this study, an approach is adopted by using the James Paul Gee model for the identification of gender discrimination. As a matter of fact, gender discrimination is not consistent in its nature and intensity across global societies and varies as social, geographical, and cultural background change. The World has been changed enormously in every aspect of life, and there are also obvious changes towards gender discrimination, prejudices, and biases, but still, the world has a long way to go to recognize women as equal as men in every sphere of life. The history of the world is full of gender-based incidents and violence. Now the time came that this issue must be seriously addressed and to eradicate this evil, which will lead to harmonize society and consequently heading towards peace and prosperity. The study was carried out by a mixed model research method. The data was extracted from the contents of five Pakistani English newspapers out of a total of 23 daily English newspapers, and likewise, five Indian daily English newspapers out of 52 those were published 2018-2019. Two news stories from each of these newspapers, in total, twenty news stories were taken as sampling for this research. Content and semiotic analysis techniques were used to analyze through James Paul Gee's seven building tasks of language. The resources of renowned e-papers are utilized, and the highlighted cases in Pakistani newspapers of Indian gender-based stories and vice versa are scrutinized as per the requirement of this research paper. For analysis of the written stretches of discourse taken from e-papers and processing of data for the focused problem, James Paul Gee 'Seven Building Tasks of Language' is used. Tabulation of findings is carried to pinpoint the issue with certainty. Findings after processing the data showed that there is a gross human rights violation on the basis of gender discrimination. The print media needs a more realistic representation of what is what not what seems to be. The study recommends the equality and parity of genders.

Keywords: gender discrimination, print media, Paul Gee model, subcontinent

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Authors: Kate Allman, Heather Maranges, Elise Dykhuis

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Moral Growth Mindset (MGM) is the belief that one has the capacity to become a more moral person, as opposed to a fixed conception of one’s moral ability and capacity (Han et al., 2018). Building from Dweck’s work in incremental implicit theories of intelligence (2008), Moral Growth Mindset (Han et al., 2020) extends growth mindsets into the moral dimension. The concept of MGM has the potential to help researchers understand how both mindsets and interventions can impact character development, and it has even been shown to have connections to voluntary service engagement (Han et al., 2018). Understanding the contexts in which MGM might be cultivated could help to promote the further cultivation of character, in addition to prosocial behaviors like service engagement, which may, in turn, promote larger scale engagement in social justice-oriented thoughts, feelings, and behaviors. In particular, college may be a place to intentionally cultivate a growth mindset toward moral capacities, given the unique developmental and maturational components of the college experience, including contextual opportunity (Lapsley & Narvaez, 2006) and independence requiring the constant consideration, revision, and internalization of personal values (Lapsley & Woodbury, 2016). In a semester-long, quasi-experimental study, we examined the impact of a pedagogical approach designed to cultivate college student character development on participants’ MGM. With an intervention (n=69) and a control group (n=97; Pre-course: 27% Men; 66% Women; 68% White; 18% Asian; 2% Black; <1% Hispanic/Latino), we investigated whether college courses that intentionally incorporate character education pedagogy (Lamb, Brant, Brooks, 2021) affect a variety of psychosocial variables associated with moral thoughts, feelings, identity, and behavior (e.g. moral growth mindset, honesty, compassion, etc.). The intervention group consisted of 69 undergraduate students (Pre-course: 40% Men; 52% Women; 68% White; 10.5% Black; 7.4% Asian; 4.2% Hispanic/Latino) that voluntarily enrolled in five undergraduate courses that encouraged students to engage with key concepts and methods of character development through the application of research-based strategies and personal reflection on goals and experiences. Moral Growth Mindset was measured using the four-item Moral Growth Mindset scale (Han et al., 2020), with items such as You can improve your basic morals and character considerably on a six-point Likert scale from 1 (strongly disagree) to 6 (strongly agree). Higher scores of MGM indicate a stronger belief that one can become a more moral person with personal effort. Reliability at Time 1 was Cronbach’s ɑ= .833, and at Time 2 Cronbach’s ɑ= .772. An Analysis of Covariance (ANCOVA) was conducted to explore whether post-course MGM scores were different between the intervention and control when controlling for pre-course MGM scores. The ANCOVA indicated significant differences in MGM between groups post-course, F(1,163) = 8.073, p = .005, R² = .11, where descriptive statistics indicate that intervention scores were higher than the control group at post-course. Results indicate that intentional character development pedagogy can be leveraged to support the development of Moral Growth Mindset and related capacities in undergraduate settings.

Keywords: moral personality, character education, incremental theories of personality, growth mindset

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Authors: Asmaa M. Marzouk, Abdallah M. Elshaer

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Despite the well-recognized value of shopping as a revenue-generating resource, little effort was made to investigate what is the structure of tourists’ shopping behavior, which in turn, affect their travel experience. The purpose of this paper is to study the structure of tourists’ shopping process to better understand their shopping behavior by investigating factors that influence this activity other than hotels tyranny. This study specifically aims to propose a model incorporating those all variables. This empirical study investigates the shopping experience of international tourists using a questionnaire aimed to examine multinational samples selected from the tourist population visiting a specific destination in Egypt. This study highlights the various stakeholders that make tourists do shop independent of hotels. The results, therefore, demonstrate the relationship between the shopping process entities involved and configure the variables within the model in a way that provides a viable solution for visitors to avoid the tyranny of hotel facilities and amenities on the public markets.

Keywords: hotels’ amenities, shopping process, tourist behavior, tourist satisfaction

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Authors: Ye Sun, Han-Youl Lee, Kathy Musa-Veloso, Nabil Bosco

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Japan has been experiencing global ageing of population with the World’s leading life expectancy (80.8 y for men and 86.9 y for women) and among the lowest birth rate. Preventive nutrition-based approaches have been identified by the health authorities as one of the strategies to increase the healthy life expectancy and reduce the healthcare costs. However, the nutritional needs and status of the senior population have not been well characterized to provide targeted solutions. This study aims to describe the age- and gender-specific prevalence of inadequacy of macro- and micronutrients intake based on the latest Japan National Health and Nutrition Survey (JNHNS) 2014. JNHNS collected data on the consumption of foods and beverages using 1-day semi-weight household dietary record. Nutrient intake levels were then calculated using the Japanese standard tables of food composition. Where applicable, Japanese population-specific estimated average requirements (EAR) were used as a benchmark to determine the prevalence of potential nutrient intake inadequacy, and adequate intake (AI) were used for nutrients with no available EARs. In all, 3403 senior adults aged 60 y and above and 3324 young adults aged 19 to 59 y were included in the 2014 JNHNS. Age- and gender-specific differences were observed in the mean nutrient intakes as well as the prevalence of inadequacy. Among the 22 nutrients examined, the prevalence of inadequacy for iron, vitamin C, magnesium, potassium, and folic acid in the senior adults was significantly lower than young adults, suggesting potentially healthier dietary choices by the seniors. However, there was still a considerable proportion of seniors who did not meet the requirement for key nutrients like vitamin B1 (67%), calcium (57%), vitamin A (48%), magnesium (47%), vitamin E (44%), and vitamin B6 (41%). Inadequate nutrient intake is generally more prevalent among elderly males than females for many nutrients, with the exception of iron (prevalence of inadequacy: 21% versus 42%) which could partly be explained by the higher intake recommendations for the females. In conclusion, high prevalence of nutrient inadequacy exists in older adults, with a potentially worsened picture for men. Such inadequacies could have multiple health implications including physical frailty and mental health. Further study is warranted to investigate the food consumption patterns that could explain the observed nutrient inadequacies, and to eventually develop nutrition-based solutions tailored to the needs of specific subgroups of the population.

Keywords: ageing, national health and nutrition survey, nutrients, nutrition

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Authors: James Purnama, Riri Fitri Sari

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We investigate the machine learning algorithm selection problem in the term of a depth image based eye gaze estimation, with respect to its essential difficulty in reducing the number of required training samples and duration time of training. Statistics based prediction accuracy are increasingly used to assess and evaluate prediction or estimation in gaze estimation. This article evaluates Root Mean Squared Error (RMSE) and R-Squared statistical analysis to assess machine learning methods on depth camera data for gaze estimation. There are 4 machines learning methods have been evaluated: Random Forest Regression, Regression Tree, Support Vector Machine (SVM), and Linear Regression. The experiment results show that the Random Forest Regression has the lowest RMSE and the highest R-Squared, which means that it is the best among other methods.

Keywords: gaze estimation, gaze tracking, eye tracking, kinect, regression model, orange python

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Authors: Ju-young Hwang, Hyo-Gyoung Kwak, Hong Jae Yim

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This paper introduces a numerical analysis method for reinforced-concrete (RC) structures exposed to fire and compares the result with experimental results. The proposed analysis method for RC structure under the high temperature consists of two procedures. First step is to decide the temperature distribution across the section through the heat transfer analysis by using the time-temperature curve. After determination of the temperature distribution, the nonlinear analysis is followed. By considering material and geometrical non-linearity with the temperature distribution, nonlinear analysis predicts the behavior of RC structure under the fire by the exposed time. The proposed method is validated by the comparison with the experimental results. Finally, Prediction model to describe the status of after-cooling concrete can also be introduced based on the results of additional experiment. The product of this study is expected to be embedded for smart structure monitoring system against fire in u-City.

Keywords: RC structures, heat transfer analysis, nonlinear analysis, after-cooling concrete model

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Authors: Manuel Urueña Palomo

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In this paper, we introduce the study of a new solution to gravitational singularities by violating the energy conditions of the Penrose Hawking singularity theorems. We consider that a shift to negative energies, and thus, to negative masses, takes place at the event horizon of a black hole, justified by the original, singular and exact Schwarzschild solution. These negative energies are supported by relativistic particle physics considering the negative energy solutions of the Dirac equation, which states that a time transformation shifts to a negative energy particle. In either general relativity or full Newtonian mechanics, these negative masses are predicted to be repulsive. It is demonstrated that the model fits actual observations, and could possibly clarify the size of observed and unexplained supermassive black holes, when considering the inflation that would take place inside the event horizon where massive particles interact antigravitationally. An approximated solution of the model proposed could be simulated in order to compare it with these observations.

Keywords: black holes, CPT symmetry, negative mass, time transformation

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Authors: Aref Yazdani, Ali Tofighi

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We study a simulative model for production of stable micro black holes based on investigation on thermodynamics of LHC experiment. We show that how this production can be achieved through a thermodynamic process of stability. Indeed, this process can be done through a very small amount of powerful fuel. By applying the second law of black hole thermodynamics at the scale of quantum gravity and perturbation expansion of the given entropy function, a time-dependent potential function is obtained which is illustrated with exact numerical values in higher dimensions. Seeking for the conditions for stability of micro black holes is another purpose of this study. This is proven through an injection method of putting the exact amount of energy into the final phase of the production which is equivalent to the same energy injection into the center of collision at the LHC in order to stabilize the produced particles. Injection of energy into the center of collision at the LHC is a new pattern that it is worth a try for the first time.

Keywords: micro black holes, LHC experiment, black holes thermodynamics, extra dimensions model

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Authors: Mahmoud M. AbuAlSamen, Tamam El-Elimat

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Amid the economic crisis in Jordan, the Jordanian government has opted for a knowledge economy where education is promoted as a mean for economic development. University education usually comes at the expense of study-related stress that may adversely impact the health of students. Since stress is a latent variable that is difficult to measure, a valid tool should be used in doing so. The effort-reward imbalance (ERI) is a model used as a measurement tool for occupational stress. The model was built on the notion of reciprocity, which relates ‘effort’ to ‘reward’ through the mediating ‘over-commitment’. Reciprocity assumes equilibrium between both effort and reward, where ‘high’ effort is adequately compensated with ‘high’ reward. When this equilibrium is violated (i.e., high effort with low reward), this may elicit negative emotions and stress, which have been correlated to adverse health conditions. The theory of ERI was established in many different parts of the world, and associations with chronic diseases and the health of workers were explored at length. While much of the effort-reward imbalance was investigated in work conditions, there has been a growing interest in understanding the validity of the ERI model when applied to other social settings such as schools and universities. The ERI questionnaire was developed in Arabic recently to measure ERI among high school teachers. However, little information is available on the validity of the ERI questionnaire in university students. A cross-sectional study was conducted on 833 students in Jordan to measure the validity and reliability of the ERI questionnaire in Arabic among university students. Reliability, as measured by Cronbach’s alpha of the effort, reward, and overcommitment scales, was 0.73, 0.76, and 0.69, respectively, suggesting satisfactory reliability. The factorial structure was explored using principal axis factoring. The results fitted a five-solution model where both the effort and overcommitment were uni-dimensional while the reward scale was three-dimensional with its factors, namely being ‘support’, ‘esteem’, and ‘security’. The solution explained 56% of the variance in the data. The established ERI theory was replicated with excellent validity in this study. The effort-reward ratio in university students was 1.19, which suggests a slight degree of failed reciprocity. The study also investigated the association of effort, reward, overcommitment, and ERI with participants’ demographic factors and self-reported health. ERI was found to be significantly associated with absenteeism (p < 0.0001), past history of failed courses (p=0.03), and poor academic performance (p < 0.001). Moreover, ERI was found to be associated with poor self-reported health among university students (p=0.01). In conclusion, the Arabic ERI questionnaire is reliable and valid for use in measuring effort-reward imbalance in university students in Jordan. The results of this research are important in informing higher education policy in Jordan.

Keywords: effort-reward imbalance, factor analysis, validity, self-reported health

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Authors: Josephine Shamash, Stuart Smith

Abstract:

We examine reasons for introducing definitions in teaching mathematics in a number of different cases. We try to determine if, where, and when to provide a definition, and which definition to choose. We characterize different types of definitions and the different purposes we may have for formulating them, and detail examples of each type. Giving a definition at a certain stage can sometimes be detrimental to the development of the concept image. In such a case, it is advisable to delay the precise definition to a later stage. We describe two models, the 'successive approximation model', and the 'model of the extending definition' that fit such situations. Detailed examples that fit the different models are given based on material taken from a number of textbooks, and analysis of the way the concept is introduced, and where and how its definition is given. Our conclusions, based on this analysis, is that some of the definitions given may cause discontinuities in the learning sequence and constitute obstacles and unnecessary cognitive conflicts in the formation of the concept definition. However, in other cases, the discontinuity in passing from definition to definition actually serves a didactic purpose, is unavoidable for the mathematical evolution of the concept image, and is essential for students to deepen their understanding.

Keywords: concept image, mathematical definitions, mathematics education, mathematics teaching

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Authors: Vadivel Ayyasamy

Abstract:

The present approach deals with the identification of Emotions and classification of Emotional patterns at Phrase-level with respect to Positive and Negative Orientation. The proposed approach considers emotion triggered terms, its co-occurrence terms and also associated sentences for recognizing emotions. The proposed approach uses Part of Speech Tagging and Emotion Actifiers for classification. Here sentence patterns are broken into phrases and Neuro-Fuzzy model is used to classify which results in 16 patterns of emotional phrases. Suitable intensities are assigned for capturing the degree of emotion contents that exist in semantics of patterns. These emotional phrases are assigned weights which supports in deciding the Positive and Negative Orientation of emotions. The approach uses web documents for experimental purpose and the proposed classification approach performs well and achieves good F-Scores.

Keywords: emotions, sentences, phrases, classification, patterns, fuzzy, positive orientation, negative orientation

Procedia PDF Downloads 363