Search results for: pandemic. Economics variables shocks

Authors: U. Sabura Banu, S. K. Lakshmanaprabu

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The improvement of meta-heuristic algorithm encourages control engineer to design an optimal controller for industrial process. Most real-world industrial processes are non-linear multivariable process with high interaction. Even in sub-process unit, thousands of loops are available mostly interacting in nature. Optimal controller design for such process are still challenging task. Closed loop controller design by multiloop PID involves a tedious procedure by performing interaction study and then PID auto-tuning the loop with higher interaction. Finally, detuning the controller to accommodate the effects of the other process variables. Fractional order PID controllers are replacing integer order PID controllers recently. Design of Multiloop Fractional Order (MFO) PID controller is still more complicated. Cuckoo algorithm, a swarm intelligence technique is used to optimally tune the MFO PID controller with easiness minimizing Integral Time Absolute Error. The closed loop performance is tested under servo, regulatory and servo-regulatory conditions.

Keywords: Cuckoo algorithm, mutliloop fractional order PID controller, two Interacting conical tank process

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Authors: Abdullah Eqal Al Mazrooei

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In this paper, a nonlinear dynamical system is presented. This system is a bilinear class. The bilinear systems are very important kind of nonlinear systems because they have many applications in real life. They are used in biology, chemistry, manufacturing, engineering, and economics where linear models are ineffective or inadequate. They have also been recently used to analyze and forecast weather conditions. Bilinear systems have three advantages: First, they define many problems which have a great applied importance. Second, they give us approximations to nonlinear systems. Thirdly, they have a rich geometric and algebraic structures, which promises to be a fruitful field of research for scientists and applications. The type of nonlinearity that is treated and analyzed consists of bilinear interaction between the states vectors and the system input. By using some properties of the tensor product, these systems can be transformed to linear systems. But, here we discuss the nonlinearity when the state vector is multiplied by itself. So, this model will be able to handle evolutions according to the Lotka-Volterra models or the Lorenz weather models, thus enabling a wider and more flexible application of such models. Here we apply by using an estimator to estimate temperatures. The results prove the efficiency of the proposed system.

Keywords: Lorenz models, nonlinear systems, nonlinear estimator, state-space model

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Authors: Shruti Chopra, Vikas Rao Vadi

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In the era of the digital world, the Internet of Things (IoT) has been receiving significant attention. Its ubiquitous connectivity between humans, machines to machines (M2M) and machines to humans provides it a potential to transform the society and establish an ecosystem to serve new dimensions to the economy of the country. Thereby, this study has attempted to identify the challenges that seem prevalent in IoT adoption in India through the literature survey. Further, the data has been collected by taking the opinions of experts to conduct the foresight analysis and it has been analyzed with the help of scenario planning process – Micmac, Mactor, Multipol, and Smic-Prob. As a methodology, the study has identified the relationship between variables through variable analysis using Micmac and actor analysis using Mactor, this paper has attempted to generate the entire field of possibilities in terms of hypotheses and construct various scenarios through Multipol. And lastly, the findings of the study include final scenarios that are selected using Smic-Prob by assigning the probability to all the scenarios (including the conditional probability). This study may help the practitioners and policymakers to remove the obstacles to successfully implement the IoT in India.

Keywords: Internet of Thing (IoT), foresight analysis, scenario planning, challenges, policymaking

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Authors: Andreas Aceranti, Simonetta Vernocchi, Marco Colorato, Daniel Zaccariello

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Our study explores the usefulness of implementing facial expression recognition capabilities and using the Facial Action Coding System (FACS) in contexts where the other person is wearing a mask. In the communication process, the subjects use a plurality of distinct and autonomous reporting systems. Among them, the system of mimicking facial movements is worthy of attention. Basic emotion theorists have identified the existence of specific and universal patterns of facial expressions related to seven basic emotions -anger, disgust, contempt, fear, sadness, surprise, and happiness- that would distinguish one emotion from another. However, due to the COVID-19 pandemic, we have come up against the problem of having the lower half of the face covered and, therefore, not investigable due to the masks. Facial-emotional behavior is a good starting point for understanding: (1) the affective state (such as emotions), (2) cognitive activity (perplexity, concentration, boredom), (3) temperament and personality traits (hostility, sociability, shyness), (4) psychopathology (such as diagnostic information relevant to depression, mania, schizophrenia, and less severe disorders), (5) psychopathological processes that occur during social interactions patient and analyst. There are numerous methods to measure facial movements resulting from the action of muscles, see for example, the measurement of visible facial actions using coding systems (non-intrusive systems that require the presence of an observer who encodes and categorizes behaviors) and the measurement of electrical "discharges" of contracting muscles (facial electromyography; EMG). However, the measuring system invented by Ekman and Friesen (2002) - "Facial Action Coding System - FACS" is the most comprehensive, complete, and versatile. Our study, carried out on about 1,500 subjects over three years of work, allowed us to highlight how the movements of the hands and upper part of the face change depending on whether the subject wears a mask or not. We have been able to identify specific alterations to the subjects’ hand movement patterns and their upper face expressions while wearing masks compared to when not wearing them. We believe that finding correlations between how body language changes when our facial expressions are impaired can provide a better understanding of the link between the face and body non-verbal language.

Keywords: facial action coding system, COVID-19, masks, facial analysis

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Authors: Ikpechukwu Njoku

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The study examined appraisal of shipping trade influence on the economic growth in Nigeria from 1981-2016 by the use of secondary data collected from the Central Bank of Nigeria. The main objectives are to examine the trend of shipping trade in Nigeria as well as determine the influence of economic growth on gross domestic product (GDP). The study employed both descriptive and influential tools. The study adopted cointegration regression method for the analysis of each of the variables (shipping trade, external reserves and external debts). The results show that there is a statistically significant relationship between GDP and external reserves with p-value 0.0190. Also the result revealed that there is a statistically significant relationship between GDP and shipping trade with p-value 0.000. However, shipping trade and external reserves contributed positively at 1% and 5% level of significance respectively while external debts impacted negatively to GDP at 5% level of significance with a long run variance of cointegration regression. Therefore, the study suggests that government should do all it can to curtail foreign dominance and repatriation of profit for a more sustainable economy as well as upgrade port facilities, prevent unnecessary delays and encourage exportable goods for maximum deployment of ships.

Keywords: external debts, external reserve, GDP, shipping trade

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Authors: Kaycee Bills

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This study will determine if students with disabilities have higher student loan debt payments than other student populations. The hypothesis was that students with disabilities would have significantly higher student loan debt payments than other students due to the length of time they spend in school. Using the Bachelorette and Beyond Study Wave 2015/017 dataset, quantitative methods were employed. These data analysis methods included linear regression and a correlation matrix. Due to the exploratory nature of the study, the significance levels for the overall model and each variable were set at .05. The correlation matrix demonstrated that students with certain types of disabilities are more likely to fall under higher student loan payment brackets than students without disabilities. These results also varied among the different types of disabilities. The result of the overall linear regression model was statistically significant (p = .04). Despite the overall model being statistically significant, the majority of the significance values for the different types of disabilities were null. However, several other variables had statistically significant results, such as veterans, people of minority races, and people who attended private schools. Implications for how this impacts the economy, capitalism, and financial wellbeing of various students are discussed.

Keywords: disability, student loan debt, higher education, social work

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Authors: Ana Paula Almeida Castaldelli Maciel, Gabriela Medeiros, Amanda de Souza Machado, Maria Clara Pilatti, Ralpho Rinaldo dos Reis, Silvio Cesar Sampaio

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Sustainable agricultural systems are crucial to ensuring global food security and the long-term production of nutritious food. Comprehensive soil and water management practices, including nutrient management, balanced fertilizer use, and appropriate waste management, are essential for sustainable agriculture. Swine wastewater (SWW) treatment has become a significant focus due to environmental concerns related to heavy metals, antibiotics, resistant pathogens, and nutrients. In South America, small farms use soil to dispose of animal waste, a practice that is expected to increase with global pork production. The potential of SWW as a nutrient source is promising, contributing to global food security, nutrient cycling, and mineral fertilizer reduction. Short- and long-term studies evaluated the effects of SWW on soil and plant parameters, such as nutrients, heavy metals, organic matter (OM), cation exchange capacity (CEC), and pH. Although promising results have been observed in short- and medium-term applications, long-term applications require more attention due to heavy metal concentrations. Organic soil amendment strategies, due to their economic and ecological benefits, are commonly used to reduce the bioavailability of heavy metals. However, the rate of degradation and initial levels of OM must be monitored to avoid changes in soil pH and release of metals. The study aimed to evaluate the long-term effects of SWW application on soil fertility parameters, focusing on calcium (Ca), magnesium (Mg), and potassium (K), in addition to CEC and OM. Experiments were conducted at the Universidade Estadual do Oeste do Paraná, Brazil, using 24 drainage lysimeters for nine years, with different application rates of SWW and mineral fertilization. Principal Component Analysis (PCA) was then conducted to summarize the composite variables, known as principal components (PC), and limit the dimensionality to be evaluated. The retained PCs were then correlated with the original variables to identify the level of association between each variable and each PC. Data were interpreted using Analysis of Variance - ANOVA for general linear models (GLM). As OM was not measured in the 2007 soybean experiment, it was assessed separately from PCA to avoid loss of information. PCA and ANOVA indicated that crop type, SWW, and mineral fertilization significantly influenced soil nutrient levels. Soybeans presented higher concentrations of Ca, Mg, and CEC. The application of SWW influenced K levels, with higher concentrations observed in SWW from biodigesters and higher doses of swine manure. Variability in nutrient concentrations in SWW due to factors such as animal age and feed composition makes standard recommendations challenging. OM levels increased in SWW-treated soils, improving soil fertility and structure. In conclusion, the application of SWW can increase soil fertility and crop productivity, reducing environmental risks. However, careful management and long-term monitoring are essential to optimize benefits and minimize adverse effects.

Keywords: contamination, water research, biodigester, nutrients

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Authors: M. Panahian

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A global challenge which is of paramount significance today is the issue of devising innovative solutions to tackle the environmental issues, as well as more intelligent and foresightful consumption of and management of natural resources. Changes in global climate resulting from the burning of fossil fuel and the rise in the level of energy consumption are a few examples of environmental issues detrimental to any form of life on earth, which are aggravated year by year. Overall, energy-efficient designs and construction strategies can be studied at three scales: building, block, and city. Nevertheless, as the available literature suggests, the greatest emphasis has been on building and city scales, and little has been done as to the energy-efficient designs at block scale. Therefore, the aim of the current research is to investigate the influences of residential block scale envelope on the energy consumption in buildings. To this end, a case study of residential block scale has been selected in the city of Isfahan, in Iran, situated in a hot and dry climate with cold winters. Eventually, the most effective variables in energy consumption, concerning the block scale envelope, will be concluded.

Keywords: sustainability, passive energy saving solutions, residential block scale, energy efficiency

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Authors: W. K. Zahra, M. A. El-Beltagy, R. R. Elkhadrawy

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So many practical problems in science and technology developed over the past decays. For instance, the mathematical boundary layer theory or the approximation of solution for different problems described by differential equations. When such problems consider large or small parameters, they become increasingly complex and therefore require the use of asymptotic methods. In this work, we consider the singularly perturbed boundary value problems which contain very small parameters. Moreover, we will consider these perturbation parameters as random variables. We propose a numerical method to solve this kind of problems. The proposed method is based on an exponential spline, Shishkin mesh discretization, and polynomial chaos expansion. The polynomial chaos expansion is used to handle the randomness exist in the perturbation parameter. Furthermore, the Monte Carlo Simulations (MCS) are used to validate the solution and the accuracy of the proposed method. Numerical results are provided to show the applicability and efficiency of the proposed method, which maintains a very remarkable high accuracy and it is ε-uniform convergence of almost second order.

Keywords: singular perturbation problem, polynomial chaos expansion, Shishkin mesh, two small parameters, exponential spline

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Authors: Japnoor Garcha, Andrew P. Smith, A. James

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There has been a significant increase in the prevalence and estimates of neurodevelopmental disorders, especially autism spectrum disorders, in the last decade. The literature has seen increasing research on understanding wellbeing and mental health. To understand the association and interaction of wellbeing and mental health with autism and ADHD, a survey was given to 560 secondary school students. The survey used the wellbeing process questionnaire, the autism spectrum quotient, the ADHD self-report scale, and the strengths and difficulties questionnaire. The analysis conducted using SPSS showed that there was a significant correlation between anxiety, depression, A.Q., and ADHD. Anxiety and depression were also significantly correlated with all wellbeing and SDQ variables. The regression analysis showed that anxiety was significantly associated with positive wellbeing, negative wellbeing, emotional problems, and prosocial behaviour, whereas depression was significantly associated with positive wellbeing, negative wellbeing, physical health, flourishing, conduct problems, emotional problems and peer problems.

Keywords: ADHD traits, anxiety, autistic traits, depression

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Authors: Ashkan Shafee, Ahamd Fahimifar, Sajjad V. Maghvan

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Promotion of the Fiber Reinforced Concrete (FRC) as a construction material for civil engineering projects has invoked numerous researchers to investigate their mechanical behavior. Even though there is satisfactory information about the effects of fiber type and length, concrete mixture, casting type and other variables on the strength and deformability parameters of FRC, the numerical modeling of such materials still needs research attention. The focus of this study is to investigate the feasibility of Concrete Damaged Plasticity (CDP) model in prediction of Macro-synthetic FRC structures behavior. CDP model requires the tensile behavior of concrete to be well characterized. For this purpose, a series of uniaxial direct tension and four point bending tests were conducted on the notched specimens to define bilinear tension softening (post-peak tension stress-strain) behavior. With these parameters obtained, the flexural behavior of macro-synthetic FRC beams were modeled and the results showed a good agreement with the experimental measurements.

Keywords: concrete damaged plasticity, fiber reinforced concrete, finite element modeling, macro-synthetic fibers, uniaxial tensile test

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Authors: Shahrzad Maghsoodi, Hamid Reza Ranazi

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This paper is devoted to exploration of Chichak (hematite) deposit, using electrical resistivity, chargeability and statistical methods. Chichak hematite deposit is located in Chichak area west Azarbaijan, northwest of Iran. There are some outcrops of hematite bodies in the area. The goal of this study was to identify the depth, thickness and shape of these bodies and to explore other probabile hematite bodies. Therefore nine profiles were considered to be surveyed by RS and IP method by utilizing an innovative electrode array so called CRSP (Combined Resistivity Sounding and Profiling). IP and RS sections were completed along each profile. In addition, the RS and IP data were analyzed and relation between these two variables was determined by statistical tools. Finally, hematite bodies were identified in each of the sections. The results showed that hematite bodies have a resistivity lower than 125 Ωm and very low chargeability, lower than 8 mV⁄V. After geophysical study some points were proposed for drilling, results obtained from drilling confirm the geophysical results.

Keywords: Hematite deposit, Iron exploration, Electrical resistivity, Chargeability, Iran, Chichak, Statistical, CRSP electrodes array

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Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

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The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

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Authors: Sepehr Moradi, Mehdi Asadi Rad

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This study is to evaluate the live weight of adult pigeons to investigate about their sex, race, their mutual effects and some auxiliary variables in 4 races of Kabood, Tizpar, Parvazy, and Namebar. In this paper, 152 pieces of pigeons as 76 male and female pairs with equal age are studied randomly. Then the birds were weighted by a scale with one gram precision. Software was used for statistical analysis. Mean live weight of adult male and female pigeons in 4 races (Kabood, Tizpar, Parvazy and Namebar with (15, 20, 20, 21) and (20, 21, 18, 17) records were, (530±56, 388.75±32, 392±34, 552±48) and (446±34, 342±32, 341±46, 457±57) gr, respectively. Difference weight of adult live of male with female was significant in 1% level (P < 0.01). Difference live weight of male adult pigeon was significant in 5% level (P < 0.05). Different live weight of female adult pigeon between Kabood, Parvazy and Tizpar races were significant in 5% level (P < 0.05) but mean live weight Kabood race with Namebar race and Parvazy with Tizpar were not significant. The results showed that most and least mean live weights belonged to Namebar of the male pigeon race and Parvazy of the female pigeon race.

Keywords: Iranian Native Pigeons, adult weight, live weight, adult pigeons

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Authors: E. Benga, T. Tengen, A. Alugongo

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Periodic and continuous inventory models are the two classical management tools used to handle inventories. These models have advantages and disadvantages. The implementation of both continuous (r,Q) inventory and periodic (R, S) inventory models in most manufacturing plants comes with higher cost. Such high inventory costs are due to the fact that most manufacturing plants are not flexible enough. Since demand and lead-time are two important variables of every inventory models, their effect on the flexibility of the manufacturing plant matter most. Unfortunately, these effects are not clearly understood by managers. The reason is that the decision parameters of the continuous (r, Q) inventory and periodic (R, S) inventory models are not designed to effectively deal with the issues of uncertainties such as poor manufacturing performances, delivery performance supplies performances. There is, therefore, a need to come up with a predictive and hybrid inventory model that can combine in some sense the feature of the aforementioned inventory models. A linear combination technique is used to hybridize both continuous (r, Q) inventory and periodic (R, S) inventory models. The behavior of such hybrid inventory model is described by a differential equation and then optimized. From the results obtained after simulation, the continuous (r, Q) inventory model is more effective than the periodic (R, S) inventory models in the short run, but this difference changes as time goes by. Because the hybrid inventory model is more cost effective than the continuous (r,Q) inventory and periodic (R, S) inventory models in long run, it should be implemented for strategic decisions.

Keywords: periodic inventory, continuous inventory, hybrid inventory, optimization, manufacturing plant

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Authors: Tabinda Sadiq, Tehmina Ashfaq Qazi, Hoor Shumail

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Recently, the advent of emerging technology has created an emerging generation of restaurant marketing. It explores the aspects that influence customers’ decision-making process in selecting a restaurant after reading food bloggers' reviews online. The motivation behind this research is to investigate the correlation between the credibility of the source and their attitude toward restaurant visits. The researcher collected the data by distributing a survey questionnaire through google forms by employing the Source credibility theory. Non- probability purposive sampling technique was used to collect data. The questionnaire used a predeveloped and validated scale by Ohanian to measure the relationship. Also, the researcher collected data from 250 respondents in order to investigate the influence of food bloggers on Gen Z's decision-making process. SPSS statistical version 26 was used for statistical testing and analyzing the data. The findings of the survey revealed that there is a moderate positive correlation between the variables. So, it can be analyzed that food bloggers do have an impact on Generation Z's decision making process.

Keywords: credibility, decision making, food bloggers, generation z, e-wom

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Authors: Carla Silva

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Recent development of information and communication technology enables us to acquire, collect, analyse data in various fields of socioeconomic – technological systems. Along with the increase of economic globalization and the evolution of information technology, data mining has become an important approach for economic data analysis. As a result, there has been a critical need for automated approaches to effective and efficient usage of massive amount of educational data, in order to support institutions to a strategic planning and investment decision-making. In this article, we will address data from several different perspectives and define the applied data to sciences. Many believe that 'big data' will transform business, government, and other aspects of the economy. We discuss how new data may impact educational policy and educational research. Large scale administrative data sets and proprietary private sector data can greatly improve the way we measure, track, and describe educational activity and educational impact. We also consider whether the big data predictive modeling tools that have emerged in statistics and computer science may prove useful in educational and furthermore in economics. Finally, we highlight a number of challenges and opportunities for future research.

Keywords: data mining, research analysis, investment decision-making, educational research

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Authors: Aruna Bhat

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Culture can be placed within the social structure that embodies both the creation of social groups, and the manner in which they interact with each other. As many critics have pointed out, culture in the Postmodern context has often been considered a commodity, and indeed it shares many attributes with commercial products. Popular culture follows many patterns of behavior derived from Economics, from the simple principle of supply and demand, to the creation of marketable demographics which fit certain criterion. This trend is exemplary visible in contemporary fiction, especially in contemporary science fiction; Cyberpunk fiction in particular which is an off shoot of pure science fiction. William Gibson is one such author who in his works portrays such a scenario, and in his The Bridge Trilogy he adds another level of interpretation to this state of affairs, by describing a world that is centered on industrialization of a new kind – that focuses around data in the cyberspace. In this new world, data has become the most important commodity, and man has become nothing but a nodal point in a vast ocean of raw data resulting into commodification of each thing including Culture. This paper will attempt to study the presence of above mentioned elements in William Gibson’s The Bridge Trilogy. The theories applied will be Postmodernism and Cultural studies.

Keywords: culture, commodity, cyberpunk, data, postmodern

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Authors: Margareth E. Bolla, Ludfi Djakfar, Achmad Wicaksono

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The increase in the number of motorcycle users in Indonesia is in line with the increase in accidents involving motorcycles. Several previous studies have shown that humans are the biggest factor causing accidents, and the driver's personality factor will affect his behavior on the road. This study was conducted to see how a person's personality traits will affect the probability of having an accident while driving. The Big Five Inventory (BFI) questionnaire and the Honda Riding Trainer (HRT) simulator were used as measuring tools, while the analysis carried out was logistic regression analysis. The results of the descriptive analysis of the respondent's personality based on the BFI show that the majority of drivers have the dominant character of neuroticism (34%), while the smallest group is the driver with the dominant type of openness character (6%). The percentage of motorists who were not involved in an accident was 54%. The results of the logistic regression analysis form a mathematical model as follows Y = -3.852 - 0.288 X1 + 0.596 X2 + 0.429 X3 - 0.386 X4 - 0.094 X5 + 0.436 X6 + 0.162 X7, where the results of hypothesis testing indicate that the variables openness, conscientiousness, extraversion, agreeableness, neuroticism, history of traffic accidents and age at starting driving did not have a significant effect on the probability of a motorcyclist being involved in an accident.

Keywords: accidents, BFI, probability, simulator

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Authors: Alexander Vaninsky

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The objective of this paper is finding the way of economic restructuring - that is, change in the shares of sectoral gross outputs - resulting in the maximum possible increase in the gross domestic product (GDP) combined with decreases in energy consumption and CO2 emissions. It uses an input-output model for the GDP and factorial models for the energy consumption and CO2 emissions to determine the projection of the gradient of GDP, and the antigradients of the energy consumption and CO2 emissions, respectively, on a subspace formed by the structure-related variables. Since the gradient (antigradient) provides a direction of the steepest increase (decrease) of the objective function, and their projections retain this property for the functions' limitation to the subspace, each of the three directional vectors solves a particular problem of optimal structural change. In the next step, a type of factor analysis is applied to find a convex combination of the projected gradient and antigradients having maximal possible positive correlation with each of the three. This convex combination provides the desired direction of the structural change. The national economy of the United States is used as an example of applications.

Keywords: economic restructuring, input-output analysis, divisia index, factorial decomposition, E3 models

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Authors: Meesun Sun, Yongmin Kim

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Estimating maintenance cost is crucial in defense management because it affects military budgets and availability of equipment. When it comes to estimating maintenance cost of the deployed equipment, time series forecasting can be applied with the actual historical cost data. It is more difficult issue to estimate maintenance cost of new equipment for which the actual costs are not provided. In this underlying context, this study proposes an analytical method for maintenance cost estimating relationships (CERs) development of helicopters using linear programming. The CERs can be applied to a new helicopter because they use non-cost independent variables such as the number of engines, the empty weight and so on. In the Republic of Korea, the maintenance cost of new equipment has been usually estimated by reflecting maintenance cost to unit price ratio of the legacy equipment. This study confirms that the CERs perform well for the 10 types of airmobile helicopters in terms of mean absolute percentage error by applying leave-one-out cross-validation. The suggested method is very useful to estimate the maintenance cost of new equipment and can help in the affordability assessment of acquisition program portfolios for total life cycle systems management.

Keywords: affordability analysis, cost estimating relationship, helicopter, linear programming, maintenance cost

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Authors: Illyas Md Isa, Mohamad Idris Saidin, Mustaffa Ahmad, Norhayati Hashim

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A highly selective and sensitive carbon paste electrode modified with multiwall carbon nanotubes and 2,6–diacetylpyridine-di-(1R)–(-)–fenchone diazine tetracarbonylmolybdenum(0) complex was used for determination of trace amounts of Cu(II) using square wave anodic stripping voltammetry (SWASV). The influences of experimental variables on the proposed electrode such as pH, supporting electrolyte, preconcentration potential and time, and square wave parameters were investigated. Under optimal conditions, the proposed electrode showed a linear relationship with concentration in the range of 1.0 × 10–10 to 1.0 × 10– 6 M Cu(II) with a limit of detection 8.0 × 10–11 M. The relative standard deviation (n = 5) for a solution containing 1.0 × 10– 6 M of Cu(II) was 0.036. The presence of various cations (in 10 and 100-folds concentration) did not interfere. Electrochemical impedance spectroscopy (EIS) showed that the charge transfer at the electrode-solution interface was favourable. The proposed electrode was applied for the determination of Cu(II) in several water samples. Results agreed very well with those obtained by inductively coupled plasma-optical emission spectrometry. The modified electrode was then proposed as an alternative for determination of Cu(II).

Keywords: chemically modified electrode, Cu(II), square wave anodic stripping voltammetry, tetracarbonylmolybdenum(0)

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Authors: Peter Unoh Bassey

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The study examined the influence of Costa and McCrae’s Neo-PI Factor and early adolescent’s school social adjustment in Cross River State, Nigeria. The research adopted the causal-comparative design also known as the ex-post facto with about one thousand and eighteen (1,018) students who were randomly selected from one stream of JSS 1 classes in 19 schools out of seventy-three (73) in the study area. Data were collected using two instruments one is the NEO-PI scale, and students school social adjustment questionnaire. Three research questions and three research hypotheses were postulated and tested at 0.05 level of significance. The analysis of data was carried out using both the independent t-test statistics and the one-way analysis of variance (ANOVA). The analyzed result indicated that the five dimensions had a significant influence on students school social adjustment. A post hoc was equally carried out to show the relative significant difference among the study variables. In view of the above, it was recommended that teachers, parents and educational psychologists should be involved to enhance students the confidence to overcome their social adjustment problem.

Keywords: Costa and McCrae’s NEO-PI Factor, early adolescents, school, social adjustment

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Authors: Godswill Nwabuisi Osuafor, Sonto Maria Maputle

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Background: Abounding studies found that religiosity and social factors modulate alcohol use among university students. However, there is a scarcity of empirical studies examining the protective effects of religiosity and other social factors on alcohol use and abuse in South African universities. The aim of this study was therefore to assess the protective effects of religiosity and roles of social factors on alcohol use among university students. Methodology: A survey on the use of alcohol among 416 university students was conducted using structured questionnaire in 2014. Data were sourced on religiosity and contextual variables. Students were classified as practicing intrinsic religiosity or extrinsic religiosity based on the response to the measures of religiosity. Descriptive, chi square and binary logistic analyses were used in processing the data. Result: Results revealed that alcohol use was associated with religiosity, religion, sex, family history of alcohol use and experimenting with alcohol. Reporting alcohol abuse was significantly predicted by sex, family history of alcohol use and experimenting with alcohol. Religiosity mediated lower alcohol use whereas family history of alcohol use and experimenting with alcohol promoted alcohol use and abuse. Conclusion: Families, religious groups and societal factors may be the specific niches for intervention on alcohol use among university students.

Keywords: religiosity, alcohol use, protective factors, university students

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Authors: Jasper C. Dioco

Abstract:

The study was done to investigate the relationship of taxi company safety climate and drivers’ safety motivation and knowledge on taxi drivers’ safety performance. Data were collected from three Taxi Companies with taxi drivers as participants (N = 84). The Hiligaynon translated version of Transportation Companies’ Climate Scale (TCCS), Safety Motivation and Knowledge Scale, Occupational Safety Motivation Questionnaire and Global Safety Climate Scale were used to study the relationships among four parameters: (a) Taxi company safety climate; (b) Safety motivation; (c) Safety knowledge; and (d) Safety performance. Correlational analyses found that there is no relation between safety climate and safety performance. A Hierarchical regression demonstrated that safety motivation predicts the most variance in safety performance. The results will greatly impact how taxi company can increase safe performance through the confirmation of the proximity of variables to organizational outcome. A strong positive safety climate, in which employees perceive safety to be a priority and that managers are committed to their safety, is likely to increase motivation to be safety. Hence, to improve outcomes, providing knowledge based training and health promotion programs within the organization must be implemented. Policy change might include overtime rules and fatigue driving awareness programs.

Keywords: safety climate, safety knowledge, safety motivation, safety performance, taxi drivers

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Authors: Christian Gabriel Mariveles, Darelle Jay Gallardo, Leslie Dayaoen, Laurenz Paul Diaz

Abstract:

True experimental research with descriptive analysis was conducted. Utilizing Quicklime (Calcium Oxide) for self-healing properties of coconut husk fibre concrete brick. There are 2 setups established: the first one has the 1:1:2 ratio of calcium oxide, cement and sand, and the second one has a 2:1:2 ratio of the same variables. The bricks are made from the residences along Barangay Greater Lagro. The mixture of sand and cement is mixed with coconut husk fibers and then molded with different ratios in the molder. After the drying of cement, the researchers tested the bricks in the laboratory for compressive strength. The brick with the highest PSI is picked by the researchers to drop into freefall testing, and it makes remarkable remarks as it is deformed after dropping to different heights with a maximum of 20 feet. Unfortunately, the self-healing capabilities were not observed during the 12 weeks of monitoring. However, the brick was weighed after 12 weeks of monitoring, and it increased in weight by 0.030 kg. from 1.833 kg. to 1.863 kg. meaning that this ratio 2 has the potential to self-heal, but 12 weeks of monitoring by the researchers is not enough to conclude that it has a significant difference.

Keywords: self healing, coconut husk bricks, research, calcium oxide, utilizing quicklime

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Authors: Bailey Hall, Athena Hoppe, Tevyn Kagele, Anna Nichols, Breeanna Messner

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The Spokane Street Medicine (SSM) Program aims to deliver medical care to people experiencing homelessness in Spokane, Washington. Street medicine is designed to function in a non-traditional setting to help deliver healthcare to a largely underserved population. In this analysis, the SSM Program’s medical charts from street and shelter encounters in early 2021 were reviewed in order to identify illness and diseases in people experiencing homelessness in Spokane. More than half of the prescriptions written during these encounters were for either an antibacterial, an antibiotic, or an antifungal. Estimates of the cost to the local healthcare system are included. Initiating treatment for communicable diseases in people experiencing homelessness via street medicine efforts greatly reduces economic costs while improving health outcomes.

Keywords: ethical issues in public health, equity issues in public health, health economics, health disparities, healthcare costs, medical public health, public health ethics, street medicine

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Authors: Raeda F. Abualrub, Amani Abdulnabi

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Aim: The aims of this study were to (a) examine the levels of nurses' political efficacy and involvement in health policy; and (b) explore the relationships between political efficacy, involvement in health policy, and participants’ background variables. Background: Nurses as citizens and health care providers have the right to express their opinions and beliefs in regard to issues that are concerned with the health care system or the public health domain. Methods: A descriptive, cross-sectional design using was utilized. A self-administered questionnaire (Political Efficacy Scale & Involvement in Health Policy Scale) was completed by a convenience sample of 302 nurses. Results: The results of this study showed low levels of involvement in health policy and political efficacy and a positive weak correlation between political efficacy and involvement in health policy. The perceived level of political efficacy was associated positively with nurses’ age and experience. Conclusions: Nurse administrators and managers may empower, support, and encourage nurses to enhance their involvement in health policy. Implications for Nursing Management: The findings have implications for nursing leaders and administrators to design appropriate strategies to enhance nurses’ involvement in health policy development.

Keywords: health policy, Jordan, nurses, political efficacy

Procedia PDF Downloads 99

Authors: Juan Cuesta

Abstract:

Satellite observation is a fundamental component of air pollution monitoring systems, such as the large-scale Copernicus Programme. Next-generation satellite sensors, in orbit or programmed in the future, offer great potential to observe major air pollutants, such as tropospheric ozone, with unprecedented spatial and temporal coverage. However, satellite approaches developed for remote sensing of tropospheric ozone are based solely on measurements from a single instrument in a specific spectral range, either thermal infrared or ultraviolet. These methods offer sensitivity to tropospheric ozone located at the lowest at 3 or 4 km altitude above the surface, thus limiting their applications for ozone pollution analysis. Indeed, no current observation of a single spectral domain provides enough information to accurately measure ozone in the atmospheric boundary layer. To overcome this limitation, we have developed a multispectral synergism approach, called "IASI+GOME2", at the Laboratoire Interuniversitaire des Systèmes Atmosphériques (LISA) laboratory. This method is based on the synergy of thermal infrared and ultraviolet observations of respectively the Infrared Atmospheric Sounding Interferometer (IASI) and the Global Ozone Monitoring Experiment-2 (GOME-2) sensors embedded in MetOp satellites that have been in orbit since 2007. IASI+GOME2 allowed the first satellite observation of ozone plumes located between the surface and 3 km of altitude (what we call the lowermost troposphere), as it offers significant sensitivity in this layer. This represents a major advance for the observation of ozone in the lowermost troposphere and its application to air quality analysis. The ozone abundance derived by IASI+GOME2 shows a good agreement with respect to independent observations of ozone based on ozone sondes (a low mean bias, a linear correlation larger than 0.8 and a mean precision of about 16 %) around the world during all seasons. Using IASI+GOME2, lowermost tropospheric ozone pollution plumes are quantified both in terms of concentrations and also in the amounts of ozone photo-chemically produced along transport and also enabling the characterization of the ozone pollution, such as what occurred during the lockdowns linked to the COVID-19 pandemic. The current paper will show the IASI+GOME2 multispectral approach to observe the lowermost tropospheric ozone from space and an overview of several applications on different continents and at a global scale.

Keywords: ozone pollution, multispectral synergism, satellite, air quality

Procedia PDF Downloads 82

Authors: Deena Moustafa

Abstract:

The purpose of this paper is to describe the sources of parenting stress in mothers of Dual Diagnosis children (n =60) and examine the relationship between parenting stress and maternal psychological status (depression and well-being), also examine if there is any difference between the previous variables in different disabilities associated with Autism. A descriptive correlational design was used. Data were collected via online questionnaires. The study finds that there was no significant relationship between Autism Parenting Stress Index (APSI) scores and types of disability which associated with Autism, although Mothers with deaf autistic reported more parenting stress, Similar findings were found regarding Depressive Symptoms, as there was no significant relationship between (CESD-R) scores and types of disability which associated with Autism, also study finds that there was a significant correlation of the (APSI) with the (CESD-R) Mothers with higher overall parenting stress reported more depressive symptoms. Likewise, there was also a significant correlation between the (APSI) and the (RPWB) Mothers reporting more parenting stress also reported lower levels of well-being.

Keywords: parenting stress, maternal psychological statues, mothers of dual diagnosis, autism

Procedia PDF Downloads 456