Search results for: Allan variance

Authors: Ashok Kumar, Parveen Parveen

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India is bestowed with an extremely high population of plant species with medicinal value and even has two biodiversity hotspots. Indian systems of medicine including Ayurveda, Siddha and Unani have historically been serving humankind across the world since time immemorial. About 1500 plant species have well been documented in Ayurvedic Nighantus as official medicinal plants. Additionally, several hundred species of plants are being routinely used as medicines by local people especially tribes living in and around forests. The natural resources for medicinal plants have unscientifically been over-exploited forcing rapid depletion in their genetic diversity. Moreover, renewed global interest in herbal medicines may even lead to additional depletion of medicinal plant wealth of the country, as about 95% collection of medicinal plants for pharmaceutical preparation is being carried out from natural forests. On the other hand, huge export market of medicinal and aromatic plants needs to be seriously tapped for enhancing inflow of foreign currency. Asparagus racemosus Willd., a member of family Liliaceae, is one of thirty-two plant species that have been identified as priority species for cultivation and conservation by the National Medicinal Plant Board (NMPB), Government of India. Though attention is being focused on standardization of agro-techniques and extraction methods, little has been designed on genetic improvement and selection of desired types with higher root production and saponin content, a basic ingredient of medicinal value. The saponin not only improves defense mechanisms and controls diabetes but the roots of this species promote secretion of breast milk, improved lost body weight and considered as an aphrodisiac. There is ample scope for genetic improvement of this species for enhancing productivity substantially, qualitatively and quantitatively. It is emphasized to select desired genotypes with sufficient genetic diversity for important economic traits. Hybridization between two genetically divergent genotypes could result in the synthesis of new F1 hybrids consisting of useful traits of both the parents. The evaluation of twenty seed sources of Asparagus racemosus assembled different geographical locations of India revelled high degree of variability for traits of economic importance. The maximum genotypic and phenotypic variance was observed for shoot height among shoot related traits and for root length among root related traits. The shoot height, genotypic variance, phenotypic variance, genotypic coefficient of variance, the phenotypic coefficient of variance was recorded to be 231.80, 3924.80, 61.26 and 1037.32, respectively, where those of the root length were 9.55, 16.80, 23.46 and 41.27, respectively. The maximum genetic advance and genetic gain were obtained for shoot height among shoot-related traits and root length among root-related traits. Index values were developed for all seed sources based on the four most important traits, and Panthnagar (Uttrakhand), Jodhpur (Rajasthan), Dehradun (Uttarakhand), Chandigarh (Punjab), Jammu (Jammu & Kashmir) and Solan (Himachal Pradesh) were found to be promising seed sources.

Keywords: asparagus, genetic, genotypes, variance

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Authors: Raquel M. De sousa, Sofiane Labidi, Allan Kardec D. Barros, Alex O. Barradas Filho, Aldalea L. B. Marques

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Several parameters are established in order to measure biodiesel quality. One of them is the iodine value, which is an important parameter that measures the total unsaturation within a mixture of fatty acids. Limitation of unsaturated fatty acids is necessary since warming of a higher quantity of these ones ends in either formation of deposits inside the motor or damage of lubricant. Determination of iodine value by official procedure tends to be very laborious, with high costs and toxicity of the reagents, this study uses an artificial neural network (ANN) in order to predict the iodine value property as an alternative to these problems. The methodology of development of networks used 13 esters of fatty acids in the input with convergence algorithms of backpropagation type were optimized in order to get an architecture of prediction of iodine value. This study allowed us to demonstrate the neural networks’ ability to learn the correlation between biodiesel quality properties, in this case iodine value, and the molecular structures that make it up. The model developed in the study reached a correlation coefficient (R) of 0.99 for both network validation and network simulation, with Levenberg-Maquardt algorithm.

Keywords: artificial neural networks, biodiesel, iodine value, prediction

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Authors: Ashraf Ward

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Effect of calving interval on 305 day milk yield for first three lactations was studied in order to increase efficiency of selection schemes and to more efficiently manage Holstein cows that have been raised on small farms in Libya. Results obtained by processing data of 1476 cows, managed in 935 small scale farms, pointed out that current calving interval significantly affects on milk production for first three lactations (p<0.05). Preceding calving interval affected 305 day milk yield (p<0.05) in second lactation only. Linear regression model accounted for 20-25 % of the total variance of 305 day milk yield. Extension of calving interval over 420, 430, 450 days for first, second and third lactations respectively, did not increase milk production when converted to 305 day lactation. Stochastic relations between calving interval and calving age and month are moderated. Values of Pierson’s correlation coefficients ranged 0.38 to 0.69. Adjustment of milk production in order to reduce effect of calving interval on total phenotypic variance of milk yield is valid for first lactation only. Adjustment of 305 day milk yield for second and third lactations in order to reduce effects of factors “calving age and month” brings about, at the same time, elimination of calving interval effect.

Keywords: milk yield, Holstien, non genetic, calving

Procedia PDF Downloads 389

Authors: Salman Mohamadi, Seyed Mohammad Ali Tayaranian Hosseini, Hamidreza Amindavar

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In this paper, we provide a procedure to analyze and model EEG (electroencephalogram) signal as a time series using ARIMA-GARCH to predict an epileptic attack. The heteroskedasticity of EEG signal is examined through the ARCH or GARCH, (Autore- gressive conditional heteroskedasticity, Generalized autoregressive conditional heteroskedasticity) test. The best ARIMA-GARCH model in AIC sense is utilized to measure the volatility of the EEG from epileptic canine subjects, to forecast the future values of EEG. ARIMA-only model can perform prediction, but the ARCH or GARCH model acting on the residuals of ARIMA attains a con- siderable improved forecast horizon. First, we estimate the best ARIMA model, then different orders of ARCH and GARCH modelings are surveyed to determine the best heteroskedastic model of the residuals of the mentioned ARIMA. Using the simulated conditional variance of selected ARCH or GARCH model, we suggest the procedure to predict the oncoming seizures. The results indicate that GARCH modeling determines the dynamic changes of variance well before the onset of seizure. It can be inferred that the prediction capability comes from the ability of the combined ARIMA-GARCH modeling to cover the heteroskedastic nature of EEG signal changes.

Keywords: epileptic seizure prediction , ARIMA, ARCH and GARCH modeling, heteroskedasticity, EEG

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Authors: N. C. Ghosh, Niladri Das, Prolay Mondal, Ranajit Ghosh

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Groundwater quality deterioration due to human activities has become a prime factor of modern life. The major concern of the study is to access spatial variation of groundwater quality and to identify the sources of groundwater chemicals and its impact on human health of the concerned area. Multivariate statistical techniques, cluster, principal component analysis, and hydrochemical fancies are been applied to measure groundwater quality data on 14 parameters from 107 sites distributed randomly throughout the Birbhum district. Five factors have been extracted using Varimax rotation with Kaiser Normalization. The first factor explains 27.61% of the total variance where high positive loading have been concentrated in TH, Ca, Mg, Cl and F (Fluoride). In the studied region, due to the presence of basaltic Rajmahal trap fluoride contamination is highly concentrated and that has an adverse impact on human health such as fluorosis. The second factor explains 24.41% of the total variance which includes Na, HCO₃, EC, and SO₄. The last factor or the fifth factor explains 8.85% of the total variance, and it includes pH which maintains the acidic and alkaline character of the groundwater. Hierarchical cluster analysis (HCA) grouped the 107 sampling station into two clusters. One cluster having high pollution and another cluster having less pollution. Moreover hydromorphological facies viz. Wilcox diagram, Doneen’s chart, and USSL diagram reveal the quality of the groundwater like the suitability of the groundwater for irrigation or water used for drinking purpose like permeability index of the groundwater, quality assessment of groundwater for irrigation. Gibb’s diagram depicts that the major portion of the groundwater of this region is rock dominated origin, as the western part of the region characterized by the Jharkhand plateau fringe comprises basalt, gneiss, granite rocks.

Keywords: correlation, factor analysis, hydrological facies, hydrochemistry

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Authors: Valerii Dashuk

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The usage of the confidence intervals in economics and econometrics is widespread. To be able to investigate a random variable more thoroughly, joint tests are applied. One of such examples is joint mean-variance test. A new approach for testing such hypotheses and constructing confidence sets is introduced. Exploring both the value of the random variable and its deviation with the help of this technique allows checking simultaneously the shift and the probability of that shift (i.e., portfolio risks). Another application is based on the normal distribution, which is fully defined by mean and variance, therefore could be tested using the introduced approach. This method is based on the difference of probability density functions. The starting point is two sets of normal distribution parameters that should be compared (whether they may be considered as identical with given significance level). Then the absolute difference in probabilities at each 'point' of the domain of these distributions is calculated. This measure is transformed to a function of cumulative distribution functions and compared to the critical values. Critical values table was designed from the simulations. The approach was compared with the other techniques for the univariate case. It differs qualitatively and quantitatively in easiness of implementation, computation speed, accuracy of the critical region (theoretical vs. real significance level). Stable results when working with outliers and non-normal distributions, as well as scaling possibilities, are also strong sides of the method. The main advantage of this approach is the possibility to extend it to infinite-dimension case, which was not possible in the most of the previous works. At the moment expansion to 2-dimensional state is done and it allows to test jointly up to 5 parameters. Therefore the derived technique is equivalent to classic tests in standard situations but gives more efficient alternatives in nonstandard problems and on big amounts of data.

Keywords: confidence set, cumulative distribution function, hypotheses testing, normal distribution, probability density function

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Authors: S. Zenia, A. Menasseria, A. E. Kheidous, F. Larinouna, A. Smai, H. Saadi, F. Haddadj, A. Milla, F. Marniche

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Pheasant, is a bird of great ornamental value through the beauty of its form and colors, it is among the most popular birds. The present study was conducted in an experimental breeding. The objective of this work is to know the quality of the eggs of this bird. A total of 938 eggs were collected. To deepen the knowledge about the characteristics of external shell quality, biometric parameters were studied, among them we find the weight with a mean value of 29.2± 2, 24 g. Egg length (mm) and egg width (mm) mean value are respectively 43.01 ± 1,84 cm and 34.05 ± 1,44cm. The volume and shape index of eggs obtained are respectively 25,63±2,88cm3 and 79.00 ± 3%, shell index which recorded an average of 68%. Water loss recorded is 13%. Note that all these parameters and others may influence hatching. The analysis of variance applied for the comparison of egg weight shows that there is no significant difference in the same form factor (P> 0.05). Otherwise, the comparison test used shows a significant difference with P <0.05 for length, width, volume, density, indices of shell and water loss of eggs between the different. Indeed, several factors may explain the difference as the absence of sorting eggs during incubation and other factors that will be exposing later.

Keywords: analysis of variance, egg, hatching, morphometry of eggs Phaisan (Phasianus colchicus.L.)

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Authors: Emmanuel Abayomi Rotimi

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Context: Rabbits production plays important role in increasing animal protein supply in Nigeria. Rabbit production provides a cheap, affordable, and healthy source of meat. The growth of animals involves an increase in body weight, which can change the conformation of various parts of the body. Live weight and linear measurements are indicators of growth rate in rabbits and other farm animals. Aims: This study aimed to define the body dimensions of New Zealand rabbits and also to investigate the morphometric traits variables that contribute to body conformation by the use of principal component analysis (PCA). Methods: Data were obtained from 80 New Zealand rabbits (40 bucks and 40 does) raised in Livestock Teaching and Research Farm, Federal University Dutsinma. Data were taken on body weight (BWT), body length (BL), ear length (EL), tail length (TL), heart girth (HG) and abdominal circumference (AC). Data collected were subjected to multivariate analysis using SPSS 20.0 statistical package. Key results: The descriptive statistics showed that the mean BWT, BL, EL, TL, HG, and AC were 0.91kg, 27.34cm, 10.24cm, 8.35cm, 19.55cm and 21.30cm respectively. Sex showed significant (P<0.05) effect on all the variables examined, with higher values recorded for does. The phenotypic correlation coefficient values (r) between the morphometric traits were all positive and ranged from r = 0.406 (between EL and BL) to r = 0.909 (between AC and HG). HG is the most correlated with BWT (r = 0.786). The principal component analysis with variance maximizing orthogonal rotation was used to extract the components. Two principal components (PCs) from the factor analysis of morphometric traits explained about 80.42% of the total variance. PC1 accounted for 64.46% while PC2 accounted for 15.97% of the total variances. Three variables, representing body conformation, loaded highest in PC1. PC1 had the highest contribution (64.46%) to the total variance, and it is regarded as body conformation traits. Conclusions: This component could be used as selection criteria for improving body weight of rabbits.

Keywords: conformation, multicollinearity, multivariate, rabbits and principal component analysis

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Authors: S. P. Praveen Kumar, Bong-Su Sin, Kwon-Hee Lee

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Finned-tube heat exchangers are predominantly used in space conditioning systems, as well as other applications requiring heat exchange between two fluids. The design of finned-tube heat exchangers requires the selection of over a dozen design parameters by the designer such as tube pitch, tube diameter, tube thickness, etc. Finned-tube heat exchangers are common devices; however, their performance characteristics are complicated. In this paper, numerical studies have been carried out to analyze the performances of finned tube heat exchanger (without fins considered for experimental purpose) by predicting the characteristics of temperature difference and pressure drop. In this study, a design considering 5 design variables, maximizing the temperature difference and minimizing the pressure drop was suggested by applying DOE. In this process, L18 orthogonal array was adopted. Parametric analytical studies have been carried out using Analysis of Variance (ANOVA) to determine the relative importance of each variable with respect to the temperature difference and the pressure drop. Following the results, the final design was suggested by predicting the optimum design therefore confirming the optimized condition.

Keywords: heat exchanger, fluid analysis, heat transfer, design of experiment, analysis of variance

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Authors: Eric D. Olson

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The lesbian/gay/bisexual/transgender/queer/questioning tourist (LGBTQ+) travels more frequently, spends more money on travel, and is more likely to travel internationally compared to their straight/heterosexual counterparts. For Vietnam, this represents a huge opportunity to increase international tourism, considering social advancements and recognition of the LGBTQ+ have greatly increased in the past few years in Vietnam. For example, Vietnam’s Health Ministry confirmed in 2022 that same-sex attraction and being transgender is not a mental health condition. A robust hospitality ecosystem of LGBTQ+ tourism suppliers already exists in Vietnam catering to LGBTQ+ tourists (e.g., Gay Hanoi Tours, VietPride). Vietnam is a safe and welcoming destination with incredible nature, cosmopolitan cities, and friendly people; however, there is a dearth of academic and industry research that has examined how LGBTQ+ international tourists perceive Vietnam as an LGBTQ+ friendly destination. To rectify this gap, this research examines Vietnam as an LGBTQ+ destination in order to provide government officials, destination marketers, and industry practitioners with insight into this increasingly visible tourist market segment. A self-administered survey instrument was administered to n=375 international LGBTQ+ tourists to examine their perceptions of Vietnam. A factor analysis found three categories of LGBTQ+ factors of visitation to Vietnam: safety and security (Eigenvalue = 4.12, variance = 32.45, α = .82); LGBTQ+ attractions (Eigenvalue = 3.65 variance = 24.23, α = .75); and friendly interactions (Eigenvalue = 3.71, variance = 10.45, α = .96). Multiple regression was used to examine LGBTQ+ visitation factors and intention to visit Vietnam, F=12.20 (2, 127), p < .001, R2 = .56. Safety and security (β = 0.42, p < .001), LGBTQ+ attractions (β = 0.61, p < .001) and friendly interactions (β = 0.42, p < .001) are predictors to visit Vietnam. Results are consistent with previous research that highlight safety/security is of utmost importance to the community when traveling. Attractions, such as LGBTQ+ tours, suppliers, and festivals can also be used as a pull factor in encouraging tourism. Implications/limitations will be discussed.

Keywords: tourism, LGBTQ, vietnam, regression

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Authors: Mohd Khairul Bazli Mohd Aziz, Fadhilah Yusof, Zulkifli Yusop, Zalina Mohd Daud, Mohammad Afif Kasno

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Recent developed rainfall network design techniques have been discussed and compared by many researchers worldwide due to the demand of acquiring higher levels of accuracy from collected data. In many studies, rain-gauge networks are designed to provide good estimation for areal rainfall and for flood modelling and prediction. In a certain study, even using lumped models for flood forecasting, a proper gauge network can significantly improve the results. Therefore existing rainfall network in Johor must be optimized and redesigned in order to meet the required level of accuracy preset by rainfall data users. The well-known geostatistics method (variance-reduction method) that is combined with simulated annealing was used as an algorithm of optimization in this study to obtain the optimal number and locations of the rain gauges. Rain gauge network structure is not only dependent on the station density; station location also plays an important role in determining whether information is acquired accurately. The existing network of 84 rain gauges in Johor is optimized and redesigned by using rainfall, humidity, solar radiation, temperature and wind speed data during monsoon season (November – February) for the period of 1975 – 2008. Three different semivariogram models which are Spherical, Gaussian and Exponential were used and their performances were also compared in this study. Cross validation technique was applied to compute the errors and the result showed that exponential model is the best semivariogram. It was found that the proposed method was satisfied by a network of 64 rain gauges with the minimum estimated variance and 20 of the existing ones were removed and relocated. An existing network may consist of redundant stations that may make little or no contribution to the network performance for providing quality data. Therefore, two different cases were considered in this study. The first case considered the removed stations that were optimally relocated into new locations to investigate their influence in the calculated estimated variance and the second case explored the possibility to relocate all 84 existing stations into new locations to determine the optimal position. The relocations of the stations in both cases have shown that the new optimal locations have managed to reduce the estimated variance and it has proven that locations played an important role in determining the optimal network.

Keywords: geostatistics, simulated annealing, semivariogram, optimization

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Authors: Yusef Hedjazi, Saeedeh Nazari Nooghabi

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New information and communication technologies (ICT) as one of the main needs of Faculty members in the process of teaching and learning has used in Irans higher education system since 2000.The main purpose of this study is to investigate the role of information and communication technologies (ICT) in teaching performance of Agricultural and Natural Resources Faculties at University of Tehran. The statistical population of the study consisted of all 250 faculties in Agriculture and Natural Resources Colleges and a questionnaire was used to collect data. The reliability of the questionnaire was confirmed by computing of Cronbachs Alpha coefficient at greater than .72. The study showed a significant relationship between agricultural Faculty members teaching performance and competency in using ICT. The results of the regression analysis also explained 51.7% of the variance, teaching performance. The six independent variables that accounted for the explained variance were experience in using educational websites or software, use of educational multimedia (e.g. film and CD, etc), making a presentation using PowerPoint, familiarity with online education websites, using News group to discuss on educational subjects with colleagues and students, and using Electronic communication (messengers) to solve studentsproblems.

Keywords: information and communication technologies, agricultural and natural resources, faculties, teaching performance

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Authors: D. Supaporn, B. Julaluk

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The purposes of this study were to study symptom cluster, functional status and quality of life of patients with chronic obstructive pulmonary disease (COPD), and to examine factors related to and predicting symptom cluster, functional status and quality of life of COPD patients. The sample was 180 COPD patients multi-stage random sampling from 4 hospitals in the eastern region, Thailand. The research instruments were 8 questionnaires and recorded forms measuring personal and illness data, co-morbidity, physical and psychological symptom, health status perception, social support, and regimen adherence, functional status and quality of life. Spearman rank and Pearson correlation coefficient, exploratory factors analysis and standard multiple regression were used to analyzed data. The findings revealed that two symptom clusters were generated: physical symptom cluster including dyspnea, fatigue and insomnia; and, psychological symptom cluster including anxiety and depression. Scores of physical symptom cluster was at moderate level while that of psychological symptom cluster was at low level. Scores on functional status, social support and overall regimen adherence were at good level whereas scores on quality of life and health status perception were at moderate level. Disease severity was positively related to physical symptom cluster, psychological symptom cluster and quality of life, and was negatively related to functional status at a moderate level (rs = .512, .509, .588 and -.611, respectively). Co-morbidity was positively related to physical symptom cluster and psychological symptom cluster at a low level (r = .179 and .176, respectively). Regimen adherence was negatively related to quality of life and psychological symptom cluster at a low level (r=-.277 and -.309, respectively), and was positively related to functional status at a moderate level (r=.331). Health status perception was negatively related to physical symptom cluster, psychological symptom cluster and quality of life at a moderate to high level (r = -.567, -.640 and -.721, respectively) and was positively related to functional status at a high level (r = .732). Social support was positively related to functional status (r=.235) and was negatively related to quality of life at a low level (r=-.178). Physical symptom cluster was negatively related to functional status (r= -.490) and was positively related to quality of life at a moderate level (r=.566). Psychological symptom cluster was negatively related to functional status and was positively related to quality of life at a moderate level (r= -.566 and .559, respectively). Disease severity, co-morbidity and health status perception could predict 40.2% of the variance of physical symptom cluster. Disease severity, co-morbidity, regimen adherence and health status perception could predict 49.8% of the variance of psychological symptom cluster. Co-morbidity, regimen adherence and health status perception could predict 65.0% of the variance of functional status. Disease severity, health status perception and physical symptom cluster could predict 60.0% of the variance of quality of life in COPD patients. The results of this study can be used for enhancing quality of life of COPD patients.

Keywords: chronic obstructive pulmonary disease, functional status, quality of life, symptom cluster

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Authors: Ahmed Masrai

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Listening comprehension constitutes a considerable challenge for the second language (L2) learners, but a little is known about the explanatory power of different variables in explaining variance in listening comprehension. Since research in this area, to the researcher's knowledge, is relatively small in comparison to that focusing on the relationship between reading comprehension and factors such as vocabulary and working memory, there is a need for studies that are seeking to fill the gap in our knowledge about the specific contribution of working memory capacity (WMC), aural vocabulary knowledge and written vocabulary knowledge to explaining listening comprehension. Among 130 English as foreign language learners, the present study examines what proportion of the variance in listening comprehension is explained by aural vocabulary knowledge, written vocabulary knowledge, and WMC. Four measures were used to collect the required data for the study: (1) A-Lex, a measure of aural vocabulary knowledge; (2) XK-Lex, a measure of written vocabulary knowledge; (3) Listening Span Task, a measure of WMC and; (4) IELTS Listening Test, a measure of listening comprehension. The results show that aural vocabulary knowledge is the strongest predictor of listening comprehension, followed by WMC, while written vocabulary knowledge is the weakest predictor. The study discusses implications for the explanatory power of aural vocabulary knowledge and WMC to listening comprehension and pedagogical practice in L2 classrooms.

Keywords: listening comprehension, second language, vocabulary knowledge, working memory

Procedia PDF Downloads 349

Authors: Allan B. de Guzman, Rochelle Gabrielle R. Gatan, Ira Bianca Mae G. Gesmundo, Astley Justine H. Golosinda

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Background: While in prison, the elderly, like the younger prisoners, face specific problems and deprivations arising directly from their imprisonment, one of which is forced separation from family and loved ones. Despite the numerous studies that examined the impact of separation and separation anxiety on the emotions and behavior of young individuals, little is known about separation anxiety in the elderly population. Objective: This grounded theory study purports to describe the process of separation anxiety among incarcerated Filipino elderly men. Method: Individual interviews and participant observations were conducted with 25 incarcerated elderly Filipino men who are first-time prisoners, sentenced to lifetime imprisonment and were analyzed using constant comparative method. Results: Following Strauss and Corbin’s protocol, a four-part process emerged to describe the studied layer of human experience. The Tectonic Model of Separation Anxiety among incarcerated Filipino elderly men comprises of four phases: Winkling, Wilting, Weeding, and Weaving. Conclusion: This study has inductively and creatively explored the process of separation anxiety among the Filipino incarcerated elderly men. Findings of this study invite nurses and other clinicians to identify developmentally appropriate strategies and interventions for this vulnerable and neglected sector of society.

Keywords: elderly, grounded theory, separation anxiety, Filipino, incarcerated

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Authors: Cam Minh Tri Tien, Richard Fenrich, Tristan Shelley, Nam Mai-Duy, Allan Malano, Xuesen Zeng

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Since additive manufacturing is a layer-by-layer deposition approach, good bonding quality between adjacent layers is critically important to achieve optimal mechanical performance, including applications in pressure vessels. The need to enhance the strength of printed products, especially in the build direction where layup gaps and voids exist between the printed layers, has garnered significant attention. The proposed research will focus on improving the current Fused Deposition Modelling (FDM) process to produce polymers reinforced with chopped fibers, utilizing a controlled heat zone to enhance the adhesion between printed layers. Energy will be applied to both printed and printing layers to improve the bonding strength between adjacent layers. Through the enhanced FDM process, the mechanical performance of composite parts will experience a substantial improvement, particularly in the build direction, as compared to current FDM methods. A combination of experimental, numerical, and analytical methods will be employed to demonstrate the enhanced performance of heat-controlled 3D printed parts.

Keywords: 3D Printing, pressure vessels, interlayer bonding, controlled heat

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Authors: Fariba Dortaj, Reza Asadinejad, Akram Dortaj, Atena Baziyar

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The aim of this study was to determine the effect of distance education (based on MOOC) on the components of academic engagement of Kerman PNU. The research was quasi-experimental method that cluster sampling with an appropriate volume was used in this study (one class in experimental group and one class in controlling group). Sampling method is single-stage cluster sampling. The statistical society is students of Kerman Payam Noor University, which) were selected 40 of them as sample (20 students in the control group and 20 students in experimental group). To test the hypothesis, it was used the analysis of univariate and Co-covariance to offset the initial difference (difference of control) in the experimental group and the control group. The instrument used in this study is academic engagement questionnaire of Zerang (2012) that contains component of cognitive, behavioral and motivational engagement. The results showed that there is no significant difference between mean scores of academic components of academic engagement in experimental group and the control group on the post-test, after elimination of the pre-test. The adjusted mean scores of components of academic engagement in the experimental group were higher than the adjusted average of scores after the test in the control group. The use of technology-based education in distance education has been effective in increasing cognitive engagement, motivational engagement and behavioral engagement among students. Experimental variable with the effect size 0.26, predicted 26% of cognitive engagement component variance. Experimental variable with the effect size 0.47, predicted 47% of the motivational engagement component variance. Experimental variable with the effect size 0.40, predicted 40% of behavioral engagement component variance. So teaching with technology (MOOC) has a positive impact on increasing academic engagement and academic performance of students in educational technology. The results suggest that technology (MOOC) is used to enrich the teaching of other lessons of PNU.

Keywords: educational technology, distance education, components of academic engagement, mooc technology

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Authors: Vibha Devi, Shabina Khanam

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Hemp (Cannabis sativa) possesses a rich content of ω-6 linoleic and ω-3 linolenic essential fatty acid in the ratio of 3:1, which is a rare and most desired ratio that enhances the quality of hemp oil. These components are beneficial for the development of cell and body growth, strengthen the immune system, possess anti-inflammatory action, lowering the risk of heart problem owing to its anti-clotting property and a remedy for arthritis and various disorders. The present study employs supercritical fluid extraction (SFE) approach on hemp seed at various conditions of parameters; temperature (40 - 80) °C, pressure (200 - 350) bar, flow rate (5 - 15) g/min, particle size (0.430 - 1.015) mm and amount of co-solvent (0 - 10) % of solvent flow rate through central composite design (CCD). CCD suggested 32 sets of experiments, which was carried out. As SFE process includes large number of variables, the present study recommends the application of resampling techniques for cross-validation of the obtained data. Cross-validation refits the model on each data to achieve the information regarding the error, variability, deviation etc. Bootstrap and jackknife are the most popular resampling techniques, which create a large number of data through resampling from the original dataset and analyze these data to check the validity of the obtained data. Jackknife resampling is based on the eliminating one observation from the original sample of size N without replacement. For jackknife resampling, the sample size is 31 (eliminating one observation), which is repeated by 32 times. Bootstrap is the frequently used statistical approach for estimating the sampling distribution of an estimator by resampling with replacement from the original sample. For bootstrap resampling, the sample size is 32, which was repeated by 100 times. Estimands for these resampling techniques are considered as mean, standard deviation, variation coefficient and standard error of the mean. For ω-6 linoleic acid concentration, mean value was approx. 58.5 for both resampling methods, which is the average (central value) of the sample mean of all data points. Similarly, for ω-3 linoleic acid concentration, mean was observed as 22.5 through both resampling. Variance exhibits the spread out of the data from its mean. Greater value of variance exhibits the large range of output data, which is 18 for ω-6 linoleic acid (ranging from 48.85 to 63.66 %) and 6 for ω-3 linoleic acid (ranging from 16.71 to 26.2 %). Further, low value of standard deviation (approx. 1 %), low standard error of the mean (< 0.8) and low variance coefficient (< 0.2) reflect the accuracy of the sample for prediction. All the estimator value of variance coefficients, standard deviation and standard error of the mean are found within the 95 % of confidence interval.

Keywords: resampling, supercritical fluid extraction, hemp oil, cross-validation

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Authors: Amanpreet Kaur, Ravinder Agarwal, Amod Kumar

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Surface electromyography is a strategy to measure the muscle activity of the skin. Sensors placed on the skin recognize the electrical current or signal generated by active muscles. A lot of the research has focussed on the detection of signal from upper limb amputee with activity of triceps and biceps muscles. The purpose of this study was to correlate phantom movement and sEMG activity in residual stump muscles of transhumeral amputee from the shoulder muscles. Eight non- amputee and seven right hand amputees were recruited for this study. sEMG data were collected for the trapezius, pectoralis and teres muscles for elevation, protraction and retraction of shoulder. Contrast between the amputees and non-amputees muscles action have been investigated. Subsequently, to investigate the impact of class separability for different motions of shoulder, analysis of variance for experimental recorded data was carried out. Results were analyzed to recognize different shoulder movements and represent a step towards the surface electromyography controlled system for amputees. Difference in F ratio (p < 0.05) values indicates the distinction in mean therefore these analysis helps to determine the independent motion. The identified signal would be used to design more accurate and efficient controllers for the upper-limb amputee for researchers.

Keywords: around shoulder amputation, surface electromyography, analysis of variance, features

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Authors: Thirasak Panyaphirawat, Pairoj Sapsmarnwong, Teeratas Pornyungyuen

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This paper presents the findings of an experimental investigation of important machining parameters for the horizontal boring tool modified to mouth with a horizontal lathe machine to bore an overlength workpiece. In order to verify a usability of a modified tool, design of experiment based on Taguchi method is performed. The parameters investigated are spindle speed, feed rate, depth of cut and length of workpiece. Taguchi L9 orthogonal array is selected for four factors three level parameters in order to minimize surface roughness (Ra and Rz) of S45C steel tubes. Signal to noise ratio analysis and analysis of variance (ANOVA) is performed to study an effect of said parameters and to optimize the machine setting for best surface finish. The controlled factors with most effect are depth of cut, spindle speed, length of workpiece, and feed rate in order. The confirmation test is performed to test the optimal setting obtained from Taguchi method and the result is satisfactory.

Keywords: design of experiment, Taguchi design, optimization, analysis of variance, machining parameters, horizontal boring tool

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Authors: Sonali Agarwal

Abstract:

The investor perception about investment avenues is affected to a great degree by the current happenings, within the country, and on the global stage. The influencing events can range from government policies, bilateral trade agreements, election agendas, to changing exchange rates, appreciation and depreciation of currency, recessions, meltdowns, bankruptcies etc. The current research attempts to discover and unravel the effect of various macroeconomic variables (crude oil price, gold price, silver price and USD exchange rate) on the Indian mutual fund industry in general and the chosen funds (Axis Gold Fund, BSL Gold Fund, Kotak Gold Fund & SBI gold fund) in particular. Cointegration tests and Vector error correction equations prove that the chosen variables have strong effect on the NAVs (net asset values) of the mutual funds. However, the greatest influence is felt from the fund’s own past and current information and it is found that when an innovation of fund’s own lagged NAVs is given, variance caused is high that changes the current NAVs markedly. The study helps to highlight the interplay of macroeconomic variables and their repercussion on mutual fund industry.

Keywords: cointegration, Granger causality, impulse response, macroeconomic variables, mutual funds, stationarity, unit root test, variance decomposition, VECM

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Authors: A. C. Obosi, H. O. Osinowo, L. I. Okeke

Abstract:

Benign prostatic hyperplasia (BPH) is one among other prostate diseases with an increasing public health concern. The prevalence and increased psychological distress of BPH among men negatively impact on their health-related quality of life (HRQoL). Although several biomedical factors have been implicated in poor HRQoL among people with BPH, there is a dearth of research on the psychosocial factors predicting HRQoL among them especially in developing climes. This study, therefore, examined the psychosocial (knowledge, perceived stigma, depression, anxiety, perceived social support and illness acceptance) predictors of health-related quality of life among persons living with BPH in Ibadan, Nigeria. Biopsychosocial model and Health-related Quality of life guided this study which utilized ex-post facto design. Eighty-seven males living with BPH were purposively selected and actively participated in the study. Participants’ mean age was 61.77 ± 15.80 years. A standardized questionnaire comprising Socio-demographics and measures of health-related quality of life (α = 0.47); knowledge (α = 0.72); psychological distress (α = 0.95); perceived social support (α = 0.96) and Illness acceptance (α = 0.89) scales was utilized in the study. Data were content analysed, while bivariate correlation, hierarchical multiple regression and t-test for independent samples were computed at p < 0.05. Results revealed that 42.5% of the respondents reported poor HRQoL. Furthermore, age, length of illness, perceived stigma, depression, anxiety, knowledge, perceived social support and illness acceptance jointly predicted HRQoL significantly (R2=0.33, F(9,75)=4.05) and accounted for 33% variance in the total observed variance on HRQoL, while Illness acceptance (β=0.43), anxiety (β=-0.54), and perceived social support (β=0.16) had significant independent contributions to the observed variance on HRQoL. Illness acceptance, knowledge, perceived social support and psychological distress such as anxiety, depression and perceived stigma are important predictors of HRQoL. Therefore, it was recommended that urgent psychological intervention targeted at improving the quality of life of these persons be undertaken.

Keywords: benign prostatic hyperplasia, Health-related quality of life, prostate disorders, psychosocial factors

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Authors: Hong Li, Tingxian Li, Xudong Wang, Qinghuo Lin

Abstract:

Excess-iron (Fe) stresses involved in legume symbiotic nitrogen fixation are not understood. Our objectives were to investigate the tolerance of yardlong-bean plants to soil excess-Fe stress and antagonistic effects of organic amendments and rhizobial inoculants on plant root nodulation and stem ureide formation. The study was conducted in the tropical Hainan Island during 2012-2013. The soil was strongly acidic (pH 5.3±0.4) and highly variable in Fe concentrations(596±79 mg/kg). The treatments were arranged in a split-plot design with three blocks. The treatment effects were significant on root nodulation, stem ureide, amino acids, plant N/Fe accumulation and bean yields (P<0.05). The yardlong-bean stem allantoin, amino acids and nitrate concentrations and relative ureide % declined with high soil Fe concentrations (>300 mg/kg). It was concluded that the co-variance of excess Fe stress could inhibit legume symbiotic N fixation efficiency. Organic amendments and rhizobial inoculants could help improve crop tolerance to excess Fe stress.

Keywords: atmospheric N fixation, root nodulation, soil Fe co-variance, stem ureide, yardlong-bean plants

Procedia PDF Downloads 247

Authors: Nancy Ibrahim Abdalla, Abdelaziz Karamalla Gaiballa

Abstract:

Rangelands in semi-arid areas provide a good source for feeding huge numbers of animals and serving environmental, economic and social importance; therefore, these areas are considered economically very important for the pastoral sector in Sudan. This paper investigates the means of differentiating between different rangelands sites according to soil types using principal component analysis to assist in monitoring and assessment purposes. Three rangeland sites were identified in the study area as flat sandy sites, sand dune site, and hard clay site. Principal component analysis (PCA) was used to reduce the number of factors needed to distinguish between rangeland sites and produce a new set of data including the most useful spectral information to run satellite image processing. It was performed using selected types of data (two vegetation indices, topographic data and vegetation surface reflectance within the three bands of MODIS data). Analysis with PCA indicated that there is a relatively high correspondence between vegetation and soil of the total variance in the data set. The results showed that the use of the principal component analysis (PCA) with the selected variables showed a high difference, reflected in the variance and eigenvalues and it can be used for differentiation between different range sites.

Keywords: principal component analysis, PCA, rangeland sites, semi-arid areas, soil types

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Authors: Vimanyu Chadha, Ranganath M. Singari

Abstract:

Drilling composite materials is a frequently practiced machining process during assembling in various industries such as automotive and aerospace. However, drilling of glass fiber reinforced plastic (GFRP) composites is significantly affected by damage tendency of these materials under cutting forces such as thrust force and torque. The aim of this paper is to investigate the influence of the various cutting parameters such as cutting speed and feed rate; subsequently also to study the influence of number of layers on delamination produced while drilling a GFRP composite. A plan of experiments, based on Taguchi techniques, was instituted considering drilling with prefixed cutting parameters in a hand lay-up GFRP material. The damage induced associated with drilling GFRP composites were measured. Moreover, Analysis of Variance (ANOVA) was performed to obtain minimization of delamination influenced by drilling parameters and number layers. The optimum drilling factor combination was obtained by using the analysis of signal-to-noise ratio. The conclusion revealed that feed rate was the most influential factor on the delamination. The best results of the delamination were obtained with composites with a greater number of layers at lower cutting speeds and feed rates.

Keywords: analysis of variance, delamination, design optimization, drilling, glass fiber reinforced plastic composites, Taguchi method

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Authors: Ahmed F. Abdel Qader

Abstract:

Viral marketing has resulted in a lot of excitement recently as a novel technology in the field of marketing. The need of porting institutions to attract new customers for sporting products and services has increased, especially as many international and Arab clubs rely on them for most of their funding. These organizations, especially clubs, have outlets for selling their products and services; therefore, they are in need for new approaches that are related to modern communication and innovative distribution methods that can depend on the present audience in conveying e-ads to other users in light of the increase in social media users in the Arab world. This study aims at developing a marketing plan for sporting products and services through viral marketing of social media users. The researcher used the descriptive method. The sample consisted of 1991 social media users in 13 Arab countries. The questionnaire consisted of five themes and 42 items. Allan Dib 'one-page marketing plan' was used to develop the sporting products and services marketing plan. The study found that participants reported watching e-ads of sporting products and services that appeared during browsing social media pages; Facebook was the most used means for receiving ads about sporting products and services; sharing the product’s ad depends on the availability of incentives; purchasing sporting products and services takes place after a recommendation by a relative or a friend; and their evaluation of sporting products and services depends on the experiences of other people. The study recommends that the proposed plan should be used in marketing sporting products and services.

Keywords: viral marketing, sporting products, social media, Arab world

Procedia PDF Downloads 143

Authors: B. Marasović, S. Pivac, S. V. Vukasović

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Constructing a portfolio of investments is one of the most significant financial decisions facing individuals and institutions. In accordance with the modern portfolio theory maximization of return at minimal risk should be the investment goal of any successful investor. In addition, the costs incurred when setting up a new portfolio or rebalancing an existing portfolio must be included in any realistic analysis. In this paper rebalancing an investment portfolio in the presence of transaction costs on the Croatian capital market is analyzed. The model applied in the paper is an extension of the standard portfolio mean-variance optimization model in which transaction costs are incurred to rebalance an investment portfolio. This model allows different costs for different securities, and different costs for buying and selling. In order to find efficient portfolio, using this model, first, the solution of quadratic programming problem of similar size to the Markowitz model, and then the solution of a linear programming problem have to be found. Furthermore, in the paper the impact of transaction costs on the efficient frontier is investigated. Moreover, it is shown that global minimum variance portfolio on the efficient frontier always has the same level of the risk regardless of the amount of transaction costs. Although efficient frontier position depends of both transaction costs amount and initial portfolio it can be concluded that extreme right portfolio on the efficient frontier always contains only one stock with the highest expected return and the highest risk.

Keywords: Croatian capital market, Markowitz model, fractional quadratic programming, portfolio optimization, transaction costs

Procedia PDF Downloads 354

Authors: Matthew Buns

Abstract:

Training specificity is imperative for successful performance of the elite athlete. Virtual reality (VR) has been successfully applied to a broad range of training domains. However, to date there is little research investigating the use of VR for sport training. The purpose of this study was to address the question of whether virtual reality (VR) training can improve real world hockey shooting performance. Twenty four volunteers were recruited and randomly selected to complete the virtual training intervention or enter a control group with no training. Four primary types of data were collected: 1) participant’s experience with video games and hockey, 2) participant’s motivation toward video game use, 3) participants technical performance on real-world hockey, and 4) participant’s technical performance in virtual hockey. One-way multivariate analysis of variance (ANOVA) indicated that that the intervention group demonstrated significantly more real-world hockey accuracy [F(1,24) =15.43, p <.01, E.S. = 0.56] while shooting on goal than their control group counterparts [intervention M accuracy = 54.17%, SD=12.38, control M accuracy = 46.76%, SD=13.45]. One-way multivariate analysis of variance (MANOVA) repeated measures indicated significantly higher outcome scores on real-world accuracy (35.42% versus 54.17%; ES = 1.52) and velocity (51.10 mph versus 65.50 mph; ES=0.86) of hockey shooting on goal. This research supports the idea that virtual training is an effective tool for increasing real-world hockey skill.

Keywords: virtual training, hockey skills, video game, esports

Procedia PDF Downloads 121

Authors: Marcela de Oliveira, Guilherme Giacomini, Allan Felipe Fattori Alves, Ana Luiza Menegatti Pavan, Maria Eugenia Dela Rosa, Fernando Antonio Bacchim Neto, Diana Rodrigues de Pina

Abstract:

It is estimated that each year one death every 10 seconds (about 2 million deaths) in the world is attributed to tuberculosis (TB). Even after effective treatment, TB leaves sequelae such as, for example, pulmonary fibrosis, compromising the quality of life of patients. Evaluations of the aforementioned sequel are usually performed subjectively by radiology specialists. Subjective evaluation may indicate variations inter and intra observers. The examination of x-rays is the diagnostic imaging method most accomplished in the monitoring of patients diagnosed with TB and of least cost to the institution. The application of computational algorithms is of utmost importance to make a more objective quantification of pulmonary impairment in individuals with tuberculosis. The purpose of this research is the use of computer algorithms to quantify the pulmonary impairment pre and post-treatment of patients with pulmonary TB. The x-ray images of 10 patients with TB diagnosis confirmed by examination of sputum smears were studied. Initially the segmentation of the total lung area was performed (posteroanterior and lateral views) then targeted to the compromised region by pulmonary sequel. Through morphological operators and the application of signal noise tool, it was possible to determine the compromised lung volume. The largest difference found pre- and post-treatment was 85.85% and the smallest was 54.08%.

Keywords: algorithm, radiology, tuberculosis, x-rays exam

Procedia PDF Downloads 385

Authors: Taehyun Kim

Abstract:

As a result of rapid urbanization, energy demands for lighting, heating and cooling of households have been concentrated in metropolitan areas. The energy resources for housing in urban areas are dominantly fossil fuel whose uses contribute to increase cost of living and carbon dioxide (CO2) emission. To achieve environmentally and economically sustainable residential development, it is important to know how energy use and cost of living can be reduced by planning and design. The purpose of this study is to examine which type of building requires less energy for housing. To do so, carbon footprint (CF) quiz survey was employed which estimates the amount of carbon dioxide required to support households’ consumption of energy uses for housing. The housing carbon footprints (HCF) of 500 households of Seoul, Korea in summer and winter were estimated and compared in three major types of housing: single-family (detached), row-house and apartment. In addition, its differences of HCF were estimated between tower and flat type of apartment. The results of T-test and analysis of variance (ANOVA) provide statistical evidence that housing type is related to housing energy use. Average HCF of detached house was higher than other housing types. Between two types of apartment, tower type shows higher HCF than flat type in winter. These findings may provide new perspectives on CF application in sustainable architecture and urban design.

Keywords: analysis of variance, carbon footprint, energy use, housing type

Procedia PDF Downloads 463