Search results for: variance Shukla

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

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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

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Authors: Nancy Ibrahim Abdalla, Abdelaziz Karamalla Gaiballa

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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

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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: Satyavati Shukla, Lakhan V. Rathod, Mohan V. Khire

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Rapid urbanization changes the land use/land cover pattern of a developing region. Due to these land surface changes, stream flow of the rivers also changes. It is important to investigate the factors affecting hydrological characteristics of the river basin for better river basin management planning. This study is aimed to understand the effect of Land Use/Land Cover (LU/LC) changes on stream flow of Upper Bhima River basin which is highly stressed in terms of water resources. In this study, Upper Bhima River basin is divided into two adjacent sub-watersheds: Mula-Mutha (urbanized) sub-watershed and Bhima (non-urbanized) sub-watershed. First of all, LU/LC changes were estimated over 1980, 2002, and 2009 for both Mula-Mutha and Bhima sub-watersheds. Further, stream flow simulations were done using Soil and Water Assessment Tool (SWAT) for the streams draining both watersheds. Results revealed that stream flow was relatively higher for urbanized sub-watershed. Through Sensitivity Analysis it was observed that out of all the parameters used, base flow was the most sensitive parameter towards LU/LC changes.

Keywords: land use/land cover, remote sensing, stream flow, urbanization

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Authors: Ankita Shukla

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The promotion and support of breastfeeding is a global priority with benefits for maternal and infant health, especially in low income and middle-income countries where the probability of child survival is still very low. In India too it has been well established that breastfeeding increases the survival of the child. However, the breastfeeding levels are quite low in the country. Examining the socio-economic inequality in breastfeeding pattern can help to the causal pathways responsible for early breastfeeding termination. This paper tries to understand the socio-economic differential in breastfeeding patterns among Indian women. Data is used from nationally representative National Family Health Survey-3. Using Cox regression modelling techniques, the analysis found that the likelihood of having small breastfeeding duration increased with increasing household wealth status similarly education also has negative effect on breastfeeding duration. The considerable gender difference is also visible in India, likelihood of stopping breastfeeding was significantly higher among female children compared with male children. To understand the cultural factors or norms responsible for the early termination of breastfeeding more in depth/qualitative studies are needed.

Keywords: breastfeeding, India, socio-economic inequality, women education

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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

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Authors: Matthew Buns

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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

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Authors: Shipra Shukla, Gaurav Chaudhary, S. K. Tewari, Mahesh Pal, D. K. Upreti

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Cassia tora L. is widely distributed in tropical Asian countries, commonly known as sickle pod. Various parts of the plant are reported for their medicinal value due to presence of anthraquinones, phenolic compounds, emodin, β-sitosterol, and chrysophanol. Therefore a sensitive analytical procedure using UHPLC-ESI-MS/MS was developed and validated for simultaneous quantification of five phenolic compounds in leaf, stem and root extracts of Cassia tora. Rapid chromatographic separation of compounds was achieved on Acquity UHPLC BEH C18 column (50 mm×2.1 mm id, 1.7µm) column in 2.5 min. Quantification was carried out using negative electrospray ionization in multiple-reaction monitoring mode. The method was validated as per ICH guidelines and showed good linearity (r2 ≥ 0.9985) over the concentration range of 0.5-200 ng/mL. The intra- and inter-day precisions and accuracy were within RSDs ≤ 1.93% and ≤ 1.90%, respectively. The developed method was applied to investigate variation of five phenolic compounds in the three geographical collections. Results indicated significant variation among analyzed samples collected from different locations in India.

Keywords: Cassia tora, phenolic compounds, quantification, UHPLC-ESI-MS/MS

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Authors: Yogesh Shukla

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Many attempts have been made to study temperature distribution problem in human tissues under normal environmental and physiological conditions at constant arterial blood temperature. But very few attempts have been made to investigate temperature distribution in human tissues under different arterial blood temperature. In view of above, a finite element model has been developed to unsteady temperature distribution in dermal region in human body. The model has been developed for one dimension unsteady state case. The variation in parameters like thermal conductivity, blood mass flow and metabolic activity with respect to position and time has been incorporated in the model. Appropriate boundary conditions have been framed. The central difference approach has been used in space variable and trapezoidal rule has been employed a long time variable. Numerical results have been obtained to study relationship among temperature and time.

Keywords: rate of metabolism, blood mass flow rate, thermal conductivity, heat generation, finite element method

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Authors: Taehyun Kim

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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

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Authors: Sandeep Santosh, O. P. Sahu

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In this paper, performance comparison of wideband covariance matrix sparse representation (W-CMSR) method with other existing wideband Direction of Arrival (DOA) estimation methods has been made.W-CMSR relies less on a priori information of the incident signal number than the ordinary subspace based methods.Consider the perturbation free covariance matrix of the wideband array output. The diagonal covariance elements are contaminated by unknown noise variance. The covariance matrix of array output is conjugate symmetric i.e its upper right triangular elements can be represented by lower left triangular ones.As the main diagonal elements are contaminated by unknown noise variance,slide over them and align the lower left triangular elements column by column to obtain a measurement vector.Simulation results for W-CMSR are compared with simulation results of other wideband DOA estimation methods like Coherent signal subspace method (CSSM), Capon, l1-SVD, and JLZA-DOA. W-CMSR separate two signals very clearly and CSSM, Capon, L1-SVD and JLZA-DOA fail to separate two signals clearly and an amount of pseudo peaks exist in the spectrum of L1-SVD.

Keywords: W-CMSR, wideband direction of arrival (DOA), covariance matrix, electrical and computer engineering

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Authors: Nelson Bii, Christopher Ouma, John Odhiambo

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Non-response is a potential source of errors in sample surveys. It introduces bias and large variance in the estimation of finite population parameters. Regression models have been recognized as one of the techniques of reducing bias and variance due to random non-response using auxiliary data. In this study, it is assumed that random non-response occurs in the survey variable in the second stage of cluster sampling, assuming full auxiliary information is available throughout. Auxiliary information is used at the estimation stage via a regression model to address the problem of random non-response. In particular, the auxiliary information is used via an improved Nadaraya-Watson kernel regression technique to compensate for random non-response. The asymptotic bias and mean squared error of the estimator proposed are derived. Besides, a simulation study conducted indicates that the proposed estimator has smaller values of the bias and smaller mean squared error values compared to existing estimators of finite population mean. The proposed estimator is also shown to have tighter confidence interval lengths at a 95% coverage rate. The results obtained in this study are useful, for instance, in choosing efficient estimators of the finite population mean in demographic sample surveys.

Keywords: mean squared error, random non-response, two-stage cluster sampling, confidence interval lengths

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Authors: Prasenjit Singha, Ajay Kumar Shukla

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To produce high-quality steel in larger volumes, dynamic control of composition and temperature throughout the process is essential. In this paper, we developed a mass transfer model based on thermodynamics to simulate the ladle metallurgy steel-making process using FactSage and its macro facility. The overall heat and mass transfer processes consist of one equilibrium chamber, two non-equilibrium chambers, and one adiabatic reactor. The flow of material, as well as heat transfer, occurs across four interconnected unit chambers and a reactor. We used the macro programming facility of FactSage™ software to understand the thermochemical model of the secondary steel making process. In our model, we varied the oxygen content during the process and studied their effect on the composition of the final hot metal and slag. The model has been validated with respect to the plant data for the steel composition, which is similar to the ladle metallurgy steel-making process in the industry. The resulting composition profile serves as a guiding tool to optimize the process of ladle metallurgy in steel-making industries.

Keywords: desulphurization, degassing, factsage, reactor

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Authors: Amin Amani, Masomeh Reihany Shirvan, Mahla Nabizadeh Mashizi, Mohadese Khoshtinat, Mohammad Elyas Ansarinia

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The purpose of this study is the relationship between a healthy lifestyle and risky behavior in physical education students of Bojnourd schools. The study sample consisted of teenagers studying in second and third grade of Bojnourd's high schools. According to level sampling, 604 students studying in the second grade, and 600 students studying in third grade were tested from physical education schools in Bojnourd. For sample selection, populations were divided into 4 area including north, East, West and South. Then according to the number of students of each area, sample size of each level was determined. Two questionnaires were used to collect data in this study which were consisted of three parts: The demographic data, Iranian teenagers' risk taking (IARS) and prevention methods with emphasize on the importance of family role were examined. The Central and dispersion indices, such as standard deviation, multiple variance analysis, and multivariate regression analysis were used. Results showed that the observed F is significant (P ≤ 0.01) and 21% of variance related to risky behavior is explained by the lack of awareness. Given the significance of the regression, the coefficients of risky behavior in teenagers in prediction equation showed that each of teenagers' risky behavior can have an impact on healthy lifestyle.

Keywords: healthy lifestyle, high-risk behavior, students, physical education

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Authors: M. Sakthivel, A. Devaki, D. Balasubramanyam, P. Kumarasamy, A. Raja, R. Anilkumar, H. Gopi

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The genetic parameters of growth traits in the New Zealand White rabbits maintained at Sheep Breeding and Research Station, Sandynallah, The Nilgiris, India were estimated by partitioning the variance and covariance components. The (co)variance components of body weights at weaning (W42), post-weaning (W70) and marketing (W135) age and growth efficiency traits viz., average daily gain (ADG), relative growth rate (RGR) and Kleiber ratio (KR) estimated on a daily basis at different age intervals (1=42 to 70 days; 2=70 to 135 days and 3=42 to 135 days) from weaning to marketing were estimated by restricted maximum likelihood, fitting six animal models with various combinations of direct and maternal effects. Data were collected over a period of 15 years (1998 to 2012). A log-likelihood ratio test was used to select the most appropriate univariate model for each trait, which was subsequently used in bivariate analysis. Heritability estimates for W42, W70 and W135 were 0.42 ± 0.07, 0.40 ± 0.08 and 0.27 ± 0.07, respectively. Heritability estimates of growth efficiency traits were moderate to high (0.18 to 0.42). Of the total phenotypic variation, maternal genetic effect contributed 14 to 32% for early body weight traits (W42 and W70) and ADG1. The contribution of maternal permanent environmental effect varied from 6 to 18% for W42 and for all the growth efficiency traits except for KR2. Maternal permanent environmental effect on most of the growth efficiency traits was a carryover effect of maternal care during weaning. Direct maternal genetic correlations, for the traits in which maternal genetic effect was significant, were moderate to high in magnitude and negative in direction. Maternal effect declined as the age of the animal increased. The estimates of total heritability and maternal across year repeatability for growth traits were moderate and an optimum rate of genetic progress seems possible in the herd by mass selection. The estimates of genetic and phenotypic correlations among body weight traits were moderate to high and positive; among growth efficiency traits were low to high with varying directions; between body weights and growth efficiency traits were very low to high in magnitude and mostly negative in direction. Moderate to high heritability and higher genetic correlation in body weight traits promise good scope for genetic improvement provided measures are taken to keep the inbreeding at the lowest level.

Keywords: genetic parameters, growth traits, maternal effects, rabbit genetics

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Authors: Prateek Guleria, Shubham Sharma, Rakesh Kumar Shukla, Harshit Sharma

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Performance measurement of small and medium-sized businesses is the primary need for all companies to survive and thrive in a dynamic global company. A structured and systematic, integrated organization increases employee reliability, sustainability, and loyalty. This paper is a case study of a gear manufacturing industry that was facing the problem of rejection due to dents and damages in gear. The DMAIC cycle, along with different tools used in the research work includes SIPOC (Supply, Input, Process, Output, Control) Pareto analysis, Root & Cause analysis, and FMEA (Failure Mode and Effect Analysis). The six-sigma level was improved from 4.06 to 3.46, and the rejection rate was reduced from 7.44% to 1.56%. These findings highlighted the influence of a Lean Six Sigma module in the gear manufacturing unit, which has already increased operational quality and continuity to increase market success and meet customer expectations. According to the findings, applying lean six sigma tools will result in increased productivity. The results could assist businesses in deciding the quality tools that were likely to improve efficiency, competitiveness, and expense.

Keywords: six sigma, DMAIC, SIPOC, failure mode, effect analysis

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Authors: Khandoker Akib Mohammad

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While analyzing time-to-event data, it is possible that a certain fraction of subjects will never experience the event of interest, and they are said to be cured. When this feature of survival models is taken into account, the models are commonly referred to as cure models. In the presence of covariates, the conditional survival function of the population can be modelled by using the cure model, which depends on the probability of being uncured (incidence) and the conditional survival function of the uncured subjects (latency), and a combination of logistic regression and Cox proportional hazards (PH) regression is used to model the incidence and latency respectively. In this paper, we have shown the asymptotic normality of the profile likelihood estimator via asymptotic expansion of the profile likelihood and obtain the explicit form of the variance estimator with an implicit function in the profile likelihood. We have also shown the efficient score function based on projection theory and the profile likelihood score function are equal. Our contribution in this paper is that we have expressed the efficient information matrix as the variance of the profile likelihood score function. A simulation study suggests that the estimated standard errors from bootstrap samples (SMCURE package) and the profile likelihood score function (our approach) are providing similar and comparable results. The numerical result of our proposed method is also shown by using the melanoma data from SMCURE R-package, and we compare the results with the output obtained from the SMCURE package.

Keywords: Cox PH model, cure model, efficient score function, EM algorithm, implicit function, profile likelihood

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Authors: Tahmina Sultana, Yasser Hassan

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Vehicle technologies rapidly evolving due to their multifaceted advantages. Adapted different vehicle technologies like connectivity and automation on the same roads with conventional vehicles controlled by human drivers may increase speed disparity in mixed vehicle technologies. Identifying relationships between speed distribution measures of different vehicles and road geometry can be an indicator of speed disparity in mixed technologies. Previous studies proved that speed disparity measures and traffic accidents are inextricably related. Horizontal curves from three geographic areas were selected based on relevant criteria, and speed data were collected at the midpoint of the preceding tangent and starting, ending, and middle point of the curve. Multiple linear mixed effect models (LME) were developed using the instantaneous speed measures representing the speed of vehicles at different points of horizontal curves to recognize relationships between speed variance (standard deviation) and road geometry. A simulation-based framework (Monte Carlo) was introduced to check the speed disparity on horizontal curves in mixed vehicle technologies when consideration is given to the interactions among connected vehicles (CVs), autonomous vehicles (AVs), and non-connected vehicles (NCVs) on horizontal curves. The Monte Carlo method was used in the simulation to randomly sample values for the various parameters from their respective distributions. Theresults show that NCVs had higher speed variation than CVs and AVs. In addition, AVs and CVs contributed to reduce speed disparity in the mixed vehicle technologies in any penetration rates.

Keywords: autonomous vehicles, connected vehicles, non-connected vehicles, speed variance

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Authors: Deepshikha Shukla, C. H. Solanki, Mayank K. Desai

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Amongst all the natural hazards, earthquakes have the potential for causing the greatest damages. Since the earthquake forces are random in nature and unpredictable, the quantification of the hazards becomes important in order to assess the hazards. The time and place of a future earthquake are both uncertain. Since earthquakes can neither be prevented nor be predicted, engineers have to design and construct in such a way, that the damage to life and property are minimized. Seismic hazard analysis plays an important role in earthquake design structures by providing a rational value of input parameter. In this paper, both mathematical, as well as computational methods adopted by researchers globally in the past five years, will be discussed. Some mathematical approaches involving the concepts of Poisson’s ratio, Convex Set Theory, Empirical Green’s Function, Bayesian probability estimation applied for seismic hazard and FOSM (first-order second-moment) algorithm methods will be discussed. Computational approaches and numerical model SSIFiBo developed in MATLAB to study dynamic soil-structure interaction problem is discussed in this paper. The GIS-based tool will also be discussed which is predominantly used in the assessment of seismic hazards.

Keywords: computational methods, MATLAB, seismic hazard, seismic measurements

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Authors: Roya Maqami, Kaveh Qaderi Bagajan, Mohammad Mahdi Yousefi, Saeed Moradi

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The purpose of this study is to investigate the efficacy of solution-focused group therapy on improving the depressed mothers of child abuser families. This study was carried out in the form of a semi-pilot, pre-test and post-test on two groups (experimental and control). Subjects include all mothers and their children that are the members of Shush and Naser Khosro child home. Beck Depression Inventory and Child Trauma Questionnaire were used to collect data. First, child abuse questionnaire was completed by children, Then Beck Depression Inventory was completed by their mothers that 22 of them were recognized as depressed and randomly divided in two groups of experimental and control. After applying pre-test for both of these groups, the intervention of solution- focused group therapy was performed in five sessions on experimental group. Finally, post-test was applied on both groups and subsequently in a month, follow-up test was performed. T-test, multivariate variance, and repeated measurement analysis of variance were used to analyze the data. According to the findings, it can be concluded that this therapy leads to the improvement of depressed mother's mood. As a result, the intervention of solution-focused group therapy is useful in order to improve the depressing mood of mothers of child abuser families.

Keywords: child abuse, depressed mothers, child abuser families, solution focused group therapy

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Authors: Adem Peker, Yüksel Eroğlu, İsmail Ay

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As the information and communication technologies have become embedded in everyday life of adolescents, both their possible benefits and risks to adolescents are being identified. The information and communication technologies provide opportunities for adolescents to connect with peers and to access to information. However, as with other social connections, users of information and communication devices have the potential to meet and interact with in harmful ways. One emerging example of such interaction is cyber bullying. Cyber bullying occurs when someone uses the information and communication technologies to harass or embarrass another person. Cyber bullying can take the form of malicious text messages and e-mails, spreading rumours, and excluding people from online groups. Cyber bullying has been linked to psychological problems for cyber bullies and victims. Therefore, it is important to determine how internet addiction contributes to cyber bullying. Building on this question, this study takes a closer look at the relationship between internet addiction and cyber bullying. For this purpose, in this study, based on descriptive relational model, it was hypothesized that loss of control, excessive desire to stay online, and negativity in social relationships, which are dimensions of internet addiction, would be associated positively with cyber bullying and victimization. Participants were 383 high school students (176 girls and 207 boys; mean age, 15.7 years). Internet addiction was measured by using Internet Addiction Scale. The Cyber Victim and Bullying Scale was utilized to measure cyber bullying and victimization. The scales were administered to the students in groups in the classrooms. In this study, stepwise regression analyses were utilized to examine the relationships between dimensions of internet addiction and cyber bullying and victimization. Before applying stepwise regression analysis, assumptions of regression were verified. According to stepwise regression analysis, cyber bullying was predicted by loss of control (β=.26, p<.001) and negativity in social relationships (β=.13, p<.001). These variables accounted for 9 % of the total variance, with the loss of control explaining the higher percentage (8 %). On the other hand, cyber victimization was predicted by loss of control (β=.19, p<.001) and negativity in social relationships (β=.12, p<.001). These variables altogether accounted for 8 % of the variance in cyber victimization, with the best predictor loss of control (7 % of the total variance). The results of this study demonstrated that, as expected, loss of control and negativity in social relationships predicted cyber bullying and victimization positively. However, excessive desire to stay online did not emerge a significant predictor of both cyberbullying and victimization. Consequently, this study would enhance our understanding of the predictors of cyber bullying and victimization since the results proposed that internet addiction is related with cyber bullying and victimization.

Keywords: cyber bullying, internet addiction, adolescents, regression

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Authors: Pradeep Kumar, Shalinee Shukla

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Pavement plays a vital role in the socio-economic development of a country. Bituminous roads construction with conventional paving grade bitumen obtained from hot mix plant creates pollution and involves emission of greenhouse gases, also the construction of pavements at very high temperature is not feasible or desirable for high rainfall and snowfall areas. This problem of overheating can be eliminated by the construction of pavements with the usage of emulsified cold mixes which will eliminate emissions and help in the reduction of fuel requirement at mixing plant, which leads to energy conservation. Cold mix is a mixture of unheated aggregate and emulsion or cutback and filler. The primary objective of this research is to assess the volumetric mix design parameters of recycled aggregates with cold mixing technology and also to assess the impact of additives on volumetric mix characteristics. In this present study, bituminous pavement materials are reclaimed using cold mix technology, and Marshall specimens are prepared with the help of slow setting type 2 (SS-2) cationic bitumen emulsion as a binder for recycled aggregates. This technique of road construction is more environmentally friendly and can be done in adverse weather conditions.

Keywords: cold mixes, bitumen emulsion, recycled aggregates, volumetric properties

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Authors: Olakanmi Oladayo Olufemi, Bamifewe Olusegun James, Badmus Yaya Opeyemi, Adegoke Kayode

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The wireless sensor network (WSN) has made a significant contribution to the emergence of various intelligent services or cloud-based applications. Most of the time, these data are stored on a cloud platform for efficient management and sharing among different services or users. However, the sensitivity of the data makes them prone to various confidentiality and performance-related attacks during and after harvesting. Various security schemes have been developed to ensure the integrity and confidentiality of the WSNs' data. However, their specificity towards particular attacks and the resource constraint and heterogeneity of WSNs make most of these schemes imperfect. In this paper, we propose a secure variance-aware routing and authentication scheme with two-tier verification to collect, share, and manage WSN data. The scheme is capable of classifying WSN into different subnets, detecting any attempt of wormhole and black hole attack during harvesting, and enforcing access control on the harvested data stored in the cloud. The results of the analysis showed that the proposed scheme has more security functionalities than other related schemes, solves most of the WSNs and cloud security issues, prevents wormhole and black hole attacks, identifies the attackers during data harvesting, and enforces access control on the harvested data stored in the cloud at low computational, storage, and communication overheads.

Keywords: data block, heterogeneous IoT network, data harvesting, wormhole attack, blackhole attack access control

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Authors: Wipada Chaiwchan

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This research aims to study behaviors in using social networks of Corporate personnel of Suan Sunandha Rajabhat University. The sample used in the study were two groups: 1) Academic Officer 70 persons and 2) Operation Officer 143 persons were used in this study. The tools in this research consisted of questionnaire which the data were analyzed by using percentage, average (X) and Standard deviation (S.D.) and Independent Sample T-Test to test the difference between the mean values obtained from two independent samples, and One-way anova to analysis of variance, and Multiple comparisons to test that the average pair of different methods by Fisher’s Least Significant Different (LSD). The study result found that the most of corporate personnel have purpose in using social network to information awareness aspect was knowledge and online conference with social media. By using the average more than 3 hours per day in everyday. Using time in working in one day and there are computers connected to the Internet at home, by using the communication in the operational processes. Behaviors using social networks in relation to gender, age, job title, department, and type of personnel. Hypothesis testing, and analysis of variance for the effects of this analysis is divided into three aspects: The use of online social networks, the attitude of the users and the security analysis has found that Corporate Personnel of Suan Sunandha Rajabhat University. Overall and specifically at the high level, and considering each item found all at a high level. By sorting of the social network (X=3.22), The attitude of the users (X= 3.06) and the security (X= 3.11). The overall behaviors using of each side (X=3.11).

Keywords: social network, behaviors, social media, computer information systems

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Authors: Hailekiros Tadesse Tekle, Yemane Tsehaye, Fetien Abay

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Barley (Hordeum vulgare L.) is one of the most important cereal crops in the world, grown for the poor farmers in Tigray with low yield production. The purpose of this research was to estimate the performance of 166 barley genotypes against the quantitative traits with detailed analysis of the variance component, heritability, genetic advance, and genetic usefulness parameters. The finding of ANOVA was highly significant variation (p ≤ 0:01) for all the genotypes. We found significant differences in coefficient of variance (CV of 15%) for 5 traits out of the 12 quantitative traits. The topmost broad sense heritability (H2) was recorded for seeds per spike (98.8%), followed by thousand seed weight (96.5%) with 79.16% and 56.25%, respectively, of GAM. The traits with H2 ≥ 60% and GA/GAM ≥ 20% suggested the least influenced by the environment, governed by the additive genes and direct selection for improvement of such beneficial traits for the studied genotypes. Hence, the 20 outstanding recombinant inbred lines (RIL) barley genotypes performing early maturity, high yield, and 1000 seed weight traits simultaneously were the top ranked group barley genotypes out of the 166 genotypes. These are; G5, G25, G33, G118, G36, G123, G28, G34, G14, G10, G3, G13, G11, G32, G8, G39, G23, G30, G37, and G26. They were early in maturity, high TSW and GYP (TSW ≥ 55 g, GYP ≥ 15.22 g/plant, and DTM below 106 days). In general, the 166 genotypes were classified as high (group 1), medium (group 2), and low yield production (group 3) genotypes in terms of yield and yield component trait analysis by clustering; and genotype parameter analysis such as the heritability, genetic advance, and genetic usefulness traits in this investigation.

Keywords: barley, clustering, genetic advance, heritability, usefulness, variability, yield

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Authors: Shriya Shukla, Lachin Fernando

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Pneumonia, a leading cause of mortality in young children globally, presents significant diagnostic challenges, particularly in resource-limited settings. This study presents an approach to diagnosing pediatric pneumonia using Chest X-Ray (CXR) images, employing a lightweight MobileNetV2 model enhanced with synthetic data augmentation. Addressing the challenge of dataset scarcity and imbalance, the study used a Variational Autoencoder-Generative Adversarial Network (VAE-GAN) to generate synthetic CXR images, improving the representation of normal cases in the pediatric dataset. This approach not only addresses the issues of data imbalance and scarcity prevalent in medical imaging but also provides a more accessible and reliable diagnostic tool for early pneumonia detection. The augmented data improved the model’s accuracy and generalization, achieving an overall accuracy of 95% in pneumonia detection. These findings highlight the efficacy of the MobileNetV2 model, offering a computationally efficient yet robust solution well-suited for resource-constrained environments such as mobile health applications. This study demonstrates the potential of synthetic data augmentation in enhancing medical image analysis for critical conditions like pediatric pneumonia.

Keywords: pneumonia, MobileNetV2, image classification, GAN, VAE, deep learning

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Authors: Kalu Ram Meena, Aditi Kar Gangopadhyay, Satrajit Mandal

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Two normal populations with different means and same variance are considered, where the variances are known. The population with the smaller sample mean is selected. Various estimators are constructed for the mean of the selected normal population. Finally, they are compared with respect to the bias and MSE risks by the method of Monte-Carlo simulation and their performances are analysed with the help of graphs.

Keywords: estimation after selection, Brewster-Zidek technique, estimators, selected populations

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Authors: J. B. Frisch, D. Evandiloff, P. Martin, N. Ouizille, F. Pires

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Smart Beta strategies intend to be an asset management revolution with reference to classical cap-weighted indices. Indeed, these strategies allow a better control on portfolios risk factors and an optimized asset allocation by taking into account specific risks or wishes to generate alpha by outperforming indices called 'Beta'. Among many strategies independently used, this paper focuses on four of them: Minimum Variance Portfolio, Equal Risk Contribution Portfolio, Maximum Diversification Portfolio, and Equal-Weighted Portfolio. Their efficiency has been proven under constraints like momentum or market phenomenon, suggesting a reconsideration of cap-weighting.
 To further increase strategy return efficiency, it is proposed here to compare their strengths and weaknesses inside time intervals corresponding to specific identifiable market phases, in order to define adapted strategies depending on pre-specified situations. 
Results are presented as performance curves from different combinations compared to a benchmark. If a combination outperforms the applicable benchmark in well-defined actual market conditions, it will be preferred. It is mainly shown that such investment 'rules', based on both historical data and evolution of Smart Beta strategies, and implemented according to available specific market data, are providing very interesting optimal results with higher return performance and lower risk.
 Such combinations have not been fully exploited yet and justify present approach aimed at identifying relevant elements characterizing them.

Keywords: smart beta, minimum variance portfolio, equal risk contribution portfolio, maximum diversification portfolio, equal weighted portfolio, combinations

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Authors: Phoutsathaphone Sibounheuang, Phayom Sookaneknun Olson, Chanuttha Ploylearmsang, Santiparp Sookaneknun, Chanthanom Manithip

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Patient satisfaction is an outcome that can be measured and used to improve diabetes care and management. There are limited instruments for assessing patient satisfaction covering the whole process of diabetes management. In this study, the questionnaire was developed with items pooled from a systematic review of qualitative studies of patients’ and healthcare providers’ perspectives in diabetes management. The questionnaire consists of 11 domains with 45 items. The Thai version was translated to Lao and then checked by back-translating it into Thai. We tested the questionnaire on 150 diabetes patients in Thailand and 150 in Lao People Democratic Republic (PDR). Validity was performed by factor analysis and Pearson correlation. Internal consistency reliability was estimated by calculating Cronbach’s alpha. The study was approved by the Mahasarakham University Ethics Committee, and the National Ethics Committee for Health Research, Lao PDR. The Thai and Lao versions showed the construct validity by principal component analysis. This consisted of 11 domains which account for 71.23% of the variance (Thai version) and 71.66% of the variance (Lao version) in the total patient satisfaction scores. The Kaiser-Meyer-Olkin (KMO) measures were 0.85 for the Thai version and 0.75 for the Lao version. The Bartlett tests of sphericity of both versions were significant (p < 0.001). The factor loadings of all items in both versions were > 0.40. The convergent validity of the Thai and Lao versions was 93.63% and 79.54% respectively. The discriminant validity for the Thai and Lao versions was 92.68% and 88.68% respectively. Cronbach’s alpha was 0.95 in both versions. The Patient Satisfaction Questionnaire (PSQ) in both versions had acceptable properties. This study has yielded evidence supporting the validity and reliability of both versions.

Keywords: construct validity, diabetes management, patient satisfaction, questionnaire development, reliability

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Authors: Anurakti Shukla, Sudhakar Srivastava

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Cyanobacteria are known for rapid growth rates, high biomass, and the ability to accumulate potentially toxic elements and contaminants. The present work was planned to develop a low-cost, feasible prototype, CyanoClean, for the growth of a cyanobacterial consortium for the removal of arsenic (As) from water. The cyanobacterial consortium consisting of Oscillatoria, Phormidiumand Gloeotrichiawas used, and the conditions for optimal growth of the consortium were standardized. A pH of 7.6, initial cyanobacterial biomass of 10 g/L, and arsenite [As(III)] and arsenate [As(V)] concentration of 400 μΜand 600 μM, respectively, were found to be suitable. The CyanoClean prototype was designed with acrylic sheet and had arrangements for optimal cyanobacterial growth in natural sunlight and also in artificial light. The As removal experiments in concentration- and duration-dependent manner demonstrated removal of up to 39-69% and 9-33% As respectively from As(III) and As(V)-contaminated water. In field testing of CyanoClean, natural As-contaminated groundwater was used, and As reduction was monitored when a flow rate of 3 L/h was maintained. In a field experiment, As concentration in groundwater was found to reduce from 102.43 μg L⁻¹ to <10 μg L⁻¹ after 6 h in natural sunlight. However, in shaded conditions under artificial light, the same result was achieved after 9 h. The CyanoClean prototype is of simple design and can be easily up-scaled for application at a small- to medium-size land and shall be affordable even for a low- to middle-income group farmer.

Keywords: cyanoclean, gloeotrichia, oscillatoria, phormidium, phycoremediation

Procedia PDF Downloads 104