Search results for: the soil variables

Authors: Yagmur Soylu, Emir Ozeren, Erol Esen, Digdem M. Siyez, Ozlem Belkis, Ezgi Burc, Gülce Demirgurz

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The aim of the study is to determine the predictive power of personal growth initiative, socio-demographic variables (such as sex, grade, and working condition) on career adaptability and optimism of bachelor students in Dokuz Eylul University in Turkey. According to career construction theory, career adaptability is viewed as a psychosocial construct, which refers to an individual’s resources for dealing with current and expected tasks, transitions and traumas in their occupational roles. Career optimism is defined as positive results for future career development of individuals in the expectation that it will achieve or to put the emphasis on the positive aspects of the event and feel comfortable about the career planning process. Personal Growth Initiative (PGI) is defined as being proactive about one’s personal development. Additionally, personal growth is defined as the active and intentional engagement in the process of personal. A study conducted on college students revealed that individuals with high self-development orientation make more effort to discover the requirements of the profession and workspaces than individuals with low levels of personal development orientation. University life is a period that social relations and the importance of academic activities are increased, the students make efforts to progress through their career paths and it is also an environment that offers opportunities to students for their self-realization. For these reasons, personal growth initiative is potentially an important variable which has a key role for an individual during the transition phase from university to the working life. Based on the review of the literature, it is expected that individual’s personal growth initiative, sex, grade, and working condition would significantly predict one’s career adaptability. In the relevant literature, it can be seen that there are relatively few studies available on the career adaptability and optimism of university students. Most of the existing studies have been carried out with limited respondents. In this study, the authors aim to conduct a comprehensive research with a large representative sample of bachelor students in Dokuz Eylul University, Izmir, Turkey. By now, personal growth initiative and career development constructs have been predominantly discussed in western contexts where individualistic tendencies are likely to be seen. Thus, the examination of the same relationship within the context of Turkey where collectivistic cultural characteristics can be more observed is expected to offer valuable insights and provide an important contribution to the literature. The participants in this study were comprised of 1500 undergraduate students being included from thirteen faculties in Dokuz Eylul University. Stratified and random sampling methods were adopted for the selection of the participants. The Personal Growth Initiative Scale-II and Career Futures Inventory were used as the major measurement tools. In data analysis stage, several statistical analysis concerning the regression analysis, one-way ANOVA and t-test will be conducted to reveal the relationships of the constructs under investigation. At the end of this project, we will be able to determine the level of career adaptability and optimism of university students at varying degrees so that a fertile ground is likely to be created to carry out several intervention techniques to make a contribution to an emergence of a healthier and more productive youth generation in psycho-social sense.

Keywords: career optimism, career adaptability, personal growth initiative, university students

Procedia PDF Downloads 405

Authors: Hwayeon Song

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The long-term purpose of research and development (R&D) programs is to strengthen national competitiveness by developing new knowledge and technologies. Thus, it is important to determine a proper budget for government programs to maintain the vigor of R&D when the total funding is tight due to the national deficit. In this regard, a ripple effect analysis for the budgetary changes in R&D programs is necessary as well as an investigation of the current status. This study proposes a new approach using Artificial Neural Networks (ANN) for both tasks. It particularly focuses on R&D programs related to Construction and Transportation (C&T) technology in Korea. First, key factors in C&T technology are explored to draw impact indicators in three areas: economy, society, and science and technology (S&T). Simultaneously, ANN is employed to evaluate the relationship between data variables. From this process, four major components in R&D including research personnel, expenses, management, and equipment are assessed. Then the ripple effect analysis is performed to see the changes in the hypothetical future by modifying current data. Any research findings can offer an alternative strategy about R&D programs as well as a new analysis tool.

Keywords: Artificial Neural Networks, construction and transportation technology, Government Research and Development, Ripple Effect

Procedia PDF Downloads 228

Authors: Abhijith Asok

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This paper presents a generalized approach for the simple linear data transformation, Y=bX, through an integration of multidimensional coordinate geometry, vector space theory and polygonal geometry. The scaling is performed by adding an additional ’Dummy Dimension’ to the n-dimensional data, which helps plot two dimensional component-wise straight lines on pairs of dimensions. The end result is a set of scaled extensions of observations in any of the 2n spatial divisions, where n is the total number of applicable dimensions/dataset variables, created by shifting the n-dimensional plane along the ’Dummy Axis’. The derived scaling factor was found to be dependent on the coordinates of the common point of origin for diverging straight lines and the plane of extension, chosen on and perpendicular to the ’Dummy Axis’, respectively. This result indicates the geometrical interpretation of a linear data transformation and hence, opportunities for a more informed choice of the factor ’b’, based on a better choice of these coordinate values. The paper follows on to identify the effect of this transformation on certain popular distance metrics, wherein for many, the distance metric retained the same scaling factor as that of the features.

Keywords: data transformation, dummy dimension, linear transformation, scaling

Procedia PDF Downloads 286

Authors: Amin Mojiri, Hamidi Abdul Aziz

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Leachate is created while water penetrates through the waste in a landfill, carrying some forms of pollutants. In literature, for treatment of wastewater and leachate, different ways of biological treatment were used. Sequencing batch reactor (SBR) is a kind of biological treatment. This study investigated the co-treatment of landfill leachate and domestic waste water by SBR and powdered activated carbon augmented (PAC) SBR process. The response surface methodology (RSM) and central composite design (CCD) were employed. The independent variables were aeration rate (L/min), contact time (h), and the ratio of leachate to wastewater mixture (%; v/v)). To perform an adequate analysis of the aerobic process, three dependent parameters, i.e. COD, color, and ammonia-nitrogen (NH3-N or NH4-N) were measured as responses. The findings of the study indicated that the PAC-SBR showed a higher performance in elimination of certain pollutants, in comparison with SBR. With the optimal conditions of aeration rate (0.6 L/min), leachate to waste water ratio (20%), and contact time (10.8 h) for the PAC-SBR, the removal efficiencies for color, NH3-N, and COD were 72.8%, 98.5%, and 65.2%, respectively.

Keywords: co-treatment, landfill Leachate, wastewater, sequencing batch reactor, activate carbon

Procedia PDF Downloads 454

Authors: Mohammed Adamu Musa, Shehu Saminu Babba

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The technological trend towards waste utilization and cost reduction in industrial processing has attracted use of Rice Husk as a value added material. Both rice husk (RH) and Rice Husk Ash (RHA) has been found suitable for wide range of domestic as well as industrial applications. Therefore, the purpose of this research is to produce high grade sodium silicate from rice husk ash by considering the effect of temperature and time of heating as the process variables. The experiment was performed by heating the rice husk at temperatures 500 °C, 600 °C, 700 °C and 800 °C and time 60min, 90min, 120min and 150min were used to obtain the ash. 1.0M of aqueous sodium hydroxide solution was used to dissolve the silicate from the ash, which contained crude sodium silicate. In addition, the ash was neutralized by adding 5M of HCL until the pH reached 3.5 to give silica gel. At 6000C and 120mins, 94.23% silica was obtained from the RHA. At higher temperatures (700 °C and 800 °C) the percentage yield of silica reduced due to surface melting and carbon fixation in the lattice caused by presence of potassium. For this research, 600 °C is considered to be the optimum temperature for silica production from RHA. Silica produced from RHA can generate aggregate value and can be used in areas such as pulp and paper, plastic and rubber reinforcement industries.

Keywords: burning, rice husk, rice husk ash, silica, silica gel, temperature

Procedia PDF Downloads 221

Authors: Devatha Kalyan Kumar, R. Poovarasan

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In this paper, we have taken certain important factors and health parameters of diabetes patients especially among children by birth (pediatric congenital) where using the above three metrics methods we are going to assess the importance of each attributes in the dataset and thereby determining the most highly responsible and co-related attribute causing diabetics among young patients. We use cost optimization, control chart and Spearmen methodologies for the real-time application of finding the data efficiency in this diabetes dataset. The Spearmen methodology is the correlation methodologies used in software development process to identify the complexity between the various modules of the software. Identifying the complexity is important because if the complexity is higher, then there is a higher chance of occurrence of the risk in the software. With the use of control; chart mean, variance and standard deviation of data are calculated. With the use of Cost optimization model, we find to optimize the variables. Hence we choose the Spearmen, control chart and cost optimization methods to assess the data efficiency in diabetes datasets.

Keywords: correlation, congenital diabetics, linear relationship, monotonic function, ranking samples, pediatric

Procedia PDF Downloads 247

Authors: Parul Bhalla, Sarvesh Palria

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Wetlands are areas of land that are either temporarily or permanently covered by water. Wetlands exhibit enormous diversity according to their genesis, geographical location, water regime and chemistry, dominant plants and soil or sediment characteristics. The spatial and temporal characteristics of wetland in terms of turbidity and aquatic vegetation could serve as guiding tool, in conservation prioritization of wetlands. The aquatic vegetation in the wetland is an indicator of the trophic status of the wetland which has a bearing on the water quality, the turbidity level in any wetland is indicative of the quality of the water in it. To conserve and manage wetland resources, it is important to have inventory of wetland and its catchment. Fateh Sagar wetland in Udaipur city is the one of the important wetland for tourism industry and other economic activities in the region. Realizing the importance of the wetland, the present study has been taken up with the specific objective of delineation and characterization of Fateh Sagar wetland in terms of turbidity and aquatic vegetation, using high resolution satellite data such as Cartosat and LISS IV multi-temporal data, which will efficiently bring out the changes in water spread and quality parameters. The catchment of wetland has been also characterized for various features. The study leads in to takes necessary steps to conserve the wetland and its resources.

Keywords: aquatic vegetation, catchment, turbidity status, wetland

Procedia PDF Downloads 382

Authors: Sanja Pfeifer, Nataša Šarlija, Marina Jeger, Ana Bilandžić

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The purpose of this study is to explore the different facets of growth among micro, small and medium-sized firms in Croatia and to analyze the differences between models designed for all micro, small and medium-sized firms and those in creative industries. Three growth prediction models were designed and tested using the growth of sales, employment and assets of the company as dependent variables. The key drivers of sales growth are: prudent use of cash, industry affiliation and higher share of intangible assets. Growth of assets depends on retained profits, internal and external sources of financing, as well as industry affiliation. Growth in employment is closely related to sources of financing, in particular, debt and it occurs less frequently than growth in sales and assets. The findings confirm the assumption that growth strategies of small and medium-sized enterprises (SMEs) in creative industries have specific differences in comparison to SMEs in general. Interestingly, only 2.2% of growing enterprises achieve growth in employment, assets and sales simultaneously.

Keywords: creative industries, growth prediction model, growth determinants, growth measures

Procedia PDF Downloads 315

Authors: Ge Cui, Mei Fang Chien, Chihiro Inoue

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In this research, enrichment culture using an inorganic liquid medium collected soil contaminated with 1,2-dichlorobenzene (1,2-DCB) in Sendai, Japan, was added 1,2-DCB as the sole carbon source to create a stable consortium. The purpose of this research is to analysis dominant microorganisms in the stable consortium and enzyme system which play a role in the degradation of DCBs. The consortium is now at 30 generation and is still being cultured. By the result of PCR-DGGE and clone library, two bacteria are dominant. The bacteria named sk1 was isolated. 40mg/l of 1,2-DCB and 40mg/l of 1,4-DCB were completely degraded after 32 hours and 50 hours, respectively, but no degradation occurred in the case of 1,3-DCB. By PCR, tecA1 (α-subunit of DCB dioxygenase) gene which plays a role degrading DCB to DCB dihydrodiol, and tecB (dehydrogenase) gene which plays a role degrading DCB dihydrodiol to dichlorocatechol were amplified from strain sk1. Bacteria named sk100 was also isolated. 40mg/l of 1,2-DCB was completely degraded after 32 hours, but no degradation occurred in case of 1,3-DCB and 1,4-DCB. By the result of the catalytic core region of dioxygenase amplified by PCR, gene played a role degrading DCB was analyzed. The results of this study concluded that the isolated strains which have not been reported are able to degrade 1,2-DCB stably, and the characterization of degradation and the genomic analysis which is now in progress is helpful to have an overall view of this microbial degradation.

Keywords: DCB, 1, 2-DCB degrading strains, DCB dioxygenase, enrichment culture

Procedia PDF Downloads 190

Authors: Hasan Keshavarzian, Tayebeh Nesari

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Bolted rail joint is one of the most vulnerable areas in railway track. A comprehensive approach was developed for studying the reliability of fatigue crack initiation of railroad bolt hole under random axle loads and random material properties. The operation condition was also considered as stochastic variables. In order to obtain the comprehensive probability model of fatigue crack initiation life prediction in railroad bolt hole, we used FEM, response surface method (RSM), and reliability analysis. Combined energy-density based and critical plane based fatigue concept is used for the fatigue crack prediction. The dynamic loads were calculated according to the axle load, speed, and track properties. The results show that axle load is most sensitive parameter compared to Poisson’s ratio in fatigue crack initiation life. Also, the reliability index decreases slowly due to high cycle fatigue regime in this area.

Keywords: rail-wheel tribology, rolling contact mechanic, finite element modeling, reliability analysis

Procedia PDF Downloads 371

Authors: Mounia El Hafyani, Khalid El Himdi

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Precipitation is one of the key variables in water resource planning. The importance of modeling wet and dry durations is a crucial pointer in engineering hydrology. The objective of this study is to model and analyze the distribution of wet and dry durations. For this purpose, the daily rainfall data from 1967 to 2017 of the Moroccan city of Kenitra’s station are used. Three models are implemented for the distribution of wet and dry durations, namely the first-order Markov chain, the second-order Markov chain, and the truncated negative binomial law. The adherence of the data to the proposed models is evaluated using Chi-square and Kolmogorov-Smirnov tests. The Akaike information criterion is applied to assess the most effective model distribution. We go further and study the law of the number of wet and dry days among k consecutive days. The calculation of this law is done through an algorithm that we have implemented based on conditional laws. We complete our work by comparing the observed moments of the numbers of wet/dry days among k consecutive days to the calculated moment of the three estimated models. The study shows the effectiveness of our approach in modeling wet and dry durations of daily precipitation.

Keywords: Markov chain, rainfall, truncated negative binomial law, wet and dry durations

Procedia PDF Downloads 111

Authors: W. E. Igwegbe, B. C. Okoro, J. C. Osuagwu

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The study was aimed at assessing the effectiveness of reducing the concentrations of heavy metals in waste water using Pawpaw (Carica papaya) wood as a bio-sorbent. The heavy metals considered include; zinc, cadmium, lead, copper, iron, selenium, nickel, and manganese. The physiochemical properties of carica papaya stem were studied. The experimental sample was obtained from a felled trunk of matured pawpaw tree. Waste water for experimental use was prepared by dissolving soil samples collected from a dump site at Owerri, Imo state in water. The concentration of each metal remaining in solution as residual metal after bio-sorption was determined using Atomic absorption Spectrometer. The effects of ph, contact time and initial heavy metal concentration were studied in a batch reactor. The results of Spectrometer test showed that there were different functional groups detected in the carica papaya stem biomass. Optimum bio-sorption occurred at pH 5.9 with 5g/100ml solution of bio-sorbent. The results of the study showed that the treated wastewater is fit for irrigation purpose based on Canada wastewater quality guideline for the protection of Agricultural standard. This approach thus provides a cost effective and environmentally friendly option for treating waste water.

Keywords: biomass, bio-sorption, Carica papaya, heavy metal, wastewater

Procedia PDF Downloads 355

Authors: Yoonsuh Jung

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As DNA microarray data contain relatively small sample size compared to the number of genes, high dimensional models are often employed. In high dimensional models, the selection of tuning parameter (or, penalty parameter) is often one of the crucial parts of the modeling. Cross-validation is one of the most common methods for the tuning parameter selection, which selects a parameter value with the smallest cross-validated score. However, selecting a single value as an "optimal" value for the parameter can be very unstable due to the sampling variation since the sample sizes of microarray data are often small. Our approach is to choose multiple candidates of tuning parameter first, then average the candidates with different weights depending on their performance. The additional step of estimating the weights and averaging the candidates rarely increase the computational cost, while it can considerably improve the traditional cross-validation. We show that the selected value from the suggested methods often lead to stable parameter selection as well as improved detection of significant genetic variables compared to the tradition cross-validation via real data and simulated data sets.

Keywords: cross validation, parameter averaging, parameter selection, regularization parameter search

Procedia PDF Downloads 400

Authors: John Wangui, Charles Gachene, Stephen Mureithi, Boniface Kiteme

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Land use changes caused by demographic, natural variability, economic, technological and policy factors affect the goods and services derived from an ecosystem. In the past few decades, Lake Ol Bolossat catchment in Nyandarua County Kenya has been facing challenges of land cover changes threatening its capacity to perform ecosystems functions and adversely affecting communities and ecosystems downstream. This study assessed land cover changes in the catchment for a period of twenty eight years (from 1986 to 2014). Analysis of three Landsat images i.e. L5 TM 1986, L5 TM 1995 and L8 OLI/TIRS 2014 was done using ERDAS 9.2 software. The results show that dense forest, cropland and area under water increased by 27%, 29% and 3% respectively. On the other hand, open forest, dense grassland, open grassland, bushland and shrubland decreased by 3%, 3%, 11%, 26% and 1% respectively during the period under assessment. The lake was noted to have increased due to siltation caused by soil erosion causing a reduction in Lake’s depth and consequently causing temporary flooding of the wetland. The study concludes that the catchment is under high demographic pressure which would lead to resource use conflicts and therefore formulation of mitigation measures is highly recommended.

Keywords: land cover, land use change, land degradation, Nyandarua, Remote sensing

Procedia PDF Downloads 350

Authors: Indri Mahadiraka Rumamby, R. R. Dwinanti Rika Marthanty, Jessica Sjah

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Smoothed particle hydrodynamics (SPH) was originally created to simulate nonaxisymmetric phenomena in astrophysics. However, this method still has several shortcomings, namely the high computational cost required to model values with high resolution and problems with boundary conditions. The difficulty of modeling boundary conditions occurs because the SPH method is influenced by particle deficiency due to the integral of the kernel function being truncated by boundary conditions. This research aims to answer if SPH modeling with a focus on boundary layer interactions and continuous flow can produce quantifiably accurate values with low computational cost. This research will combine algorithms and coding in the main program of meandering river, continuous flow algorithm, and solid-fluid algorithm with the aim of obtaining quantitatively accurate results on solid-fluid interactions with the continuous flow on a meandering channel using the SPH method. This study uses the Fortran programming language for modeling the SPH (Smoothed Particle Hydrodynamics) numerical method; the model is conducted in the form of a U-shaped meandering open channel in 3D, where the channel walls are soil particles and uses a continuous flow with a limited number of particles.

Keywords: smoothed particle hydrodynamics, computational fluid dynamics, numerical simulation, fluid mechanics

Procedia PDF Downloads 110

Authors: Mehrdad Shahrbanozadeh, Gholam Abbas Barani, Saeed Shojaee

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In this study, a finite element (Seep3D model) and an artificial neural network (ANN) model were developed to simulate flow through dam foundation. Seep3D model is capable of simulating three-dimensional flow through a heterogeneous and anisotropic, saturated and unsaturated porous media. Flow through the Shahid Abbaspour dam foundation has been used as a case study. The FEM with 24960 triangular elements and 28707 nodes applied to model flow through foundation of this dam. The FEM being made denser in the neighborhood of the curtain screen. The ANN model developed for Shahid Abbaspour dam is a feedforward four layer network employing the sigmoid function as an activator and the back-propagation algorithm for the network learning. The water level elevations of the upstream and downstream of the dam have been used as input variables and the piezometric heads as the target outputs in the ANN model. The two models are calibrated and verified using the Shahid Abbaspour’s dam piezometric data. Results of the models were compared with those measured by the piezometers which are in good agreement. The model results also revealed that the ANN model performed as good as and in some cases better than the FEM.

Keywords: seepage, dam foundation, finite element method, neural network, seep 3D model

Procedia PDF Downloads 457

Authors: Byung Ho Jung, Dong Hoon Lim

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Logistic regression is a statistical method for analyzing a dataset in which there are one or more independent variables that determine an outcome. Logistic regression is used extensively in numerous disciplines, including the medical and social science fields. In this paper, we address the problem of estimating parameters in the logistic regression based on MapReduce framework with RHadoop that integrates R and Hadoop environment applicable to large scale data. There exist three learning algorithms for logistic regression, namely Gradient descent method, Cost minimization method and Newton-Rhapson's method. The Newton-Rhapson's method does not require a learning rate, while gradient descent and cost minimization methods need to manually pick a learning rate. The experimental results demonstrated that our learning algorithms using RHadoop can scale well and efficiently process large data sets on commodity hardware. We also compared the performance of our Newton-Rhapson's method with gradient descent and cost minimization methods. The results showed that our newton's method appeared to be the most robust to all data tested.

Keywords: big data, logistic regression, MapReduce, RHadoop

Procedia PDF Downloads 259

Authors: Amrit Gupta, Suchi Rani, Vineeta Agarwal, Swast Tiwari, Anup Kumar, Sachin Sharma

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Pregnancy is a unique state in which a balance of immune tolerance and suppression is necessary to protect the fetus without compromising the mother’s health. Human papilloma virus (HPV) is viral infection which mainly gets transmitted through sexual contact. The HPV infection can cause infections in the placenta and increase the inflammatory response in the mother, affecting pregnancy outcomes. This may result in adverse maternal and neonatal outcomes. The objectives of this research are to evaluate the effect on clinical course in pregnancy and maternal outcome in pregnant women with HPV infection and to evaluate the effect on neonatal health in terms of adverse clinical effects. Methodology: The prospective cohort study was done in a tertiary care institution over two years. In this study, 250 participants were recruited. The study included pregnant women who attended the antenatal clinic for routine check-ups. Written informed consent was obtained from each participant. Participants were asked to fill out a detailed questionnaire about their lifestyle, including demographic characteristics, sexual behaviors, past gynecological history, and medical and surgical history. HPV was the preliminary screening method, and a Pap smear was done in patients who came out to be HPV positive. Samples were collected with the cotton stick or HC2 sampler brush. Cyto-brush was rotated 3–5 times in the region of ecto-cervix. After the collection of the sample, it was dissolved in PBS buffer and stored at − 80° for HPV DNA analysis. HPV DNA was detected using a hybrid capture assay (marketed as Digene HC2 high-risk HPV DNA test; Cat. No./ID: 5199–1220). The cohort was divided into two study groups: 1) those who were HPV positive and 2) those who were HPV negative. The chi-square test is used to compare categorical variables across groups. AQ5 Unpaired t-tests and independent sample tests are used to test the statistical significance of intergroup mean differences. P-values are considered significant if they are less than 0.05. In MS Windows, SPSS20 (IBM Corporation; NY, USA) was used for statistical analysis of all data. Results: Out of 228 pregnant women, 27.63% (n=63) of pregnant women were found positive for the HPV DNA test. In comparing the HPV-positive (N=63) and HPV-negative (N=165) groups using chi-square tests, several demographic variables exhibited statistically significant differences. Habitat distribution shows a significant difference (p<0.001), with 28.6% of HPV-positive individuals residing in rural areas compared to 8.5% of HPV-negative individuals. The presence of morbidity besides HPV infection differed significantly (p<0.001), with HPV-positive participants more likely to have additional morbidities (54%) compared to HPV-negative participants (32.1%). The mode of delivery showed significant differences (p<0.05), particularly in emergency lower segment cesarean section (HPV+: 41.3%, HPV-: 23.6%). Gestational age at delivery was significantly lower in the HPV-positive group (median 37.28 weeks, IQR 36.43-37.85) compared to the HPV-negative group (median 37.71 weeks, IQR 37.14-38.42), with a P-value of 0.003. Finally, birth weight was significantly lower in the HPV-positive group (median 2.75 kg, IQR 2.5-2.9425) compared to the HPV-negative group (median 2.9 kg, IQR 2.67-3.25) with a P-value of 0.001. Conclusion: In summary, our study offers valuable insights into the relationship between HPV infection during pregnancy, basic demographic factors and maternal and neonatal health outcomes.

Keywords: human papilloma virus, maternal health, fetal outcome, pregnancy

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Authors: Magda Cepeda, Frances Hodgson, Ann Jopson

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There are different barriers people face when choosing to cycle for commuting purposes. This study examined the role of psycho-social factors predicting the intention to cycle to commute in Mexico City. An extended version of the theory of planned behaviour was developed and utilized with a simple random sample of 401 road users. We applied exploratory and confirmatory factor analysis and after identifying five factors, a structural equation model was estimated to find the relationships among the variables. The results indicated that cycling attributes, attitudes to cycling, social comparison and social image and prestige were the most important factors influencing intention to cycle. Although the results from this study are specific to Mexico City, they indicate areas of interest to transportation planners in other regions especially in those cities where intention to cycle its linked to its perceived image and there is political ambition to instigate positive cycling cultures. Moreover, this study contributes to the current literature developing applications of the Theory of Planned Behaviour.

Keywords: cycling, latent variable model, perception, theory of planned behaviour

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Authors: Mahta Eskandarnejad

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The aim of this paper was to compare physical activity and mental toughness in the staff and students of the University of Tabriz. 615 people participated in this study and filled demographic questionnaire, mental thoughness48 (MTQ48) questionnaire and habitual physical activity questionnaire (Baecke physical activity questionnaire). The research sample included 355 students and 260 staff (615 questionnaires). For analyzing hypotheses MANOVA, correlation and independent t-test were used. Based on the result; some subscales of mental toughness and physical activity were significantly related. The result showed the significant correlation between mental toughness and physical activity in student and no significant correlation in staff. Students were significantly physically more active than staff, and mental toughness was higher in staff. There was no difference in mental toughness variable between active participants (active staff and student). The results of this study showed that mental toughness could influence the way a person cope with living conditions. It is expected that mental toughness changes can lead to changing in levels of physical activity. It should be noted that the other variables should not be ignored.

Keywords: Baecke physical activity questionnaire, mental toughness, physical activity, university staff, university student

Procedia PDF Downloads 375

Authors: Denise De Fátima Fernandes Barbosa, Tyane Mayara Ferreira Oliveira, Diego Jorge Maia Lima, Paula Renata Amorim Lessa, Ana Karina Bezerra Pinheiro, Cintia Gondim Pereira Calou, Glauberto Da Silva Quirino, Hellen Lívia Oliveira Catunda, Tatiana Gomes Guedes, Nicolau Da Costa

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The aim of this study is to evaluate the use of Digital Cervicography (DC) in the diagnosis of precancerous lesions related to Human Papillomavirus (HPV). Cross-sectional study with a quantitative approach, of evaluative type, held in a health unit linked to the Pro Dean of Extension of the Federal University of Ceará, in the period of July to August 2015 with a sample of 33 women. Data collecting was conducted through interviews with enforcement tool. Franco (2005) standardized the technique used for DC. Polymerase Chain Reaction (PCR) was performed to identify high-risk HPV genotypes. DC were evaluated and classified by 3 judges. The results of DC and PCR were classified as positive, negative or inconclusive. The data of the collecting instruments were compiled and analyzed by the software Statistical Package for Social Sciences (SPSS) with descriptive statistics and cross-references. Sociodemographic, sexual and reproductive variables were analyzed through absolute frequencies (N) and their respective percentage (%). Kappa coefficient (κ) was applied to determine the existence of agreement between the DC of reports among evaluators with PCR and also among the judges about the DC results. The Pearson's chi-square test was used for analysis of sociodemographic, sexual and reproductive variables with the PCR reports. It was considered statistically significant (p<0.05). Ethical aspects of research involving human beings were respected, according to 466/2012 Resolution. Regarding the socio-demographic profile, the most prevalent ages and equally were those belonging to the groups 21-30 and 41-50 years old (24.2%). The brown color was reported in excess (84.8%) and 96.9% out of them had completed primary and secondary school or studying. 51.5% were married, 72.7% Catholic, 54.5% employed and 48.5% with income between one and two minimum wages. As for the sexual and reproductive characteristics, prevailed heterosexual (93.9%) who did not use condoms during sexual intercourse (72.7%). 51.5% had a previous history of Sexually Transmitted Infection (STI), and HPV the most prevalent STI (76.5%). 57.6% did not use contraception, 78.8% underwent examination Cancer Prevention Uterus (PCCU) with shorter time interval or equal to one year, 72.7% had no cases of Cervical Cancer in the family, 63.6% were multiparous and 97% were not vaccinated against HPV. DC identified good level of agreement between raters (κ=0.542), had a specificity of 77.8% and sensitivity of 25% when compared their results with PCR. Only the variable race showed a statistically significant association with CRP (p=0.042). DC had 100% acceptance amongst women in the sample, revealing the possibility of other experiments in using this method so that it proves as a viable technique. The DC positivity criteria were developed by nurses and these professionals also perform PCCU in Brazil, which means that DC can be an important complementary diagnostic method for the appreciation of these professional’s quality of examinations.

Keywords: gynecological examination, human papillomavirus, nursing, papillomavirus infections, uterine lasmsneop

Procedia PDF Downloads 283

Authors: Daniel O. Wasonga, Jouko Kleemola, Laura Alakukku, Pirjo Makela

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Cassava (Manihot esculenta Crantz) is a major food crop for millions of people in the tropics. Growth and yield of cassava in the arid-tropics are seriously constrained by intermittent water deficit and low soil K content. Therefore, experiments were conducted to investigate the effects of interaction between water deficit and K fertigation on growth and yield response of biofortified cassava at early growth phase. Yellow cassava cultivar was grown under controlled glasshouse conditions in 5-L pots containing 1.7 kg of pre-fertilized potting mix. Plants were watered daily for 30 days after planting. Treatments were three watering levels (30%, severe water deficit; 60%, mild water deficit; 100%, well-watered), on which K (0.01, 1, 4, 16 and 32 mM) was split. Plants were harvested at 90 days after planting. Leaf area was smallest in plants grown with 30% watering and 0.01 mM K, and largest in plants grown with 100% watering and 32 mM K. Leaf, root, and total dry mass decreased in water-stressed plants. However, dry mass was markedly higher when plants were grown with 16 mM K under all watering levels in comparison to other K concentrations. The highest leaf, root and total dry mass were in plants with 100% watering and 16 mM K. In conclusion, K improved the growth of plants under water deficit and thus, K application on soils with low moisture and low K may improve the productivity of cassava.

Keywords: dry mass, interaction, leaf area, Manihot esculenta

Procedia PDF Downloads 101

Authors: Pablo Oteiza, Ricardo Alvarez, Mehrdad Pirnia, Fuat Can

Abstract:

To effectively combat climate change, many countries around the world have committed to a decarbonisation of their electricity, along with promoting a large-scale integration of renewable energy sources (RES). While this trend represents a unique opportunity to effectively combat climate change, achieving a sound and cost-efficient energy transition towards low-carbon power systems poses significant challenges for the multi-year Transmission Network Expansion Planning (TNEP) problem. The objective of the multi-year TNEP is to determine the necessary network infrastructure to supply the projected demand in a cost-efficient way, considering the evolution of the new generation mix, including the integration of RES. The rapid integration of large-scale RES increases the variability and uncertainty in the power system operation, which in turn increases short-term flexibility requirements. To meet these requirements, flexible generating technologies such as energy storage systems must be considered within the TNEP as well, along with proper models for capturing the operational challenges of future power systems. As a consequence, TNEP formulations are becoming more complex and difficult to solve, especially for its application in realistic-sized power system models. To meet these challenges, there is an increasing need for developing efficient algorithms capable of solving the TNEP problem with reasonable computational time and resources. In this regard, a promising research area is the use of artificial intelligence (AI) techniques for solving large-scale mixed-integer optimization problems, such as the TNEP. In particular, the use of AI along with mathematical optimization strategies based on decomposition has shown great potential. In this context, this paper presents an efficient algorithm for solving the multi-year TNEP problem. The algorithm combines AI techniques with Column Generation, a traditional decomposition-based mathematical optimization method. One of the challenges of using Column Generation for solving the TNEP problem is that the subproblems are of mixed-integer nature, and therefore solving them requires significant amounts of time and resources. Hence, in this proposal we solve a linearly relaxed version of the subproblems, and trained a binary classifier that determines the value of the binary variables, based on the results obtained from the linearized version. A key feature of the proposal is that we integrate the binary classifier into the optimization algorithm in such a way that the optimality of the solution can be guaranteed. The results of a study case based on the HRP 38-bus test system shows that the binary classifier has an accuracy above 97% for estimating the value of the binary variables. Since the linearly relaxed version of the subproblems can be solved with significantly less time than the integer programming counterpart, the integration of the binary classifier into the Column Generation algorithm allowed us to reduce the computational time required for solving the problem by 50%. The final version of this paper will contain a detailed description of the proposed algorithm, the AI-based binary classifier technique and its integration into the CG algorithm. To demonstrate the capabilities of the proposal, we evaluate the algorithm in case studies with different scenarios, as well as in other power system models.

Keywords: integer optimization, machine learning, mathematical decomposition, transmission planning

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Authors: Haidong Li, Weishou Shen, Guoping Lv, Tao Wang

Abstract:

Aiming to overcome the limitation of the application of traditional remote sensing (RS) technique in the mine eco-environmental monitoring, in this paper, we first classified the eco-environmental damages caused by mining activities and then introduced the principle, classification and characteristics of the Light Detection and Ranging (LiDAR) technique. The potentiality of LiDAR technique in the mine eco-environmental monitoring was analyzed, particularly in extracting vertical structure parameters of vegetation, through comparing the feasibility and applicability of traditional RS method and LiDAR technique in monitoring different types of indicators. The application situation of LiDAR technique in extracting typical mine indicators, such as land destruction in mining areas, damage of ecological integrity and natural soil erosion. The result showed that the LiDAR technique has the ability to monitor most of the mine eco-environmental indicators, and exhibited higher accuracy comparing with traditional RS technique, specifically speaking, the applicability of LiDAR technique on each indicator depends on the accuracy requirement of mine eco-environmental monitoring. In the item of large mine, LiDAR three-dimensional point cloud data not only could be used as the complementary data source of optical RS, Airborne/Satellite LiDAR could also fulfill the demand of extracting vertical structure parameters of vegetation in large areas.

Keywords: LiDAR, mine, ecological damage, monitoring, traditional remote sensing technique

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Authors: Ram Dayal

Abstract:

Since inception of the modern Olympic Games in 1896 in Athens, Greece, it has undergone a paradigm shift over a period of more than a century. It originated with the purpose of inculcating physical and moral qualities, sense of aesthetics, ethical and spiritual value and educating young people, through the spread of the philosophy of amateurism, which is free from the vices of racial discrimination, any country’s domination, corruption, doping menace and political interference. Now, it has metamorphosed into the arena where only professionalism matters and has been reduced to the show of strength for countries analogous to the cold war. Rather than spirit of sports, the economics of sports is the more relevant underpinning. Changes in medal tally over a period of time and its correlation with the changing geo-political structure have been evaluated quantitatively using regression analyses, which have yielded statistically significant relationship among variables. The present study also tries to explore this shift in Olympic spirit through historical approach, using books, thesis, dissertations, articles, related documents. The present study will help evaluate the Olympic ideals with modern perspective and the need to replace or reinstall the same in order to nurture and rejuvenate the modern Olympic movement.

Keywords: challenges, games, olympic, sports

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Authors: Yu-Chen Chang, Yen-Ping Peng, Wei-Yu Chen, Ku-Fan Chen

Abstract:

Contamination of soil and groundwater has become a serious and widespread environmental problem. In this study, sustained-release persulfate tablets were developed using persulfate powder and a modified cellulose binder for organic-contaminated groundwater remediation. Conventional cement-based persulfate-releasing materials were also synthesized for the comparison. The main objectives of this study were to: (1) evaluate the release rates of the remedial tablets; (2) obtain the optimal formulas of the tablets; and (3) evaluate the effects of the tablets on the subsurface environment. The results of batch experiments show that the optimal parameter for the preparation of the persulfate-releasing tablet was persulfate:cellulose = 1:1 (wt:wt) with a 5,000 kg F/cm2 of pressure application. The cellulose-based persulfate tablet was able to release 2,030 mg/L of persulfate per day for 10 days. Compared to cement-based persulfate-releasing materials, the persulfate release rates of the cellulose-based persulfate tablets were much more stable. Moreover, since the tablets are soluble in water, no waste will be produced in the subsurface. The results of column tests show that groundwater flow would shorten the release time of the tablets. This study successfully developed unique persulfate tablets based on green remediation perspective. The efficacy of the persulfate-releasing tablets on the removal of organic pollutants needs to be further evaluated. The persulfate tablets are expected to be applied for site remediation in the future.

Keywords: sustained-release persulfate tablet, modified cellulose, green remediation, groundwater

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Authors: Mohieddine Benghersallah, Lakhdar Boulanouar, Salim Belhadi

Abstract:

Currently, higher production rate with required quality and low cost is the basic principle in the competitive manufacturing industry. This is mainly achieved by using high cutting speed and feed rates. Elevated temperatures in the cutting zone under these conditions shorten tool life and adversely affect the dimensional accuracy and surface integrity of component. Thus it is necessary to find optimum cutting conditions (cutting speed, feed rate, machining environment, tool material and geometry) that can produce components in accordance with the project and having a relatively high production rate. Response surface methodology is a collection of mathematical and statistical techniques that are useful for modelling and analysis of problems in which a response of interest is influenced by several variables and the objective is to optimize this response. The work presented in this paper examines the effects of cutting parameters (cutting speed, feed rate and depth of cut) on to the surface roughness through the mathematical model developed by using the data gathered from a series of milling experiments performed.

Keywords: Statistical analysis (RSM), Bearing steel, Coating inserts, Tool life, Surface Roughness, End milling.

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Authors: Maria Poulou

Abstract:

The study investigated how teachers’ self-rated Emotional Intelligence (EI), competence in implementing Social and Emotional Learning (SEL) skills and teaching efficacy relate to teacher-student relationships and students’ emotional and behavioral difficulties. Participants were 98 elementary teachers from public schools in central Greece. They completed the Self-Rated Emotional Intelligence Scale (SREIS), the Teacher SEL Beliefs Scale, the Teachers’ Sense of Efficacy Scale (TSES), the Student-Teacher Relationships Scale-Short Form (STRS-SF) and the Strengths and Difficulties Questionnaire (SDQ) for 617 of their students, aged 6-11 years old. Structural equation modeling was used to examine an exploratory model of the variables. It was demonstrated that teachers’ emotional intelligence, SEL beliefs and teaching efficacy were significantly related to teacher-student relationships, but they were not related to students’ emotional and behavioral difficulties. Rather, teachers’ perceptions of teacher-students relationships were significantly related to these difficulties. These findings and their implications for research and practice are discussed.

Keywords: emotional intelligence, social and emotional learning, teacher-student relationships, teaching efficacy

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Authors: Kamal Bahrin Jaafar

Abstract:

The study area is located at Bukit Kukus, Penang where the construction of twin road project in ongoing. A landslide event has occurred on 19th October 2018, which causes fatal deaths. The purpose of this study is to figure out the causes of failure, the estimated volume of failure, and its balance. The study comprises of unmanned aerial vehicle (UAV) sensing and resistivity survey. The resistivity method includes spreading three lines of 200m length resistivity survey with the depth of penetration in the subsurface not exceeding 35m. The result of UAV shows the current view of the site condition. Based on resistivity result, the dominant layer in the study area consists of residual soil/filling material with a thickness of more than 35m. Three selected cross sections from construction drawing are overlain with the current cross sections to understand more on the condition of the subsurface profile. By comparison, there is a difference between past and present topography. The combination of result from the previous data and current condition shows the calculated volume of failure is 85,000 m³, and its balance is 50,000 m³. In conclusion, the failure occurs since the contractor has conducted the construction works without following the construction drawing supplied by the consultant. Besides, the cause of failure is triggered by the geology condition, such as a fault that should be considered prior to the commencement of work.

Keywords: UAV, landslide, resistivity survey, cause of failure

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Authors: Ramazan Livaoğlu, Tufan Çakır

Abstract:

The performance of rectangular tanks during earthquakes has been observed to depend significantly on the existence of water in the container and the presence of the backfill acting on tank wall. Therefore, in design of rectangular tanks, the topics of fluid-structure-backfill interactions and determination of modal characteristics of the interaction system have traditionally been one of the great theoretical and practical controversy. Although finite element method has been and will continue to be used to a significant extent in treating the response of the system, experimental verification of numerical models remains prerequisite for their adoption and reliable application in practice. Thus, in this study, the numerical and experimental investigations were performed on the backfill-exterior wall-fluid interaction system. Firstly, three dimensional finite element model (3D-FEM) was developed to acquire modal frequencies and mode shapes of the system by means of ANSYS. Secondly, a series of in-situ tests were fulfilled to define modal characteristics of same system to determine the applicability of the FEM to a real physical situation under field conditions. Finally, comparing the theoretical predictions from the model to results from experimental measurement, a close agreement was found between theory and experiment. Thus, it can be easily stated that experimental verification provides strong support for the use of proposed model in further investigations.

Keywords: fluid-structure interaction, modal analysis, rectangular tank, soil structure interaction

Procedia PDF Downloads 376