Search results for: the soil variables

Authors: Rajeshwar Singh

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The presence of multicollinearity is common in handling with several explanatory variables simultaneously due to exhibiting a linear relationship among them. A great problem arises in understanding the impact of explanatory variables on the dependent variable. Thus, the method of least squares estimation gives inexact estimates. In this case, it is advised to detect its presence first before proceeding further. Using the ridge regression degree of its occurrence is reduced but principal components regression gives good estimates in this situation. This paper discusses well-known techniques of the ridge and principal components regressions and applies to get the estimates of coefficients by both techniques. In addition to it, this paper also discusses the conflicting claim on the discovery of the method of ridge regression based on available documents.

Keywords: conflicting claim on credit of discovery of ridge regression, multicollinearity, principal components and ridge regressions, variance inflation factor

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Authors: Godwin Chigozie Okpara, Eugene Iheanacho

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This paper examined the dynamic behavior of stock market development and the growth of Nigerian economy. The variables; market capitalization ratio, turnover ratio and liquidity proxies by the ratio of market capitalization to gross domestic product were sourced and computed from the Nigerian stock exchange fact books and the CBN statistical bulletin of the Central Bank of Nigeria. The variables were tested and found stationary and cointregrated using the augumented Dickey Fuller unit root test and the Johnson cointegration test respectively. The dynamic behavior of the stock market development model was verified using the error correction model. The result shows that about 0.4l percent of the short run deviation is corrected every year and also reveals that market capitalization ratio and market liquidity are positive and significant function of economic growth. In other words market capitalization ratio and liquidity positively and significantly impact economic growth. Market development variables such as turnover ratio and market restriction can exert positive but insignificant impact on the growth of the economy suggesting that securities transaction relative to the size of the securities market are not high enough to significantly engender economic growth in Nigeria. In the light of this, the researchers recommend that the regulatory body as well as the government, should provide a conducive environment capable of encouraging the growth and development of the stock market. This if well articulated will enhance the market turnover and the growth of the economy.

Keywords: market capitalization ratio, turnover ratio, liquidity, unit root test, cointegration

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Authors: Harsha B. R., Anil Kumar K. S.

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Climate and soils are the two most dynamic entities among the factors affecting growth and grapes productivity. Studying of prevailing climate over the years in a region provides sufficient information related to management practices to be carried out in vineyards. Evaluating the suitability of vineyard soils under different climatic conditions serves as the yardstick to analyse the performance of grapevines. This study was formulated to study the climate and evaluate the site-suitability of soils in vineyards of southern Karnataka, which has registered its superiority in the quality production of wine. Ten soil profiles were excavated for suitability evaluation of soils, and six taluks were studied for climatic analysis. In almost all the regions studied, recharge starts at the end of the May or June months, peaking in either September or October months. Soil Starts drying from mid of December months in the taluks studied. Bangalore North (Rajanukunte) soils were highly suited for grapes cultivation with no or slight limitations. Bangalore North (GKVK Farm) was moderately suited with slight to moderate limitations of slope and available nitrogen content. Moderate suitability was observed in the rest of the profiles studied in Eastern dry zone soils with the slight to moderate limitations of either organic carbon or available nitrogen or both in the Eastern dry zone. Magadi (Southern dry zone) soils were moderately suitable with slight to moderate limitations of graveliness, available nitrogen, organic carbon, and exchangeable sodium percentage. Sustainable performance of vineyards in terms of yield can be achieved in these taluks by managing the constraints existing in soils.

Keywords: climatic analysis, dry zone, water recharge, growing period, suitability, sustainability

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Authors: M. B. Sokoto, L. Tanko, Y. M. Abdullahi

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The study aimed at examining the impact of climatic factors (rainfall, minimum and maximum temperature) on the productivity of major cereals in Sokoto state, Nigeria. Secondary data from 1997-2008 were used in respect of annual yield of Major cereals crops (maize, millet, rice, and sorghum (t ha-1). Data in respect of climate was collected from Sokoto Energy Research Centre (SERC) for the period under review. Data collected was analyzed using descriptive statistics, correlation and regression analysis. The result of the research reveals that there is variation in the trend of the climatic factors and also variation in cereals output. The effect of average temperature on yields has a negative effect on crop yields. Similarly, rainfall is not significant in explaining the effect of climate on cereal crops production. The study has revealed to some extend the effect of climatic variables, such as rainfall, relative humidity, maximum and minimum temperature on major cereals production in Sokoto State. This will assist in planning ahead in cereals production in the area. Other factors such as soil fertility, correct timing of planting and good cultural practices (such as spacing of strands), protection of crops from weeds, pests and diseases and planting of high yielding varieties should also be taken into consideration for increase yield of cereals.

Keywords: cereals, climate, impact, major, productivity

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Authors: R. Rajeswari

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An investigation was carried out to know the SOC stock and its change over time in benchmark soils of different agroclimatic zones of Tamil Nadu. Roth.C model was used to assess SOC stock under existing and alternate cropping pattern. Soil map prepared on 1:50,000 scale from Natural Resources Information System (NRIS) employed under satellite data (IRS-1C/1D-PAN sharpened LISS-III image) was used to estimate SOC stock in different agroclimatic zones of Tamil Nadu. Fifteen benchmark soils were selected in different agroclimatic zones of Tamil Nadu based on their land use and the areal extent to assess SOC level and its change overtime. This revealed that, between eleven years of period (1997 - 2007). SOC buildup was higher in soils under horticulture system, followed by soils under rice cultivation. Among different agroclimatic zones of Tamil Nadu hilly zone have the highest SOC stock, followed by north eastern, southern, western, cauvery delta, north western, and high rainfall zone. Although organic carbon content in the soils of North eastern, southern, western, North western, Cauvery delta were less than high rainfall zone, the SOC stock was high. SOC density was higher in high rainfall and hilly zone than other agroclimatic zones of Tamil Nadu. Among low rainfall regions of Tamil Nadu cauvery delta zone recorded higher SOC density. Roth.C model was used to assess SOC stock under existing and alternate cropping pattern in viz., Periyanaickenpalayam series (western zone), Peelamedu series (southern zone), Vallam series (north eastern zone), Vannappatti series (north western zone) and Padugai series (cauvery delta zone). Padugai series recorded higher TOC, BIO, and HUM, followed by Periyanaickenpalayam series, Peelamedu series, Vallam series, and Vannappatti series. Vannappatti and Padugai series develop high TOC, BIO, and HUM under existing cropping pattern. Periyanaickenpalayam, Peelamedu, and Vallam series develop high TOC, BIO, and HUM under alternate cropping pattern. Among five selected soil series, Periyanaickenpalayam, Peelamedu, and Padugai series recorded 0.75 per cent TOC during 2025 and 2018, 2100 and 2035, 2013 and 2014 under existing and alternate cropping pattern, respectively.

Keywords: agro climatic zones, benchmark soil, land use, soil organic carbon

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Authors: A. Shafaghat, H. Khabbaz, S. Moravej, Ah. Shafaghat

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The bearing capacity of closely spaced shallow footings alters with their spacing and the shape of footing. In this study, the bearing capacity and settlement of two adjacent footings constructed on a sand layer are investigated. The effect of different footing shapes including square, circular, ring and strip on sandy soil is captured in the calculations. The investigations are carried out numerically using PLAXIS-3D software and analytically employing conventional settlement equations. For this purpose, foundations are modelled in the program with practical dimensions and various spacing ratios ranging from 1 to 5. The spacing ratio is defined as the centre-to-centre distance to the width of foundations (S/B). Overall, 24 models are analyzed; and the results are compared and discussed in detail. It can be concluded that the presence of adjacent foundation leads to the reduction in bearing capacity for round shape footings while it can increase the bearing capacity of rectangular footings in some specific distances.

Keywords: bearing capacity, finite element analysis, loose sand, settlement equations, shallow foundation

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Authors: Arum Kingsley Chinedu, Ugwuowo Fidelis Ifeanyi, Oranye Henrietta Ebele

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The Poisson regression model (PRM) is a nonlinear model that belongs to the exponential family of distribution. PRM is suitable for studying count variables using appropriate covariates and sometimes experiences the problem of multicollinearity in the explanatory variables and outliers on the response variable. This study aims to address the problem of multicollinearity and outliers jointly in a Poisson regression model. We developed an estimator called the robust modified jackknife PCKL parameter estimator by combining the principal component estimator, modified jackknife KL and transformed M-estimator estimator to address both problems in a PRM. The superiority conditions for this estimator were established, and the properties of the estimator were also derived. The estimator inherits the characteristics of the combined estimators, thereby making it efficient in addressing both problems. And will also be of immediate interest to the research community and advance this study in terms of novelty compared to other studies undertaken in this area. The performance of the estimator (robust modified jackknife PCKL) with other existing estimators was compared using mean squared error (MSE) as a performance evaluation criterion through a Monte Carlo simulation study and the use of real-life data. The results of the analytical study show that the estimator outperformed other existing estimators compared with by having the smallest MSE across all sample sizes, different levels of correlation, percentages of outliers and different numbers of explanatory variables.

Keywords: jackknife modified KL, outliers, multicollinearity, principal component, transformed M-estimator.

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Authors: B. M. Y. I. Basnayake, G. G. T. Nisansala, P. I. J. B. Wijewickrama, U. S. Weerathunga, K. W. M. Y. D. Gunasekara, N. K. Jayasekera, A. W. Kalupahana, R. S. Kalupahana, A. Silva- Fletcher, K. S. A. Kottawatta

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Antimicrobial resistance (AMR) has attracted significant attention worldwide as an emerging threat to public health. Understanding the role of livestock and wildlife with the shared environment in the maintenance and transmission of AMR is of utmost importance due to its interactions with humans for combating the issue in one health approach. This study aims to investigate the extent of AMR distribution among wild animals, livestock, and environment cohabiting in a rural ecosystem in Sri Lanka: Hambegamuwa. One square km area at Hambegamuwa was mapped using GPS as the sampling area. The study was conducted for a period of five months from November 2020. Voided fecal samples were collected from 130 wild animals, 123 livestock: buffalo, cattle, chicken, and turkey, with 36 soil and 30 water samples associated with livestock and wildlife. From the samples, Escherichia coli (E. coli) was isolated, and their AMR profiles were investigated for 12 antimicrobials using the disk diffusion method following the CLSI standard. Seventy percent (91/130) of wild animals, 93% (115/123) of livestock, 89% (32/36) of soil, and 63% (19/30) of water samples were positive for E. coli. Maximum of two E. coli from each sample to a total of 467 were tested for the sensitivity of which 157, 208, 62, and 40 were from wild animals, livestock, soil, and water, respectively. The highest resistance in E. coli from livestock (13.9%) and wild animals (13.3%) was for ampicillin, followed by streptomycin. Apart from that, E. coli from livestock and wild animals revealed resistance mainly against tetracycline, cefotaxime, trimethoprim/ sulfamethoxazole, and nalidixic acid at levels less than 10%. Ten cefotaxime resistant E. coli were reported from wild animals, including four elephants, two land monitors, a pigeon, a spotted dove, and a monkey which was a significant finding. E. coli from soil samples reflected resistance primarily against ampicillin, streptomycin, and tetracycline at levels less than in livestock/wildlife. Two water samples had cefotaxime resistant E. coli as the only resistant isolates out of 30 water samples tested. Of the total E. coli isolates, 6.4% (30/467) was multi-drug resistant (MDR) which included 18, 9, and 3 isolates from livestock, wild animals, and soil, respectively. Among 18 livestock MDRs, the highest (13/ 18) was from poultry. Nine wild animal MDRs were from spotted dove, pigeon, land monitor, and elephant. Based on CLSI standard criteria, 60 E. coli isolates, of which 40, 16, and 4 from livestock, wild animal, and environment, respectively, were screened for Extended Spectrum β-Lactamase (ESBL) producers. Despite being a rural ecosystem, AMR and MDR are prevalent even at low levels. E. coli from livestock, wild animals, and the environment reflected a similar spectrum of AMR where ampicillin, streptomycin, tetracycline, and cefotaxime being the predominant antimicrobials of resistance. Wild animals may have acquired AMR via direct contact with livestock or via the environment, as antimicrobials are rarely used in wild animals. A source attribution study including the effects of the natural environment to study AMR can be proposed as this less contaminated rural ecosystem alarms the presence of AMR.

Keywords: AMR, Escherichia coli, livestock, wildlife

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Authors: Japnoor Garcha, Andrew P. Smith

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There has been a significant increase in the prevalence and estimates of neurodevelopmental disorders specially autism spectrum disorders in the last decade. The literature has seen increasing research on understanding well-being and mental health. The current studies have focused on seeing the impact of mental health and well-being in autism spectrum disorders and ADHD both with and without a diagnosis. To further understand the association and interaction of well-being and mental health with autism and ADHD a survey was given to 560 secondary school students. The survey used the well-being process questionnaire, the autism spectrum quotient, the ADHD self-report scale, and the strengths and difficulties questionnaire. The analysis conducted using SPSS showed that there was a significant correlation between anxiety, depression, AQ and ADHD. Anxiety and depression were also significantly correlated with all well-being and SDQ variables. The regression analysis showed that anxiety was significantly associated with positive well-being, negative well-being, emotional problems and prosocial behaviour whereas depression was significantly associated with positive well-being, negative well-being, physical health, flourishing, conduct problems, emotional problems and peer problems. This interaction led to the formation of a combined variable to see what impact the variables of anxiety, depression, AQ and ADHD would have coupled together. Further analysis showed that the combined variable was significantly correlated with all outcome variables. The regression analysis showed that the Combined variable was significantly correlated with emotional problems, and hyperactivity, stress, negative coping, psychological capital and sleepiness.

Keywords: AQ, adhd, sdq, well-being, combined variable

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Authors: F. Esfandyari Darabad, Z. Samadi

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The volume of runoff caused by rainfall in the river basin has enticed the researchers in the fields of the water management resources. In this study, first of the hydrological data such as the rainfall and discharge of the Khiyav river basin of Meshkin city in the northwest of Iran collected and then the process of analyzing and reconstructing has been completed. The soil conservation service (scs) has developed a method for calculating the runoff, in which is based on the curve number specification (CN). This research implemented the following model in the Khiyav river basin of Meshkin city by the GIS techniques and concluded the following fact in which represents the usage of weight model in calculating the curve numbers that provides the possibility for the all efficient factors which is contributing to the runoff creation such as; the geometric characteristics of the basin, the basin soil characteristics, vegetation, geology, climate and human factors to be considered, so an accurate estimation of runoff from precipitation to be achieved as the result. The findings also exposed the accident-prone areas in the output of the Khiyav river basin so it was revealed that the Khiyav river basin embodies a high potential for the flood creation.

Keywords: curve number, khiyav river basin, runoff estimation, SCS

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Authors: E. H. N. Gashti, M. Malaska, K. Kujala

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The thermo-mechanical behaviour of concrete energy pile foundations with different single and double U-tube shapes incorporated was analysed using the Comsol Multi-physics package. For the analysis, a 3D numerical model in real scale of the concrete pile and surrounding soil was simulated regarding actual operation of ground heat exchangers (GHE) and the surrounding ambient temperature. Based on initial ground temperature profile measured in situ, tube inlet temperature was considered to range from 6°C to 0°C (during the contraction process) over a 30-day period. Extra thermal stresses and deformations were calculated during the simulations and differences arising from the use of two different systems (single-tube and double-tube) were analysed. The results revealed no significant difference for extra thermal stresses at the centre of the pile in either system. However, displacements over the pile length were found to be up to 1.5-fold higher in the double-tube system than the single-tube system.

Keywords: concrete energy piles, stresses, displacements, thermo-mechanical behaviour, soil-structure interactions

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Authors: Jithin S. Kumar, Ramesh Kannan Kandasami

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Geomaterials are generally porous in nature due to the presence of discrete particles and interconnected voids. The porosity present in these geomaterials play a critical role in many engineering applications such as CO2 sequestration, well bore strengthening, enhanced oil and hydrocarbon recovery, hydraulic fracturing, and subsurface waste storage. These applications involves solid-fluid interactions, which govern the changes in the porosity which in turn affect the permeability and stiffness of the medium. Injecting fluid into the geomaterials results in permeation which exhibits small or negligible deformation of the soil skeleton followed by cavity expansion/ fingering/ fracturing (different forms of instabilities) due to the large deformation especially when the flow rate is greater than the ability of the medium to permeate the fluid. The complexity of this problem increases as the geomaterial behaves like a solid and fluid under certain conditions. Thus it is important to understand this multiphysics problem where in addition to the permeation, the elastic-plastic deformation of the soil skeleton plays a vital role during fluid injection. The phenomenon of permeation and cavity expansion in porous medium has been studied independently through extensive experimental and analytical/ numerical models. The analytical models generally use Darcy's/ diffusion equations to capture the fluid flow during permeation while elastic-plastic (Mohr-Coulomb and Modified Cam-Clay) models were used to predict the solid deformations. Hitherto, the research generally focused on modelling cavity expansion without considering the effect of injected fluid coming into the medium. Very few studies have considered the effect of injected fluid on the deformation of soil skeleton. However, the porosity changes during the fluid injection and coupled elastic-plastic deformation are not clearly understood. In this study, the phenomenon of permeation and instabilities such as cavity and finger/ fracture formation will be quantified extensively by performing experiments using a novel experimental setup in addition to utilizing image processing techniques. This experimental study will describe the fluid flow and soil deformation characteristics under different boundary conditions. Further, a well refined coupled semi-analytical model will be developed to capture the physics involved in quantifying the deformation behaviour of geomaterial during fluid injection.

Keywords: solid-fluid interaction, permeation, poroelasticity, plasticity, continuum model

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Authors: Rahul Patel, S. P. Dave, M. V Shah

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Ahmedabad is a rapidly growing city in western India that is experiencing significant urbanization and industrialization. With projections indicating that it will become a metropolitan city in the near future, various construction activities are taking place, making soil testing a crucial requirement before construction can commence. To achieve this, construction companies and contractors need to periodically conduct soil testing. This study focuses on the process of creating a spatial database that is digitally formatted and integrated with geotechnical data and a Geographic Information System (GIS). Building a comprehensive geotechnical Geo-database involves three essential steps. Firstly, borehole data is collected from reputable sources. Secondly, the accuracy and redundancy of the data are verified. Finally, the geotechnical information is standardized and organized for integration into the database. Once the Geo-database is complete, it is integrated with GIS. This integration allows users to visualize, analyze, and interpret geotechnical information spatially. Using a Topographic to Raster interpolation process in GIS, estimated values are assigned to all locations based on sampled geotechnical data values. The study area was contoured for SPT N-Values, Soil Classification, Φ-Values, and Bearing Capacity (T/m2). Various interpolation techniques were cross-validated to ensure information accuracy. The GIS map generated by this study enables the calculation of SPT N-Values, Φ-Values, and bearing capacities for different footing widths and various depths. This approach highlights the potential of GIS in providing an efficient solution to complex phenomena that would otherwise be tedious to achieve through other means. Not only does GIS offer greater accuracy, but it also generates valuable information that can be used as input for correlation analysis. Furthermore, this system serves as a decision support tool for geotechnical engineers. The information generated by this study can be utilized by engineers to make informed decisions during construction activities. For instance, they can use the data to optimize foundation designs and improve site selection. In conclusion, the rapid growth experienced by Ahmedabad requires extensive construction activities, necessitating soil testing. This study focused on the process of creating a comprehensive geotechnical database integrated with GIS. The database was developed by collecting borehole data from reputable sources, verifying its accuracy and redundancy, and organizing the information for integration. The GIS map generated by this study is an efficient solution that offers greater accuracy and generates valuable information that can be used as input for correlation analysis. It also serves as a decision support tool for geotechnical engineers, allowing them to make informed decisions during construction activities.

Keywords: arcGIS, borehole data, geographic information system (GIS), geo-database, interpolation, SPT N-value, soil classification, φ-value, bearing capacity

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Authors: Mohamed Khiatine, Ramdane Bahar

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The research performed during the last years has revealed that the seismic response of the soilis significantly non linear and hysteresis to the deformationsitundergoes during earthquakes and notably during violent shaking. This nonlinear behavior of soils can be characterized by curves showing the evolution of shearmodulus and damping versus distortion. Also, in this context, geotechnical seismic engineering problems often require the characterization of dynamic soil properties over a wide range of deformation. This determination of dynamic soil properties is key to predict the seismic response of soils for important civil engineering structures. This communication discusses a numerical analysis method for evaluating the nonlinear dynamic properties of soils in Algeriausing the FLAC2D software and the database resulting from geophysical and geotechnical studies when laboratory dynamic tests are not available. The nonlinear model proposed by Ramberg-Osgood and limited by the Mohr-coulomb criterion is used.

Keywords: degradation, shear modulus, damping, ramberg-osgood, numerical analysis.

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Authors: Chantarat Manvichien, Kevin Wongleedee

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The purpose of this research was to study Thai passengers’ level of understanding and awareness of the cabin crew safety briefing in the airplane during the preparation to take off and landing. It is important to know if Thai passengers pay attention to cabin crew safety briefing and to suggest a better way to draw their attention. The independent variables included gender, age, income, levels of education, travelling purpose, and travelling frequency while the dependent variables was level of awareness. A simple random sampling method was utilized to get 400 respondents. The findings revealed the ranking the first three levels of importance by highest mean to lowest mean as follows: (1) It is important to listen to cabin crew safety briefing; (2) Cabin crew briefing is interesting; (3) Information from cabin crew safety briefing is easy to understand. In addition, the overall means was 3.27 with 0.800 SD.

Keywords: cabin crew, safety briefing, Thai passengers, awareness

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Authors: Naduni Ranasinghe

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E-learning environments are getting more popular than any other due to the impact of COVID19. Even though e-learning is one of the best solutions for the teaching-learning process in the academic process, it’s not without major challenges. Nowadays, machine learning approaches are utilized in the analysis of how behavioral factors lead to better adoption and how they related to better performance of the students in eLearning environments. During the pandemic, we realized the academic process in the eLearning approach had a major issue, especially for the performance of the students. Therefore, an approach that investigates student behaviors in eLearning environments using a data-intensive machine learning approach is appreciated. A hybrid approach was used to understand how each previously told variables are related to the other. A more quantitative approach was used referred to literature to understand the weights of each factor for adoption and in terms of performance. The data set was collected from previously done research to help the training and testing process in ML. Special attention was made to incorporating different dimensionality of the data to understand the dependency levels of each. Five independent variables out of twelve variables were chosen based on their impact on the dependent variable, and by considering the descriptive statistics, out of three models developed (Random Forest classifier, SVM, and Decision tree classifier), random forest Classifier (Accuracy – 0.8542) gave the highest value for accuracy. Overall, this work met its goals of improving student performance by identifying students who are at-risk and dropout, emphasizing the necessity of using both static and dynamic data.

Keywords: academic performance prediction, e learning, learning analytics, machine learning, predictive model

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Authors: Hasan G. Elmazoghi, Aisha I. Alzayani, Lubna S. Bentaher

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Rainfall is a highly non-linear phenomena, which requires application of powerful supervised data mining techniques for its accurate prediction. In this study the Artificial Neural Network (ANN) technique is used to predict the mean monthly historical rainfall data collected from BENINA station in Benghazi for 31 years, the period of “1977-2006” and the results are compared against the observed values. The specific objective to achieve this goal was to determine the best combination of weather variables to be used as inputs for the ANN model. Several statistical parameters were calculated and an uncertainty analysis for the results is also presented. The best ANN model is then applied to the data of one year (2007) as a case study in order to evaluate the performance of the model. Simulation results reveal that application of ANN technique is promising and can provide reliable estimates of rainfall.

Keywords: neural networks, rainfall, prediction, climatic variables

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Authors: Thi Thanh Nga Pham, Damien Philippon, Alexis Drogoul, Thi Thu Thuy Nguyen, Tien Cong Nguyen

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Mekong River Delta region of Vietnam is recognized as one of the most vulnerable to climate change due to flooding and seawater rise and therefore an increased burden of climate change-related diseases. Changes in temperature and precipitation are likely to alter the incidence and distribution of vector-borne diseases such as dengue fever. In this region, the peak of the dengue epidemic period is around July to September during the rainy season. It is believed that climate is an important factor for dengue transmission. This study aims to enhance the capacity of dengue prediction by the relationship of dengue incidences with climate and environmental variables for Mekong River Delta of Vietnam during 2005-2015. Mathematical models for vector-host infectious disease, including larva, mosquito, and human being were used to calculate the impacts of climate to the dengue transmission with incorporating geospatial data for model input. Monthly dengue incidence data were collected at provincial level. Precipitation data were extracted from satellite observations of GSMaP (Global Satellite Mapping of Precipitation), land surface temperature and land cover data were from MODIS. The value of seasonal reproduction number was estimated to evaluate the potential, severity and persistence of dengue infection, while the final infected number was derived to check the outbreak of dengue. The result shows that the dengue infection depends on the seasonal variation of climate variables with the peak during the rainy season and predicted dengue incidence follows well with this dynamic for the whole studied region. However, the highest outbreak of 2007 dengue was not captured by the model reflecting nonlinear dependences of transmission on climate. Other possible effects will be discussed to address the limitation of the model. This suggested the need of considering of both climate variables and another variability across temporal and spatial scales.

Keywords: infectious disease, dengue, geospatial data, climate

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Authors: Bola Adeleke, Kayode Ogunsusi

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Heritage sites have evolved to preserve culture and heritage and also to educate and entertain tourists. Tourist travel decisions and behavior are influenced by destination image and value of the experience of tourists. Perceived value is one of the important tools for securing a competitive edge in tourism destinations. The model of Ritchie and Crouch distinguished 36 attributes of competitiveness which are classified into five factors which are quality of experience, touristic attractiveness, environment and infrastructure, entertainment/outdoor activities and cultural traditions. The study extended this model with a different grouping of the determinants of destination competitiveness. The theoretical framework used for this study assumes that apart from attractions already situated in the grove, satisfaction with destination common service, and entertainment and events, can all be used in creating a positive image for/and in attracting customers (destination selection) to visit Osun Sacred Osogbo Grove during and after annual celebrations. All these will impact positively on travel experience of customers as well as their spiritual fulfillment. Destination image has a direct impact on tourists’ satisfaction which consequently impacts on tourists’ likely future behavior on whether to revisit a cultural destination or not. The study investigated the variables responsible for destination image competitiveness of the Heritage Site; assessed the factors enhancing the destination image; and evaluated the perceived value realized by tourists from their cultural experience at the grove. A complete enumeration of tourists above 18 years of age who visited the Heritage Site within the month of March and April 2017 was taken. 240 respondents, therefore, were used for the study. The structured questionnaire with 5 Likert scales was administered. Five factors comprising 63 variables were used to determine the destination image competitiveness through principal component analysis, while multiple regressions were used to evaluate perceived value of tourists at the grove. Results revealed that 11 out of the 12 variables determining the destination image competitiveness were significant in attracting tourists to the grove. From the R-value, all factors predicted tourists’ value of experience strongly (R= 0.936). The percentage variance of customer value was explained by 87.70% of the variance of destination common service, entertainment and event satisfaction, travel environment satisfaction and spiritual satisfaction, with F-value being significant at 0.00. Factors with high alpha value contributed greatly to adding value to enhancing destination and tourists’ experience. 11 variables positively predicted tourist value with significance. Managers of Osun World Heritage Site should improve on variables critical to adding values to tourists’ experience.

Keywords: competitiveness, destination image, Osun Osogbo world heritage site, tourists

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Authors: Biruk Wolde, Atalay Ayele, Yonatan Garkabo, Trufat Hailmariam, Zemenu Germewu

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A comprehensive three-dimensional (3D) geological modeling and engineering geological characterization of shallow subsurface soils and rocks are essential for a wide range of geotechnical and seismological engineering applications, particularly in urban environments. The spatial distribution and geological variation of the shallow subsurface of Addis Ababa city have not been studied so far in terms of geological and geotechnical modeling. This study aims at the construction of a 3D geological model, as well as provides awareness into the engineering geological characteristics of shallow subsurface soil and rock of Addis Ababa city. The 3D geological model was constructed by using more than 1500 geotechnical boreholes, well-drilling data, and geological maps. A well-known geostatistical kriging 3D interpolation algorithm was applied to visualize the spatial distribution and geological variation of the shallow subsurface. Due to the complex nature of geological formations, vertical and lateral variation of the geological profiles horizons-solid command has been selected via the Groundwater Modelling System (GMS) graphical user interface software. For the engineering geological characterization of typical soils and rocks, both index and engineering laboratory tests have been used. The geotechnical properties of soil and rocks vary from place to place due to the uneven nature of subsurface formations observed in the study areas. The constructed model ascertains the thickness, extent, and 3D distribution of the important geological units of the city. This study is the first comprehensive research work on 3D geological modeling and subsurface characterization of soils and rocks in Addis Ababa city, and the outcomes will be important for further future research on subsurface conditions in the city. Furthermore, these findings provide a reference for developing a geo-database for the city.

Keywords: 3d geological modeling, addis ababa, engineering geology, geostatistics, horizons-solid

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Authors: Kawinphat Lertpongmanee

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The purposes of this study were (1) investigate the English language learning motivation and the attainment of their English proficiency, (2) to find out how motivation and motivational variables of the high and low proficiency subjects are related to their English proficiency. The respondents were 80 fourth-year from Faculty of Management Sciences students in Rajabhat Suansunadha University. The instruments used for data collection were questionnaires. The statistically analyzed by using the SPSS program for frequency, percentage, arithmetic mean, standard deviation (SD), t-test, one-way analysis of variance (ANOVA), and Pearson correlation coefficient. The findings of this study are summarized as there was a significant difference in overall motivation between high and low proficiency groups of subjects at .05 (p < .05), but not in overall motivational variables. Additionally, the high proficiency group had a significantly higher level of intrinsic motivation than did the low proficiency group at .05 (p < .05).

Keywords: English language proficiency, faculty of management sciences, motivation factors, proficiency subjects

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Authors: Amichai Ben ari, Daniella Margalit

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Medical procedures, such as surgery, may have traumatic significance for some children. This study examines the relationship between maltreatment in children and the development Pediatric Medical Traumatic Stress (PMTS). To this end, differences in the level of distress of children after surgery were examined between two groups: children who were maltreated ("children at risk") and children from the control group ("children who are not at risk"). The study involved 230 parents of children who came to the hospital to undergo surgery. Parents filled out demographic questionnaires to measure socioeconomic variables and psychological questionnaires to measure the distress of the child and parent before surgery. After 6 months from the time of surgery, the parents again filled in the questionnaire measuring the child's distress. The results of the study showed that the level of distress experienced by children at risk after surgery was significantly higher relative to children who are not at risk. It was also found that the level of distress experienced by parents of children at risk in relation to their child’s surgery is significantly higher compared to parents of children who are not at risk. Finally, it was found that the variables: (1) pre-morbid psychological functioning of the child. (2) Parental and family functioning in daily life. (3) Exposure of the child to traumatic events. (4) Support factors for the family. Are variables that predict the development of PMTS in children after surgery, but only for children at risk and not for children who are not at risk. The significance of the findings in relation to the need to identify at-risk populations in the hospitals and the policies derived from them were discussed, and several directions were raised for further research.

Keywords: children at risk, pediatric medical traumatic stress (PMTS), PTSD, medical procedures

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Authors: Oyesoji Aremu, Taiwo Williams

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This study examined some factors (academic self-efficacy, locus of control, motivation and gender) that could predict academic dishonesty among serially frustrated students in Ogun State, South West, Nigeria. Serial academically frustrated students are students who are unable to attain and meet academic expectations set by themselves or significant others. A sample of 250 undergraduate students selected from two faculties from a University in Ogun State,South West Nigeria took part in the study. Multiple regression analysis was employed to determine the joint and relative contributions of the independent variables to the prediction of the dependent variable. T-test was used to test the hypothesis determining the gender difference between the independent variables (academic self-efficacy, locus of control and motivation) and academic dishonesty of serial academically frustrated male and female students. The results of the study showed all the independent variables jointly contributed to predicting academic dishonesty, while only academic self-efficacy and motivation had relative contributions to the dependent measure. There was no significant difference in the academic self-efficacy and motivation among males and females on academic dishonesty of the serial academically frustrated students but locus of control showed a significant difference between male and female students on academic dishonesty. Implications for counseling of the findings are discussed in the study.

Keywords: academic dishonesty, serially frustrated students, academic self-efficacy, locus of control

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Authors: Anusha Jain, Santosh Vishwanathan, Praveen K. Gupta, Shwetha S., Kavitha S. N.

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Agriculture has a major impact on the Indian economy, with the highest employment ratio than any sector of the country. Currently, most of the traditional agricultural practices and farming methods are manual, which results in farmers not realizing their maximum productivity often due to increasing in labour cost, inefficient use of water sources leading to wastage of water, inadequate soil moisture content, subsequently leading to food insecurity of the country. This research paper aims to solve this problem by developing a full-fledged web application-based platform that has the capacity to associate itself with a Microcontroller-based Automated Irrigation System which schedules the irrigation of crops based on real-time soil moisture content employing soil moisture sensors centric to the crop’s requirements using WSN (Wireless Sensor Networks) and M2M (Machine To Machine Communication) concepts, thus optimizing the use of the available limited water resource, thereby maximizing the crop yield. This robust automated irrigation system provides end-to-end automation of Irrigation of crops at any circumstances such as droughts, irregular rainfall patterns, extreme weather conditions, etc. This platform will also be capable of achieving a nationwide united farming community and ensuring the welfare of farmers. This platform is designed to equip farmers with prerequisite knowledge on tech and the latest farming practices in general. In order to achieve this, the MailChimp mailing service is used through which interested farmers/individuals' email id will be recorded and curated articles on innovations in the world of agriculture will be provided to the farmers via e-mail. In this proposed system, service is enabled on the platform where nearby crop vendors will be able to enter their pickup locations, accepted prices and other relevant information. This will enable farmers to choose their vendors wisely. Along with this, we have created a blogging service that will enable farmers and agricultural enthusiasts to share experiences, helpful knowledge, hardships, etc., with the entire farming community. These are some of the many features that the platform has to offer.

Keywords: WSN (wireless sensor networks), M2M (M/C to M/C communication), automation, irrigation system, sustainability, SAAS (software as a service), soil moisture sensor

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Authors: R. Gounina-Allouane, I. Moussaoui, N. Boukahel

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Bacillus antimicrobial metabolites, especially those of Bacillus thuringiensis (Bt), are of great interest for research because of health risks generated by the excessive use of chemical additives as well as the propagation of resistant microbial strains, caused by the massive treatment with antibiotics. The objective of this study was the selection of Bt strains producing antimicrobial peptides (bacteriocins), and the partial purification of the most powerful bacteriocins, then the determination of their spectra of antimicrobial action. A collection of twenty one Bt strains isolated from soil at Boumerdès (northern Algeria) was used for screening strains having an antagonistic activity against phylogenetically closed bacteria. Spectra of antagonistic activity of two selected strains was determined against other Bt strains, Gram positive and Gram negative bacterial strains of clinical origin and others from ATCC collection as well as yeasts isolated in human dermatology. Bacteriocins of these two strains were partially purified and their effect on the kinetics of growth of the most sensitive microbial strains was studied. The bacteriocinogenic strains were biochemically characterized and their sensitivity to antibiotics was studied.

Keywords: antimicrobial peptides, Bacillus thuringiensis, bacteriocin, partial purification

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Authors: Marziyeh Khavari

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In recent decades, climate change, global warming, and the growing population worldwide face some challenges, such as increasing food consumption and shortage of resources. Assessing how climate change could disturb crops, especially hazelnut production, seems crucial for sustainable agriculture production. For hazelnut cultivation in the mid-warm condition, such as in Iran, here we present an investigation of climate parameters and how much they are effective on fertility and nut production of hazelnut trees. Therefore, the climate change of the northern zones in Iran has investigated (1960-2017) and was reached an uptrend in temperature. Furthermore, the descriptive analysis performed on six cultivars during seven years shows how this small-scale survey could demonstrate the effects of climate change on hazelnut production and stability. Results showed that some climate parameters are more significant on nut production, such as solar radiation, soil temperature, relative humidity, and precipitation. Moreover, some cultivars have produced more stable production, for instance, Negret and Segorbe, while the Mervill de Boliver recorded the most variation during the study. Another aspect that needs to be met is training and predicting an actual model to simulate nut production through a neural network and linear regression simulation. The study developed and estimated the ANN model's generalization capability with different criteria such as RMSE, SSE, and accuracy factors for dependent and independent variables (environmental and yield traits). The models were trained and tested while the accuracy of the model is proper to predict hazelnut production under fluctuations in weather parameters.

Keywords: climate change, neural network, hazelnut, global warming

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Authors: Praveen Vayalamkuzhi, Veeraragavan Amirthalingam

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Studies on safety on highways are becoming the need of the hour as over 400 lives are lost every day in India due to road crashes. In order to evaluate the factors that lead to different levels of crash severity, it is necessary to investigate the level of safety of highways and their relation to crashes. In the present study, an attempt is made to identify the factors that contribute to road crashes and to quantify their effect on the severity of road crashes. The study was carried out on a four-lane divided rural highway in India. The variables considered in the analysis includes components of horizontal alignment of highway, viz., straight or curve section; time of day, driveway density, presence of median; median opening; gradient; operating speed; and annual average daily traffic. These variables were considered after a preliminary analysis. The major complexities in the study are the heterogeneous traffic and the speed variation between different classes of vehicles along the highway. To quantify the impact of each of these factors, statistical analyses were carried out using Logit model and also negative binomial regression. The output from the statistical models proved that the variables viz., horizontal components of the highway alignment; driveway density; time of day; operating speed as well as annual average daily traffic show significant relation with the severity of crashes viz., fatal as well as injury crashes. Further, the annual average daily traffic has significant effect on the severity compared to other variables. The contribution of highway horizontal components on crash severity is also significant. Logit models can predict crashes better than the negative binomial regression models. The results of the study will help the transport planners to look into these aspects at the planning stage itself in the case of highways operated under heterogeneous traffic flow condition.

Keywords: geometric design, heterogeneous traffic, road crash, statistical analysis, level of safety

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Authors: Hassan Sadeghi Naeini, Mozhgan Sabzehparvar, Mahdiye Jafarnezhad, Neda Brumandi, Mohammad Parsa Sabzehparvar

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This study aims to discover the relationship between the factors of aesthetics, user experience, and social sustainability concerning the design of street furniture and the impact of these factors on the emotional arousal of citizens to encourage and make them prefer to use street furniture. The method used in this research included extracting indicators related to each of the factors of aesthetics, user experience, and social sustainability from the articles and then selecting indicators related to the purpose of the research in consultation with industrial design experts and architects. Finally, 9 variables for aesthetics, 7 variables for user experience, and 5 variables for evaluating social sustainability were selected. To identify the effect of each of these factors on street furniture and to recognize their relationship with each other. A 10-scale prioritization questionnaire, from 1, the least amount of importance, to 10, the most amount of importance, was answered by architects and industrial designers on the “Pors Line” online platform for three consecutive weeks, and a total of 82 people answered the questionnaire. The results showed that by using aesthetic factors in the design of street furniture and having a positive impact on users’ experience of using the product, we could expect the occurrence of behavioral factors, such as creating constructive interaction and product acceptance so that the satisfaction of the user in the use of street furniture and optimal interaction in the urban environment is formed, followed by that, the requirements of social sustainability will be met.

Keywords: visual aesthetic, user experience, social sustainability, street furniture

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Authors: Marcio Freire Cruz, Naoaki Ono, Shigehiko Kanaya, Carlos Arthur Mattos Teixeira Cavalcante

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The systems that record patient care information, known as Electronic Medical Record (EMR) and those that monitor vital signs of patients, such as heart rate, body temperature, and blood pressure have been extremely valuable for the effectiveness of the patient’s treatment. Several kinds of research have been using data from EMRs and vital signs of patients to predict illnesses. Among them, we highlight those that intend to predict, classify, or, at least identify patterns, of sepsis illness in patients under vital signs monitoring. Sepsis is an organic dysfunction caused by a dysregulated patient's response to an infection that affects millions of people worldwide. Early detection of sepsis is expected to provide a significant improvement in its treatment. Preceding works usually combined medical, statistical, mathematical and computational models to develop detection methods for early prediction, getting higher accuracies, and using the smallest number of variables. Among other techniques, we could find researches using survival analysis, specialist systems, machine learning and deep learning that reached great results. In our research, patients are modeled as points moving each hour in an n-dimensional space where n is the number of vital signs (variables). These points can reach a sepsis target point after some time. For now, the sepsis target point was calculated using the median of all patients’ variables on the sepsis onset. From these points, we calculate for each hour the position vector, the first derivative (velocity vector) and the second derivative (acceleration vector) of the variables to evaluate their behavior. And we construct a prediction model based on a Long Short-Term Memory (LSTM) Network, including these derivatives as explanatory variables. The accuracy of the prediction 6 hours before the time of sepsis, considering only the vital signs reached 83.24% and by including the vectors position, speed, and acceleration, we obtained 94.96%. The data are being collected from Medical Information Mart for Intensive Care (MIMIC) Database, a public database that contains vital signs, laboratory test results, observations, notes, and so on, from more than 60.000 patients.

Keywords: dynamic analysis, long short-term memory, prediction, sepsis

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Authors: Flavia Cordeiro, Fabio Silva, Alvaro Eiras, Jose Luiz Acebal

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Aedes aegypti is present in the tropical and subtropical regions of the world and is a vector of several diseases such as dengue fever, yellow fever, chikungunya, zika etc. The growth in the number of arboviruses cases in the last decades became a matter of great concern worldwide. Meteorological factors like mean temperature and precipitation are known to influence the infestation by the species through effects on physiology and ecology, altering the fecundity, mortality, lifespan, dispersion behaviour and abundance of the vector. Models able to describe the dynamics of the vector population size should then take into account the meteorological variables. The relationship between meteorological factors and the population dynamics of Ae. aegypti adult females are studied to provide a good set of predictors to model the dynamics of the mosquito population size. The time-series data of capture of adult females of a public health surveillance program from the city of Lavras, MG, Brazil had its association with precipitation, humidity and temperature analysed through a set of statistical methods for time series analysis commonly adopted in Signal Processing, Information Theory and Neuroscience. Cross-correlation, multicollinearity test and whitened cross-correlation were applied to determine in which time lags would occur the influence of meteorological variables on the dynamics of the mosquito abundance. Among the findings, the studied case indicated strong collinearity between humidity and precipitation, and precipitation was selected to form a pair of descriptors together with temperature. In the techniques used, there were observed significant associations between infestation indicators and both temperature and precipitation in short, mid and long terms, evincing that those variables should be considered in entomological models and as public health indicators. A descriptive model used to test the results exhibits a strong correlation to data.

Keywords: Aedes aegypti, cross-correlation, multicollinearity, meteorological variables

Procedia PDF Downloads 163