Search results for: panel data regression analysis

Authors: Encarnación Álvarez, Rosa M. García-Fernández, Juan F. Muñoz

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Estimation of a proportion has many applications in economics and social studies. A common application is the estimation of the low income proportion, which gives the proportion of people classified as poor into a population. In this paper, we present this poverty indicator and propose to use the logistic regression estimator for the problem of estimating the low income proportion. Various sampling designs are presented. Assuming a real data set obtained from the European Survey on Income and Living Conditions, Monte Carlo simulation studies are carried out to analyze the empirical performance of the logistic regression estimator under the various sampling designs considered in this paper. Results derived from Monte Carlo simulation studies indicate that the logistic regression estimator can be more accurate than the customary estimator under the various sampling designs considered in this paper. The stratified sampling design can also provide more accurate results.

Keywords: poverty line, risk of poverty, auxiliary variable, ratio method

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Authors: Kiurski S. Jelena, Kecić S. Vesna, Aksentijević M. Snežana

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Samples of tap and wastewater were collected in three offset printing facilities in Novi Sad, Serbia. Ten physicochemical parameters were analyzed within all collected samples: pH, conductivity, m - alkalinity, p - alkalinity, acidity, carbonate concentration, hydrogen carbonate concentration, active oxygen content, chloride concentration and total alkali content. All measurements were conducted using the standard analytical and instrumental methods. Comparing the obtained results for tap water and wastewater, a clear quality difference was noticeable, since all physicochemical parameters were significantly higher within wastewater samples. The study also involves the application of simple linear regression analysis on the obtained dataset. By using software package ORIGIN 5 the pH value was mutually correlated with other physicochemical parameters. Based on the obtained values of Pearson coefficient of determination a strong positive correlation between chloride concentration and pH (r = -0.943), as well as between acidity and pH (r = -0.855) was determined. In addition, statistically significant difference was obtained only between acidity and chloride concentration with pH values, since the values of parameter F (247.634 and 182.536) were higher than F_critical (5.59). In this way, results of statistical analysis highlighted the most influential parameter of water contamination in offset printing, in the form of acidity and chloride concentration. The results showed that variable dependence could be represented by the general regression model: y = a₀ + a₁x+ k, which further resulted with matching graphic regressions.

Keywords: pollution, printing industry, simple linear regression analysis, wastewater

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Authors: Rajarshi Sharma, Rashidul Alam, Visavino Seleyi, Yuvila Sangtam

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The Intensity-Duration-Frequency (IDF) relationship of rainfall amounts is one of the most commonly used tools in water resources engineering for planning, design and operation of water resources project, or for various engineering projects against design floods. The establishment of such relationships was reported as early as in 1932 (Bernard). Since then many sets of relationships have been constructed for several parts of the globe. The objective of this research is to derive IDF relationship of rainfall for western watershed of Guwahati, Assam. These relationships are useful in the design of urban drainage works, e.g. storm sewers, culverts and other hydraulic structures. In the study, rainfall depth for 10 years viz. 2001 to 2010 has been collected from the Regional Meteorological Centre Borjhar, Guwahati. Firstly, the data has been used to construct the mass curve for duration of more than 7 hours rainfall to calculate the maximum intensity and to form the intensity duration curves. Gumbel’s frequency analysis technique has been used to calculate the probable maximum rainfall intensities for a period of 2 yr, 5 yr, 10 yr, 50 yr, 100 yr from the maximum intensity. Finally, regression analysis has been used to develop the intensity-duration-frequency (IDF) curve. Thus, from the analysis the values for the constants ‘a’,‘b’ &‘c’ have been found out. The values of ‘a’ for which the sum of the squared deviation is minimum has been found out to be 40 and when the corresponding value of ‘c’ and ‘b’ for the minimum squared deviation of ‘a’ are 0.744 and 1981.527 respectively. The results obtained showed that in all the cases the correlation coefficient is very high indicating the goodness of fit of the formulae to estimate IDF curves in the region of interest.

Keywords: intensity-duration-frequency relationship, mass curve, regression analysis, correlation coefficient

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Authors: Renata Konadu

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Over the last two decades, the concept of environmental management and its related issues have received increased attention in global discourse and on management research agenda due to climate change and other environmental challenges. To abate and avert these challenges, diverse environmental policies, strategies and practices have been adopted by businesses and economies as a whole. Extant literature has placed much emphasis on whether improved environmental operational performance improves firm performance. However, there is a huge gap in the literature with regards to whether the adoption of environmental management practices and policies has a direct relationship with environmental operational performance (EOP). The current paper is intended to provide a comprehensive perspective of how different aspects of environmental management can relate to firms EOP. Using a panel regression analysis of 149 large listed firms in the UK, the study found evidence of both negative and positive statistically significant link between some Environmental Policies (EP), Environmental Processes (EPR), Environmental Management Systems (EMS) and EOP. The findings suggest that in terms of relating EP, EPR and EMS to Greenhouse Gases (GHGs) emissions for instance, the latter should be viewed separately in Scopes 1, 2 and 3 as developed by GHG protocol. The results have useful implication for policy makers and managers when designing strategies and policies to reduce negative environmental impacts.

Keywords: environmental management, environmental operational performance, GHGs, large listed firms

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Authors: Abdullahi Yahaya Musa, Harun Rann Bakari

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The study examined the determinants of food security among households in Maiduguri, Metropolis, Borno State, Nigeria. The objectives of the study are to: examine the determinants of food security among households; identify the coping strategies employed by food-insecure households in Maiduguri, Metropolis, Borno State, Nigeria. The population of the study is 843,964 respondents out of which 400 respondents were sampled. The study used a self-developed questionnaire to collect data from four hundred (400) respondents. Four hundred (400) copies of questionnaires were administered and all were retrieved, making 100% return rate. The study employed descriptive and inferential statistics for data analysis. Descriptive statistics (frequency counts and percentages) was used to analyze the socio-economic characteristics of the respondents and objective four, while inferential statistics (logit regression analysis) was used to analyze one. Four hundred (400) copies of questionnaires were administered and all the four hundred (400) were retrieved, making a 100% return rate. The results were presented in tables and discussed according to the research objectives. The study revealed that HHA, HHE, HHSZ, HHSX, HHAS, HHI, HHFS, HHFE, HHAC and HHCDR were the determinants of food security in Maiduguri Metropolis. Relying on less preferred foods, purchasing food on credit, limiting food intake to ensure children get enough, borrowing money to buy foodstuffs, relying on help from relatives or friends outside the household, adult family members skipping or reducing a meal because of insufficient finances and ration money to household members to buy street food were the coping strategies employed by food-insecure households in Maiduguri metropolis. The study recommended that Nigeria Government should intensify the fight against the Boko haram insurgency. This will put an end to Boko Haram Insurgency and enable farmers to return to farming in Borno state.

Keywords: internally displaced persons, food security, coping strategies, descriptive statistics, logistics regression model, odd ratio

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Authors: Sheraz Gul

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The requirements for progressing a compound to clinical trials is well established and relies on the results from in-vitro and in-vivo animal tests to indicate that it is likely to be safe and efficacious when testing in humans. The typical data package required will include demonstrating compound safety, toxicity, bioavailability, pharmacodynamics (potential effects of the compound on body systems) and pharmacokinetics (how the compound is potentially absorbed, distributed, metabolised and eliminated after dosing in humans). If the desired criteria are met and the compound meets the clinical Candidate criteria and is deemed worthy of further development, a submission to regulatory bodies such as the US Food & Drug Administration for an exploratory Investigational New Drug Study can be made. The purpose of this study is to collect data to establish that the compound will not expose humans to unreasonable risks when used in limited, early-stage clinical studies in patients or normal volunteer subjects (Phase I). These studies are also designed to determine the metabolism and pharmacologic actions of the drug in humans, the side effects associated with increasing doses, and, if possible, to gain early evidence on their effectiveness. In order to reach the above goals, we have developed a pre-clinical high throughput Absorption, Distribution, Metabolism and Excretion–Toxicity (ADME–Toxicity) panel of assays to identify compounds that are likely to meet the Lead and Candidate compound acceptance criteria. This panel includes solubility studies in a range of biological fluids, cell viability studies in cancer and primary cell-lines, mitochondrial toxicity, off-target effects (across the kinase, protease, histone deacetylase, phosphodiesterase and GPCR protein families), CYP450 inhibition (5 different CYP450 enzymes), CYP450 induction, cardio-toxicity (hERG) and gene-toxicity. This panel of assays has been applied to multiple compound series developed in a number of projects delivering Lead and clinical Candidates and examples from these will be presented.

Keywords: absorption, distribution, metabolism and excretion–toxicity , drug discovery, food and drug administration , pharmacodynamics

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Authors: B. Hossen, Y. Helmut

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Soil salinity is a major problem for the coastal region of Bangladesh, which has been increasing for the last four decades. Determination of soil salinity is essential for proper land use planning for agricultural crop production. The aim of the research is to estimate and monitor the soil salinity in the study area. Remote sensing can be an effective tool for detecting soil salinity in data-scarce conditions. In the research, Landsat 8 is used, which required atmospheric and radiometric correction, and nine soil salinity indices are applied to develop a soil salinity map. Ground soil salinity data, i.e., EC value, is collected as a printed map which is then scanned and digitized to develop a point shapefile. Linear regression is made between satellite-based generated map and ground soil salinity data, i.e., EC value. The results show that maximum R² value is found for salinity index SI 7 = G*R/B representing 0.022. This minimal R² value refers that there is a negligible relationship between ground EC value and salinity index generated value. Hence, these indices are not appropriate to assess soil salinity though many studies used those soil salinity indices successfully. Therefore, further research is necessary to formulate a model for determining the soil salinity in the coastal of Bangladesh.

Keywords: soil salinity, EC, Landsat 8, salinity indices, linear regression, remote sensing

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Authors: İsmail İnce

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The aim of this study is to determine index and mechanical properties of pyroclastic rock in a practical way by means of electrical resistivity method. For this purpose, electrical resistivity, uniaxial compressive strength, point load strength, P-wave velocity, density and porosity values of 10 different pyroclastic rocks were measured in the laboratory. A simple regression analysis was made among the index-mechanical properties of the samples compatible with electrical resistivity values. A strong exponentially relation was found between index-mechanical properties and electrical resistivity values. The electrical resistivity method can be used to assess the engineering properties of the rock from which it is difficult to obtain regular shaped samples as a non-destructive method.

Keywords: electrical resistivity, index-mechanical properties, pyroclastic rocks, regression analysis

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Authors: Zunaidah Ab Hasan, Azhana Othman, Abd Halim Mohd Noor, Nor Shahrina Mohd Rafien

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Zakat is a portion of wealth contributed from financially able Muslims to be distributed to predetermine recipients; main among them are the poor and the needy. Distribution of the zakat fund is given with the objective to lift the recipients from poverty. Due to the multidimensional and multifaceted nature of poverty, it is imperative that the causes of poverty are properly identified for assistance given by zakat authorities reached the intended target. Despite, various studies undertaken to identify the poor correctly, there are reports of the poor not receiving the adequate assistance required from zakat. Thus, this study examines the determinants of poverty among applicants for zakat assistance distributed by the State Islamic Religious Council in Malacca (SIRCM). Malacca is a state in Malaysia. The respondents were based on the list of names of new zakat applicants for the month of April and May 2014 provided by SIRCM. A binary logistic regression was estimated based on this data with either zakat applications is rejected or accepted as the dependent variable and set of demographic variables and health as the explanatory variables. Overall, the logistic model successfully predicted factors of acceptance of zakat applications. Three independent variables namely gender, age; size of households and health significantly explain the likelihood of a successful zakat application. Among others, the finding suggests the importance of focusing on providing education opportunity in helping the poor.

Keywords: logistic regression, zakat distribution, status of zakat applications, poverty, education

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Authors: Li-Ching Chen

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The case-control design has been widely applied in clinical and epidemiological studies to investigate the association between risk factors and a given disease. The retrospective design can be easily implemented and is more economical over prospective studies. To adjust effects for confounding factors, methods such as stratification at the design stage and may be adopted. When some major confounding factors are difficult to be quantified, a matching design provides an opportunity for researchers to control the confounding effects. The matching effects can be parameterized by the intercepts of logistic models and the conditional logistic regression analysis is then adopted. This study demonstrates an information-matrix-based goodness-of-fit statistic to test the validity of the logistic regression model for matched case-control data. The asymptotic null distribution of this proposed test statistic is inferred. It needs neither to employ a simulation to evaluate its critical values nor to partition covariate space. The asymptotic power of this test statistic is also derived. The performance of the proposed method is assessed through simulation studies. An example of the real data set is applied to illustrate the implementation of the proposed method as well.

Keywords: conditional logistic model, goodness-of-fit, information matrix, matched case-control studies

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Authors: Raed Alsufyani, Hissam Tawfik, Victor Chang, Muthu Ramachandran

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This study investigates the factors that influence the decision by players in the healthcare sector to embrace Cloud Business Intelligence Technology with a focus on healthcare organizations in Saudi Arabia. To bring this matter into perspective, this study primarily considers the Technology-Organization-Environment (TOE) framework and the Human Organization-Technology (HOT) fit model. A survey was hypothetically designed based on literature review and was carried out online. Quantitative data obtained was processed from descriptive and one-way frequency statistics to inferential and regression analysis. Data were analysed to establish factors that influence the decision to adopt Cloud Business intelligence technology in the healthcare sector. The implication of the identified factors was measured, and all assumptions were tested. 66.70% of participants in healthcare organization backed the intention to adopt cloud business intelligence system. 99.4% of these participants considered security concerns and privacy risk have been the most significant factors in the adoption of cloud Business Intelligence (CBI) system. Through regression analysis hypothesis testing point that usefulness, service quality, relative advantage, IT infrastructure preparedness, organization structure; vendor support, perceived technical competence, government support, and top management support positively and significantly influence the adoption of (CBI) system. The paper presents quantitative phase that is a part of an on-going project. The project will be based on the consequences learned from this study.

Keywords: cloud computing, business intelligence, HOT-fit model, TOE, healthcare and innovation adoption

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Authors: Azza T. Tahera, Eman M. Ahmeda, Nadia A. Khalila, Yassin M. Nissanb

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New 3-(pyridin-4-yl)-[1,2,4] triazolo [4,3-b] pyridazine derivatives 2a-i, 4a,b and 6a,b were designed, synthesized and evaluated as cytotoxic agents. All compounds were investigated for their in vitro cytotoxicity at a single dose 10-5M concentration towards 60 cancer cell lines according to USA NCI protocol. The preliminary screening results showed that the majority of tested compounds exhibited remarkable activity against SR (leukemia) cell panel. Molecular docking for all synthesized compounds was performed on the active site of c-Met kinase. The most active compounds, 2f and 4a were further evaluated at a seven dose level screening and their IC50 as a c-Met kinase inhibitors were determined in vitro.

Keywords: triazolopyridazines, pyridazines, cytotoxic activity, cell panel

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Authors: M. Atef Gabr, M. H. Abdel Latif, Ramadan El Gamsy

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Sandwich panels comprise a thick, light-weight plastic foam such as polyurethane (PU) sandwiched between two relatively thin faces. One or both faces may be flat, lightly profiled or fully profiled. Until recently sandwich panel construction in Egypt has been widely used in cold-storage buildings, cold trucks, prefabricated buildings and insulation in construction. Recently new techniques are used in mass production of Sandwich Materials such as Reaction Injection Molding (RIM) and Vacuum bagging technique. However, in recent times their use has increased significantly due to their widespread structural applications in building systems. Structural sandwich panels generally used in Egypt comprise polyurethane foam core and thinner (0.42 mm) and high strength about 550 MPa (yield strength) flat steel faces bonded together using separate adhesives and By RIM technique. In this paper, we will use a new technique in sandwich panel preparation by using different face sheet materials in combination with polyurethane foam to form sandwich panel structures. Previously, PU Foam core with same thin 2 faces material was used, but in this work, we use different face materials and thicknesses for the upper face sheet such as Galvanized steel sheets (G.S),Aluminum sheets (Al),Fiberglass sheets (F.G) and Aluminum-Rubber composite sheets (Al/R) with polyurethane foam core 10 mm thickness and 45 Kg/m3 Density and Galvanized steel as lower face sheet. Using Aluminum-Rubber composite sheets as face sheet is considered a hybrid composite sandwich panel which is built by Hand-Layup technique by using PU glue as adhesive. This modification increases the benefits of the face sheet that will withstand different working environments with relatively small increase in its weight and will be useful in several applications. In this work, a 3-point bending test is used assistant professor to measure the most important factor in sandwich materials that is strength to weight ratio(STW) for different combinations of sandwich structures and make a comparison to study the effect of changing the face sheet material on the mechanical behavior of PU sandwich material. Also, the density of the different prepared sandwich materials will be measured to obtain the specific bending strength.

Keywords: hybrid sandwich panel, mechanical behavior, PU foam, sandwich panel, 3-point bending, flexural strength

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Authors: Leng Jian-Wei, Wang Lai-Jun, Li Ye

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In order to measure and analyze the transportation situation within the counties of Shaanxi province over a certain period of time and to promote the province's future transportation planning and development, this paper proposes a reasonable layout plan and compares model rationality. The study uses entropy weight method to measure the transportation advantages of 107 counties in Shaanxi province from three dimensions: road network density, trunk line influence and location advantage in 2013 and 2021, and applies spatial autocorrelation analysis method to analyze the spatial layout and development trend of county-level transportation, and conducts ordinary least square (OLS)regression on transportation impact factors and other influencing factors. The paper also compares the regression fitting degree of the Geographically weighted regression(GWR) model and the OLS model. The results show that spatially, the transportation advantages of Shaanxi province generally show a decreasing trend from the Weihe Plain to the surrounding areas and mainly exhibit high-high clustering phenomenon. Temporally, transportation advantages show an overall upward trend, and the phenomenon of spatial imbalance gradually decreases. People's travel demands have changed to some extent, and the demand for rapid transportation has increased overall. The GWR model regression fitting degree of transportation advantages is 0.74, which is higher than the OLS regression model's fitting degree of 0.64. Based on the evolution of transportation advantages, it is predicted that this trend will continue for a period of time in the future. To improve the transportation advantages of Shaanxi province increasing the layout of rapid transportation can effectively enhance the transportation advantages of Shaanxi province. When analyzing spatial heterogeneity, geographic factors should be considered to establish a more reliable model

Keywords: traffic dominance, GWR model, spatial autocorrelation analysis, temporal and spatial evolution

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Authors: Zuoyong Zhang, Min Yu, Jinlong Zhao, Shudong He

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The Maillard reaction can produce the flavor enhancing substance through the chemical crosslinking between free amino group of the protein or polypeptide with the carbonyl of the reducing sugar. In this research, solutions of rapeseed meal peptide and D-xylose with or without L-cysteine (RXC or RX) were heated over a range of temperatures (80-140 °C) for 2 h. It was observed that RXs had a severe browning,while RXCs accompanied by more pH decrement with the temperature increasing. Then the correlation among data of quantitative sensory descriptive analysis, free amino acid (FAA) and GC–MS of RXCs and RXs were analyzed using the partial least square regression method. Results suggested that the Maillard reaction product (MRPs) with cysteine formed at 120 °C (RXC-120) had greater sensory properties especially meat-like flavor compared to other MRPs. Meanwhile, it revealed that glutamic and glycine not only had a positive contribution to meaty aroma but also showed a significant and positive influence on umami taste of RXs based on the FAA data. Moreover, the sulfur-containing compounds showed a significant positive correlation with the meat-like flavor of RXCs, while RXs depended on furans and nitrogenous-containing compounds with more caramel-like flavor. Therefore, a MRP with strong meaty flavor could be obtained at 120 °C by addition of cysteine.

Keywords: rapeseed meal, Maillard reaction, sensory characteristics, FAA, GC–MS, partial least square regression

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Authors: Bilgen Ozluk, Ayfer Karaaslan

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Introduction: Adaptation to university life is a difficult process for students. In peer support, students are expected to help other students or sometimes adults using their helping skills. Therefore, it is expected that peer support will have significant effect on students’ adaptation to university life. Aim: This study was conducted with the aim of determining the effect of peer support on adaptation to university life in the first year students of the faculty of health sciences. Methods: The population consists of 340 first year university students receiving education in the departments of nursing, health management, social services, nutrition and dietetics, physiotherapy and rehabilitation at an university located in the province of Konya. The sample of the study consisted of 274 students who voluntarily participated in the study. The data were collected between the dates 23 May 2016 and 3 June 2016. The data were collected using the socio-demographic information, the peer support scale and the university life adaptation scale. Ethical approvals for the study and permission from the university were taken. Numbers, percentages, averages, one-Way ANOVA, pearson correlation analysis and regression analysis have been used in assessing the data. Findings: When the problems most frequently encountered by students just starting the university were ordered, problems regarding their classes took the first place by 41.6%, socio-cultural problems took the second place by 38.7%, and economic problems took the third place by 37.6%. The mean total score of the Adaptation to University Life Scale was found to be 216.78±32.15. Considering that the lowest and highest scores that can be gained from the scale are 132 and 289 respectively, it was found that the adaptation to university life levels of the students were higher than the average. The mean adaptation to university life score of the nursing students was higher than those of the students of other departments. The mean score of ‘the Peer Support Scale’ was found to be 47.24±10.27. Considering that the lowest and highest scores that can be gained from the scale are 17 and 68 respectively, it was found that the peer support levels of the students were higher than the average. As a result of the regression analysis, it was found that 20% of the total variance regarding adaptation to university life was explained by peer support. Conclution: Receiving the support peer groups becomes highly important in the university adaptation process of first-year students. Peer support will create the means for easier completion of this difficult transition process.

Keywords: adaptation to university life, first years, peer support, university student

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Authors: Surya R. Niraula, Devendra B Chhetry, Girish K. Singh, S. Nagesh, Frederick A. Connell

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Background: Although random sampling is generally considered to be the gold standard for population-based research, the majority of drug abuse research is based on non-random sampling despite the well-known limitations of this kind of sampling. Method: We compared the statistical properties of two surveys of drug abuse in the same community: one using snowball sampling of drug users who then identified “friend controls” and the other using a random sample of non-drug users (controls) who then identified “friend cases.” Models to predict drug abuse based on risk factors were developed for each data set using conditional logistic regression. We compared the precision of each model using bootstrapping method and the predictive properties of each model using receiver operating characteristics (ROC) curves. Results: Analysis of 100 random bootstrap samples drawn from the snowball-sample data set showed a wide variation in the standard errors of the beta coefficients of the predictive model, none of which achieved statistical significance. One the other hand, bootstrap analysis of the random-sample data set showed less variation, and did not change the significance of the predictors at the 5% level when compared to the non-bootstrap analysis. Comparison of the area under the ROC curves using the model derived from the random-sample data set was similar when fitted to either data set (0.93, for random-sample data vs. 0.91 for snowball-sample data, p=0.35); however, when the model derived from the snowball-sample data set was fitted to each of the data sets, the areas under the curve were significantly different (0.98 vs. 0.83, p < .001). Conclusion: The proposed method of random sampling of controls appears to be superior from a statistical perspective to snowball sampling and may represent a viable alternative to snowball sampling.

Keywords: drug abuse, matched case-control study, non-probability sampling, probability sampling

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Authors: Jingjue Bao, Ye Li, Yujie Qi

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The explosive growth of ride-hailing has reshaped residents' travel behavior and plays a crucial role in urban mobility within the built environment. Contributing to the research of the spatial variation of ride-hailing demand and its relationship to the built environment and socioeconomic factors, this study utilizes multi-source data from Haikou, China, to construct a Multi-scale Geographically Weighted Regression model (MGWR), considering spatial scale heterogeneity. The regression results showed that MGWR model was demonstrated superior interpretability and reliability with an improvement of 3.4% on R2 and from 4853 to 4787 on AIC, compared with Geographically Weighted Regression model (GWR). Furthermore, to precisely identify the surrounding environment of sampling point, DeepLabv3+ model is employed to segment street-level images. Features extracted from these images are incorporated as variables in the regression model, further enhancing its rationality and accuracy by 7.78% improvement on R2 compared with the MGWR model only considered region-level variables. By integrating multi-scale geospatial data and utilizing advanced computer vision techniques, this study provides a comprehensive understanding of the spatial dynamics between ride-hailing demand and the urban built environment. The insights gained from this research are expected to contribute significantly to urban transportation planning and policy making, as well as ride-hailing platforms, facilitating the development of more efficient and effective mobility solutions in modern cities.

Keywords: travel behavior, ride-hailing, spatial relationship, built environment, street-level image

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Authors: Mike Tsionas

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The paper develops new indices of financial stability based on an explicit model of expected utility maximization by financial institutions subject to the classical technology restrictions of neoclassical production theory. The model can be estimated using standard econometric techniques, like GMM for dynamic panel data and latent factor analysis for the estimation of co-variance matrices. An explicit functional form for the utility function is not needed and we show how measures of risk aversion and prudence (downside risk aversion) can be derived and estimated from the model. The model is estimated using data for Eurozone countries and we focus particularly on (i) the use of the modeling approach as an “early warning mechanism”, (ii) the bank- and country-specific estimates of risk aversion and prudence (downside risk aversion), and (iii) the derivation of a generalized measure of risk that relies on loan-price uncertainty.

Keywords: financial stability, banking, expected utility maximization, sub-prime crisis, financial crisis, eurozone, PIIGS

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Authors: Asowata Osamede

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Optimized gain in respect to output power of stand-alone photovoltaic (PV) systems is one of the major focus of PV in recent times. This is evident to its low carbon emission and efficiency. Power failure or outage from commercial providers in general does not promote development to the public and private sector, these basically limit the development of industries. The need for a well-structured PV system is of importance for an efficient and cost-effective monitoring system. The purpose of this paper is to validate the maximum power point of an off-grid PV system taking into consideration the most effective tilt and orientation angles for PV's in the southern hemisphere. This paper is based on analyzing the system using a solar charger with MPPT from a pulse width modulation (PWM) perspective. The power conditioning device chosen is a solar charger with MPPT. The practical setup consists of a PV panel that is set to an orientation angle of 0o north, with a corresponding tilt angle of 36 o, 26o and 16o. The load employed in this set-up are three Lead Acid Batteries (LAB). The percentage fully charged, charging and not charging conditions are observed for all three batteries. The results obtained in this research is used to draw the conclusion that would provide a benchmark for researchers and scientist worldwide. This is done so as to have an idea of the best tilt and orientation angles for maximum power point in a basic off-grid PV system. A quantitative analysis would be employed in this research. Quantitative research tends to focus on measurement and proof. Inferential statistics are frequently used to generalize what is found about the study sample to the population as a whole. This would involve: selecting and defining the research question, deciding on a study type, deciding on the data collection tools, selecting the sample and its size, analyzing, interpreting and validating findings Preliminary results which include regression analysis (normal probability plot and residual plot using polynomial 6) showed the maximum power point in the system. The best tilt angle for maximum power point tracking proves that the 36o tilt angle provided the best average on time which in turns put the system into a pulse width modulation stage.

Keywords: power-conversion, meteonorm, PV panels, DC-DC converters

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

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

Keywords: accidents, BFI, probability, simulator

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Authors: Cecília M. Antão, Paulo Jorge Nogueira

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Breast cancer (BC) is the first cause of cancer mortality among Portuguese women. This retrospective observational study aimed at identifying comorbidities associated with BC female patients admitted to Portuguese public hospitals (2010-2018), investigating the effect of comorbidities on BC mortality rate, and building a predictive model using logistic regression. Results showed that the BC mortality in Portugal decreased in this period and reached 4.37% in 2018. Adjusted odds ratio indicated that secondary malignant neoplasms of liver, of bone and bone marrow, congestive heart failure, and diabetes were associated with an increased chance of dying from breast cancer. Although the Lisbon district (the most populated area) accounted for the largest percentage of BC patients, the logistic regression model showed that, besides patient’s age, being resident in Bragança, Castelo Branco, or Porto districts was directly associated with an increase of the mortality rate.

Keywords: breast cancer, comorbidities, logistic regression, adjusted odds ratio

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Authors: Keiko Naito, Y. Nakashima, S. Yamauchi, Y. Kunitani, Y. Ishigami, K. Numata, M. Mizobe, Y. Homma, J. Takahashi, T. Inoue, T. Shiga, H. Funakoshi

Abstract:

Background: A presence of severe acidemia, defined as pH < 7.2, is common during endotracheal intubation for critically ill patients in the emergency department (ED). Severe acidemia is widely recognized as a predisposing factor for intubation failure. However, it is unclear that acidemic condition itself actually makes endotracheal intubation more difficult. We aimed to evaluate if a presence of severe acidemia before intubation is associated with the lower first attempt intubation success rate in the ED. Methods: This is a retrospective observational cohort study in the ED of an urban hospital in Japan. The collected data included patient demographics, such as age, sex, and body mass index, presence of one or more factors of modified LEMON criteria for predicting difficult intubation, reasons for intubation, blood gas levels, airway equipment, intubation by emergency physician or not, and the use of the rapid sequence intubation technique. Those with any of the following were excluded from the analysis: (1) no blood gas drawn before intubation, (2) cardiopulmonary arrest, and (3) under 18 years of age. The primary outcome was the first attempt intubation success rates between a severe acidemic patients (SA) group and a non-severe acidemic patients (NA) group. Logistic regression analysis was used to test the first attempt success rates for intubations between those two groups. Results: Over 5 years, a total of 486 intubations were performed; 105 in the SA group and 381 in the NA group. The univariate analysis showed that the first attempt intubation success rate was lower in the SA group than in the NA group (71.4% vs 83.5%, p < 0.01). The multivariate logistic regression analysis identified that severe acidemia was significantly associated with the first attempt intubation failure (OR 1.9, 95% CI 1.03-3.68, p = 0.04). Conclusions: A presence of severe acidemia before endotracheal intubation lowers the first attempt intubation success rate in the ED.

Keywords: acidemia, airway management, endotracheal intubation, first-attempt intubation success rate

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Authors: P. Kazymbet, G. Abildinova, K.Makhambetov, M. Bakhtin, D. Rybalkina, K. Zhumadilov

Abstract:

Conducted cytogenetic research in workers Stepnogorsk Mining-Chemical Combine (Akmola region) with the study of 26341 chromosomal metaphase. Using a regression analysis with program DataFit, version 5.0, dependence between exposure dose and the following cytogenetic exponents has been studied: frequency of aberrant cells, frequency of chromosomal aberrations, frequency of the amounts of dicentric chromosomes, and centric rings. Experimental data on calibration curves "dose-effect" enabled the development of a mathematical model, allowing on data of the frequency of aberrant cells, chromosome aberrations, the amounts of dicentric chromosomes and centric rings calculate the absorbed dose at the time of the study. In the dose range of 0.1 Gy to 5.0 Gy dependence cytogenetic parameters on the dose had the following equation: Y = 0,0067е^0,3307х (R2 = 0,8206) – for frequency of chromosomal aberrations; Y = 0,0057е^0,3161х (R2 = 0,8832) –for frequency of cells with chromosomal aberrations; Y =5 Е-0,5е^0,6383 (R2 = 0,6321) – or frequency of the amounts of dicentric chromosomes and centric rings on cells. On the basis of cytogenetic parameters and regression equations calculated absorbed dose in workers of uranium production at the time of the study did not exceed 0.3 Gy.

Keywords: Stepnogorsk, mathematical modeling, cytogenetic, dicentric chromosomes

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Authors: Mário Ernesto Sitoe, Orlando Zacarias

Abstract:

University education is influenced by several factors that range from the adoption of strategies to strengthen the whole process to the academic performance improvement of the students themselves. This work uses data mining techniques to develop a predictive model to identify students with a tendency to evasion and retention. To this end, a database of real students’ data from the Department of University Admission (DAU) and the Department of Mathematics and Informatics (DMI) was used. The data comprised 388 undergraduate students admitted in the years 2009 to 2014. The Weka tool was used for model building, using three different techniques, namely: K-nearest neighbor, random forest, and logistic regression. To allow for training on multiple train-test splits, a cross-validation approach was employed with a varying number of folds. To reduce bias variance and improve the performance of the models, ensemble methods of Bagging and Stacking were used. After comparing the results obtained by the three classifiers, Logistic Regression using Bagging with seven folds obtained the best performance, showing results above 90% in all evaluated metrics: accuracy, rate of true positives, and precision. Retention is the most common tendency.

Keywords: evasion and retention, cross-validation, bagging, stacking

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Authors: Haitao Yang, Jianming Lv, Fei Xu, Xintong Wang, Yilin Huang, Lanting Xia, Xuewu Zhu

Abstract:

Given a fixed fund, purchasing fewer hosts of higher capability or inversely more of lower capability is a must-be-made trade-off in practices for building a Hadoop big data platform. An exploratory study is presented for a Housing Big Data Platform project (HBDP), where typical big data computing is with SQL queries of aggregate, join, and space-time condition selections executed upon massive data from more than 10 million housing units. In HBDP, an empirical formula was introduced to predict the performance of host clusters potential for the intended typical big data computing, and it was shaped via a regression approach. With this empirical formula, it is easy to suggest an optimal cluster configuration. The investigation was based on a typical Hadoop computing ecosystem HDFS+Hive+Spark. A proper metric was raised to measure the performance of Hadoop clusters in HBDP, which was tested and compared with its predicted counterpart, on executing three kinds of typical SQL query tasks. Tests were conducted with respect to factors of CPU benchmark, memory size, virtual host division, and the number of element physical host in cluster. The research has been applied to practical cluster procurement for housing big data computing.

Keywords: Hadoop platform planning, optimal cluster scheme at fixed-fund, performance predicting formula, typical SQL query tasks

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Authors: Churamani Pokhrel, C. B. Jha, S. R. Niraula, P. R. Pokharel

Abstract:

Human identification is one of the most challenging subjects that man has confronted. The determination of adult sex and stature are two of the four key factors (sex, stature, age, and race) in identification of an individual. Craniofacial and odontometric parameters are important tools for forensic anthropologists when it is not possible to apply advanced techniques for identification purposes. The present study provides anthropometric correlation of the parameters with stature and gender and also devises regression formulae for reconstruction of stature. A total of 312 Nepalese students with equal distribution of sex i.e., 156 male and 156 female students of age 18-35 years were taken for the study. Total of 10 parameters were measured (age, sex, stature, head circumference, head length, head breadth, facial height, bi-zygomatic width, mesio-distal canine width and inter-canine distance of both maxilla and mandible). Co-relation and regression analysis was done to find the association between the parameters. All parameters were found to be greater in males than females and each was found to be statistically significant. Out of total 312 samples, the best regressor for the determination of stature was head circumference and mandibular inter-canine width and that for gender was head circumference and right mandibular teeth. The accuracy of prediction was 83%. Regression equations and analysis generated from craniofacial and odontometric parameters can be a supplementary approach for the estimation of stature and gender when extremities are not available.

Keywords: craniofacial, gender, odontometric, stature

Procedia PDF Downloads 190

Authors: K. D. Sharma, M. Parida, S. S. Jain, Anju Saini, V. K. Katiyar

Abstract:

Air quality models form one of the most important components of an urban air quality management plan. Various statistical modeling techniques (regression, multiple regression and time series analysis) have been used to predict air pollution concentrations in the urban environment. These models calculate pollution concentrations due to observed traffic, meteorological and pollution data after an appropriate relationship has been obtained empirically between these parameters. Artificial neural network (ANN) is increasingly used as an alternative tool for modeling the pollutants from vehicular traffic particularly in urban areas. In the present paper, an attempt has been made to model traffic air pollution, specifically CO concentration using neural networks. In case of CO concentration, two scenarios were considered. First, with only classified traffic volume input and the second with both classified traffic volume and meteorological variables. The results showed that CO concentration can be predicted with good accuracy using artificial neural network (ANN).

Keywords: air quality management, artificial neural network, meteorological variables, statistical modeling

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Authors: Segun Thompson Bolarinwa, Munacinga Simatele, Adedamola Victoria Adegbuyi

Abstract:

Using World Bank’s nascent measure of sustainability, this paper examines the relationship between informality and sustainability in selected 7 African and 7 European developing economies. Specifically, the work examines the roles of informality on sustainability, interactive effect of globalisation in the nexus and the threshold of informality on sustainability suing spatial econometric and dynamic panel threshold panel models. Overall, the results indicate mixed effects of positive and negative pf informality on sustainability in Africa and Europe respectively. Recommendations are presented.

Keywords: spatial and dynamic, informality, Africa, Europe, globalisation, sustainability

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Authors: Agim Kukelii, Gevorg Sargsyan

Abstract:

This study, focusing on the base regional area (county level), estimates the effect of natural disaster damages on aggregate personal income, aggregate wages, wages per worker, aggregate employment, and aggregate income transfer. The study further estimates the dynamics of personal income, employment, and wages under natural disaster shocks. Southeast Texas, located at the center of Golf Coast, is hit by meteorological and hydrological caused natural disasters yearly. On average, there are more than four natural disasters per year that cane an estimated damage average of 2.2% of real personal income. The study uses the panel data method to estimate the average effect of natural disasters on the area’s economy (personal income, wages, employment, and income transfer). It also uses Panel Vector Autoregressive (PVAR) model to study the dynamics of macroeconomic variables under natural disaster shocks. The study finds that the average effect of natural disasters is positive for personal income and income transfer and is negative for wages and employment. The PVAR and the impulse response function estimates reveal that natural disaster shocks cause a decrease in personal income, employment, and wages. However, the economy’s variables bounce back after three years. The novelty of this study rests on several aspects. First, this is the first study to investigate the effects of natural disasters on macroeconomic variables at a regional level. Second, the study uses direct measures of natural disaster damages. Third, the study estimates that the time that the local economy takes to absorb the natural disaster damages shocks is three years. This is a relatively good reaction to the local economy, therefore, adding to the “resiliency” hypothesis. The study has several implications for policymakers, businesses, and households. First, this study serves to increase the awareness of local stakeholders that natural disaster damages do worsen, macroeconomic variables, such as personal income, employment, and wages beyond the immediate damages to residential and commercial properties, physical infrastructure, and discomfort in daily lives. Second, the study estimates that these effects linger on the economy on average for three years, which would require policymakers to factor in the time area need to be on focus.

Keywords: natural disaster damages, macroeconomics effects, PVAR, panel data

Procedia PDF Downloads 86