Search results for: multivariate statistical analysis

Authors: Si Chen, Le Zhang, Xian He

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The research explored the influences of public open space system on housing price through hedonic models, in order to support better open space plans and economic policies. We have three initial hypotheses: 1) public open space system has an overall positive influence on surrounding housing prices. 2) Different public open space types have different levels of influence on motivating surrounding housing prices. 3) Walking and driving accessibilities from property to public open spaces have different statistical relation with housing prices. Cook County, Illinois, was chosen to be a study area since data availability, sufficient open space types, and long-term open space preservation strategies. We considered the housing attributes, driving and walking accessibility scores from houses to nearby public open spaces, and driving accessibility scores to hospitals as influential features and used real housing sales price in 2010 as a dependent variable in the built hedonic model. Through ordinary least squares (OLS) regression analysis, General Moran’s I analysis and geographically weighted regression analysis, we observed the statistical relations between public open spaces and housing sale prices in the three built hedonic models and confirmed all three hypotheses.

Keywords: hedonic model, public open space, housing sale price, regression analysis, accessibility score

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Authors: A. Sathiya Susuman

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Background: The importance of maternal and child healthcare services cannot be stressed enough. These services are very important for the health and health outcomes of the mother and that of the child and in ensuring that both maternal and child deaths are prevented. The objective of the study is to inspire good quality maternal and child health care services in Swaziland. Specifically, is Swaziland on track with the 2015 Millennium Development Goals? Methods: The study used secondary data from the Swaziland Demographic and Health Survey 2006-07. This is an explorative and descriptive study which used pre-selected variables to study factors influencing the use of maternal and child healthcare services in Swaziland. Different types of examinations, such as univariate, bivariate, and multivariate statistical analysis were adopted. Results: The study findings showed a high use rate of antenatal care (97.3%) and delivery care (74.0%), and a low rate of postnatal care use (20.5%). The uptake childhood immunization is also high in the country, averaging more than 80.0%. Moreover, certain factors which were found to be influencing the use of maternal healthcare and childhood immunization include: woman’s age, parity, media exposure, maternal education, wealth status, and residence. The findings also revealed that these factors affect the use of maternal and child health differently. Conclusion: It is important to study factors related to maternal and child health uptake to inform relevant stakeholders about possible areas of improvement. Programs to educate families about the importance of maternal and child healthcare services should be implemented. Swaziland needs to work hard on child survival and maternal health care services, no doubt it is on track with the MDG 4 & 5.

Keywords: maternal healthcare, antenatal care, delivery care, postnatal care, child health, immunization, socio-economic and demographic factors

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Authors: Alessandro Suardi, Rodolfo Picchio, Domenico Coaloa, Maria Bonaventura Forleo, Nadia Palmieri, Luigi Pari

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The reconversion process of the Italian sugar supply chain to bio-energy supply chains, as a result of the 2006 Sugar CMO reform, have involved research to define the best logistics, the most adapted energy crops for the Italian territory and their sustainability. Rapeseed (Brassica napus L.), Giant reed (Arundo donax L.) and Poplar (Poplar ssp.) are energy crops considered strategic for the development of Italian energy supply-chains. This study analyzed the environmental and the economic impacts on the farm level of these three energy crops. The environmental assessment included six farming units, two per crop, which were extracted from a sample of 251 rapeseed farm units (2751 ha), 7 giant reed farm units (7.8 ha), and 91 poplar farm units (440 ha) using a statistical multivariate analysis. Life Cycle Assessment (LCA) research method has been used to evaluate and compare the sustainability of the agricultural phases of the crops studied. The impact analyses have been performed at mid-point and end-point levels. The results of the analysis shown that the fertilization, is the major source of environmental impact of the agricultural phase due to the production of the fertilizers and the soil emissions of GHG following the treatment. The perennial energy crops studied (Arundo donax L., Poplar ssp.) were environmentally more sustainable if compared with the annual crop (Brassica napus L.) for all the impact categories at mid-point and end-point levels analyzed. The most relevant impact category influenced by the agricultural process result the fossil depletion, mainly due to the fossil fuels consumed during the mineral fertilizers production (urea). Human health was the most affected damage category at the end point level. Poplar result the energy crop with the best environmental performance for the Italian territory, in the distribution areas most suitable for its cultivation.

Keywords: LCA, energy crops, rapeseed, giant reed, poplar

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Authors: Mohamad Reza Khodabakhsh

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Drug use and addiction are major biological, psychological, and social problems. In drug abuse treatment, it is important to pay attention to personality problems and coping methods of patients. Today, the third-wave treatments in psychotherapy emphasize people's awareness and acceptance of feelings and emotions, cognitions, and behaviors instead of challenging cognitions. For this reason, this research was conducted with the aim of investigating the effectiveness of group therapy based on acceptance and commitment to self-criticism and coping strategies of people with drug use disorder. This research was a quasi-experimental type of research (pre-test-post-test design with an unequal control group), and the statistical population of this research included all men with drug use disorder in Mashhad, 174 of whom among the 75 people eligible for this research, 30 of them were selected by available sampling method and randomly assigned to two experimental and control groups. In this research, Gilbert's self-criticism scale was used to measure self-criticism, and Andler and Barker's coping strategies questionnaire was used to measure coping strategies. Therapeutic intervention (treatment based on acceptance and commitment) was performed on the experimental group for eight sessions of 90 minutes, and then post-tests were taken from both groups, and multivariate analysis of covariance (MANCOVA) was used to analyze the data. The results showed that treatment based on acceptance and commitment significantly reduced self-criticism and improved coping strategies used by patients with drug use disorder (p>0.01). Therefore, treatment based on acceptance and commitment has been effective in reducing self-criticism and improving the coping strategies of patients with drug use disorder due to teaching clients to accept thoughts and conditions.

Keywords: treatment based on acceptance and commitment, self-criticism, coping strategies, addiction

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Authors: Hema Bhardwaj, D. Srinivasa Rao

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Technology for analysing, processing, and extracting meaningful data from enormous and complicated datasets can be termed as "big data." The technique of big data mining and big data analysis is extremely helpful for business movements such as making decisions, building organisational plans, researching the market efficiently, improving sales, etc., because typical management tools cannot handle such complicated datasets. Special computational and statistical issues, such as measurement errors, noise accumulation, spurious correlation, and storage and scalability limitations, are brought on by big data. These unique problems call for new computational and statistical paradigms. This research paper offers an overview of the literature on big data mining, its process, along with problems and difficulties, with a focus on the unique characteristics of big data. Organizations have several difficulties when undertaking data mining, which has an impact on their decision-making. Every day, terabytes of data are produced, yet only around 1% of that data is really analyzed. The idea of the mining and analysis of data and knowledge discovery techniques that have recently been created with practical application systems is presented in this study. This article's conclusion also includes a list of issues and difficulties for further research in the area. The report discusses the management's main big data and data mining challenges.

Keywords: big data, data mining, data analysis, knowledge discovery techniques, data mining challenges

Procedia PDF Downloads 89

Authors: Shael Brown, Reza Farivar

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Persistence diagrams capture valuable topological features of datasets that other methods cannot uncover. Still, their adoption in data pipelines has been limited due to the lack of publicly available tools in R (and python) for analyzing groups of them with machine learning and statistical inference. In an easy-to-use and scalable R package called TDApplied, we implement several applied analysis methods tailored to groups of persistence diagrams. The two main contributions of our package are comprehensiveness (most functions do not have implementations elsewhere) and speed (shown through benchmarking against other R packages). We demonstrate applications of the tools on simulated data to illustrate how easily practical analyses of any dataset can be enhanced with topological information.

Keywords: machine learning, persistence diagrams, R, statistical inference

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Authors: W. Sriwattanapongse, S. Prasitwattanaseree, S. Wongtrangan

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The transportation accidents mortality is a major problem that leads to loss of human lives, and economic. The objective was to identify patterns of statistical modeling for estimating mortality rates due to transportation accidents in Thailand by using data from 2000 to 2009. The data was taken from the death certificate, vital registration database. The number of deaths and mortality rates were computed classifying by gender, age, year and region. There were 114,790 cases of transportation accidents deaths. The highest average age-specific transport accident mortality rate is 3.11 per 100,000 per year in males, Southern region and the lowest average age-specific transport accident mortality rate is 1.79 per 100,000 per year in females, North-East region. Linear, poisson and negative binomial models were chosen for fitting statistical model. Among the models fitted, the best was chosen based on the analysis of deviance and AIC. The negative binomial model was clearly appropriate fitted.

Keywords: transportation accidents, mortality, modeling, analysis of deviance

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi

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This study was designed to find the best stochastic model (using of time series analysis) for annual extreme streamflow (peak and maximum streamflow) of Karkheh River at Iran. The Auto-regressive Integrated Moving Average (ARIMA) model used to simulate these series and forecast those in future. For the analysis, annual extreme streamflow data of Jelogir Majin station (above of Karkheh dam reservoir) for the years 1958–2005 were used. A visual inspection of the time plot gives a little increasing trend; therefore, series is not stationary. The stationarity observed in Auto-Correlation Function (ACF) and Partial Auto-Correlation Function (PACF) plots of annual extreme streamflow was removed using first order differencing (d=1) in order to the development of the ARIMA model. Interestingly, the ARIMA(4,1,1) model developed was found to be most suitable for simulating annual extreme streamflow for Karkheh River. The model was found to be appropriate to forecast ten years of annual extreme streamflow and assist decision makers to establish priorities for water demand. The Statistical Analysis System (SAS) and Statistical Package for the Social Sciences (SPSS) codes were used to determinate of the best model for this series.

Keywords: stochastic models, ARIMA, extreme streamflow, Karkheh river

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Authors: Zilong Peng, Jun Fan

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With the improvement of the living standards, the requirement on the acoustic comfort of the vehicle interior environment is becoming higher. The rain-the-roof producing interior noise is a common phenomenon for the vehicle, which usually discourages the conversation, especially for the heavy rain. This paper presents some numerical results about the rain-the-roof noise. The impact of each water drop is modeled as a short pulse, and the excitation locations on the roof are generated randomly. The vehicle body is simplified to a box closed with some certain-thickness shells. According to the main frequency components of the rain excitation, the analyzing frequency range is divided as low, high and middle frequency domains, which makes the vehicle body are modeled using finite element method (FEM), statistical energy analysis (SEA) and hybrid FE-SEA method, respectively. Furthermore, the effect of spatial distribution density and size of the rain on the sound pressure level are also discussed. These results may provide a guide for designing a more silent vehicle in the special weather.

Keywords: rain-the-roof noise, vehicle, finite element method, statistical energy analysis

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Authors: Oliver Chunho Ma, Tszying Chang

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Background: Traditional Chinese Medicine (TCM) has been widely used in the treatment of eczema. However, there is currently a lack of comprehensive research on the overall effectiveness of TCM in treating eczema, particularly using the Eczema Area and Severity Index (EASI) score as an evaluation tool. Meta-analysis can integrate the results of multiple studies to provide more convincing evidence. Objective: To conduct a systematic review and meta-analysis based on the EASI score to evaluate the overall effectiveness of TCM in the treatment of eczema. Specifically, the study will review and analyze published clinical studies that investigate TCM treatments for eczema and use the EASI score as an outcome measure, comparing the differences in improving the severity of eczema between TCM and other treatment modalities, such as conventional Western medicine treatments. Methods: Relevant studies, including randomized controlled trials (RCTs) and non-randomized controlled trials, that involve TCM treatment for eczema and use the EASI score as an outcome measure will be searched in medical literature databases such as PubMed, CNKI, etc. Relevant data will be extracted from the selected studies, including study design, sample size, treatment methods, improvement in EASI score, etc. The methodological quality and risk of bias of the included studies will be assessed using appropriate evaluation tools (such as the Cochrane Handbook). The results of the selected studies will be statistically analyzed, including pooling effect sizes (such as standardized mean differences, relative risks, etc.), subgroup analysis (e.g., different TCM syndromes, different treatment modalities), and sensitivity analysis (e.g., excluding low-quality studies). Based on the results of the statistical analysis and quality assessment, the overall effectiveness of TCM in improving the severity of eczema will be interpreted. Expected outcomes: By integrating the results of multiple studies, we expect to provide more convincing evidence regarding the specific effects of TCM in improving the severity of eczema. Additionally, subgroup analysis and sensitivity analysis can further elucidate whether the effectiveness of TCM treatment is influenced by different factors. Besides, we will compare the results of the meta-analysis with the clinical data from our clinic. For both the clinical data and the meta-analysis results, we will perform descriptive statistics such as means, standard deviations, percentages, etc. and compare the differences between the two using statistical tests such as independent samples t-test or non-parametric tests to assess the statistical differences between them.

Keywords: Eczema, traditional Chinese medicine, EASI, systematic review, meta-analysis

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Authors: Juan David Sepulveda

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This article reflects the current stage of progress in the project “Determining technological trends in energy generation”. At first it was oriented towards finding out those trends by employing such tools as the scientometrics community had proved and accepted as effective for getting reliable results. Because a documented methodological guide for this purpose could not be found, the decision was made to reorient the scope and aim of this project, changing the degree of interest in pursuing the objectives. Therefore it was decided to propose and implement a novel guide from the elements and techniques found in the available literature. This article begins by explaining the elements and considerations taken into account when implementing and applying this methodology, and the tools that led to the implementation of a software application for patent revision. Univariate analysis helped recognize the technological leaders in the field of energy, and steered the way for a multivariate analysis of this sample, which allowed for a graphical description of the techniques of mature technologies, as well as the detection of emerging technologies. This article ends with a validation of the methodology as applied to the case of fuel cells.

Keywords: energy, technology mapping, patents, univariate analysis

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Authors: Hamid Hanifi, Adel Azar, Alireza Booshehri

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In order to know about the capability level of R & D units in automotive industry, it is essential that organizations always compare themselves with standard level and higher than themselves so that to be improved continuously. In this research, with respect to the importance of this issue, we have tried to present an assessment model for R & D capabilities having reviewed on new products development in automotive industry of Iran. Iran Khodro Company was selected for the case study. To this purpose, first, having a review on the literature, about 200 indicators effective in R & D capabilities and new products development were extracted. Then, of these numbers, 29 indicators which were more important were selected by industry and academia experts and the questionnaire was distributed among statistical population. Statistical population was consisted of 410 individuals in Iran Khodro Company. We used the 410 questionnaires for exploratory factor analysis and then used the data of 308 questionnaires from the same population randomly for confirmatory factor analysis. The results of exploratory factor analysis led to categorization of dimensions in 9 secondary dimensions. Naming the dimensions was done according to a literature review and the professors’ opinion. Using structural equation modeling and AMOS software, confirmatory factor analysis was conducted and ultimate model with 9 secondary dimensions was confirmed. Meanwhile, 9 secondary dimensions of this research are as follows: 1) Research and design capability, 2) Customer and market capability, 3) Technology capability, 4) Financial resources capability, 5) Organizational chart, 6) Intellectual capital capability, 7) NPD process capability, 8) Managerial capability and 9) Strategy capability.

Keywords: research and development, new products development, structural equations, exploratory factor analysis, confirmatory factor analysis

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Authors: Sukhvinder Kaur, Jayanta Bora, Ashok Agarwal, Sangeeta Kaul

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Background: HIV and STI transmission can be prevented if condoms are used properly, but condom tear may lead to infections even if are used consistently. Studies reveal high rates of condom breakage among Female Sex Workers (FSWs). USAID PHFI-PIPPSE is piloting a prevention model among high risk groups at Thane district of Maharashtra, India by implementing prevention and advocacy efforts for such risk behaviors. The current analysis highlights the correlates of condom breakage among FSWs from Thane. Method: A Behavioral Tracking Survey was conducted in 2014-15 among 503 FSWs through probability-based two stage random sampling from 3,660 FSWs at 100 hotspots, to understand levels of high risk behaviors, awareness and exposure to prevention programs. Bi-variate and multivariate-logistic regression methods used to assess the association of condom breakage while having sex with age, STI occurrence, anal sex with clients and alcohol consumption. Only self-reported STIs (Genital sore/ulcer, yellowish/ greenish discharge from vagina with/without foul smell, lower abdominal pain without diarrhea/dysentery or menses) were considered. Major Findings: Results depicted FSWs who reported condom breakage while having sex with any type of partner (paying clients, non-paying partners and other than main partner husband/boyfriend) had significantly high number of STIs (42.3% vs 16.9 %, P, 0.000) and had started sexual relationship in <16 years of age (31.0% vs 16.4 %, P, 0.000). Multivariate analysis after controlling the age at sex, knowledge about HIV and literacy, highlighted significantly higher odds of condom breakage among FSWs who have reported currently suffering with STI [AOR 2.91, 95% CI 1.75 - 4.83; P, 0.000]; who had anal sex with their paying client [AOR 2.59, 95% CI 1.59 - 4.19; P, 0.000]; and who consumed alcohol in the last 12 months [AOR 1.89, 95% CI 1.01 - 3.53; P, 0.047]. Conclusion: Risky behavior like anal sex with paying clients and impact of alcohol while having sex are main factors for condom breakage among young sex workers; and condom breakage leads to STIs. Hence, program interventions should address measures for prevention of condom breakage for HIV/STI prevention.

Keywords: female sex workers, condom breakage, anal sex, young sex workers

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Authors: Masoud Sheidai

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Biologists with a special field of population genetics and phylogeny have different research tasks such as populations’ genetic variability and divergence, species relatedness, the evolution of genetic and morphological characters, and identification of DNA SNPs with adaptive potential. To tackle these problems and reach a concise conclusion, they must use the proper and efficient statistical and bioinformatic methods as well as suitable genetic and morphological characteristics. In recent years application of different bioinformatic and statistical methods, which are based on various well-documented assumptions, are the proper analytical tools in the hands of researchers. The species delineation is usually carried out with the use of different clustering methods like K-means clustering based on proper distance measures according to the studied features of organisms. A well-defined species are assumed to be separated from the other taxa by molecular barcodes. The species relationships are studied by using molecular markers, which are analyzed by different analytical methods like multidimensional scaling (MDS) and principal coordinate analysis (PCoA). The species population structuring and genetic divergence are usually investigated by PCoA and PCA methods and a network diagram. These are based on bootstrapping of data. The Association of different genes and DNA sequences to ecological and geographical variables is determined by LFMM (Latent factor mixed model) and redundancy analysis (RDA), which are based on Bayesian and distance methods. Molecular and morphological differentiating characters in the studied species may be identified by linear discriminant analysis (DA) and discriminant analysis of principal components (DAPC). We shall illustrate these methods and related conclusions by giving examples from different edible and medicinal plant species.

Keywords: GWAS analysis, K-Means clustering, LFMM, multidimensional scaling, redundancy analysis

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Authors: Wendu Pang, Yaxin Luo, Junhong Li, Yu Zhao, Danni Cheng, Yufang Rao, Minzi Mao, Ke Qiu, Yijun Dong, Fei Chen, Jun Liu, Jian Zou, Haiyang Wang, Wei Xu, Jianjun Ren

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We aimed to compare the prognostic prediction value of positive lymph node number (PLNN) to the American Joint Committee on Cancer (AJCC) tumor, lymph node, and metastasis (TNM) staging system for patients with hypopharyngeal squamous cell carcinoma (HPSCC). A total of 826 patients with HPSCC from the Surveillance, Epidemiology, and End Results database (2004–2015) were identified and split into two independent cohorts: training (n=461) and validation (n=365). Univariate and multivariate Cox regression analyses were used to evaluate the prognostic effects of PLNN in patients with HPSCC. We further applied six Cox regression models to compare the survival predictive values of the PLNN and AJCC TNM staging system. PLNN showed a significant association with overall survival (OS) and cancer-specific survival (CSS) (P < 0.001) in both univariate and multivariable analyses, and was divided into three groups (PLNN 0, PLNN 1-5, and PLNN>5). In the training cohort, multivariate analysis revealed that the increased PLNN of HPSCC gave rise to significantly poor OS and CSS after adjusting for age, sex, tumor size, and cancer stage; this trend was also verified by the validation cohort. Additionally, the survival model incorporating a composite of PLNN and TNM classification (C-index, 0.705, 0.734) performed better than the PLNN and AJCC TNM models. PLNN can serve as a powerful survival predictor for patients with HPSCC and is a surrogate supplement for cancer staging systems.

Keywords: hypopharyngeal squamous cell carcinoma, positive lymph nodes number, prognosis, prediction models, survival predictive values

Procedia PDF Downloads 118

Authors: Raquel P. F. Guiné, Susana R. Matos, Daniela V. T. A. Costa, Fernando J. Gonçalves

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Because blueberries are worldwide recognized as a good source of beneficial components, their consumption has increased in the past decades, and so have the scientific works about their properties. Hence this work was undertaken to evaluate the effect of some production and conservation factors on the properties of blueberries from cultivar Bluecrop. The physical and chemical analyses were done according to established methodologies and then all data was treated using software SPSS for assessment of the possible differences among the factors investigated and/or the correlations between the variables at study. The results showed that location of production influenced some of the berries properties (caliber, sugars, antioxidant activity, color and texture) and that the age of the bushes was correlated with moisture, sugars and acidity, as well as lightness. On the other hand, altitude of the farm only was correlated to sugar content. With regards to conservation, it influenced only anthocyanins content and DPPH antioxidant activity. Finally, the type of extract and the order of extraction had a pronounced influence on all the phnolic properties evaluated.

Keywords: Antioxidant activity, blueberry, conservation, geographical origin, phenolic compounds, statistical analysis

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Authors: Ndidi F. Amulu, Patrick E. Amulu, Gordian O. Mbah, Callistus N. Ude

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Comparative analysis of the properties of melon seed, coconut fruit and their oil yield were evaluated in this work using standard analytical technique AOAC. The results of the analysis carried out revealed that the moisture contents of the samples studied are 11.15% (melon) and 7.59% (coconut). The crude lipid content are 46.10% (melon) and 55.15% (coconut).The treatment combinations used (leaching time, leaching temperature and solute: solvent ratio) showed significant difference (p < 0.05) in yield between the samples, with melon oil seed flour having a higher percentage range of oil yield (41.30 – 52.90%) and coconut (36.25 – 49.83%). The physical characterization of the extracted oil was also carried out. The values gotten for refractive index are 1.487 (melon seed oil) and 1.361 (coconut oil) and viscosities are 0.008 (melon seed oil) and 0.002 (coconut oil). The chemical analysis of the extracted oils shows acid value of 1.00mg NaOH/g oil (melon oil), 10.050mg NaOH/g oil (coconut oil) and saponification value of 187.00mg/KOH (melon oil) and 183.26mg/KOH (coconut oil). The iodine value of the melon oil gave 75.00mg I2/g and 81.00mg I2/g for coconut oil. A standard statistical package Minitab version 16.0 was used in the regression analysis and analysis of variance (ANOVA). The statistical software mentioned above was also used to optimize the leaching process. Both samples gave high oil yield at the same optimal conditions. The optimal conditions to obtain highest oil yield ≥ 52% (melon seed) and ≥ 48% (coconut seed) are solute - solvent ratio of 40g/ml, leaching time of 2hours and leaching temperature of 50oC. The two samples studied have potential of yielding oil with melon seed giving the higher yield.

Keywords: Coconut, Melon, Optimization, Processing

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Authors: Wajiha Javed, Arsalan Jabbar, Nelofer Mehboob, Muhammad Tafseer, Zahid Memon

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Introduction: Researchers globally have strived to explore diverse factors that augment the continuation and uptake of family planning methods. Clients’ satisfaction is one of the core determinants facilitating continuation of family planning methods. There is a major debate yet scanty evidence to contrast public and private sectors with respect to client satisfaction. The objective of this study is to compare quality-of-care provided by public and private sectors of Pakistan through a client satisfaction lens. Methods: We used Pakistan Demographic Heath Survey 2012-13 dataset (Sindh province) on a total of 3133 Married Women of Reproductive Age (MWRA) aged 15-49 years. Source of family planning (public/private sector) was the main exposure variable. Outcome variable was client satisfaction judged by ten different dimensions of client satisfaction. Means and standard deviations were calculated for continuous variable while for categorical variable frequencies and percentages were computed. For univariate analysis, Chi-square/Fisher Exact test was used to find an association between clients’ satisfaction in public and private sectors. Ten different multivariate models were made. Variables were checked for multi-collinearity, confounding, and interaction, and then advanced logistic regression was used to explore the relationship between client satisfaction and dependent outcome after adjusting for all known confounding factors and results are presented as OR and AOR (95% CI). Results: Multivariate analyses showed that clients were less satisfied in contraceptive provision from private sector as compared to public sector (AOR 0.92,95% CI 0.63-1.68) even though the result was not statistically significant. Clients were more satisfied from private sector as compared to the public sector with respect to other determinants of quality-of-care (follow-up care (AOR 3.29, 95% CI 1.95-5.55), infection prevention (AOR 2.41, 95% CI 1.60-3.62), counseling services (AOR 2.01, 95% CI 1.27-3.18, timely treatment (AOR 3.37, 95% CI 2.20-5.15), attitude of staff (AOR 2.23, 95% CI 1.50-3.33), punctuality of staff (AOR 2.28, 95% CI 1.92-4.13), timely referring (AOR 2.34, 95% CI 1.63-3.35), staff cooperation (AOR 1.75, 95% CI 1.22-2.51) and complications handling (AOR 2.27, 95% CI 1.56-3.29).

Keywords: client satisfaction, family planning, public private partnership, quality of care

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Authors: Ruttana Phetsitong, Patama Vapattanawong, Malee Sunpuwan, Marc Voelker

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The majority of care for older people at home in Thai society falls upon caregivers resulting in caregiver’s mental health problem. Beyond individual characteristics, household factors might have a profound effect on the caregiver’s mental health. But reliable data capturing this at the household level have been limited to date. The objectives of the present study were to explore the levels of Thai caregiver’s mental health and to investigate the factors affecting the mental health at household level. Data were obtained from the 2011 National Survey of Thai Older Persons conducted by the National Statistical Office of Thailand. Caregiver’s mental health was measured by using the 15- items-short version of the Thai Mental Health Indicator (TMHI-15) developed by the Department of Mental Health, the Ministry of Public Health. Multivariate logistic regression models were used to explore the impact of potential factors on caregiver’s mental health. The THMI-15 produced an overall average caregiver mental health score of 30.9 out of 45 (SD 5.3). The score can be categorized into good (34.02-45), fair (27.01-34), and poor (0-27). Duration of care for older people, household wealth, and functional dependency of the older people significantly predicted total caregiver’s mental health. Household economic factor was key in predicting better mental health. Compared to those poorest households, the adjusted effect of the fifth quintile household wealth was high (OR=2.34; 95%CI=1.47-3.73). The findings of this study provide a fuller picture to a better understanding of the level and factors that cause the mental health of Thai caregivers. Health care providers and policymakers should consider these factors when designing interventions aimed at alleviating caregiver’s psychological burden when provided care for older people at home.

Keywords: caregiver’s mental health, household, older people, Thailand

Procedia PDF Downloads 119

Authors: Ndidi F. Amulu, Godian O. Mbah, Maxwel I. Onyiah, Callistus N. Ude

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Analysis of the properties of coconut (Cocos nucifera) and its oil was evaluated in this work using standard analytical techniques. The analyses carried out include proximate composition of the fruit, extraction of oil from the fruit using different process parameters and physicochemical analysis of the extracted oil. The results showed the percentage (%) moisture, crude lipid, crude protein, ash, and carbohydrate content of the coconut as 7.59, 55.15, 5.65, 7.35, and 19.51 respectively. The oil from the coconut fruit was odourless and yellowish liquid at room temperature (30oC). The treatment combinations used (leaching time, leaching temperature and solute: solvent ratio) showed significant differences (P˂0.05) in the yield of oil from coconut flour. The oil yield ranged between 36.25%-49.83%. Lipid indices of the coconut oil indicated the acid value (AV) as 10.05 Na0H/g of oil, free fatty acid (FFA) as 5.03%, saponification values (SV) as 183.26 mgKOH-1 g of oil, iodine value (IV) as 81.00 I2/g of oil, peroxide value (PV) as 5.00 ml/ g of oil and viscosity (V) as 0.002. A standard statistical package minitab version 16.0 program was used in the regression analysis and analysis of variance (ANOVA). The statistical software mentioned above was also used to generate various plots such as single effect plot, interactions effect plot and contour plot. The response or yield of oil from the coconut flour was used to develop a mathematical model that correlates the yield to the process variables studied. The maximum conditions obtained that gave the highest yield of coconut oil were leaching time of 2 hrs, leaching temperature of 50 oC and solute/solvent ratio of 0.05 g/ml.

Keywords: coconut, oil-extraction, optimization, physicochemical, proximate

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Authors: Khin Aye Myint, Mohd Rafii Yusop, Mohd Yusoff Abd Samad, Shairul Izan Ramlee, Mohd Din Amiruddin, Zulkifli Yaakub

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The narrow base of genetic is the main obstacle of breeding and genetic improvement in oil palm industry. In order to broaden the genetic bases, the Malaysian Palm Oil Board has been extensively collected wild germplasm from its original area of 11 African countries which are Nigeria, Senegal, Gambia, Guinea, Sierra Leone, Ghana, Cameroon, Zaire, Angola, Madagascar, and Tanzania. The germplasm collections were established and maintained as a field gene bank in Malaysian Palm Oil Board (MPOB) Research Station in Kluang, Johor, Malaysia to conserve a wide range of oil palm genetic resources for genetic improvement of Malaysian oil palm industry. Therefore, assessing the performance and genetic diversity of the wild materials is very important for understanding the genetic structure of natural oil palm population and to explore genetic resources. Principal component analysis (PCA) and Cluster analysis are very efficient multivariate tools in the evaluation of genetic variation of germplasm and have been applied in many crops. In this study, eight populations of MPOB-Senegal oil palm germplasm were studied to explore the genetic variation pattern using PCA and cluster analysis. A total of 20 yield and yield component traits were used to analyze PCA and Ward’s clustering using SAS 9.4 version software. The first four principal components which have eigenvalue >1 accounted for 93% of total variation with the value of 44%, 19%, 18% and 12% respectively for each principal component. PC1 showed highest positive correlation with fresh fruit bunch (0.315), bunch number (0.321), oil yield (0.317), kernel yield (0.326), total economic product (0.324), and total oil (0.324) while PC 2 has the largest positive association with oil to wet mesocarp (0.397) and oil to fruit (0.458). The oil palm population were grouped into four distinct clusters based on 20 evaluated traits, this imply that high genetic variation existed in among the germplasm. Cluster 1 contains two populations which are SEN 12 and SEN 10, while cluster 2 has only one population of SEN 3. Cluster 3 consists of three populations which are SEN 4, SEN 6, and SEN 7 while SEN 2 and SEN 5 were grouped in cluster 4. Cluster 4 showed the highest mean value of fresh fruit bunch, bunch number, oil yield, kernel yield, total economic product, and total oil and Cluster 1 was characterized by high oil to wet mesocarp, and oil to fruit. The desired traits that have the largest positive correlation on extracted PCs could be utilized for the improvement of oil palm breeding program. The populations from different clusters with the highest cluster means could be used for hybridization. The information from this study can be utilized for effective conservation and selection of the MPOB-Senegal oil palm germplasm for the future breeding program.

Keywords: cluster analysis, genetic variability, germplasm, oil palm, principal component analysis

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Authors: Madhusudan Purohit, Stephen Philip, Bharathkumar Inturi

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In this paper we report the quantitative structure activity relationship of novel bis-triazole derivatives for predicting the activity profile. The full model encompassed a dataset of 46 Bis- triazoles. Tripos Sybyl X 2.0 program was used to conduct CoMSIA QSAR modeling. The Partial Least-Squares (PLS) analysis method was used to conduct statistical analysis and to derive a QSAR model based on the field values of CoMSIA descriptor. The compounds were divided into test and training set. The compounds were evaluated by various CoMSIA parameters to predict the best QSAR model. An optimum numbers of components were first determined separately by cross-validation regression for CoMSIA model, which were then applied in the final analysis. A series of parameters were used for the study and the best fit model was obtained using donor, partition coefficient and steric parameters. The CoMSIA models demonstrated good statistical results with regression coefficient (r2) and the cross-validated coefficient (q2) of 0.575 and 0.830 respectively. The standard error for the predicted model was 0.16322. In the CoMSIA model, the steric descriptors make a marginally larger contribution than the electrostatic descriptors. The finding that the steric descriptor is the largest contributor for the CoMSIA QSAR models is consistent with the observation that more than half of the binding site area is occupied by steric regions.

Keywords: 3D QSAR, CoMSIA, triazoles, novel heterocycles

Procedia PDF Downloads 422

Authors: Alireza Ansariyar, Safieh Laaly

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Over the last decades, the vehicle industry has shown increased interest in integrating autonomous, connected, and electrical technologies in vehicle design with the primary hope of improving mobility and road safety while reducing transportation’s environmental impact. Using the State of Maryland (M.D.) in the United States as a pilot study, this research investigates CAVs’ fuel consumption and air pollutants (C.O., PM, and NOx) and utilizes meaningful linear regression models to predict CAV’s environmental effects. Maryland transportation network was simulated in VISUM software, and data on a set of variables were collected through a comprehensive survey. The number of pollutants and fuel consumption were obtained for the time interval 2010 to 2021 from the macro simulation. Eventually, four linear regression models were proposed to predict the amount of C.O., NOx, PM pollutants, and fuel consumption in the future. The results highlighted that CAVs’ pollutants and fuel consumption have a significant correlation with the income, age, and race of the CAV customers. Furthermore, the reliability of four statistical models was compared with the reliability of macro simulation model outputs in the year 2030. The error of three pollutants and fuel consumption was obtained at less than 9% by statistical models in SPSS. This study is expected to assist researchers and policymakers with planning decisions to reduce CAV environmental impacts in M.D.

Keywords: connected and autonomous vehicles, statistical model, environmental effects, pollutants and fuel consumption, VISUM, linear regression models

Procedia PDF Downloads 423

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

Procedia PDF Downloads 471

Authors: Ng'etich K. Stephen

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Abstract—Globally analytics in basketball has advanced tremendously in the last decade. Organizations are leveraging the insights to improve team and player performance and, in the long run, generate revenue out of it. Due to limited basketball game-related statistics in African competitions, teams are unaware of how they compete with other continental basketball teams. The purpose of this study is to evaluate the regional difference in basketball game-related statistics between African teams that played in the newly formed league, the basketball African league and the European league. The basketball African league, a competition created through the partnership between NBA and FIBA, offers a good starting point since it has valuable basketball metrics to analyze. This study sought to use multivariate linear discriminant analysis to identify the game-related statistics that discriminate the teams in Euro league and the basketball African league.

Keywords: basketball africa league, basketball, euroleague, fiba, africa

Procedia PDF Downloads 75

Authors: Marziyeh Yousefi, Hossein Nassaji

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This paper reports the results of a meta-analysis of studies on the effects of instruction mode on learning second language pragmatics during the last decade (from 2006 to 2016). After establishing related inclusion/ exclusion criteria, 39 published studies were retrieved and included in the present meta-analysis. Studies were later coded for face-to-face and computer-assisted mode of instruction. Statistical procedures were applied to obtain effect sizes. It was found that Computer-Assisted-Language-Learning studies generated larger effects than Face-to-Face instruction.

Keywords: meta-analysis, effect size, L2 pragmatics, comprehensive meta-analysis, face-to-face, computer-assisted language learning

Procedia PDF Downloads 198

Authors: M. E. Khiav, D. J. Borah, H. T. S. Santos, V. T. Faria

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For automobile companies, it has become very important to ensure sound quality in manufacturing and assembling in order to prevent occurrence of defects and to reduce the amount of parts replacements to be done in the service centers during the warranty period. Statistical Process Control (SPC) is widely used as the tool to analyze the quality of such processes and plays a significant role in the improvement of the processes by identifying the patterns and the location of the defects. In this paper, a case study has been conducted on an Iranian automobile company. This paper performs a quality analysis of a particular component called “Internal Bearing for the Back Wheel” of a particular car model, manufactured by the company, based on the 10 million data received from its service centers located all over the country. By creating control charts including X bar–S charts and EWMA charts, it has been observed after the year 2009, the specific component underwent frequent failures and there has been a sharp dip in the average distance covered by the cars till the specific component requires replacement/maintenance. Correlation analysis was performed to find out the reasons that might have affected the quality of the specific component in all the cars produced by the company after the year 2009. Apart from manufacturing issues, some political and environmental factors have been identified to have a potential impact on the quality of the component. A maiden attempt has been made to analyze the quality issues within an Iranian automobile manufacturer; such issues often get neglected in developing countries. The paper also discusses the possibility of political scenario of Iran and the country’s environmental conditions affecting the quality of the end products, which not only strengthens the extant literature but also provides a new direction for future research.

Keywords: capability analysis, car manufacturing, statistical process control, quality control, quality tools

Procedia PDF Downloads 347

Authors: Marc S. Paolella, Pawel Polak

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The paper proposes a framework for large-scale portfolio optimization which accounts for all the major stylized facts of multivariate financial returns, including volatility clustering, dynamics in the dependency structure, asymmetry, heavy tails, and non-ellipticity. It introduces a so-called risk fear portfolio strategy which combines portfolio optimization with active risk monitoring. The former selects optimal portfolio weights. The latter, independently, initiates market exit in case of excessive risks. The strategy agrees with the stylized fact of stock market major sell-offs during the initial stage of market downturns. The advantages of the new framework are illustrated with an extensive empirical study. It leads to superior multivariate density and Value-at-Risk forecasting, and better portfolio performance. The proposed risk fear portfolio strategy outperforms various competing types of optimal portfolios, even in the presence of conservative transaction costs and frequent rebalancing. The risk monitoring of the optimal portfolio can serve as an early warning system against large market risks. In particular, the new strategy avoids all the losses during the 2008 financial crisis, and it profits from the subsequent market recovery.

Keywords: comfort, financial crises, portfolio optimization, risk monitoring

Procedia PDF Downloads 502

Authors: Nargess Fasihmardanloo

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The aim of this study was to comparatively study the motivations of women to physical activity in Iran and selected Arab countries Based on individual, social and Islamic components. The present study was a descriptive comparative study that was performed by field method. The statistical population of the study included female athletes in Iran and Arab countries. A total of 184 people from Iran and 179 people from Arab countries (Iraq, UAE, and Jordan) were selected through available sampling as a research sample. The research tool included a questionnaire. The validity of the questionnaire was confirmed and its reliability in a pilot study was 0.95 through Cronbach's alpha. The questionnaire was translated into Persian in Iran and translated into Arabic for the selected countries and was provided to the participants electronically and through cyberspace. Finally, 363 questionnaires were collected. Manova multivariate analysis of variance using spss22 software was used to analyze the data. Findings showed that between Iranian women athletes and women athletes in selected Arab countries in the components of intrapersonal motivation (p = 0.009 and f = 6.978), interpersonal motivation (p = 0.050 and f = 3.875), There is a significant difference between social motives (p = 0.001 and f = 27.619) and Islamic motives (p = 0.001 and f = 11.339). And this difference is significant at the level of p <0.01 and p <0.05. In other words, in the component of intrapersonal motivations, the average of this component in Iranian female athletes (M = 59.77) was higher than female athletes in selected Arab countries (M = 55.53). In the interpersonal motivations component, the average of this component in Iranian female athletes (M = 26.87) was lower than in female athletes in selected Arab countries (M = 28.62). In the component of social motivations, the average of this component in Iranian female athletes (M = 33.08) was lower than female athletes in selected Arab countries (M = 39.64). In the component of Islamic motives, the average of this component in Iranian female athletes (M = 21.55) was higher than female athletes in selected Arab countries (M = 19.04).

Keywords: athletes, motivation, women, Islamic

Procedia PDF Downloads 73

Authors: Helena López-Moreno, Antoni Rodríguez-Sánchez, Carmen Viñas-Arrebola, Cesar Porras-Amores

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The ventilated façade has great advantages when compared to traditional façades as it reduces the air conditioning thermal loads due to the stack effect induced by solar radiation in the air chamber. Optimizing energy consumption by using a ventilated façade can be used not only in newly built buildings but also it can be implemented in existing buildings, opening the field of implementation to energy building retrofitting works. In this sense, the following three prototypes of façade where designed, built and further analyzed in this research: non-ventilated façade (NVF); slightly ventilated façade (SLVF) and strongly ventilated façade (STVF). The construction characteristics of the three facades are based on the Spanish regulation of building construction “Technical Building Code”. The façades have been monitored by type-k thermocouples in a representative day of the summer season in Madrid (Spain). Moreover, an analysis of variance (ANOVA) with repeated measures, studying the thermal lag in the ventilated and no-ventilated façades has been designed. Results show that STVF façade presents higher levels of thermal inertia as the thermal lag reduces up to 100% (daily mean) compared to the non-ventilated façade. In addition, the statistical analysis proves that an increase of the ventilation holes size in STVF façades does not improve the thermal lag significantly (p > 0.05) when compared to the SLVF façade.

Keywords: ventilated façade, energy efficiency, thermal behavior, statistical analysis

Procedia PDF Downloads 464