Search results for: Statistical analysis (RSM)

Authors: Md Rezaul Karim, Farha Taznin

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The purpose of this study was to assess and describe the individual and household characteristics of farmers, to measure the attitude of farmers towards climate adaptation farming practices and to explore the individual and household factors contributing in predicting their attitude towards climate adaptation farming practices. Data were collected through personal interviews using a pre-tested interview schedule. The data collection was done at Biral Upazila under Dinajpur district in Bangladesh from 1st November to 15 December 2018. Besides descriptive statistical parameters, Pearson’s Product Moment Correlation Coefficient (r), multiple regression and step-wise multiple regression analysis were used for the statistical analysis. Findings indicated that the highest proportion (77.6 percent) of the farmers had moderately favorable attitudes, followed by only 11.2 percent with highly favorable attitudes and 11.2 percent with slightly favorable attitudes towards climate adaptation farming practices. According to the computed correlation coefficients (r), among the 10 selected factors, five of them, such as education of household head, farm size, annual household income, organizational participation, and information access by extension services, had a significant relationship with the attitude of farmers towards climate-smart practices. The step-wise multiple regression results showed that two characteristics as education of household head and information access by extension services, contributed 26.2% and 5.1%, respectively, in predicting farmers' attitudes towards climate adaptation farming practices. In addition, more than two-thirds of farmers cited their opinion to the problems in response to ‘price of vermi species is high and it is not easily available’ as 1st ranked problem, followed by ‘lack of information for innovative climate-smart technologies’. This study suggests that policy implications are necessary to promote extension education and information services and overcome the obstacles to climate adaptation farming practices. It further recommends that research study should be conducted in diverse contexts of nationally or globally.

Keywords: factors, attitude, climate adaptation, farming practices, Bangladesh

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Authors: Ching Louis Liu, Edmund Kazmierczak, Tim Miller

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Safety analysis for multi-agent systems is complicated by the, potentially nonlinear, interactions between agents. This paper proposes a method for analyzing the safety of multi-agent systems by explicitly focusing on interactions and the accident data of systems that are similar in structure and function to the system being analyzed. The method creates a Bayesian network using the accident data from similar systems. A feature of our method is that the events in accident data are labeled with HAZOP guide words. Our method uses an Ontology to abstract away from the details of a multi-agent implementation. Using the ontology, our methods then constructs an “Interaction Map,” a graphical representation of the patterns of interactions between agents and other artifacts. Interaction maps combined with statistical data from accidents and the HAZOP classifications of events can be converted into a Bayesian Network. Bayesian networks allow designers to explore “what it” scenarios and make design trade-offs that maintain safety. We show how to use the Bayesian networks, and the interaction maps to improve multi-agent system designs.

Keywords: multi-agent system, safety analysis, safety model, integration map

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Authors: Ibtisam Mahmoud Mohammed Sultan

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The present research aimed to identify the level of both emotional and emotional competence among students in Tikrit University aimed to know the assumptions in statistical significance for both variables as gender variables (m-f) and specialty (scientific-humanistic), as research to learn what Relationship between emotional safety and efficiency alanfaalet Tikrit University students. The researcher built emotional security measure (54) as built measure emotional competence (46), as the researcher extract full alsaykomtrih characteristics of both scales. The research sample consisted of (600) students selected by the random way and applying the scales on a basic search sample and processed statistical data using a variety of methods, including statistical test (test T.) and Pearson correlation coefficient, the researcher found a set of results. The following: 1. that the Tikrit University students possess a high level of emotional security. 2. to safely enjoy passionate males more than females. 3. that there is no difference between students of scientific and humanitarian specialization in variable emotional security. 4. that the Tikrit University students enjoy a high level of emotional competence. 5. the female-male outperforming in emotional competence level. 6. the humanitarian specialization students Excel in emotional competence for those of specialty. 7. the existence of a positive correlation between variables. Through search results, the researcher has developed a set of conclusions, proposals, and recommendations.

Keywords: relation, emotional security, students, efficiency

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Authors: Abadou Yacine, Faid Hayette

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Significant investigations were performed on the use and impact on physical properties along with the mechanical strength of the recycled and reused E-glass waste powder. However, it has been modelled how recycled display e-waste glass may affect the characteristics and qualities of dune sand mortar. To be involved in this field, an investigation has been done with the substitution of dune sand for recycled E-glass waste and constant water-cement ratios. The linear relationship between the dune sand mortar and E-glass mortar mix % contributes to the model's reliability. The experimental data was exposed to regression analysis using JMP Statistics software. The regression model with one predictor presented the general form of the equation for the prediction of the five properties' characteristics of dune sand mortar from the substitution ratio of E-waste glass and curing age. The results illustrate that curing a long-term process produced an E-glass waste mortar specimen with the highest compressive strength of 68 MPa in the laboratory environment. Anova analysis indicated that the curing at long-term has the utmost importance on the sorptivity level and ultrasonic pulse velocity loss. Furthermore, the E-glass waste powder percentage has the utmost importance on the compressive strength and improvement in dynamic elasticity modulus. Besides, a significant enhancement of radiation-shielding applications.

Keywords: ANOVA analysis, E-glass waste, durability and sustainability, radiation-shielding

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Authors: Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

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Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.

Keywords: conditional generative adversarial net, market and credit risk management, neural network, time series

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Authors: Zhaojun Wang, Zongdi Sun, Qinqin Cui, Xingwan Ren

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Based on multivariate statistical analysis theory, this paper uses the principal component analysis method, Mahalanobis distance analysis method and fitting method to establish the photovoltaic health model to evaluate the health of photovoltaic panels. First of all, according to weather conditions, the photovoltaic panel variable data are classified into five categories: sunny, cloudy, rainy, foggy, overcast. The health of photovoltaic panels in these five types of weather is studied. Secondly, a scatterplot of the relationship between the amount of electricity produced by each kind of weather and other variables was plotted. It was found that the amount of electricity generated by photovoltaic panels has a significant nonlinear relationship with time. The fitting method was used to fit the relationship between the amount of weather generated and the time, and the nonlinear equation was obtained. Then, using the principal component analysis method to analyze the independent variables under five kinds of weather conditions, according to the Kaiser-Meyer-Olkin test, it was found that three types of weather such as overcast, foggy, and sunny meet the conditions for factor analysis, while cloudy and rainy weather do not satisfy the conditions for factor analysis. Therefore, through the principal component analysis method, the main components of overcast weather are temperature, AQI, and pm2.5. The main component of foggy weather is temperature, and the main components of sunny weather are temperature, AQI, and pm2.5. Cloudy and rainy weather require analysis of all of their variables, namely temperature, AQI, pm2.5, solar radiation intensity and time. Finally, taking the variable values in sunny weather as observed values, taking the main components of cloudy, foggy, overcast and rainy weather as sample data, the Mahalanobis distances between observed value and these sample values are obtained. A comparative analysis was carried out to compare the degree of deviation of the Mahalanobis distance to determine the health of the photovoltaic panels under different weather conditions. It was found that the weather conditions in which the Mahalanobis distance fluctuations ranged from small to large were: foggy, cloudy, overcast and rainy.

Keywords: fitting, principal component analysis, Mahalanobis distance, SPSS, MATLAB

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Authors: Lesley Clack, Rachel Ellison, Elizabeth Chambers

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A belief exists that there are huge gender and racial disparities among hospital CEO’s in the United States, and historically, male, Caucasian healthcare executives have made significantly larger salaries than females and other races. With a recent focus on reducing barriers and disparities in healthcare, it remains to be seen whether there have been changes in these disparities over time. The purpose of this study was to explore disparities among salaries of hospital executives in the United States. Analysis of salary data was conducted utilizing online hospital salary databases. Statistical analysis was conducted to examine the significance of the differences. Results indicated that there had been improvements in disparities among some ethnicities. Gender disparities remain the largest gap. The implications of this study are significant for the field of healthcare management as disparities can affect both social dynamics and organizational culture. Understanding where disparities lie is the first step towards bridging the gap and reducing barriers for cultural diversity within healthcare management.

Keywords: health care, disparities, management, executives

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Authors: Mustafa Altin, Gamze Fahriye Pehlivan, Sadiye Didem Boztepe Erkis, Sakir Tasdemir, Sevda Altin

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In this study, an experimental study was executed related to the strength of wooden materials which have been commonly used both in the past and present against pressure and whether fire retardant materials used against fire have any effects or not. Totally, 81 samples which included three different wood species, three different sizes, two different fire retardants and two unprocessed samples were prepared. Compressive pressure tests were applied to the prepared samples, their variance analyses were executed in accordance with the obtained results and it was aimed to determine the most convenient wooden materials and fire-retardant coating material. It was also determined that the species of wood and the species of coating caused the decrease and/or increase in the resistance against pressure.

Keywords: resistance of wood against pressure, species of wood, variance analysis, wood coating, wood fire safety

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Authors: Imelda Atengco Milan

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This research is aimed to assess the effectiveness and status of Islamic branding amongst hypermarkets from respondents perspective in the Kingdom of Bahrain such as Lulu, Geant and Carrefour and It was identified in terms of pure advertisement, religious norms and culture, certified halal product/ brand, consumption barriers and attitude towards other products/ brand. Included here are also the essentials in modern marketing including problems encountered and recommendations which will be revealed through the findings of the study. The methods used are descriptive and quantitative with sample analysis through quite a number of populations. Formulation of Sample questionnaire is done according to the variables and items used to measure reliability of statistics. The measurement of validity on the conduct of the surveys has been done according to Chronbach’s value (greater than 0.7). Pearson correlation was used as part of statistical analysis as well. It must show continuously that the model used is aligned towards factors indicated.

Keywords: pure advertisement, religious norms & culture, certified halal product, attitude towards other brand and consumption barriers

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Authors: Srushti R. Joshi, Ujjwal Rakesh, Spoorthi Sripad

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The rapid advancement of remote sensing technologies has revolutionized plant health monitoring, offering valuable insights for precision agriculture and environmental management. This paper presents a comprehensive comparative analysis between the widely employed normalized difference vegetation index (NDVI) and state-of-the-art hyperspectral sensors in the context of plant health assessment. The study aims to elucidate the weigh ups of spectral resolution. Employing a diverse range of vegetative environments, the research utilizes simulated datasets to evaluate the performance of NDVI and hyperspectral sensors in detecting subtle variations indicative of plant stress, disease, and overall vitality. Through meticulous data analysis and statistical validation, this study highlights the superior performance of hyperspectral sensors across the parameters used.

Keywords: normalized difference vegetation index, hyperspectral sensor, spectral resolution, infrared

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Authors: Dongjoo Chin

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The purpose of this study was to investigate the effectiveness of an Early Intensive Behavioral Intervention (EIBI) program on infants with autism spectrum disorder (ASD) and to explore the factors predicting the effectiveness of the program, focusing on the infant's age, language ability, problem behaviors, and parental stress. 19 pairs of infants aged between 2 and 5 years who have had been diagnosed with ASD, and their parents participated in an EIBI program at a clinic providing evidence-based treatment based on applied behavior analysis. The measurement tools which were administered before and after the EIBI program and compared, included PEP-R, a curriculum evaluation, K-SIB-R, K-Vineland-II, K-CBCL, and PedsQL for the infants, and included PSI-SF and BDI-II for the parents. Statistical analysis was performed using a sample t-test and multiple regression analysis and the results were as follows. The EIBI program showed significant improvements in overall developmental age, curriculum assessment, and quality of life for infants. There was no difference in parenting stress or depression. Furthermore, measures for both children and parents at the start of the program predicted neither PEP-R nor the degree of improvement in curriculum evaluation measured six months later at the end of the program. Based on these results, the authors suggest future directions for developing an effective intensive early intervention (EIBI) program for infants with ASD in Korea, and discuss the implications and limitations of this study.

Keywords: applied behavior analysis, autism spectrum disorder, early intensive behavioral intervention, parental stress

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Authors: Ozcan Baris Citil

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The aim of the present study is the determination of the effects of variations in the proximate analysis, cholesterol content and fatty acid compositions of Helix aspersa. Garden snails (Helix aspersa) were picked up by hand from the Central Anatolia Region of Turkey, in autumn (November) in 2015. Fatty acid methyl esters (FAMEs) and cholesterol analysis were analyzed by gas chromatography (GC). The protein contents of snail muscle were determined with Kjeldahl distillation units. Statistical comparisons were made by using SPSS Software (version 16.0). Thirty different fatty acids of different saturation levels were detected. As the predominant fatty acids, stearic acid (C18:0), oleic acid (C18:1ω9), linoleic acid (C18:2ω6), palmitic acid (C16:0), arachidonic acid (C20:4ω6), eicosadienoic acid (C20:2) and linolenic acid (C18:3ω3) were found in Helix aspersa. Palmitic acid (C16:0) was identified as the major SFA in autumn. Linoleic acid (C18:2ω6), eicosadienoic acid (C20:2) and arachidonic acid (C20:4ω6) have the highest levels among the PUFAs. In the present study, ω3 were found 5.48% in autumn. Linolenic acid and omega-3 fatty acid amounts in the autumn decreased significantly but cholesterol content was not affected in Helix aspersa in autumn (November) in 2015.

Keywords: Helix aspersa, fatty acid, SFA, PUFA, cholesterol

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Authors: Leena-Maria Alyedreessy

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Self-esteem is thought to be determined by ones’ own feeling of being included, liked and accepted by others. This research explores whether this concept may also be applied in the virtual world and assesses whether there is any relationship between Twitter users' self-esteem and the amount of interactions they receive. 20 female Arab participants were given a survey asking them about their Twitter interactions and their feelings of having an imagined audience to fill out and a Rosenberg Self-Esteem Assessment to complete. After completion and statistical analysis, results showed a significant correlation between the feeling of being Twitter elite, the feeling of having a lot of people listening to your tweets and having a lot of interactions with high self-esteem. However, no correlations were detected for low-self-esteem and low interactions.

Keywords: twitter, social media, self-esteem, narcissism, interactions

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

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Rainfall and runoff phenomenon is a chaotic and complex outcome of nature which requires sophisticated modelling and simulation methods for explanation and use. Time Series modelling allows runoff data analysis and can be used as forecasting tool. In the paper attempt is made to model river runoff data and predict the future behavioural pattern of river based on annual past observations of annual river runoff. The river runoff analysis and predict are done using ARIMA model. For evaluating the efficiency of prediction to hydrological events such as rainfall, runoff and etc., we use the statistical formulae applicable. The good agreement between predicted and observation river runoff coefficient of determination (R²) display that the ARIMA (4,1,1) is the suitable model for predicting Karkheh River runoff at Iran.

Keywords: time series modelling, ARIMA model, river runoff, Karkheh River, CLS method

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Authors: Amir Mabhout, Toktam Ghafarian, Amirhossein Farzin, Zahra Makki, Sajjad Alizadeh, Amirhossein Ghavi

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The high number of Netflix subscribers makes it attractive for data scientists to extract valuable knowledge from the viewers' behavioural analyses. This paper presents a set of statistical insights into viewers' viewing history. After that, a deep learning model is used to predict the future watching behaviour of the users based on previous watching history within the Netflixlatte data pool. Netflixlatte in an aggregated and anonymized data pool of 320 Netflix viewers with a length 250 000 data points recorded between 2008-2022. We observe insightful correlations between the distribution of viewing time and the COVID-19 pandemic outbreak. The presented deep learning model predicts future movie and TV series viewing habits with an average loss of 0.175.

Keywords: data analysis, deep learning, LSTM neural network, netflix

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Authors: Sagri Sharma

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Analysis of diseases integrating multi-factors increases the complexity of the problem and therefore, development of frameworks for the analysis of diseases is an issue that is currently a topic of intense research. Due to the inter-dependence of the various parameters, the use of traditional methodologies has not been very effective. Consequently, newer methodologies are being sought to deal with the problem. Supervised Learning Algorithms are commonly used for performing the prediction on previously unseen data. These algorithms are commonly used for applications in fields ranging from image analysis to protein structure and function prediction and they get trained using a known dataset to come up with a predictor model that generates reasonable predictions for the response to new data. Gene expression profiles generated by DNA analysis experiments can be quite complex since these experiments can involve hypotheses involving entire genomes. The application of well-known machine learning algorithm - Support Vector Machine - to analyze the expression levels of thousands of genes simultaneously in a timely, automated and cost effective way is thus used. The objectives to undertake the presented work are development of a methodology to identify genes relevant to Hepatocellular Carcinoma (HCC) from gene expression dataset utilizing supervised learning algorithms and statistical evaluations along with development of a predictive framework that can perform classification tasks on new, unseen data.

Keywords: artificial intelligence, biomarker, gene expression datasets, hepatocellular carcinoma, machine learning, supervised learning algorithms, support vector machine

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Authors: Wenbo Du, Xiaomei Ma

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With the empowerment of Cognitive Diagnostic Assessment (CDA), various domains of language testing and assessment have been investigated to dig out more diagnostic information. What is noticeable is that most of the extant empirical CDA-based research puts much emphasis on individual-level diagnostic purpose with very few concerned about learners’ group-level performance. Even though the personalized diagnostic feedback is the unique feature that differentiates CDA from other assessment tools, group-level diagnostic information cannot be overlooked in that it might be more practical in classroom setting. Additionally, the group-level diagnostic information obtained via current CDA always results in a “flat pattern”, that is, the mastery/non-mastery of all tested skills accounts for the two highest proportion. In that case, the outcome does not bring too much benefits than the original total score. To address these issues, the present study attempts to apply cluster analysis for group classification and quantile regression analysis to pinpoint learners’ performance at different proficiency levels (beginner, intermediate and advanced) thus to enhance the interpretation of the CDA results extracted from a group of EFL learners’ reading performance on a diagnostic reading test designed by PELDiaG research team from a key university in China. The results show that EM method in cluster analysis yield more appropriate classification results than that of CDA, and quantile regression analysis does picture more insightful characteristics of learners with different reading proficiencies. The findings are helpful and practical for instructors to refine EFL reading curriculum and instructional plan tailored based on the group classification results and quantile regression analysis. Meanwhile, these innovative statistical methods could also make up the deficiencies of CDA and push forward the development of language testing and assessment in the future.

Keywords: cognitive diagnostic assessment, diagnostic feedback, EFL reading, quantile regression

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Authors: Maximilian Engelhardt, Stephan Seeck

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The COVID-19 pandemic is accelerating the already growing field of e-commerce. The resulting urban freight transport volume leads to traffic and negative environmental impact. Furthermore, the service level of parcel logistics service provider is lacking far behind the expectations of consumer. These challenges can be solved by radically reorganize the urban last mile distribution structure: parcels could be consolidated in a micro hub within the inner city and delivered within time windows by cargo bike. This approach leads to a significant improvement of consumer satisfaction with their overall delivery experience. However, this approach also leads to significantly increased costs per parcel. While there is a relevant share of online shoppers that are willing to pay for such a delivery service there are no deeper insights about this target group available in the literature. Being aware of the importance of knowing target groups for businesses, the aim of this paper is to elaborate the most important factors that determine the willingness to pay for sustainable and service-oriented parcel delivery (factor analysis) and to derive customer segments (cluster analysis). In order to answer those questions, a data set is analyzed using quantitative methods of multivariate statistics. The data set was generated via an online survey in September and October 2020 within the five largest cities in Germany (n = 1.071). The data set contains socio-demographic, living-related and value-related variables, e.g. age, income, city, living situation and willingness to pay. In a prior work of the author, the data was analyzed applying descriptive and inference statistical methods that only provided limited insights regarding the above-mentioned research questions. The analysis in an exploratory way using factor and cluster analysis promise deeper insights of relevant influencing factors and segments for user behavior of the mentioned parcel delivery concept. The analysis model is built and implemented with help of the statistical software language R. The data analysis is currently performed and will be completed in December 2021. It is expected that the results will show the most relevant factors that are determining user behavior of sustainable and service-oriented parcel deliveries (e.g. age, current service experience, willingness to pay) and give deeper insights in characteristics that describe the segments that are more or less willing to pay for a better parcel delivery service. Based on the expected results, relevant implications and conclusions can be derived for startups that are about to change the way parcels are delivered: more customer-orientated by time window-delivery and parcel consolidation, more environmental-friendly by cargo bike. The results will give detailed insights regarding their target groups of parcel recipients. Further research can be conducted by exploring alternative revenue models (beyond the parcel recipient) that could compensate the additional costs, e.g. online-shops that increase their service-level or municipalities that reduce traffic on their streets.

Keywords: customer segmentation, e-commerce, last mile delivery, parcel service, urban logistics, willingness-to-pay

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Authors: Azita Behbahaninia

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This research has been carried out to determine the water quality and physico-chemical properties Polour River, one of the most branch of Haraz River. Polour River was studied for a period of one year Samples were taken from different stations along the main branch of River polour. In water samples determined pH, DO, SO4, Cl, PO4, NO3, EC, BOD, COD, Temprature, color and number of Caliform per liter. ArcGIS was used for the zoning of phosphate concentration in the polour River basin. The results indicated that the river is polluted in polour village station, because of discharge domestic wastewater and also river is polluted in Ziar village station, because of agricultural wastewater and water is contaminated in aquaculture station, because of fish ponds wastewater. Statistical analysis shows that between independent traits and coliform regression relationship is significant at the 1% level. Coefficient explanation index indicated independent traits control 80% coliform and 20 % is for unknown parameters. The causality analysis showed Temperature (0.6) has the most positive and direct effect on coliform and sulfate has direct and negative effect on coliform. The results of causality analysis and the results of the regression analysis are matched and other forms direct and indirect effects were negligible and ignorable. Kruskal-Wallis test showed, there is different between sampling stations and studied characters. Between stations for temperature, DO, COD, EC, sulfate and coliform is at 1 % and for phosphate 5 % level of significance.

Keywords: coliform, GIS, pollution, phosphate, river

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Authors: Suelane Garcia Fontes, Silvio Luiz Stanzani, Pedro L. Pizzigatti Corrła Ronaldo G. Morato

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Environmental changes and major natural disasters are most prevalent in the world due to the damage that humanity has caused to nature and these damages directly affect the lives of animals. Thus, the study of animal behavior and their interactions with the environment can provide knowledge that guides researchers and public agencies in preservation and conservation actions. Exploratory analysis of animal movement can determine the patterns of animal behavior and with technological advances the ability of animals to be tracked and, consequently, behavioral studies have been expanded. There is a lot of research on animal movement and behavior, but we note that a proposal that combines resources and allows for exploratory analysis of animal movement and provide statistical measures on individual animal behavior and its interaction with the environment is missing. The contribution of this paper is to present the framework AniMoveMineR, a unified solution that aggregates trajectory analysis and data mining techniques to explore animal movement data and provide a first step in responding questions about the animal individual behavior and their interactions with other animals over time and space. We evaluated the framework through the use of monitored jaguar data in the city of Miranda Pantanal, Brazil, in order to verify if the use of AniMoveMineR allows to identify the interaction level between these jaguars. The results were positive and provided indications about the individual behavior of jaguars and about which jaguars have the highest or lowest correlation.

Keywords: data mining, data science, trajectory, animal behavior

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Authors: G. M. Hamada, A. A. Al-Gathe, A. M. Al-Khudafi

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Determination of water saturation in sandstone is a vital question to determine the initial oil or gas in place in reservoir rocks. Water saturation determination using electrical measurements is mainly on Archie’s formula. Consequently accuracy of Archie’s formula parameters affects water saturation values rigorously. Determination of Archie’s parameters a, m, and n is proceeded by three conventional techniques, Core Archie-Parameter Estimation (CAPE) and 3-D. This work introduces the hybrid system of parallel self-organizing neural network (PSONN) targeting accepted values of Archie’s parameters and, consequently, reliable water saturation values. This work focuses on Archie’s parameters determination techniques; conventional technique, CAPE technique, and 3-D technique, and then the calculation of water saturation using current. Using the same data, a hybrid parallel self-organizing neural network (PSONN) algorithm is used to estimate Archie’s parameters and predict water saturation. Results have shown that estimated Arche’s parameters m, a, and n are highly accepted with statistical analysis, indicating that the PSONN model has a lower statistical error and higher correlation coefficient. This study was conducted using a high number of measurement points for 144 core plugs from a sandstone reservoir. PSONN algorithm can provide reliable water saturation values, and it can supplement or even replace the conventional techniques to determine Archie’s parameters and thereby calculate water saturation profiles.

Keywords: water saturation, Archie’s parameters, artificial intelligence, PSONN, sandstone reservoir

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Authors: Manar Aslan, Ayfer Karaaslan

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Purpose: The aim of this study was to determine the attitude towards the use of the maiden name of the Turkish people. Methods: For the study group who lives in the center of Konya/Turkey and people aged 16-65 years, as the sample identified 1,000 people with simple random between the months of February to May 2013. The survey created by the researchers, for investigating the perception of using the maiden name of the people of Konya consists of 25 questions with demographic characteristics. For statistical analysis of the obtained data made using SPSS 20, chi-square test and one-way analysis of variance methods of frequency, average, were evaluated as percentage distribution. Results: The traditional view of Konya increasing age increases, decreases the desire to use her maiden name. So look favorably than younger generations to use maiden name. In parallel with the level of educational levels are increasing utilization rates maiden name. Thus, individuals with higher levels of education are more positive look at the use of her maiden name. Looking at the marital status; compared to individuals with a single against the use of her maiden name of individuals who are married are more negative attitude.

Keywords: Maiden name, public viewpoint, utilization, women

Procedia PDF Downloads 277

Authors: Marlon P. Perez

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The study entitled “The Effect of Leader Motivating Language on Work Performance and Job Satisfaction as Perceived by the Employees of SoroSoro Ibaba Development Cooperative (SIDC)” primarily aims to evaluate the effect of leader’s use of motivating language in terms of the three types of speech acts namely, direction-giving language, empathetic language and meaning-making language with regard to the work performance and job satisfaction of the employees. The study made use of the descriptive method of this research that it followed certain processes in gathering the necessary and accurate information. Furthermore, survey questionnaires were used in order to congregate the respondents’ outlooks, opinions, and insight in the study. These survey questionnaires were distributed to one hundred fifty (150) employees from the five (5) outlets of SoroSoro Ibaba Development Cooperative (SIDC) in Batangas City who were chosen as the respondents of the study. However, only hundred twenty (120) out of one hundred fifty (150) or eighty (80) percent of the questionnaires were retrieved. Moreover, to accomplish the objectives of the study, different statistical treatments were used for the interpretation and analysis of the gathered data. These were the relative frequency, weighted mean, one-way analysis of variance and Pearson r. Based on those statistical treatments, researchers came up with the following results: first, most of the respondents were below 35 years old, males, college graduates and in regular status; second, direction-giving language, empathetic language, and meaning-making language affect the work performance and job satisfaction of the employees to a great extent; third, there was a non-significant difference with regards to the effect of leader motivating language on the work performance and job satisfaction of the employee; and, last, there was a significant relationship on the assessment of the effect of leader motivating language on work performance and job satisfaction when grouped according to respondents’ profile. Based on these results, various recommendations were conceptualized such as the designing of proposed activities like communication workshop and team-building to augment the communication between the leader and an employee. These activities could help for the development and attainment of an excellent communication within the different organizations and companies that are very important to any business success.

Keywords: leader motivating language, work performance, job satisfaction, employees

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Authors: Nazih Ramadan, Manal Mohy-Eldine, Amani Hanoon, Alaa Shehab

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Background and Aims: The study of fingerprints is widely used in providing a clue regarding identity. Age and gender identification from fingerprints is an important step in forensic anthropology in order to minimize the list of suspects search. The aim of this study was to determine finger ridge density and patterns among Egyptians, and to estimate age and gender using ridge densities. Materials and Methods: This study was conducted on 177 randomly-selected healthy Egyptian subjects (90 males and 87 females). They were divided into three age groups; Group (a): from 6-< 12 years, group (b) from 12-< 18 years and group (c) ≥ 18 years. Bilateral digital prints, from every subject, were obtained by the inking procedure. Ridge count per 25 mm² was determined together with assessment of ridge pattern type. Statistical analysis was done with references to different age and sex groups. Results: There was a statistical significant difference in ridge density between the different age groups; where younger ages had significantly higher ridge density than older ages. Females proved to have significantly higher ridge density than males. Also, there was a statistically significant negative correlation between age and ridge density. Ulnar loops were the most frequent pattern among Egyptians then whorls then arches then radial loops. Finally, different regression models were constructed to estimate age and gender from fingerprints ridge density. Conclusion: fingerprint ridge density can be used to identify both age and sex of subjects. Further studies are recommended on different populations, larger samples or using different methods of fingerprint recording and finger ridge counting.

Keywords: age, sex identification, Egyptian population, fingerprints, ridge density

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Authors: H. Nouri, I. E. Achouri, A. Grimes, H. Ait Said, M. Aissou, Y. Zebboudj

Abstract:

This paper aims to analysis the behaviour of DC corona discharge in wire-to-plate electrostatic precipitators (ESP). Current-voltage curves are particularly analysed. Experimental results show that discharge current is strongly affected by the applied voltage. The proposed method of current identification is to use the method of least squares. Least squares problems that of into two categories: linear or ordinary least squares and non-linear least squares, depending on whether or not the residuals are linear in all unknowns. The linear least-squares problem occurs in statistical regression analysis; it has a closed-form solution. A closed-form solution (or closed form expression) is any formula that can be evaluated in a finite number of standard operations. The non-linear problem has no closed-form solution and is usually solved by iterative.

Keywords: electrostatic precipitator, current-voltage characteristics, least squares method, electric field, magnetic field

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Authors: J. K. Karapetyan

Abstract:

In this paper seismological-statistical analysis of actual instrumental data on the main tremor of the Great Japan earthquake 11.03.2011 is implemented for finding out the dependence between maximal values of peak ground accelerations (PGA) and epicentric distances. A number of peculiarities of manifestation of accelerations' maximum values at the interval of long epicentric distances are revealed which do not correspond with current scales of seismic intensity.

Keywords: earthquakes, instrumental records, seismic hazard, Japan

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Authors: Panos Xenos, Milton Nektarios, John Yfantopoulos

Abstract:

Background: Policy makers, professional organizations and payers have introduced a variety of initiatives and reforms for the health systems worldwide, aimed at improving hospital efficiency. Their efforts are concentrated in two main categories: to constrain increasing healthcare costs and to enhance quality of services provided. Research Objectives: This study examines the efficiency of 112 Greek public hospitals for the year 2009, evaluates the importance of bootstrapping techniques and investigates the effect of contextual factors on hospital efficiency. Furthermore, the effect of qualitative evidence, on hospital efficiency is explored using data from 28 large hospitals. Methods: We applied Data Envelopment Analysis, augmented by bootstrapping techniques, to estimate efficiency scores. In order to measure the effect of environmental factors on hospital efficiency we used Tobit regression analysis. The significance of our models is evaluated using statistical tests to compare distributions. Results: The Kolmogorov-Smirnov test between the original and the bootstrap-corrected efficiency indicates that their distributions are significantly different (p-value<0.01). The environmental factors, that seem to influence efficiency, are Occupancy Rating and the ratio between Outpatient Visits and Inpatient Days. Results indicate that the inclusion of the quality variable in DEA modelling generates statistically significant variations in efficiency scores (p-value<0.05). Conclusions: The inclusion of quality variables and the use of bootstrap resampling in efficiency analysis impose a statistically significant effect on the distribution of efficiency scores. As a policy conclusion we highlight the importance of these methods on hospital efficiency analysis and, by implication, on healthcare resource allocation.

Keywords: hospitals, efficiency, quality, data envelopment analysis, Greek public hospital sector

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Authors: Guo Jinhong

Abstract:

The purpose of this study is to explore the association between board member functions and information disclosure levels. Based on the literature variables, such as the characteristics of the board of directors in the past, a single comprehensive indicator is established as a substitute variable for board functions, and the information disclosure evaluation results published by the Securities and Foundation are used to measure the information disclosure level of the company. This study focuses on companies listed on the Taiwan Stock Exchange from 2006 to 2010 and uses descriptive statistical analysis, univariate analysis, correlation analysis and ordered normal probability (Ordered Probit) regression for empirical analysis. The empirical results show that there is a significant positive correlation between the function of board members and the level of information disclosure. This study also conducts a sensitivity test and draws similar conclusions, showing that boards with better board member functions have higher levels of information disclosure. In addition, this study also found that higher board independence, lower director shareholding pledge ratio, higher director shareholding ratio, and directors with rich professional knowledge and practical experience can help improve the level of information disclosure. The empirical results of this study provide strong support for the "relative regulations to improve the level of information disclosure" formulated by the competent authorities in recent years.

Keywords: function of board members, information disclosure, securities, foundation

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Authors: Ewa Rusak, Sebastian Seget, Aleksandra Mroskowiak, Mirosław Partyka, Ewa Samulska, Julia Strózik, Anna Wilk, Przemysława Jarosz-Chobot

Abstract:

Introduction: Various infections can affect children suffering from Type 1 Diabetes (T1D) because of dysfunctions of the immune system. The urinary tract and urethra of these children can be easily infected areas because of glycosuria. Aim: The microflora assessment of the urethra area of children with newly diagnosed T1D. Methods: The materials of the study were swabs taken prospectively from the urethral area of 63 children at the time of diagnosis of T1D (37 boys), then the results were correlated to the clinical parameters. In the statistical analysis, there were T student, Chi square, and U Mann-Whitney tests used. Results: The mean age was 9.4 years (6 months-17.4 years). The mean HbA1c value was 12.1% (5,6% - 20.1%). The mean value of glycosuria was 4463.2 mg/dl (0 - 9770 mg/dl). Ketoacidosis was diagnosed in 29 children (49%). The following microbial species were isolated in the collected materials: Staphylococcus epidermidis in 18 children (28.6%), Enterococcus faecalis in 17 children (27%), Candida albicans in 15 children (23.8%), coagulase-negative staphylococciin 11 children (17.5%), group B Streptococcus beta-hemolysis in 10 children (15.9%), S. aureus, E. coli, S. anginosus, C. glucuronolyticum, and A. urinae in 7 children each (11.1%), group B Streptococcus beta-hemolysis and S. hominis in 6 children each (9.5%), L. gasseri in 5 children (7.5%), C. dubliniensis in 4 children (6.3) and other, isolated cases. 2 of diagnosed patients were cultured negatively (3.2%). There were statistical correlations between the type of colonisation and patients’ sex and HbA1C value. Conclusions: It is extremely important to examine the urethral area at the time of diagnosis of T1D in order to detect inflammation and to undertake the appropriate and effective intervention.

Keywords: diabetology, skin disorders, microbiology, microflora

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Authors: Mohamed Khalifa Zayet, Salma Belal Eiid, Mushira Mohamed Dahaba

Abstract:

Introduction: Malignant tumors may not be easily detected by traditional radiographic techniques especially in an anatomically complex area like maxillofacial region. At the same time, the advent of biological functional MRI was a significant footstep in the diagnostic imaging field. Objective: The purpose of this study was to define the malignant metabolic profile of maxillofacial lesions using diffusion MRI and magnetic resonance spectroscopy, as adjunctive aids for diagnosing of such lesions. Subjects and Methods: Twenty-one patients with twenty-two lesions were enrolled in this study. Both morphological and functional MRI scans were performed, where T1, T2 weighted images, diffusion-weighted MRI with four apparent diffusion coefficient (ADC) maps were constructed for analysis, and magnetic resonance spectroscopy with qualitative and semi-quantitative analyses of choline and lactate peaks were applied. Then, all patients underwent incisional or excisional biopsies within two weeks from MR scans. Results: Statistical analysis revealed that not all the parameters had the same diagnostic performance, where lactate had the highest areas under the curve (AUC) of 0.9 and choline was the lowest with insignificant diagnostic value. The best cut-off value suggested for lactate was 0.125, where any lesion above this value is supposed to be malignant with 90 % sensitivity and 83.3 % specificity. Despite that ADC maps had comparable AUCs still, the statistical measure that had the final say was the interpretation of likelihood ratio. As expected, lactate again showed the best combination of positive and negative likelihood ratios, whereas for the maps, ADC map with 500 and 1000 b-values showed the best realistic combination of likelihood ratios, however, with lower sensitivity and specificity than lactate. Conclusion: Diffusion weighted imaging and magnetic resonance spectroscopy are state-of-art in the diagnostic arena and they manifested themselves as key players in the differentiation process of orofacial tumors. The complete biological profile of malignancy can be decoded as low ADC values, high choline and/or high lactate, whereas that of benign entities can be translated as high ADC values, low choline and no lactate.

Keywords: diffusion magnetic resonance imaging, magnetic resonance spectroscopy, malignant tumors, maxillofacial

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