Search results for: statistical procedures

Authors: Behrooz Khalilloo, Hamid Shahriari, Emad Roghanian

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Process capability indices (PCIs) are important concepts of statistical quality control and measure the capability of processes and how much processes are meeting certain specifications. An important issue in statistical quality control is parameter estimation. Under the assumption of multivariate normality, the distribution parameters, mean vector and variance-covariance matrix must be estimated, when they are unknown. Classic estimation methods like method of moment estimation (MME) or maximum likelihood estimation (MLE) makes good estimation of the population parameters when data are not contaminated. But when outliers exist in the data, MME and MLE make weak estimators of the population parameters. So we need some estimators which have good estimation in the presence of outliers. In this work robust M-estimators for estimating these parameters are used and based on robust parameter estimators, robust process capability indices are introduced. The performances of these robust estimators in the presence of outliers and their effects on process capability indices are evaluated by real and simulated multivariate data. The results indicate that the proposed robust capability indices perform much better than the existing process capability indices.

Keywords: multivariate process capability indices, robust M-estimator, outlier, multivariate quality control, statistical quality control

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Authors: Arkaprabha Bhattacharyya, Makarand Hastak

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The COVID-19 pandemic is unprecedented in terms of its global reach and economic impacts. Historically, investment in infrastructure development projects has been touted to boost the economic growth of a nation. The State and Local governments responsible for delivering infrastructure assets work under tight budgets. Therefore, it is important to understand which infrastructure projects have the highest potential of boosting economic growth in the post-pandemic era. This paper presents relationships between infrastructure projects and economic growth. Statistical relationships between investment in different types of infrastructure projects (transit, water and wastewater, highways, power, manufacturing etc.) and indicators of economic growth are presented using historic data between 2002 and 2020 from the U.S. Census Bureau and U.S. Bureau of Economic Analysis (BEA). The outcome of the paper is the comparison of statistical correlations between investment in different types of infrastructure projects and indicators of economic growth. The comparison of the statistical correlations is useful in ranking the types of infrastructure projects based on their ability to influence economic prosperity. Therefore, investment in the infrastructures with the higher rank will have a better chance of boosting the economic growth. Once, the ranks are derived, they can be used by the decision-makers in infrastructure investment related decision-making process.

Keywords: economic growth, infrastructure development, infrastructure projects, strategic investment

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Authors: Jelena Vucicevic

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Reliability analysis represents a very important task in different areas of work. In any industry, this is crucial for maintenance, efficiency, safety and monetary costs. There are ways to calculate reliability, unreliability, failure density and failure rate. This paper will try to introduce another way of calculating reliability by using R statistical software. R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. The R programming environment is a widely used open source system for statistical analysis and statistical programming. It includes thousands of functions for the implementation of both standard and new statistical methods. R does not limit user only to operation related only to these functions. This program has many benefits over other similar programs: it is free and, as an open source, constantly updated; it has built-in help system; the R language is easy to extend with user-written functions. The significance of the work is calculation of time to failure or reliability in a new way, using statistic. Another advantage of this calculation is that there is no need for technical details and it can be implemented in any part for which we need to know time to fail in order to have appropriate maintenance, but also to maximize usage and minimize costs. In this case, calculations have been made on diesel generator fans but the same principle can be applied to any other part. The data for this paper came from a field engineering study of the time to failure of diesel generator fans. The ultimate goal was to decide whether or not to replace the working fans with a higher quality fan to prevent future failures. Seventy generators were studied. For each one, the number of hours of running time from its first being put into service until fan failure or until the end of the study (whichever came first) was recorded. Dataset consists of two variables: hours and status. Hours show the time of each fan working and status shows the event: 1- failed, 0- censored data. Censored data represent cases when we cannot track the specific case, so it could fail or success. Gaining the result by using R was easy and quick. The program will take into consideration censored data and include this into the results. This is not so easy in hand calculation. For the purpose of the paper results from R program have been compared to hand calculations in two different cases: censored data taken as a failure and censored data taken as a success. In all three cases, results are significantly different. If user decides to use the R for further calculations, it will give more precise results with work on censored data than the hand calculation.

Keywords: censored data, R statistical software, reliability analysis, time to failure

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Authors: Josef Fládr, Jiří Němeček, Veronika Koudelková, Petr Bílý

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Mechanical parameters of cementitious composites differ quite significantly based on the composition of cement matrix. They are also influenced by mixing times and procedure. The research presented in this paper was aimed at identification of differences in microstructure of normal strength (NSC) and differently mixed high strength (HSC) cementitious composites. Scanning electron microscopy (SEM) investigation together with energy dispersive X-ray spectroscopy (EDX) phase analysis of NSC and HSC samples was conducted. Evaluation of interfacial transition zone (ITZ) between the aggregate and cement matrix was performed. Volume share, thickness, porosity and composition of ITZ were studied. In case of HSC, samples obtained by several different mixing procedures were compared in order to find the most suitable procedure. In case of NSC, ITZ was identified around 40-50% of aggregate grains and its thickness typically ranged between 10 and 40 µm. Higher porosity and lower share of clinker was observed in this area as a result of increased water-to-cement ratio (w/c) and the lack of fine particles improving the grading curve of the aggregate. Typical ITZ with lower content of Ca was observed only in one HSC sample, where it was developed around less than 15% of aggregate grains. The typical thickness of ITZ in this sample was similar to ITZ in NSC (between 5 and 40 µm). In the remaining four HSC samples, no ITZ was observed. In general, the share of ITZ in HSC samples was found to be significantly smaller than in NSC samples. As ITZ is the weakest part of the material, this result explains to large extent the improved mechanical properties of HSC compared to NSC. Based on the comparison of characteristics of ITZ in HSC samples prepared by different mixing procedures, the most suitable mixing procedure from the point of view of properties of ITZ was identified.

Keywords: electron diffraction spectroscopy, high strength concrete, interfacial transition zone, normal strength concrete, scanning electron microscopy

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Authors: Arash Sepehri Bonab

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Techniques to switch cells between development and differentiation, which tend to be commonly exclusive, are utilized in arrange to supply an expansive cell mass that can perform particular separated capacities required for the tissue to develop. Approaches to tissue engineering center on the have to give signals to cell populaces to advance cell multiplication and separation. Current tissue regenerative procedures depend primarily on tissue repair by transplantation of synthetic/natural inserts. In any case, restrictions on the existing procedures have expanded the request for tissue designing approaches. Tissue engineering innovation and stem cell investigation based on tissue building have made awesome advances in overcoming the issues of tissue and organ damage, useful loss, and surgical complications. Bone tissue has the capability to recover itself; in any case, surrenders of a basic estimate anticipate the bone from recovering and require extra support. The advancement of bone tissue building has been utilized to form useful options to recover the bone. This paper primarily portrays current advances in tissue engineering in different fields of bone and talks about the long-term trend of tissue designing innovation in the treatment of complex diseases.

Keywords: tissue engineering, bone, technologies, treatment

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Authors: M. Pramila Devi, N. V. N. Indra Kiran

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Control charts, predominantly in the form of X-bar chart, are important tools in statistical process control (SPC). They are useful in determining whether a process is behaving as intended or there are some unnatural causes of variation. A process is out of control if a point falls outside the control limits or a series of point’s exhibit an unnatural pattern. In this paper, a study is carried out on four training algorithms for CCPs recognition. For those algorithms optimal structure is identified and then they are studied for type I and type II errors for generalization without early stopping and with early stopping and the best one is proposed.

Keywords: control chart pattern recognition, neural network, backpropagation, generalization, early stopping

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Authors: Rabia Waseem, Low Kah Hin, Najihah Mohamed Hashim

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The variability in the chemical components of the Syzygium species essential oils has been evaluated. The leaves of Syzygium species have been collected from Perak, Malaysia. The essential oils extracted by using the conventional Hydro-distillation extraction procedure and analyzed by using Gas chromatography System attached with Mass Spectrometry (GCMS). Twenty-seven constituents were found in Syzygium species in which the major constituents include: α-Pinene (3.94%), α-Thujene (2.16%), α-Terpineol (2.95%), g-Elemene (2.89%) and D-Limonene (14.59%). The aim of this study was the comparison between the evaluated data and existing literature to fortify the major variability through statistical analysis.

Keywords: chemotaxonomy, cluster analysis, essential oil, medicinal plants, statistical analysis

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Authors: Tamanna Goyal, Divya Bansal, Sanjeev Sofat

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In world-threatening terrorist attacks, where early detection, distinction, and prediction are effective diagnosis techniques and for functionally accurate and precise analysis of terrorism data, there are so many data mining & statistical approaches to assure accuracy. The computational extraction of derived patterns is a non-trivial task which comprises specific domain discovery by means of sophisticated algorithm design and analysis. This paper proposes an approach for similarity extraction by obtaining the useful attributes from the available datasets of terrorist attacks and then applying feature selection technique based on the statistical impurity measures followed by clustering techniques on the basis of similarity measures. On the basis of degree of participation of attributes in the rules, the associative dependencies between the attacks are analyzed. Consequently, to compute the similarity among the discovered rules, we applied a weighted similarity measure. Finally, the rules are grouped by applying using hierarchical clustering. We have applied it to an open source dataset to determine the usability and efficiency of our technique, and a literature search is also accomplished to support the efficiency and accuracy of our results.

Keywords: association rules, clustering, similarity measure, statistical approaches

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Authors: Wi-Sun Ryu, Eun-Kee Bae

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Prior studies have shown that patients with right hemispheric stroke are likely to seek medical service compared with those with left hemispheric stroke. However, the underlying mechanism for this phenomenon is unknown. In the present study, we generated lesion probability maps in a patient with right and left middle cerebral artery infarct and statistically compared. We found that precentral gyrus-Brodmann area 44, a language area in the left hemisphere - involvement was significantly higher in patients with left hemispheric stroke. This finding suggests that a language dysfunction was more noticeable, thereby taking more patients to hospitals.

Keywords: cerebral infarct, brain MRI, statistical parametric mapping, middle cerebral infarct

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Authors: Agnieszka Leszczynska

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Flexibility and agility constitute the most dominant features of modern human resource management systems. The former pertains to procedures, practices and competences of human resources, and the latter to the procedures and practices’ effectiveness in dealing with changing conditions in the surrounding environment. The purpose of the paper is to present the relations between the flexibility and agility of human resources and achieving sustainable competitiveness. Based upon hitherto research, we develop a conceptual model that links the constructs together. The conducted study is of theoretical and conceptual nature. Critical literature analysis and the synthesis method were applied. A premise was made that the three dimensions of HR (Human Resources) flexibility (employee skill flexibility, employee behaviour flexibility, and HR practice flexibility) and HR agility affect competitiveness, by increasing the flexibility, creativity of human resources, and improving quality performance, and exert an impact upon the quality of life of employees and social relations. In particular, the agility and flexibility of human resources contribute to the growth of adaptability and strategic orientation, which directly affects the organization's competitiveness. The research results will help to better understand the impact of flexibility and agility related to the HRM (Human Resources Management) system upon the implementation of the concept of sustainable development in the organization.

Keywords: agility, human resource, sustainable competitiveness, sustainable development

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Authors: P. V. S. Mascarenhas, B. C. P. Albuquerque, D. J. F. Campos, L. L. Almeida, V. R. Domingues, L. C. S. M. Ozelim

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Retaining slope structures are increasingly considered in geotechnical engineering projects due to extensive urban cities growth. These kinds of engineering constructions may present instabilities over the time and may require reinforcement or even rebuilding of the structure. In this context, statistical analysis is an important tool for decision making regarding retaining structures. This study approaches the failure probability of the construction of a retaining wall over the debris of an old and collapsed one. The new solution’s extension length will be of approximately 350 m and will be located over the margins of the Lake Paranoá, Brasilia, in the capital of Brazil. The building process must also account for the utilization of the ruins as a caisson. A series of in situ and laboratory experiments defined local soil strength parameters. A Standard Penetration Test (SPT) defined the in situ soil stratigraphy. Also, the parameters obtained were verified using soil data from a collection of masters and doctoral works from the University of Brasília, which is similar to the local soil. Initial studies show that the concrete wall is the proper solution for this case, taking into account the technical, economic and deterministic analysis. On the other hand, in order to better analyze the statistical significance of the factor-of-safety factors obtained, a Monte Carlo analysis was performed for the concrete wall and two more initial solutions. A comparison between the statistical and risk results generated for the different solutions indicated that a Gabion solution would better fit the financial and technical feasibility of the project.

Keywords: economical analysis, probability of failure, retaining walls, statistical analysis

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Authors: Said Benkaciali, Mourad Haddadi, Abdallah Khellaf, Kacem Gairaa, Mawloud Guermoui

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In this study, many experiments were carried out to assess the influence of the input parameters on the performance of multilayer perceptron which is one the configuration of the artificial neural networks. To estimate the daily global solar radiation on the horizontal surface, we have developed some models by using seven combinations of twelve meteorological and geographical input parameters collected from a radiometric station installed at Ghardaïa city (southern of Algeria). For selecting of best combination which provides a good accuracy, six statistical formulas (or statistical indicators) have been evaluated, such as the root mean square errors, mean absolute errors, correlation coefficient, and determination coefficient. We noted that multilayer perceptron techniques have the best performance, except when the sunshine duration parameter is not included in the input variables. The maximum of determination coefficient and correlation coefficient are equal to 98.20 and 99.11%. On the other hand, some empirical models were developed to compare their performances with those of multilayer perceptron neural networks. Results obtained show that the neural networks techniques give the best performance compared to the empirical models.

Keywords: empirical models, multilayer perceptron neural network, solar radiation, statistical formulas

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Authors: Alena Dadova, Katarina Holla, Anna Cidlinova, Linda Makovicka Osvaldova, Jiri Vala, Samuel Kockar

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Occupational health and safety (ASH) is an area in which procedures and applications are constantly evolving and changing through legislation and new directives and guidelines. In this way, the relevant organizations strive to ensure continuous progress and the advantage of up-to-date information to ensure safety and prevent occupational accidents. Three ESENER surveys have been carried out in the European Union, led by the Agency for Safety and Health at Work (EU-OSHA). On the basis of surveys, it was determined how European workplaces manage risks and how they manage the field of safety and health protection at work. Thousands of companies and organizations in the European Union were involved in the surveys. Organizations and businesses were presented with a questionnaire that focused on the following topics: the impact of general risks on the field of OSH and the possibility of their management, psychosocial risks and other factors such as stress, harassment and bullying, and employee participation in OSH procedures. The article is dedicated to the fundamental conclusions from these surveys and their subsequent connection with the strategic intent of the Strategic Framework of European Union for the years 2021 - 2027. In the conclusion, emerging risks are identified and EU will soon have to deal with them.

Keywords: ESENER, emerging risks, strategic framework in OSH, EU

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Authors: Jane A. Luke

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Persistent pressure passed on to manufacturers from escalating consumer expectations and the ever growing global competitiveness have produced a rapidly increasing interest in the development of various manufacturing strategy models. Academic and industrial circles are taking keen interest in the field of manufacturing strategy. Many manufacturing strategies are currently centered on the traditional concepts of focused manufacturing capabilities such as quality, cost, dependability and innovation. Process capability indices was conducted assuming that the process under study is in statistical control and independent observations are generated over time. However, in practice, it is very common to come across processes which, due to their inherent natures, generate autocorrelated observations. The degree of autocorrelation affects the behavior of patterns on control charts. Even, small levels of autocorrelation between successive observations can have considerable effects on the statistical properties of conventional control charts. When observations are autocorrelated the classical control charts exhibit nonrandom patterns and lack of control. Many authors have considered the effect of autocorrelation on the performance of statistical process control charts. In this paper, the effect of autocorrelation on confidence intervals for different PCIs was included. Stationary Gaussian processes is explained. Effect of autocorrelation on PCIs is described in detail. Confidence intervals for Cp and Cpk are constructed for PCIs when data are both independent and autocorrelated. Confidence intervals for Cp and Cpk are computed. Approximate lower confidence limits for various Cpk are computed assuming AR(1) model for the data. Simulation studies and industrial examples are considered to demonstrate the results.

Keywords: autocorrelation, AR(1) model, Bissell’s approximation, confidence intervals, statistical process control, specification limits, stationary Gaussian processes

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Authors: Asma Ameur, Dhafer Malouche

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Hotel competitiveness research is an essential phase of the marketing strategy for any hotel. Certainly, knowing the hotels' competitors helps the hotelier to grasp its position in the market and the citizen to make the right choice in picking a hotel. Thus, competitiveness is an important indicator that can be influenced by various factors. In fact, the issue of competitiveness, this ability to cope with competition, remains a difficult and complex concept to define and to exploit. Therefore, the purpose of this article is to make an exploratory study to calculate a competitiveness indicator for hotels. Further on, this paper makes it possible to determine the criteria of direct or indirect effect on the image and the perception of a hotel. The actual research is used to look into the right model for hotel ‘competitiveness. For this reason, we exploit different theoretical contributions in the field of machine learning. Thus, we use some statistical techniques such as the Principal Component Analysis (PCA) to reduce the dimensions, as well as other techniques of statistical modeling. This paper presents a survey covering of the techniques and methods in hotel competitiveness research. Furthermore, this study allows us to deduct the significant variables that influence the determination of hotel’s competitors. Lastly, the discussed experiences in this article found that the hotel competitors are influenced by several factors with different rates.

Keywords: competitiveness, e-reputation, hotels' competitors, online hotel’ review, principal component analysis, statistical modeling

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Authors: Shekoufeh Behdad, Amirhossein Yadegari, Leila Ghodrati, Saman Yadegari

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Context: Preoperative anxiety is a common psychological reaction experienced by all patients undergoing surgery. It can have negative effects on the patient's well-being and even impact surgical outcomes. Therefore, finding effective interventions to reduce preoperative anxiety is important in improving patient care. Research Aim: The aim of this study is to compare the effects of oral administration of zaleplon (5 mg) and alprazolam (0.5 mg) on preoperative anxiety levels in women undergoing gynecological abdominal surgery. Methodology: This study is a double-blind, randomized clinical trial conducted after receiving approval from the university's ethics committee and obtaining written informed consent from the patients. The night before the surgery, patients were randomly assigned to receive either 0.5 mg of alprazolam or 5 mg of zaleplon orally. Anxiety levels, measured using a 10-cm visual analog scale, and hemodynamic variables (blood pressure and heart rate) were assessed before drug administration and on the morning of the operation after the patient entered the pre-operation room. Findings: The study found that there were no significant differences in mean anxiety levels or hemodynamic variables before and after administration of either drug in both groups (P value > 0.05). This suggests that both 0.5 mg of alprazolam and 5 mg of zaleplon effectively reduce preoperative anxiety in women undergoing abdominal surgery without serious side effects. Theoretical Importance: This study contributes to the understanding of the effectiveness of alprazolam and zaleplon in reducing preoperative anxiety. It adds to the existing literature on pharmacological interventions for anxiety management, specifically in the context of gynecological abdominal surgery. Data Collection: Data for this study were collected through the assessment of anxiety levels using a visual analog scale and measuring hemodynamic variables, including systolic, diastolic, and mean arterial blood pressures, as well as heart rate. These measurements were taken before drug administration and on the morning of the surgery. Analysis Procedures: Statistical analysis was performed to compare the mean anxiety levels and hemodynamic variables before and after drug administration in the two groups. The significance of the differences was determined using appropriate statistical tests. Questions Addressed: This study aimed to answer the question of whether there are differences in the effects of alprazolam and zaleplon on preoperative anxiety levels in women undergoing gynecological abdominal surgery. Conclusion: The oral administration of both 0.5 mg of alprazolam and 5 mg of zaleplon the night before surgery effectively reduces preoperative anxiety in women undergoing abdominal surgery. These findings have important implications for the management of preoperative anxiety and can contribute to improving the overall surgical experience for patients.

Keywords: zaleplon, alprazolam, premedication, abdominal surgery

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Authors: Guozhen Li, Philip Hall, Nick Miles, Tao Wu

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This paper presents a numerical investigation of two horizontally mounted four-lobed swirl pipes in terms of swirl induction effectiveness into flows passing through them. The swirl flows induced by the two swirl pipes have the potential to improve the efficiency of Clean-In-Place procedures in a closed processing system by local intensification of hydrodynamic impact on the internal pipe surface. Pressure losses, swirl development within the two swirl pipe, swirl induction effectiveness, swirl decay and wall shear stress variation downstream of two swirl pipes are analyzed and compared. It was found that a shorter length of swirl inducing pipe used in joint with transition pipes is more effective in swirl induction than when a longer one is used, in that it has a less constraint to the induced swirl and results in slightly higher swirl intensity just downstream of it with the expense of a smaller pressure loss. The wall shear stress downstream of the shorter swirl pipe is also slightly larger than that downstream of the longer swirl pipe due to the slightly higher swirl intensity induced by the shorter swirl pipe. The advantage of the shorter swirl pipe in terms of swirl induction is more significant in flows with a larger Reynolds Number.

Keywords: swirl pipe, swirl effectiveness, CFD, wall shear stress, swirl intensity

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Authors: Filiz Ersoz, Taner Ersoz, Tugrul Bayraktar

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Renewable energy is referred to as "clean energy" and common popular support for the use of renewable energy (RE) is to provide electricity with zero carbon dioxide emissions. This study provides useful insight into the European Union (EU) RE, especially, into electricity generation obtained from renewables, and their targets. The objective of this study is to identify groups of European countries, using multivariate statistical analysis and selected indicators. The hierarchical clustering method is used to decide the number of clusters for EU countries. The conducted statistical hierarchical cluster analysis is based on the Ward’s clustering method and squared Euclidean distances. Hierarchical cluster analysis identified eight distinct clusters of European countries. Then, non-hierarchical clustering (k-means) method was applied. Discriminant analysis was used to determine the validity of the results with data normalized by Z score transformation. To explore the relationship between the selected indicators, correlation coefficients were computed. The results of the study reveal the current situation of RE in European Union Member States.

Keywords: share of electricity generation, k-means clustering, discriminant, CO2 emission

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Authors: Ana Staneva, Vessela Stoimenova

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A parametric estimation of the MBP with Power Series offspring distribution family is considered in this paper. The MLE for the parameters is obtained in the case when the observable data are incomplete and consist only with the generation sizes of the family tree of MBP. The parameter estimation is calculated by using the Monte Carlo EM algorithm. The estimation for the posterior distribution and for the offspring distribution parameters are calculated by using the Bayesian approach and the Gibbs sampler. The article proposes various examples with bivariate branching processes together with computational results, simulation and an implementation using R.

Keywords: Bayesian, branching processes, EM algorithm, Gibbs sampler, Monte Carlo methods, statistical estimation

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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: Avhasei Dorothy Rasifudi, Josephine Mandizha

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Cardiovascular risk factors continue to be the leading cause of death in the majority of developed and developing countries. In 2011, the World Health Organization reported that every year an estimated 17 million people globally die of CVD, representing 30% of all global deaths, particularly caused by heart attacks and strokes. The purpose of the study was to determine and describe the prevalence of selected cardiovascular risk factors among university of Venda staff. A cross-sectional study was conducted among 100 staff aged 20-65 years. The anthropometric measurements were conducted in accordance to and with standardized procedures advocated by the International Society for the Advanced Kinanthropometry. Weight, Height, waist circumference and hip circumference were measured for calculation of body mass index and waist-hip ratio. Blood pressure was measured using a Heine cuff and sphygmomanometer. Questionnaire was administered to gather demographic details and cardiovascular risk factors of hypertension and obesity. Data were analyzed using mean and standard deviation. The parameter t-test was applied to test significance level at p ≤ 0.05 between sexes. The statistical significance was set at p ≤ 0.05. The prevalence of hypertension was 23% with the highest prevalence amongst those aged 40 years and above. Factors found to be to be significantly associated with hypertension were gender, age, physical inactivity and family history. Prevalence of obesity was 43%, with the highest prevalence among those aged 40 years. The factors associated with obesity were diet, age and physical activity. The prevalence of hypertension and obesity in the study were high.

Keywords: cardiovascular, prevalence, risk factors, staff

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Authors: Gholam Reza Mirzaei, Mehran Roost

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This research was conducted with the aim of predicting the relationship between coronavirus anxiety and psychological hardiness in employees working at Shahid Beheshti Hospital in Shiraz. The current research design was descriptive and correlational. The statistical population of the research consisted of all the employees of Shahid Beheshti Hospital in Shiraz in 2021. From among the statistical population, 220 individuals were selected and studied based on available sampling. To collect data, Kobasa's psychological hardiness questionnaire and coronavirus anxiety questionnaire were used. After collecting the data, the scores of the participants were analyzed using Pearson's correlation coefficient multiple regression analysis and SPSS-24 statistical software. The results of Pearson's correlation coefficient showed that there is a significant negative correlation between psychological hardiness and its components (challenge, commitment, and control) with coronavirus anxiety; also, psychological hardiness with a beta coefficient of 0.20 could predict coronavirus anxiety in hospital employees. Based on the results, plans can be made to enhance psychological hardiness through educational workshops to relieve the anxiety of the healthcare staff.

Keywords: the corona virus, commitment, hospital employees, psychological hardiness

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Authors: Jose Flores, Nadia Gamboa

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A proper water quality management requires the establishment of a monitoring network. Therefore, evaluation of the efficiency of water quality monitoring networks is needed to ensure high-quality data collection of critical quality chemical parameters. Unfortunately, in some Latin American countries water quality monitoring programs are not sustainable in terms of recording historical data or environmentally representative sites wasting time, money and valuable information. In this study, multivariate statistical techniques, such as principal components analysis (PCA) and hierarchical cluster analysis (HCA), are applied for identifying the most significant monitoring sites as well as critical water quality parameters in the monitoring network of the Jequetepeque River basin, in northern Peru. The Jequetepeque River basin, like others in Peru, shows socio-environmental conflicts due to economical activities developed in this area. Water pollution by trace elements in the upper part of the basin is mainly related with mining activity, and agricultural land lost due to salinization is caused by the extensive use of groundwater in the lower part of the basin. Since the 1980s, the water quality in the basin has been non-continuously assessed by public and private organizations, and recently the National Water Authority had established permanent water quality networks in 45 basins in Peru. Despite many countries use multivariate statistical techniques for assessing water quality monitoring networks, those instruments have never been applied for that purpose in Peru. For this reason, the main contribution of this study is to demonstrate that application of the multivariate statistical techniques could serve as an instrument that allows the optimization of monitoring networks using least number of monitoring sites as well as the most significant water quality parameters, which would reduce costs concerns and improve the water quality management in Peru. Main socio-economical activities developed and the principal stakeholders related to the water management in the basin are also identified. Finally, water quality management programs will also be discussed in terms of their efficiency and sustainability.

Keywords: PCA, HCA, Jequetepeque, multivariate statistical

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Authors: Ju Yeon Lee, Seol Ah Oh, Hong il Kim, Hae Yong Do, Sung Won Choi

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The purpose of this study was to develop a Well-being and Moments Scale (WAMS) for evaluating the efficacy of ‘vacationing’ as a form of mental health recuperation. ‘Vacationing’ is defined as a going outside one’s usual environment to seek refreshment and relief from one’s daily life. To develop WAMS, we followed recommended procedures for scale development, including reviewing related studies, conducting focus group interviews to elucidate the need for this assessment area, and modifying items based on expert opinion. Through this process, we developed the WAMS. The psychometric properties of the WAMS were then tested in two separate samples. Exploratory factor analysis (EFA) was conducted using 1.41 participants (mean age = 30.45 years; range: 20-50 years) to identify the underlying 3-factor structure of 'Positive Emotions', 'Life Satisfaction' and 'Self-Confidence.' The 26 items retained based on the EFA procedures were associated with excellent reliability (i.e., α = 0.93). Confirmatory factor analysis was then conducted using 200 different participants (mean age = 29.51 years; range: 20-50 years) and revealed good model fit for our hypothesized 3-factor model. Convergent validity tests also revealed correlations with other scales in the expected direction and range. Study limitations as well as the importance and utility of WMAS are also discussed.

Keywords: vacationing, positive affect, life satisfaction, self-confidence, WAMS

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Authors: Nahida Sultana

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Globally, an estimated 58 million people have chronic hepatitis C virus infection, with about 1.5 million new infections occurring per year. The hepatitis C virus is a blood-borne virus, and most infections occur through exposure to blood from unsafe injection practices, unsafe health care, unscreened blood transfusion, injection drug use, and sexual practices that lead to exposure to blood. Hepatitis C virus (HCV) causes chronic infections that mainly affect the liver leading to liver diseases. This study aimed to determine whether there is any significant association between HCV transmission risk factors in relation to genotypes in HCV-infected Bangladeshi patients. After quantification of HCV viral load, 36 samples were randomly selected for HCV genotyping and risk factor measurement. A greater proportion of genotype 1 (p > 0.05) patients (40%) underwent blood transfusion compared to patients (22.6%) with genotype 3 infections. More genotype 1 patient underwent surgery and invasive procedures (20%), and rather than those with genotype 3 patients (16.1%). The history of IDUs (25.8%) and sexual exposure (3.2%) are only prevalent in genotype 3 patients and absent in patients with genotype 1 (p >0.05). There was no significant statistical difference found in HCV transmission risk factors (blood transfusion, IDUs, Surgery& interventions, sexual transmission) between patients infected with genotypes 1 and 3. In HCV infection, genotype may have no relation to transmission risk factors among Bangladeshi patients.

Keywords: HCV genotype, alanine aminotransferase (ALT), HCV viral load, IDUs

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Authors: Jaskaran Singh Sidhu

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Aim: The purpose of this study is to find the relationship between wellness among sportsmen and non sportsmen. Methodology: The present study is an experimental study for 80 senior secondary volleyball players of 16-19 years of age from Ludhiana District of Punjab (India), and 80 non-sportsperson were taken from senior secondary school of Ludhiana district. The sample for this study was taken through a random sampling technique. Tools: A five point scale havinf 50 items was used to acess the wellness Statistical Analysis: To find out the relationship among the variables exists or not, a t-test was used to test the significance of the difference between the means. Statistics for each characteristic were calculated; Mean, Standard deviation, Standard error of Mean. Data were analyzed using SPSS (statistical package for the social sciences). Statistical significance was set at p < 0.05. Results: Substantial deviations were noted at p<0.5 in the totality of wellness. Sportsmen show significant differences exist at p<0.5 in three parameters of wellness i.e., physical wellness, mental wellness, and social wellness. In spiritual and emotional wellness attributes, non-sportsmen shows significant difference at p<0.5. Conclusion: From the data interpretation it reflects that overall wellness can be improved by participation in sports. It further noted in study that participation in sports promote the attributes of wellness i.e., physical wellness, mental wellness, emotional wellness and social wellness.

Keywords: physical, mental, social, emotional, wellness, spiritual

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Authors: Qasim Kriri, Harsh B. Desai

Abstract:

Water supply and sanitation in Saudi Arabia is portrayed by difficulties and accomplishments. One of the fundamental difficulties is water shortage. With a specific end goal to beat water shortage, significant ventures have been attempted in sea water desalination, water circulation, sewerage, and wastewater treatment. The motivation behind Statistical Process Control (SPC) is to decide whether the execution of a procedure is keeping up an acceptable quality level [AQL]. SPC is an analytical decision-making method. A fundamental apparatus in the SPC is the Control Charts, which follow the inconstancy in the estimations of the item quality attributes. By utilizing the suitable outline, administration can decide whether changes should be made with a specific end goal to keep the procedure in charge. The two most important quality factors in the distilled water which were taken into consideration were pH (Potential of Hydrogen) and TDS (Total Dissolved Solids). There were three stages at which the quality checks were done. The stages were as follows: (1) Water at the source, (2) water after chemical treatment & (3) water which is sent for packing. The upper specification limit, central limit and lower specification limit are taken as per Saudi water standards. The procedure capacity to accomplish the particulars set for the quality attributes of Berain water Factory chose to be focused by the proposed SPC system.

Keywords: acceptable quality level, statistical quality control, control charts, process charts

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Authors: Xianghe Dai, Dennis Lam, Therese Sheehan, Naveed Rehman, Jie Yang

Abstract:

Concrete is one of the most used construction materials that may be made onsite as fresh concrete and then placed in formwork to produce the desired shapes of structures. It has been recognized that the raw materials and mix proportion of concrete dominate the mechanical characteristics of hardened concrete, and the curing method and environment applied to the concrete in early stages of hardening will significantly influence the concrete properties, such as compressive strength, durability, permeability etc. In construction practice, there are various curing methods to maintain the presence of mixing water throughout the early stages of concrete hardening. They are also beneficial to concrete in hot weather conditions as they provide cooling and prevent the evaporation of water. Such methods include ponding or immersion, spraying or fogging, saturated wet covering etc. Also there are various curing methods that may be implemented to decrease the level of water lost which belongs to the concrete surface, such as putting a layer of impervious paper, plastic sheeting or membrane on the concrete to cover it. In the concrete material laboratory, accelerated strength gain methods supply the concrete with heat and additional moisture by applying live steam, coils that are subject to heating or pads that have been warmed electrically. Currently when determining the mechanical parameters of a concrete, the concrete is usually sampled from fresh concrete on site and then cured and tested in laboratories where standardized curing procedures are adopted. However, in engineering practice, curing procedures in the construction sites after the placing of concrete might be very different from the laboratory criteria, and this includes some standard curing procedures adopted in the laboratory that can’t be applied on site. Sometimes the contractor compromises the curing methods in order to reduce construction costs etc. Obviously the difference between curing procedures adopted in the laboratory and those used on construction sites might over- or under-estimate the real concrete quality. This paper presents the effect of three typical curing methods (air curing, water immersion curing, plastic film curing) and of maintaining concrete in steel moulds on the compressive strength development of normal concrete. In this study, Portland cement with 30% fly ash was used and different curing periods, 7 days, 28 days and 60 days were applied. It was found that the highest compressive strength was observed from concrete samples to which 7-day water immersion curing was applied and from samples maintained in steel moulds up to the testing date. The research results implied that concrete used as infill in steel tubular members might develop a higher strength than predicted by design assumptions based on air curing methods. Wrapping concrete with plastic film as a curing method might delay the concrete strength development in the early stages. Water immersion curing for 7 days might significantly increase the concrete compressive strength.

Keywords: compressive strength, air curing, water immersion curing, plastic film curing, maintaining in steel mould, comparison

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Authors: Maria Arechavaleta, Mark Halpin

Abstract:

In the United States, costs of solar energy systems have declined to the point that they are viable options for most consumers. However, there are no consistent procedures for specifying sufficient systems. The factors that must be considered are energy consumption, potential solar energy production, and cost. The traditional method of specifying solar energy systems is based on assumed daily levels of available solar energy and average amounts of daily energy consumption. The mismatches between energy production and consumption are usually mitigated using battery energy storage systems, and energy use is curtailed when necessary. The main consumer decision question that drives the total system cost is how much unserved (or curtailed) energy is acceptable? Of course additional solar conversion equipment can be installed to provide greater peak energy production and extra energy storage capability can be added to mitigate longer lasting low solar energy production periods. Each option increases total cost and provides a benefit which is difficult to quantify accurately. An approach to quantify the cost-benefit of adding additional resources, either production or storage or both, based on the statistical concepts of loss-of-energy probability and expected unserved energy, is presented in this paper. Relatively simple calculations, based on site-specific energy availability and consumption data, can be used to show the value of each additional increment of production or storage. With this incremental benefit-cost information, consumers can select the best overall performance combination for their application at a cost they are comfortable paying. The approach is based on a statistical analysis of energy consumption and production characteristics over time. The characteristics are in the forms of curves with each point on the curve representing an energy consumption or production value over a period of time; a one-minute period is used for the work in this paper. These curves are measured at the consumer location under the conditions that exist at the site and the duration of the measurements is a minimum of one week. While greater accuracy could be obtained with longer recording periods, the examples in this paper are based on a single week for demonstration purposes. The weekly consumption and production curves are overlaid on each other and the mismatches are used to size the battery energy storage system. Loss-of-energy probability and expected unserved energy indices are calculated in addition to the total system cost. These indices allow the consumer to recognize and quantify the benefit (probably a reduction in energy consumption curtailment) available for a given increase in cost. Consumers can then make informed decisions that are accurate for their location and conditions and which are consistent with their available funds.

Keywords: battery energy storage systems, loss of load probability, residential renewable energy, solar energy systems

Procedia PDF Downloads 206

Authors: Guebli Abdelkader, Regiueg Madani, Sbaa Bouabdellah

Abstract:

The goals of this study are to find ways to determine the value of dynamic priorities in motor learning between some basic skills in beginner’s basketball (U14), based on skills of shooting and defense against the shooter. Our role is to expose the statistical results in compare & correlation between samples of study in tests skills for the shooting and defense against the shooter. In order to achieve this objective, we have chosen 40 boys in middle school represented in four groups, two controls group’s (CS1, CS2) ,and two experimental groups (ES1: training on skill of shooting, skill of defense against the shooter, ES2: experimental group training on skill of defense against the shooter, skill of shooting). For the statistical analysis, we have chosen (F & T) tests for the statistical differences, and test (R) for the correlation analysis. Based on the analyses statistics, we confirm the importance of classifying priorities of basketball basic skills during the motor learning process. Admit that the benefits of experimental group training are to economics in the time needed for acquiring new motor kinetic skills in basketball. In the priority of ES2 as successful dynamic motor learning method to enhance the basic skills among beginner’s basketball.

Keywords: basic skills, basketball, motor learning, children

Procedia PDF Downloads 132