Search results for: advanced statistical analysis

Authors: Bita Payami-Shabestari, Dariush Eslami

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The purpose of this paper is to develop a multi-product economic production quantity model under vendor management inventory policy and restrictions including limited warehouse space, budget, and number of orders, average shortage time and maximum permissible shortage. Since the “costs” cannot be predicted with certainty, it is assumed that data behave under uncertain environment. The problem is first formulated into the framework of a bi-objective of multi-product economic production quantity model. Then, the problem is solved with three multi-objective decision-making (MODM) methods. Then following this, three methods had been compared on information on the optimal value of the two objective functions and the central processing unit (CPU) time with the statistical analysis method and the multi-attribute decision-making (MADM). The results are compared with statistical analysis method and the MADM. The results of the study demonstrate that augmented-constraint in terms of optimal value of the two objective functions and the CPU time perform better than global criteria, and goal programming. Sensitivity analysis is done to illustrate the effect of parameter variations on the optimal solution. The contribution of this research is the use of random costs data in developing a multi-product economic production quantity model under vendor management inventory policy with several constraints.

Keywords: economic production quantity, random cost, supply chain management, vendor-managed inventory

Procedia PDF Downloads 112

Authors: S. Karklina, I. Erins

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The main problem is that there is a very low innovation performance in Latvia. Since Latvia is a Member State of European Union, it also shall have to fulfill the set targets and to improve innovative results. Universities are one of the main performers to provide innovative capacity of country. University, industry and government need to cooperate for getting best results. The intellectual property is one of the indicators to determine innovation level in the country or organization and patents are one of the characteristics of intellectual property. The objective of the article is to determine indicators characterizing innovative environment in Latvia and influence of the development of universities on them. The methods that will be used in the article to achieve the objectives are quantitative and qualitative analysis of the literature, statistical data analysis, and graphical analysis methods.

Keywords: HEI, innovations, Latvia, patents

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Authors: Mette Pedersen

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This paper outlines the criteria that assessment specialists use when they design the 'Persuasive Essay' task for the four Advanced Placement World Language and Culture Exams (AP French, German, Italian, and Spanish). The 'Persuasive Essay' is a free-response, source-based, standardized measure of presentational writing. Each 'Persuasive Essay' item consists of three sources (an article, a chart, and an audio) and a prompt, which is a statement of the topic phrased as an interrogative sentence. Due to its richness of source materials and due to the amount of time that test takers are given to prepare for and write their responses (a total of 55 minutes), the 'Persuasive Essay' is the free-response task on the AP World Language and Culture Exams that goes to the greatest lengths to unleash the test takers' proficiency potential. The author focuses on the work that goes into designing the 'Persuasive Essay' task, outlining best practices for the selection of topics and sources, the interplay that needs to be present among the sources and the thinking behind the articulation of prompts for the 'Persuasive Essay' task. Using released 'Persuasive Essay' items from the AP World Language and Culture Exams and accompanying data on test taker performance, the author shows how different passages, and features of passages, have succeeded (and sometimes not succeeded) in eliciting writing proficiency among test takers over time. Data from approximately 215.000 test takers per year from 2014 to 2017 and approximately 35.000 test takers per year from 2012 to 2013 form the basis of this analysis. The conclusion of the study is that test taker performance improves significantly when the sources that test takers are presented with express directly opposing viewpoints. Test taker performance also improves when the interrogative prompt that the test takers respond to is phrased as a yes/no question. Finally, an analysis of linguistic difficulty and complexity levels of the printed sources reveals that test taker performance does not decrease when the complexity level of the article of the 'Persuasive Essay' increases. This last text complexity analysis is performed with the help of the 'ETS TextEvaluator' tool and the 'Complexity Scale for Information Texts (Scale)', two tools, which, in combination, provide a rubric and a fully-automated technology for evaluating nonfiction and informational texts in English translation.

Keywords: advanced placement world language and culture exams, designing presentational writing assessments, large-scale standardized assessments of written language proficiency, source-based language testing

Procedia PDF Downloads 121

Authors: Sangbok Lee

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There has been much effort on process improvement for outpatient clinics to provide quality and acute care to patients. One of the efforts is no-show analysis or prediction. This work analyzes patient no-shows along with patient health conditions. The health conditions refer to clinical symptoms that each patient has, out of the followings; hyperlipidemia, diabetes, metastatic solid tumor, dementia, chronic obstructive pulmonary disease, hypertension, coronary artery disease, myocardial infraction, congestive heart failure, atrial fibrillation, stroke, drug dependence abuse, schizophrenia, major depression, and pain. A dataset from a regional hospital is used to find the relationship between the number of the symptoms and no-show probabilities. Additional analysis reveals how each symptom or combination of symptoms affects no-shows. In the above analyses, cross-classification of patients by age and gender is carried out. The findings from the analysis will be used to take extra care to patients with particular health conditions. They will be forced to visit clinics by being informed about their health conditions and possible consequences more clearly. Moreover, this work will be used in the preparation of making institutional guidelines for patient reminder systems.

Keywords: healthcare system, no show analysis, process improvment, statistical data analysis

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Authors: Hatice Karakoyun, Mustafa Akdag

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This study has been made to examine the attitudes of pre-school teachers towards values education. The study has been made as a general scanning model. The study’s working group contains 108 pre-school teachers who worked in Diyarbakır, Turkey. In this study Values Education Attitude Scale (VEAS), which developed by Yaşaroğlu (2014), was used. In order to analyze the data for sociodemographic structure, percentage and frequency values were examined. The Kolmogorov-Smirnov method was used in determination of the normal distribution of data. During analyzing the data, KolmogorovSimirnov test and the normal curved histograms were examined to determine which statistical analyzes would be applied on the scale and it was found that the distribution was not normal. Thus, the Mann Whitney U analysis technique which is one of the nonparametric statistical analysis techniques were used to test the difference of the scores obtained from the scale in terms of independent variables. According to the analyses, it seems that pre-school teachers’ attitudes toward values education are positive. According to the scale with the highest average, it points out that pre-school teachers think that values education is very important for students’ and children’s future. The variables included in the scale (gender, seniority, age group, education, school type, school place) seem to have no effect on the pre-school teachers’ attitude grades which joined to the study.

Keywords: attitude scale, pedagogy, pre-school teacher, values education

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Authors: Longkui Zhu, Zhengcao Li

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High temperature gas-cooled reactors (HTGRs) are considered as one of the next-generation advanced nuclear reactors, in which porous nuclear graphite is used as neutron moderators, reflectors, structure materials, and cooled by inert helium. Radioactive tritium and ¹⁴C are generated in terms of reactions of thermal neutrons and ⁶Li, ¹⁴N, ¹⁰B impurely within nuclear graphite and the coolant during HTGRs operation. Currently, hydrogen and nitrogen diffusion behavior together with nuclear graphite microstructure evolution were investigated to minimize the radioactive waste release, using thermogravimetric analysis, X-ray computed tomography, the BET and mercury standard porosimetry methods. It is found that the peak value of graphite weight loss emerged at 573-673 K owing to nitrogen diffusion from graphite pores to outside when the system was subjected to vacuum. Macropore volume became larger while porosity for mesopores was smaller with temperature ranging from ambient temperature to 1073 K, which was primarily induced by coalescence of the subscale pores. It is suggested that the porous nuclear graphite should be first subjected to vacuum at 573-673 K to minimize the nitrogen and the radioactive 14°C before operation in HTGRs. Then, results on hydrogen diffusion show that the diffusible hydrogen and tritium could permeate into the coolant with diffusion coefficients of > 0.5 × 10⁻⁴ cm²·s⁻¹ at 50 bar. As a consequence, the freshly-generated diffusible tritium could release quickly to outside once formed, and an effective approach for minimizing the amount of radioactive tritium is to make the impurity contents extremely low in nuclear graphite and the coolant. Besides, both two- and three-dimensional observations indicate that macro and mesopore volume along with total porosity decreased with temperature at 50 bar on account of synergistic effects of applied compression strain, sharpened pore morphology, and non-uniform temperature distribution.

Keywords: advanced high temperature gas-cooled reactor, hydrogen and nitrogen diffusion, microstructure evolution, nuclear graphite, radioactive waste management

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Authors: Moon Ho Do, Sin-Hee Park, Jae Hyuk Lee, Kyo Hee Cho, Jae Kyung Chae, Sun Yeou Kim

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Long-term hyperglycemic conditions associated with diabetes lead to the formation of advanced glycation end-products (AGEs). Highly reactive glucose metabolites, methylglyoxal (MGO) and glyoxal (GO), induced carbonyl stress and it may induce cellular damage, cross-linking of proteins, and glycation, playing an important role in the impairment of kidney function. Small molecules that have the ability to inhibit AGE formation, and even break preformed AGEs have a beneficial impact on metabolic syndrome, diabetes, and cancer. We quantified contents of polyphenols in nuts and investigated the protective effect of nuts and polyphenols on MGO-induced cytotoxicity in porcine kidney epithelial cells (LLC-PK1). Moreover, we evaluated the inhibitory effect of AGEs formation in the presence of MGO or GO and possess the ability to break preformed AGEs. In this study, we confirmed twenty polyphenols in diverse nuts using LC-MS/MS system. Nuts and polyphenols play a protective role in LLC-PK1 cells by reducing MGO-induced cytotoxicity. They could also prevent the formation of MGO or GO-mediated AGEs and Break AGEs crosslink. It can be surmised that increased consumption of nuts would be an effective means of preventing diabetic diseases.

Keywords: advanced glycation end products, LLC-PK1, methylglyoxal, nut, polyphenol

Procedia PDF Downloads 252

Authors: Boudemagh Naime

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Automatic radar detection requires some methods of adapting to variations in the background clutter in order to control their false alarm rate. The problem becomes more complicated in non-Gaussian environment. In fact, the conventional approach in real time applications requires a complex statistical modeling and much computational operations. To overcome these constraints, we propose another approach based on artificial neural network (ANN-CMLD-CFAR) using a Back Propagation (BP) training algorithm. The considered environment follows a log-normal distribution in the presence of multiple Rayleigh-targets. To evaluate the performances of the considered detector, several situations, such as scale parameter and the number of interferes targets, have been investigated. The simulation results show that the ANN-CMLD-CFAR processor outperforms the conventional statistical one.

Keywords: radat detection, ANN-CMLD-CFAR, log-normal clutter, statistical modelling

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Authors: Fatih Sulak, Betül A. Özdemir, Beyza Bozdemir

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In order to improve symmetric key research, several competitions had been arranged by organizations like National Institute of Standards and Technology (NIST) and International Association for Cryptologic Research (IACR). In recent years, the importance of authenticated encryption has rapidly increased because of the necessity of simultaneously enabling integrity, confidentiality and authenticity. Therefore, at January 2013, IACR announced the Competition for Authenticated Encryption: Security, Applicability, and Robustness (CAESAR Competition) which will select secure and efficient algorithms for authenticated encryption. Cryptographic algorithms are anticipated to behave like random mappings; hence, it is important to apply statistical randomness tests to the outputs of the algorithms. In this work, the statistical randomness tests in the NIST Test Suite and the other recently designed randomness tests are applied to six second round algorithms of the CAESAR Competition. It is observed that AEGIS achieves randomness after 3 rounds, Ascon permutation function achieves randomness after 1 round, Joltik encryption function achieves randomness after 9 rounds, Morus state update function achieves randomness after 3 rounds, Pi-cipher achieves randomness after 1 round, and Tiaoxin achieves randomness after 1 round.

Keywords: authenticated encryption, CAESAR competition, NIST test suite, statistical randomness tests

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Authors: Lina Wu, Wenyi Lu, Ye Li

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Regarding heavy video game players for boys and super online chat lovers for girls as a symbolic phrase in the current adolescent culture, this project of data analysis verifies the displacement effect on deteriorating mathematics performance. To evaluate correlation or regression coefficients between a factor of playing video games or chatting online and mathematics performance compared with other factors, we use multivariate analysis technique and take gender difference into account. We find the most important reason for the negative sign of the displacement effect on mathematics performance due to students’ poor academic background. Statistical analysis methods in this project could be applied to study internet users’ academic performance from the high school education to the college education.

Keywords: correlation coefficients, displacement effect, multivariate analysis technique, regression coefficients

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Authors: Emily Simango, T. Chitura

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Background: Bovine brucellosis is among the most neglected zoonotic diseases in developing countries, where it is endemic and a growing challenge to public health. The development of cost-effective control measures for the disease can only be affirmed by the knowledge of the disease epidemiology and the ability to define its risk profiles. The aim of the study was to document the trend of bovine brucellosis and the control measures adopted following reported cases during the period 2014 to 2019 in South Africa. Methods: Data on confirmed cases of bovine brucellosis was retrieved from the website of the World Organisation of Animal Health (WOAH). Data was analysed using the Statistical Package for Social Sciences (IBM SPSS, 2022) version 29.0. Descriptive analysis (frequencies and percentages) and the Analysis of variance (ANOVA) were utilized for statistical significance (p<0.05). Results: The data retrieved in our study revealed an overall average bovine brucellosis prevalence of 8.48. There were statistically significant differences in bovine brucellosis prevalence across the provinces for the years 2016 and 2019 (p≥0.05), with the Eastern Cape Province having the highest prevalence in both instances. Documented control measures for the disease were limited to killing and disposal of disease cases as well as vaccination of susceptible animals. Conclusion: Bovine brucellosis is real in South Africa, with the risk profiles differing across the provinces. Information on brucellosis control measures in South Africa, as reported to the WOAH, is not comprehensive.

Keywords: zoonotic, endemic, Eastern Cape province, vaccination

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Authors: Pebri Nurhayati, Rozanah Ahlam Fadiyah

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In the development of the city often use rural areas that can not be separated from the change in land use that lead to the degradation of urban green space in the city fringe. In the long run, the degradation of green open space this can impact on the decline of ecological, psychological and public health. Therefore, this research aims to (1) determine the relationship between the parameters of the degradation rate of urban development with green space, (2) develop a spatial model of the impact of urban development on the degradation of green open space with remote sensing techniques and Geographical Information Systems in an integrated manner. This research is a descriptive research with data collection techniques of observation and secondary data . In the data analysis, to interpret the direction of urban development and degradation of green open space is required in 2005-2010 ASTER image with NDVI. Of interpretation will generate two maps, namely maps and map development built land degradation green open space. Secondary data related to the rate of population growth, the level of accessibility, and the main activities of each city map is processed into a population growth rate, the level of accessibility maps, and map the main activities of the town. Each map is used as a parameter to map the degradation of green space and analyzed by non-parametric statistical analysis using Crosstab thus obtained value of C (coefficient contingency). C values were then compared with the Cmaximum to determine the relationship. From this research will be obtained in the form of modeling spatial map of the City Development Impact Degradation Green Space in Urban Fringe eastern city of Yogyakarta 2005-2010. In addition, this research also generate statistical analysis of the test results of each parameter to the degradation of green open space in the Urban Fringe eastern city of Yogyakarta 2005-2010.

Keywords: spatial analysis, urban development, degradation of green space, urban fringe

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Authors: Surajit Bhattacharya, Daniel Veltri, Atit A. Patel, Daniel N. Cox

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miRNAs have emerged as key post-transcriptional regulators of gene expression, however identification of biologically-relevant target genes for this epigenetic regulatory mechanism remains a significant challenge. To address this knowledge gap, we have developed a novel tool in R, Intra-miR-ExploreR, that facilitates integrated discovery of miRNA targets by incorporating target databases and novel target prediction algorithms, using statistical methods including Pearson and Distance Correlation on microarray data, to arrive at high confidence intragenic miRNA target predictions. We have explored the efficacy of this tool using Drosophila melanogaster as a model organism for bioinformatics analyses and functional validation. A number of putative targets were obtained which were also validated using qRT-PCR analysis. Additional features of the tool include downloadable text files containing GO analysis from DAVID and Pubmed links of literature related to gene sets. Moreover, we are constructing interaction maps of intragenic miRNAs, using both micro array and RNA-seq data, focusing on neural tissues to uncover regulatory codes via which these molecules regulate gene expression to direct cellular development.

Keywords: miRNA, miRNA:mRNA target prediction, statistical methods, miRNA:mRNA interaction network

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Authors: Miky Lee, K. Kim, D. Lim, D. Cho

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This paper presents the planning, rationale for test specification derivation, sampling requirements, test facilities, and result analysis used to conduct lifetime expectancy endurance tests on power window switches (PWS) considering thermally induced mechanical stress under diurnal cyclic temperatures during normal operation (power cycling). The detail process of analysis and test results on the selected PWS set were discussed in this paper. A statistical approach to ‘life time expectancy’ was given to the measurement standards dealing with PWS lifetime determination through endurance tests. The approach choice, within the framework of the task, was explained. The present task was dedicated to voltage drop measurement to derive lifetime expectancy while others mostly consider contact or surface resistance. The measurements to perform and the main instruments to measure were fully described accordingly. The failure data from tests were analyzed to conclude lifetime expectancy through statistical method using Weibull cumulative distribution function. The first goal of this task is to develop realistic worst case lifetime endurance test specification because existing large number of switch test standards cannot induce degradation mechanism which makes the switches less reliable. 2nd goal is to assess quantitative reliability status of PWS currently manufactured based on test specification newly developed thru this project. The last and most important goal is to satisfy customer’ requirement regarding product reliability.

Keywords: power window switch, endurance test, Weibull function, reliability, degradation mechanism

Procedia PDF Downloads 219

Authors: Benson Ade Eniola Afere

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This paper introduces a family of fourth-order hybrid beta polynomial kernels developed for statistical analysis. The assessment of these kernels' performance centers on two critical metrics: asymptotic mean integrated squared error (AMISE) and kernel efficiency. Through the utilization of both simulated and real-world datasets, a comprehensive evaluation was conducted, facilitating a thorough comparison with conventional fourth-order polynomial kernels. The evaluation procedure encompassed the computation of AMISE and efficiency values for both the proposed hybrid kernels and the established classical kernels. The consistently observed trend was the superior performance of the hybrid kernels when compared to their classical counterparts. This trend persisted across diverse datasets, underscoring the resilience and efficacy of the hybrid approach. By leveraging these performance metrics and conducting evaluations on both simulated and real-world data, this study furnishes compelling evidence in favour of the superiority of the proposed hybrid beta polynomial kernels. The discernible enhancement in performance, as indicated by lower AMISE values and higher efficiency scores, strongly suggests that the proposed kernels offer heightened suitability for statistical analysis tasks when compared to traditional kernels.

Keywords: AMISE, efficiency, fourth-order Kernels, hybrid Kernels, Kernel density estimation

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Authors: P. Selyshchev

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We consider fluctuations of defects density taking into account their interaction. Stochastic field of displacement generation rate gives random defect distribution. We determinate statistical characteristics (mean and dispersion) of random field of point defect distribution as function of defect generation parameters, temperature and properties of irradiated crystal.

Keywords: irradiation, primary defects, interaction, fluctuations

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Authors: Khaled M. Alhawiti

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This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: speech recognition, acoustic phonetic, artificial intelligence, hidden markov models (HMM), statistical models of speech recognition, human machine performance

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Authors: Rashid Ahmed , John N. Avaritsiotis

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Many signal subspace-based approaches have already been proposed for determining the fixed Direction of Arrival (DOA) of plane waves impinging on an array of sensors. Two procedures for DOA estimation based neural networks are presented. First, Principal Component Analysis (PCA) is employed to extract the maximum eigenvalue and eigenvector from signal subspace to estimate DOA. Second, minor component analysis (MCA) is a statistical method of extracting the eigenvector associated with the smallest eigenvalue of the covariance matrix. In this paper, we will modify a Minor Component Analysis (MCA(R)) learning algorithm to enhance the convergence, where a convergence is essential for MCA algorithm towards practical applications. The learning rate parameter is also presented, which ensures fast convergence of the algorithm, because it has direct effect on the convergence of the weight vector and the error level is affected by this value. MCA is performed to determine the estimated DOA. Preliminary results will be furnished to illustrate the convergences results achieved.

Keywords: Direction of Arrival, neural networks, Principle Component Analysis, Minor Component Analysis

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Authors: Lu Ren, You-Liang Fang, Yan-Gang Zhao

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In recent years, the application of BIM (Building Information Modelling) to construction schedule plan has been the focus of more and more researchers. In order to assess the reasonable level of the BIM-based construction schedule plan, that is whether the schedule can be completed on time, some researchers have introduced reliability theory to evaluate. In the process of evaluation, the uncertain factors affecting the construction schedule plan are regarded as random variables, and probability distributions of the random variables are assumed to be normal distribution, which is determined using two parameters evaluated from the mean and standard deviation of statistical data. However, in practical engineering, most of the uncertain influence factors are not normal random variables. So the evaluation results of the construction schedule plan will be unreasonable under the assumption that probability distributions of random variables submitted to the normal distribution. Therefore, in order to get a more reasonable evaluation result, it is necessary to describe the distribution of random variables more comprehensively. For this purpose, cubic normal distribution is introduced in this paper to describe the distribution of arbitrary random variables, which is determined by the first four moments (mean, standard deviation, skewness and kurtosis). In this paper, building the BIM model firstly according to the design messages of the structure and making the construction schedule plan based on BIM, then the cubic normal distribution is used to describe the distribution of the random variables due to the collecting statistical data of the random factors influencing construction schedule plan. Next the reliability analysis of the construction schedule plan based on BIM can be carried out more reasonably. Finally, the more accurate evaluation results can be given providing reference for the implementation of the actual construction schedule plan. In the last part of this paper, the more efficiency and accuracy of the proposed methodology for the reliability analysis of the construction schedule plan based on BIM are conducted through practical engineering case.

Keywords: BIM, construction schedule plan, cubic normal distribution, reliability analysis

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Authors: Wassim Katerji, Mercedes Farjas, Carmen Morillo

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Terrain-Based Analysis results in derived products from an input DEM and these products are needed to perform various analyses. To efficiently use these products in decision-making, their accuracies must be estimated systematically. This paper proposes a procedure to assess the accuracy of these derived products, by calculating the accuracy of the slope dataset and its significance, taking as an input the accuracy of the DEM. Based on the output of previously published research on modeling the relative accuracy of a DEM, specifically ASTER and SRTM DEMs with Lebanon coverage as the area of study, analysis have showed that ASTER has a low significance in the majority of the area where only 2% of the modeled terrain has 50% or more significance. On the other hand, SRTM showed a better significance, where 37% of the modeled terrain has 50% or more significance. Statistical analysis deduced that the accuracy of the slope dataset, calculated on a cell-by-cell basis, is highly correlated to the accuracy of the input DEM. However, this correlation becomes lower between the slope accuracy and the slope significance, whereas it becomes much higher between the modeled slope and the slope significance.

Keywords: terrain-based analysis, slope, accuracy assessment, Digital Elevation Model (DEM)

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Authors: Samson Henry Dogo, Allan Clark, Elena Kulinskaya

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The objective in meta-analysis is to combine results from several independent studies in order to create generalization and provide evidence based for decision making. But recent studies show that the magnitude of effect size estimates reported in many areas of research finding changed with year publication and this can impair the results and conclusions of meta-analysis. A number of sequential methods have been proposed for monitoring the effect size estimates in meta-analysis. However they are based on statistical theory applicable to fixed effect model (FEM). For random-effects model (REM), the analysis incorporates the heterogeneity variance, tau-squared and its estimation create complications. In this paper proposed the use of Gombay and Serbian (2005) truncated CUSUM-type test with asymptotically valid critical values for sequential monitoring of REM. Simulation results show that the test does not control the Type I error well, and is not recommended. Further work required to derive an appropriate test in this important area of application.

Keywords: meta-analysis, random-effects model, sequential test, temporal changes in effect sizes

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Authors: Adel M. Qatawneh

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This paper aimed to determine the importance of knowledge innovation for external audit on anti-corruption in the entire Jordanian bank companies are listed in Amman Stock Exchange (ASE). The study importance arises from the need to recognize the Knowledge innovation for external audit and anti-corruption as the development in the world of business, the variables that will be affected by external audit innovation are: reliability of financial data, relevantly of financial data, consistency of the financial data, Full disclosure of financial data and protecting the rights of investors to achieve the objectives of the study a questionnaire was designed and distributed to the society of the Jordanian bank are listed in Amman Stock Exchange. The data analysis found out that the banks in Jordan have a positive importance of Knowledge innovation for external audit on anti-corruption. They agree on the benefit of Knowledge innovation for external audit on anti-corruption. The statistical analysis showed that Knowledge innovation for external audit had a positive impact on the anti-corruption and that external audit has a significantly statistical relationship with anti-corruption, reliability of financial data, consistency of the financial data, a full disclosure of financial data and protecting the rights of investors.

Keywords: knowledge innovation, external audit, anti-corruption, Amman Stock Exchange

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Authors: Harshkumar K. Desai, Anuj K. Desai, Jay P. Patel, Snehal V. Trivedi, Yogendrasinh Parmar

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The need of continuous improvement in a product or process in this era of global competition leads to apply value engineering for functional and aesthetic improvement in consideration with economic aspect too. Solar industries located at G.I.D.C., Makarpura, Vadodara, Gujarat, India; a manufacturer of variety of CNC Machines had a challenge to analyze the structural design of column, base, carriage and table of CNC Milling Machine in the account of reduction of overall weight of a machine without affecting the rigidity and accuracy at the time of operation. The identified task is the first attempt to validate and optimize the proposed design of ribbed structure statically using advanced modeling and analysis tools in a systematic way. Results of stress and deformation obtained using analysis software are validated with theoretical analysis and found quite satisfactory. Such optimized results offer a weight reduction of the final assembly which is desired by manufacturers in favor of reduction of material cost, processing cost and handling cost finally.

Keywords: CNC milling machine, optimization, finite element analysis (FEA), weight reduction

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Authors: Prasansha Kumari

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Financial Literacy is the possession of knowledge and understanding of financial matters. Financial Literacy often entails the knowledge of properly making decisions pertaining to certain personal financial areas like real estate, insurance investing, and savings. This paper intends to identify and analyze the financial knowledge among university undergraduates by using 200 undergraduates in four faculties of University of Kelaniya, Sri Lanka. Collected data will be analyzed by descriptive research method using SPSS package. Expected outcomes are considerable percentage of undergraduates have basic knowledge on financial matters while it has a law percentage for advanced financial literacy among undergraduates. Students from faculty of Commerce and Management and Science have good understanding about financial matters than undergraduates in other two faculties

Keywords: advanced finance, undergraduates, financial literacy, savings

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Authors: Mohamed Osama Hassaan

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Recent earthquakes have demonstrated the vulnerability of older reinforced concrete buildings to fail under imposed seismic loads. Accordingly, the need to strengthen existing reinforced concrete structures, mainly columns, to resist high seismic loads has increased. Conventional strengthening techniques such as using steel plates, steel angles and concrete overlay are used to achieve the required increase in strength or ductility. However, techniques using advanced composite materials are established. The column's splice zone is the most critical zone that failed under seismic loads. There are three types of splice zone failure that can be observed under seismic action, namely, Failure of the flexural plastic hinge region, shear failure and failure due to short lap splice. A lapped splice transfers the force from one bar to another through the concrete surrounding both bars. At any point along the splice, force is transferred from one bar by a bond to the surrounding concrete and also by a bond to the other bar of the pair forming the splice. The integrity of the lap splice depends on the development of adequate bond length. The R.C. columns built in seismic regions are expected to undergo a large number of inelastic deformation cycles while maintaining the overall strength and stability of the structure. This can be ensured by proper confinement of the concrete core. The last type of failure is focused in this research. There are insufficient studies that address the problem of strengthening existing reinforced concrete columns at splice zone through confinement with “advanced composite materials". Accordingly, more investigation regarding the seismic behavior of strengthened reinforced concrete columns using the new generation of composite materials such as (Carbon fiber polymer), (Glass fiber polymer), (Armiad fiber polymer).

Keywords: strengthening, columns, advanced composite materials, earthquakes

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Authors: James M. Geidner

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Objective: The purpose of this meta-analysis was to examine the evidence for the effectiveness of exercise interventions on reducing metabolic components in children and/or adolescents diagnosed with Paediatric Metabolic Syndrome. Methods: A computerized search was made from four databases: PubMed, PsycInfo, SPORTDiscus, Cochrane Central Register. The analysis was restricted to children and adolescents with metabolic syndrome examining the effect of exercise interventions on metabolic components. Effect size and 95% confidence interval were calculated and the heterogeneity of the studies was estimated using Cochran’s Q-statistic and I2. Bias was assessed using multiple tools and statistical analyses. Results: Thirteen studies, consisting of 19 separate trials, were selected for the meta-analysis as they fulfilled the inclusion criteria (n=908). Exercise interventions resulted in decreased waist circumference, systolic blood pressure, diastolic blood pressure, fasting glucose, insulin resistance, triglycerides, and High-Density Lipoprotein Cholesterol (HDL-C). Conclusions: This meta-analysis provides insights into the effectiveness of exercise interventions on markers of Paediatric Metabolic Syndrome in children and adolescents.

Keywords: metabolic syndrome, syndrome x, pediatric, meta-analysis

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Authors: Mehmet Erdi Korkmaz, Mustafa Günay

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Nowadays, grinding is frequently replaced with hard turning for reducing set up time and higher accuracy. This paper focused on mathematical modeling of average surface roughness (Ra) in hard turning of AISI L2 grade (DIN 1.2210) cold work tool steel with ceramic tools. The steel was hardened to 60±1 HRC after the heat treatment process. Cutting speed, feed rate, depth of cut and tool nose radius was chosen as the cutting conditions. The uncoated ceramic cutting tools were used in the machining experiments. The machining experiments were performed according to Taguchi L27 orthogonal array on CNC lathe. Ra values were calculated by averaging three roughness values obtained from three different points of machined surface. The influences of cutting conditions on surface roughness were evaluated as statistical and experimental. The analysis of variance (ANOVA) with 95% confidence level was applied for statistical analysis of experimental results. Finally, mathematical models were developed using the artificial neural networks (ANN). ANOVA results show that feed rate is the dominant factor affecting surface roughness, followed by tool nose radius and cutting speed.

Keywords: ANN, hard turning, DIN 1.2210, surface roughness, Taguchi method

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Authors: Douglas W. Scott

Abstract:

The Allemande from J. S. Bach's Partita for solo flute (BWV 1013) presents many unique challenges for any flautist, especially in terms of segmentation analysis required to select breathing places in the first half. Without claiming to identify a 'correct' solution to this problem, this paper analyzes the section in terms of a set of techniques based around a statistical property commonly (if not ubiquitously) found in music, namely Zipf’s law. Specifically, the paper considers violations of this expected profile at various levels of analysis, an approach which has yielded interesting insights in previous studies. The investigation is then grounded by considering four actual solutions to the problem found in recordings made by different flautists, which opens up the possibility of expanding Zipfian analysis to include a consideration of inter-onset-intervals (IOIs). It is found that significant deviations from the expected Zipfian distributions can reveal and highlight stylistic choices made by different performers.

Keywords: inter-onset-interval, Partita for solo flute, BWV 1013, segmentation analysis, Zipf’s law

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Authors: Mimoza Canga, Irene Malagnino, Giulia Malagnino, Alketa Qafmolla, Ruzhdie Qafmolla, Vito Antonio Malagnino

Abstract:

The goal of the present study was to analyze the risk factors regarding dental fear. This observational study was conducted during the period of February 2020 - April 2022 in Albania. The sample was composed of 200 participants, of which 40% were males and 60% were females. The participants' age range varied from 35 to 75 years old. We divided them into four age groups: 35-45, 46-55, 56-65, and 66-75 years old. Statistical analysis was performed using IBM SPSS Statistics 23.0. Data were scrutinized by the Post Hoc LSD test in analysis of variance (ANOVA). The P ≤ 0.05 values were considered significant. Data analysis included Confidence Interval (95% CI). The prevailing age range in the sample was mostly from 55 to 65 years old, 35.6% of the patients. In all, 50% of the patients had extreme fear about the fact that the dentist may be infected with Covid-19, 12.2% of them had low dental fear, and 37.8% had extreme dental fear. However, data collected from the current study indicated that a large proportion of patients 49.5% of them had high dental fear regarding the dentist not respecting the quarantine due to COVID-19, in comparison with 37.2% of them who had low dental fear and 13.3% who had extreme dental fear. The present study confirmed that 22.2% of the participants had an extreme fear of poor hygiene practices of the dentist that have been associated with the transmission of COVID-19 infection, 57.8% had high dental fear, and 20% of them had low dental fear. The present study showed that 50% of the patients stated that another factor that causes extreme fear was that the patients feel pain after interventions in the oral cavity. Strong associations were observed between dental fear and pain 95% CI; 0.24-0.52, P-value ˂ .0001. The results of the present study confirmed strong associations between dental fear and the fact that the dentist may be infected with Covid-19 (95% CI; 0.46-0.70, P-value ˂ .0001). Similarly, the analysis of the present study demonstrated that there was a statistically significant correlation between dental fear and poor hygiene practices of the dentist with 95% CI; 0.82-1.02, P-value ˂ .0001. On the basis of our statistical data analysis, the dentist did not respect the quarantine due to COVID-19 having a significant impact on dental fear with a P-value of ˂ .0001. This study shows important risk factors that significantly increase dental fear.

Keywords: Covid-19, dental fear, pain, past dreadful experiences

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Authors: Fina O. Faithpraise, Effiong O. Obisung, Azele E. Peter, Chris R. Chatwin

Abstract:

This study investigates and identifies consumer attitude as a major influence that results in non-technical losses in the Nigerian electricity supply sector. This discovery is revealed by the combination of quantitative and qualitative research to complete a survey. The dataset employed is a simple random sampling of households using electricity (public power supply), and the number of units chosen is based on statistical power analysis. The units were subdivided into two categories (household with and without electrical meters). The hypothesis formulated was tested and analyzed using a chi-square statistical method. The results obtained shows that the critical value for the household with electrical prepared meter (EPM) was (9.488 < 427.4) and those without electrical prepared meter (EPMn) was (9.488 < 436.1) with a p-value of 0.01%. The analysis demonstrated so far established the real-time position, which shows that the wrong attitude towards handling the electricity supplied (not turning off light bulbs and electrical appliances when not in use within the rooms and outdoors within 12 hours of the day) characterized the non-technical losses in the power sector. Therefore the adoption of efficient lighting attitudes in individual households as recommended by the researcher is greatly encouraged. The results from this study should serve as a model for energy efficiency and use for the improvement of electricity consumption as well as a stable economy.

Keywords: attitudinal change, household, non-technical losses, prepared meter

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