Search results for: categorical statistics

Authors: Subhashini Chaturvedi

Abstract:

The New World Order of the 21st century which is largely lead by Global Technological Leadership, and a workforce of United Nations coming together in the wake of our planet's future. The objective of this study is to understand the approach taken to implement sustainable use of resources and adequate architectural interventions. The framework of global policies in terms of sustainability has to be checked whether they commensurate and do justice to various nations with highly variable resource availability and development index. The method used to analyse the subject is a study of linkage between Age, Development, and exertion of the land, which attribute to the history of nations worldwide. The study also questions whether the use of term Sustainability is even ethical to be suggested in under developed or developing nations. Evolving through examples of American Imperialism to steady decline of Indian state of Punjab over last few decades, shows how sustainability has acted like scoop taken from a whole container in case of developed societies whereas it has acted like scratching the bottom of an empty container in case of embryonic societies where needs for sustenance are still far fed. The result comes out in favour of more innovative and rational implementation of architecture, sustainability and urban planning in context to indigenous space of a society and its statistics. The bridge to reduce the gap of fiscal deficit in resource premises can be consolidated by balancing on a global level majorly and this research paper is in the pursuance of the same idea.

Keywords: developing nations, economy, holistic development, innovation, logical approach, statistics, USA

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Authors: Gabriel Odeh Ankeli

Abstract:

The study determined how mentoring enhanced strategy can increase self-efficacy of secondary school students in physics in education zone C of Benue State, Nigeria. The study was guided by two research questions while two hypotheses were formulated and tested at 0.05 level of significance. The design of the study was the quasi-experimental, non-randomized, pre-test and post-test control groups. The population of the study consisted of 4,064 SS two physics students in the 94 schools in Education Zone C. The sample comprised 406 SS two physics students drawn from 10 schools using multi-stage sampling technique. The research instrument adapted and used for data collection was Students Self-Efficacy Scale (SSES). The research instrument was subjected to a reliability analysis using Cronbachs Alpha which yielded a reliability co-efficient of 0.84. Data collected were analyzed using discriptive statistics of mean and standard deviation to answer the research questions while inferential statistics of Analysis of Covariance (ANCOVA) was used to test the hypotheses. The findings revealed that students who were exposed to mentoring exhibited lower self-efficacy levels (F 1,405 = 2.751, P = 0.09˃0.05) than those students who were not exposed to mentoring. There was significant difference between male and female students’ self-efficacy level (F 1,211 = 5.496, P = 0.02˂0.05). Based on these findings, it was recommended among others that longer duration of mentoring period should be encouraged when using the mentoring strategy for better enhancement of Self-efficacy of students.

Keywords: physics, self-efficacy, mentoring enhanced strategy, students

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Authors: Naomi Weiner-Levy

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The Mofet Institute of Research, established a School of Professional Development, the only one of its kind in Israel and throughout the world. It offers specialized programs for teacher educators, providing them with the professional knowledge and skills. The studies aim at updating teachers about rapidly changing knowledge and skills. Teacher educators are conceptualized as shifting from first order practitioners (school teachers) to second order practitioners. Those who train teachers are referred to as third order practitioners. The instructors in the School of Professional Development are third-order practitioners – teacher educators specializing in teaching their colleagues. Collegial guidance by teachers’ college staff members is no simple task: Tutors must be expert in their field of specialization, as well as in instruction. Moreover, although colleagues, they have to position themselves within the group as authoritative figures in terms of instruction and knowledge. To date, the role and professional identity of these third-order practitioners, has not been studied. To understand the nature and development of professional identity, a qualitative study was conducted in which 12 tutors of various subjects were interviewed. These were analyzed by categorical content analysis. The findings, assessed professional identity through a post-modern prism, while examining the interplay among events that tutors experienced, the knowledge they acquired and the structuring of their professional identity. The Tutors’ identity transformed through negotiating with ‘self’ and ‘other’ in the class, and constructed by their mutual experiences as tutors and learners. Understanding the function and identity of tutors facilitates comprehension of this unique training process for teacher educators.

Keywords: professional development, professional identity, teacher education, tutoring

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Authors: Wei-Hwa Chiang, Wei-Ting Hsu, Yuan-Chi Liu, Cheng-Che Tsai

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A sustainable built environment aims for minimizing both regional and global environmental impact while maintaining a healthy living for individuals. Sustainability of performing venues has rarely been discussed when compared with residential, office, and other popular building types. Life-cycle carbon emission due to the high standard requirements in acoustics, stage engineering, HVAC, and building structure need to be carefully examined. This can be complicated by social-economic and cultural concerns in addition to technical excellence. This paper reported case-based study and statistics of performing venues regarding urban connectivity and spatial layouts in enhancing facility usage and promoting cultural vitality. Interviews conducted for a major venue at Taipei indicated high linkage with surrounding leisure activity and the need for quality pedestrian and additional spaces open to the general public. Statistics of venues with various size and function suggested the possibility and strategies limit the size and height of reception and foyer spaces, and to maximize their use when there are no performances. Design strategies are identified to increase visual contact or facility sharing between the artists and the audience or the general public in reducing facility size and promoting potential involvement in cultural activities.

Keywords: sustainability, performing venue, design, operation

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Authors: Mehran Naghizaderokni, Asscar Janalizadechobbasty

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This paper explores probabilistic method for assessing the liquefaction potential of sandy soils. The current simplified methods for assessing soil liquefaction potential use a deterministic safety factor in order to determine whether liquefaction will occur or not. However, these methods are unable to determine the liquefaction probability related to a safety factor. A solution to this problem can be found by reliability analysis.This paper presents a reliability analysis method based on the popular certain liquefaction analysis method. The proposed probabilistic method is formulated based on the results of reliability analyses of 190 field records and observations of soil performance against liquefaction. The results of the present study show that confidence coefficient greater and smaller than 1 does not mean safety and/or liquefaction in cadence for liquefaction, and for assuring liquefaction probability, reliability based method analysis should be used. This reliability method uses the empirical acceleration attenuation law in the Chalos area to derive the probability density distribution function and the statistics for the earthquake-induced cyclic shear stress ratio (CSR). The CSR and CRR statistics are used in continuity with the first order and second moment method to calculate the relation between the liquefaction probability, the safety factor and the reliability index. Based on the proposed method, the liquefaction probability related to a safety factor can be easily calculated. The influence of some of the soil parameters on the liquefaction probability can be quantitatively evaluated.

Keywords: liquefaction, reliability analysis, chalos area, civil and structural engineering

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Authors: Mayuko Matsuoka

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This presentation reports the relationships among EFL(English as a Foreign Language) students’ story comprehension in reading a story written in English and Japanese and empathic reactions. The main focus is put on their self-reflection on past study experiences, one of the empathic reactions after reading a story. One hundred fifty-five first-year university students in Japan read three SRL-themed stories written in English (their foreign language) and those written in Japanese (their mother tongue). The levels of the stories are equivalent, at CEFR(Common European Framework of Reference for Languages) B2 level. The result of categorical correlation analysis shows significant moderate correlations among three empathic reactions in a group reading English versions: having similar emotions as a protagonist, reflecting on their past study experiences, and getting lessons from a story. In addition, the result of logistic regression analysis for the data in a group reading English versions shows the chance of getting lessons from a story significantly approximately doubles if participants’ scores of a comprehension test increases by one, while it approximately triples if participants’ self-reflection occurs. These results do not appear in a group reading Japanese versions. The findings imply that self-reflection may support their comprehension of the English texts and leads to the participants’ getting lessons about SRL.

Keywords: comprehension, lesson, self-reflection, SRL

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Authors: Isaac Yeboah

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Physical activity (PA) is considered the best preventative tool for maintaining physical health and extending lifespan because it offers a range of benefits. However, for people to benefit from physical activity, it must be done at a level that can enhance fitness, health, and overall well-being. Therefore, this study aimed to determine the link between physical activity participation levels and cardiorespiratory fitness (CRF). The study employed the descriptive correlational design. The census sampling technique included all 190 teaching staff from the two senior high schools in the Dormaa East District. An adapted International Physical Activity Questionnaire (IPAQ) and standardized physical fitness tests were used for data collection. Descriptive statistics of frequency counts and percentages were used to answer the research questions, while inferential statistics of Pearson Product Moment Correlation and the independent sample t-test were used to test hypotheses one and two, respectively. A moderately negative (r = -.156) relationship existed between physical activity participation levels and CRF. Female teachers demonstrated a statistically significant value (p = .045) than males. The study concluded that the reported physical activity levels of the teachers did not reflect their CRF. The implication is that either the participants overestimated their physical activity participation levels or the intensity of the activities was not high enough to affect physiological changes. For the teachers' CRF to improve, it was suggested, among other things, that regular physical activity sessions of the appropriate mixes of FITT be organized.

Keywords: physical activity, participation levels, cardiorespiratory fitness, sedentary lifestyle, teachers

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Authors: Stephen Vera, Tabitha Black, Charalambos Cleanthous, Ryan Sain

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A gender comparison of USA commercial pilots’ demographics and views of CRM, social desirability and locus of control were surveyed. The Aviation safety locus of control (ASLOC) was used to measure external (ASLOC-E) or internal (ASLOC-I) aviation safety locus of control. The gender differences were explored using the ASLOC scores as a categorical variable. A differential comparison of crew resource management (CRM), based on the Federal Aviation Administration’s (FAA) guidelines was conducted. The results indicated that the proportion of female to male respondents matches the current ratio of USA commercial pilots. Moreover, there were no significant differences regarding overall education and the total number of communication classes one took. Regarding CRM issues, there were no significant differences on their views regarding the roles of the PIC, stress, time management, and managing a flight team. The females scored significantly lower on aeronautical decision making (ADM) and communications. There were no significant differences on either the Balanced Inventory of Desirable Responding (BIDR) impression management (IM) or self-deceptive enhancement (SDE). Although there were no overall significant differences on the ASLOC, the females did score higher on the internal subscale than did the males. An additional comparison of socially desirable responding indicates that all scores may be invalid, especially from the female respondents.

Keywords: social desirability, safety locus of control, crew resource management, commercial pilots

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Authors: Bouthiba Amina

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The estimation of the statistics bound to the precipitation represents a vast domain, which puts numerous challenges to meteorologists and hydrologists. Sometimes, it is necessary, to approach in value the extreme events for sites where there is little, or no datum, as well as their periods of return. The search for a model of the frequency of the heights of daily rains dresses a big importance in operational hydrology: It establishes a basis for predicting the frequency and intensity of floods by estimating the amount of precipitation in past years. The most known and the most common approach is the statistical approach, It consists in looking for a law of probability that fits best the values observed by the random variable " daily maximal rain " after a comparison of various laws of probability and methods of estimation by means of tests of adequacy. Therefore, a frequent analysis of the annual series of daily maximal rains was realized on the data of 54 pluviometric stations of the pond of high and average. This choice was concerned with five laws usually applied to the study and the analysis of frequent maximal daily rains. The chosen period is from 1970 to 2013. It was of use to the forecast of quantiles. The used laws are the law generalized by extremes to three components, those of the extreme values to two components (Gumbel and log-normal) in two parameters, the law Pearson typifies III and Log-Pearson III in three parameters. In Algeria, Gumbel's law has been used for a long time to estimate the quantiles of maximum flows. However, and we will check and choose the most reliable law.

Keywords: return period, extreme flow, statistics laws, Gumbel, estimation

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Authors: Bingchun Liu, Pei-Chann Chang, Natasha Huang, Dun Li

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Machine Learning and Data Mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a wildly used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, Air Quality Classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a hybrid classification model based on information theory and Support Vector Machine (SVM) using the air quality data of four cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from Jan 1, 2014 to April 30, 2016. China's Ministry of Environmental Protection has classified the daily air quality into 6 levels namely Serious Pollution, Severe Pollution, Moderate Pollution, Light Pollution, Good and Excellent based on their respective Air Quality Index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM Machine Learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), Artificial Neural Network (ANN) and K-Nearest Neighbours (KNN) models in terms of accuracy as well as complexity.

Keywords: machine learning, air quality classification, air quality index, information gain, support vector machine, cross-validation

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Authors: Elmahdi Khalil, Saad Enniari, Mostapha Zbakh

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Cloud computing promises to increase innovation and the velocity with witch applications are deployed, all while helping any enterprise meet most IT service needs at a lower total cost of ownership and higher return investment. As the march of cloud continues, it brings both new opportunities and new security challenges. To take advantages of those opportunities while minimizing risks, we think that Intrusion Detection Systems (IDS) integrated in the cloud is one of the best existing solutions nowadays in the field. The concept of intrusion detection was known since past and was first proposed by a well-known researcher named Anderson in 1980's. Since that time IDS's are evolving. Although, several efforts has been made in the area of Intrusion Detection systems for cloud computing environment, many attacks still prevail. Therefore, the work presented in this paper proposes a multi criteria analysis and a comparative study between several IDS architectures designated to work in a cloud computing environments. To achieve this objective, in the first place we will search in the state of the art of several consistent IDS architectures designed to work in a cloud environment. Whereas, in a second step we will establish the criteria that will be useful for the evaluation of architectures. Later, using the approach of multi criteria decision analysis Mac Beth (Measuring Attractiveness by a Categorical Based Evaluation Technique we will evaluate the criteria and assign to each one the appropriate weight according to their importance in the field of IDS architectures in cloud computing. The last step is to evaluate architectures against the criteria and collecting results of the model constructed in the previous steps.

Keywords: cloud computing, cloud security, intrusion detection/prevention system, multi-criteria decision analysis

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Authors: Ibrahim Suliman Hanaish

Abstract:

Disaggregation daily rainfall using stochastic models formulated based on multivariate approach (MuDRain) is discussed in this paper. Seven rain gauge stations are considered in this study for different distances from the referred station starting from 4 km to 160 km in Peninsular Malaysia. The hourly rainfall data used are covered the period from 1973 to 2008 and July and November months are considered as an example of dry and wet periods. The cross-correlation among the rain gauges is considered for the available hourly rainfall information at the neighboring stations or not. This paper discussed the applicability of the MuDRain model for disaggregation daily rainfall to hourly rainfall for both sources of cross-correlation. The goodness of fit of the model was based on the reproduction of fitting statistics like the means, variances, coefficients of skewness, lag zero cross-correlation of coefficients and the lag one auto correlation of coefficients. It is found the correlation coefficients based on extracted correlations that was based on daily are slightly higher than correlations based on available hourly rainfall especially for neighboring stations not more than 28 km. The results showed also the MuDRain model did not reproduce statistics very well. In addition, a bad reproduction of the actual hyetographs comparing to the synthetic hourly rainfall data. Mean while, it is showed a good fit between the distribution function of the historical and synthetic hourly rainfall. These discrepancies are unavoidable because of the lowest cross correlation of hourly rainfall. The overall performance indicated that the MuDRain model would not be appropriate choice for disaggregation daily rainfall.

Keywords: rainfall disaggregation, multivariate disaggregation rainfall model, correlation, stochastic model

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Authors: Isaac Yeboah, Emmanuel Osei Sarpong

Abstract:

Physical activity (PA) is considered the best preventative tool for maintaining physical health and extending lifespan because it offers a range of benefits. However, for people to benefit from physical activity, it must be done at a level that can enhance fitness, health, and overall well-being. Therefore, this study aimed to determine the link between physical activity participation levels and cardiorespiratory fitness (CRF). The study employed the descriptive correlational design. The census sampling technique included all 190-teaching staff from the two senior high schools in the Dormaa East District. An adapted International Physical Activity Questionnaire (IPAQ) and standardized physical fitness tests were used for data collection. Descriptive statistics of frequency counts and percentages were used to answer the research questions while inferential statistics of Pearson Product Moment Correlation and the independent sample t-test were used to test hypotheses one and two respectively. A moderately negative (r = -.156) relationship existed between physical activity participation levels and CRF. Female teachers demonstrated a statistically significant value (p = .045) than males. The study concluded that the reported physical activity levels of the teachers did not reflect their CRF. The implication is that either the participants overestimated their physical activity participation levels, or the intensity of the activities was not high enough to affect physiological changes. For the teachers' CRF to improve, it was suggested, among other things, that regular physical activity sessions of the appropriate mixes of FITT be organized.

Keywords: physical activity, participation levels, cardiorespiratory fitness, sedentary lifestyle, teachers

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Authors: William Mahony, L. Jacqueline Hirth, Richard Rupp, Sandra Gonzalez, Roger Zoorob

Abstract:

Background: The impact of the COVID-19 pandemic on physicians has been considered by many researchers, but less is known about non-physician healthcare workers. The aim of this study is to examine the association of COVID-19 safety training and communication with stress. Methods: A 91-item online survey was distributed, starting January 2, 2021, to non-physician healthcare workers, including physician assistants, nurse practitioners, and medical assistants (MAs) in the United States through email and social media. A $1 donation was made to the Red Cross for each completed survey. The survey consisted of demographics, occupational questions, and perceived stress (perceived stress scale, PSS). Items on the PSS were combined for an overall score and categorized according to the severity of perceived stress. Chi-square tests were performed for bivariate analyses of categorical variables. Results: Of the 284 participants consenting to complete the survey, 197 participants completed the full survey. MAs made up most of the sample at 79%. Among all respondents, 47% had moderate PSS scores (scored between 14 and 26), and 51% had severe PSS scores (scored between 27 and 40). Unvaccinated participants reported statistically significantly lower levels of perceived stress (p = 0.002). Performing tasks outside of typical job responsibilities was not associated with PSS scores (p = .667). Discussion: Non-physician healthcare workers demonstrated a high level of perceived stress overall. The association between vaccination status and perceived stress should be examined in order to evaluate whether vaccination levels could be improved with further education about the virus and associated risks.

Keywords: COVID-19, SARS-Cov-2, nursing, public health

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Authors: Anisul Islam

Abstract:

The U.S. has a very strong trade relationship with China but with a large and persistent trade deficit. Some has argued that the undervalued Chinese Yuan is to be blamed for the persistent trade deficit. The empirical results are mixed at best. This paper empirically estimates the U.S. export function along with the U.S. import function with its trade with China with the purpose of testing for the existence of the Marshall-Lerner (ML) condition as well for the possible existence of the J-curve hypothesis. Annual export and import data will be utilized for as long as the time series data exists. The export and import functions will be estimated using advanced econometric techniques, along with appropriate diagnostic tests performed to examine the validity and reliability of the estimated results. The annual time-series data covers from 1975 to 2022 with a sample size of 48 years, the longest period ever utilized before in any previous study. The data is collected from several sources, such as the World Bank’s World Development Indicators, IMF Financial Statistics, IMF Direction of Trade Statistics, and several other sources. The paper is expected to shed important light on the ongoing debate regarding the persistent U.S. trade deficit with China and the policies that may be useful to reduce such deficits over time. As such, the paper will be of great interest for the academics, researchers, think tanks, global organizations, and policy makers in both China and the U.S.

Keywords: exports, imports, marshall-lerner condition, j-curve hypothesis, united states, china

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Authors: Olusola Akintunde Adediran

Abstract:

This study examined differential effect of Gender difference in social interaction skill of pupils with autism using token economy and video modeling as intervention strategies. A pretest, posttest, control group, quasi-experimental research design was adopted in the study. 17 participants (11 males and 6 females) were selected purposively from 5 centres in Ibadan and randomized into three groups (token economy, video modeling and control groups). Two instruments were used in the study; Autism Spectrum Rating Scale (ASRS) for 299.00 Autistic Disorder (r = 0.82) and Children’s Self-report Social Skill Scale (CS4) (r= 0.93). A descriptive statistics was used to analyse the participants social interaction data based on intervention and gender, while inferential statistics of analysis of covariance (ANCOVA) and scheffe post-hoc measure was used to anlayse three null hypotheses tested at 0.05 level of significance. The results obtained indicated that there was a significant main effect of treatment on social interaction of participants, but there was no significant of main effect of gender on the social interaction of participants, hence, (F(2,14) = .741; p > .05, eta = .050). Lastly, there was no significant interaction effect of treatment and gender of the participants, hence (F(2,10) = 2.177; p > .05, eta 2 = 202). The study has contributed to the frontiers of knowledge by establishing that social interaction of autism is attainable when token economy and video modelling are used as treatment intervention, hence, they should be adopted by the teachers, curriculum planners and other stakeholders.

Keywords: social interaction, token economy, video modelling, autism, gender

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Authors: Leila Angélica de O. Castro, Thiago R. Pereira

Abstract:

The number of refugees currently is alarming, having overcome the numbers of World War II. The objective of this research will be to examine this refugee crisis the light of the main contemporary ethical theories, mainly by analyzing whether there is an ethical obligation to assist these refugees. Among the many existing theories like virtue ethics, Kantian ethics, utilitarian ethics, ethical egoism and psychological egoism, will be the ethical theories used to analyze the current refugee crisis. The ethics of virtue is the oldest of theories, an action can be considered correct if we are acting virtuously if we predisposition to act that virtuously, where the goal is always the eudaimonia, a good life, a happy life. The Kantian ethics of the works of the philosopher Immanuel Kant, where we apply the hypothetical and categorical imperatives to find universal truths, actions that we consider to be universally correct. Utilitarian ethics believes that action will be considered as correct to bring happiness to the greatest possible number of people, even if they somehow have to bring unhappiness to any number of people. Ethical egoism should be concerned first with our individual happiness, and then we can worry about the happiness of others, so long as it causes us some happiness. Thus, action is correct since it is causing us a greater degree of happiness than unhappiness. Finally, the psychological egoism does not seek to determine whether an action is right or not, but claims that all our actions, even if they seem altruistic, actually has another motivation, which will always be a selfish motivation, that is, concerned with the our well-being. From these initial concepts, the issue of refugees, especially the question of whether states and their citizens have or not any ethical obligation to help them and receive them in their territories will be analyzed .

Keywords: refugees, ethics, obligation to help, contemporary theories

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Authors: B. O. Diyaolu

Abstract:

Viability and competency during competition is the dream of every team sports so as to have a good result. But it seems factors abound which deter the performance of even a good sports team. Different individuals with different state of mind all come together to perform in team sports with different degree of satisfaction. This study investigated the role of satisfaction on performance among Afe Babalola University team sports. Descriptive survey research design was used and the population consists of all male and female athletes in the team sports that participated in the last 2019 Ekiti State Higher Institution games (ESHIGA). Total enumeration technique was used for the three team sports; football (44), basketball (24) and volleyball (24). A total of 92 participants were involved in the research. The instrument used for the study was a modified Athlete Satisfaction Scale (ASS). The questionnaire was divided into two sections. The Cronbach’s Alpha reliability coefficient of 0.71 was obtained. The hypotheses were tested at 0.05 significant levels. The completed questionnaire was collated, coded, and analyzed using descriptive statistics of frequency counts and percentage and inferential statistics of chi-square (X²). Findings of this study revealed that satisfaction significantly influences team sports performance among Athletes of Afe Babalola University. The responsibility of satisfying athlete lies on the coaches, fans, sports administrators as well as organizers of such event, as it is not only financial reward that gives satisfaction. The performance of a team sports is quiet important and its being determined by the degree of satisfaction of each individual that make up the team. All effort must be made to satisfy athlete in order to guarantee optimum performance.

Keywords: athlete satisfaction, optimum achievement, optimum performance, sports performance and team sports

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Authors: Mary Ann Cristine R. Olgado

Abstract:

Diversity in the classroom might make it difficult to promote individualized learning, but differentiated instruction that caters to students' various learning preferences may prove to be beneficial. Hence, this study examined the effectiveness of Hybrid-Differentiated Mathematics Instruction (HDMI) in improving the students’ academic performance in Mathematics. It employed the quasi-experimental research design by using a comparative analysis of the two variables: the experimental and control groups. The learning styles of the students were identified using the Grasha-Riechmann Student Learning Style Scale (GRSLSS), which served as the basis for designing differentiated action plans in Mathematics. In addition, adapted survey questionnaires, pre-tests, and post-tests were used to gather information and were analyzed using descriptive and correlational statistics to find the relationship between variables. The experimental group received differentiated instruction for a month, while the control group received traditional teaching instruction. The study found that Hybrid-Differentiated Mathematics Instruction (HDMI) improved the academic performance of Grade 11-TVL students, with the experimental group performing better than the control group. This program has effectively tailored the teaching methods to meet the diverse learning needs of the students, fostering and enhancing a deeper understanding of mathematical concepts in Statistics & Probability, both within and beyond the classroom.

Keywords: differentiated instruction, hybrid, learning styles, academic performance

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Authors: Yin-Yee Leong, Jack C. Yue, Hsin-Chung Wang

Abstract:

Human longevity has been experiencing its largest increase since the end of World War II, and modeling the mortality rates is therefore often the focus of many studies. Among all mortality models, the Lee–Carter model is the most popular approach since it is fairly easy to use and has good accuracy in predicting mortality rates (e.g., for Japan and the USA). However, empirical studies from several countries have shown that the age parameters of the Lee–Carter model are not constant in time. Many modifications of the Lee–Carter model have been proposed to deal with this problem, including adding an extra cohort effect and adding another period effect. In this study, we propose a spatial modification and use clusters to explain why the age parameters of the Lee–Carter model are not constant. In spatial analysis, clusters are areas with unusually high or low mortality rates than their neighbors, where the “location” of mortality rates is measured by age and time, that is, a 2-dimensional coordinate. We use a popular cluster detection method—Spatial scan statistics, a local statistical test based on the likelihood ratio test to evaluate where there are locations with mortality rates that cannot be described well by the Lee–Carter model. We first use computer simulation to demonstrate that the cluster effect is a possible source causing the problem of the age parameters not being constant. Next, we show that adding the cluster effect can solve the non-constant problem. We also apply the proposed approach to mortality data from Japan, France, the USA, and Taiwan. The empirical results show that our approach has better-fitting results and smaller mean absolute percentage errors than the Lee–Carter model.

Keywords: mortality improvement, Lee–Carter model, spatial statistics, cluster detection

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Authors: Zeyad Suleiman Bataineh

Abstract:

Introduction: civilian wars are associated with severe humanitarian effects that include loss of individuals and properties. Psychological dimensions are also included depression. Objectives: the main objectives of the present study were to investigate the depression level among Syrian patients who visited internal medicine clinics and other related variables. Methods and subjects: this study was conducted based on cross sectional study design. A total of 175 patients were involved. Patients were asked to fill a questionnaire to assess the level of depression that include demographic variables such as gender, age, educational level, and social status. Beck Aaron scale for depression was used. Participation in this study was voluntary, and all patients were informed about their rights to withdraw from the study without being negatively affected. Data were entered into excel spreading sheet for all participants. SPSS version 21 was used to analyze data. Data were described as means, the standard deviation for linear variables, frequencies, and percentages for categorical variables. The relationships between variables were evaluated using independent t test and One Way ANOVA test. Significance was considered at α≤0.05. Results: Depression was found in 152 (87%) of participants. The majority of participants with depression had moderate to severe depression. Depression was significantly associated gender, age, educational level, and social status (p<0.05). Conclusion: psychological rehabilitation is required for patients who experienced civilian wars.

Keywords: mental health, deprssion, health system, psychological dimension

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Authors: Varsha V. Rohini, P. R. Shreya, B. Renukadevi

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In the web analytics the information delivery and the web usage is optimized and the analysis of data is done. The analytics is the measurement, collection and analysis of webpage data. Page statistics and user metrics are the important factor in most of the web analytics tool. This is the limitation of the existing tools. It does not provide design inputs for the optimization of information. This paper aims at providing an extension for the scope of web analytics to provide analysis and statistics of each segment of a webpage. The number of click count is calculated and the concentration of links in a web page is obtained. Its user metrics are used to help in proper design of the displayed content in a webpage by Vision Based Page Segmentation (VIPS) algorithm. When the algorithm is applied on the web page it divides the entire web page into the visual block tree. The visual block tree generated will further divide the web page into visual blocks or segments which help us to understand the usage of each segment in a page and its content. The dynamic web pages and deep web pages are used to extend the scope of web page segment analytics. Space optimization concept is used with the help of the output obtained from the Vision Based Page Segmentation (VIPS) algorithm. This technique provides us the visibility of the user interaction with the WebPages and helps us to place the important links in the appropriate segments of the webpage and effectively manage space in a page and the concentration of links.

Keywords: analytics, design optimization, visual block trees, vision based technology

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Authors: Arthur C. Tsai, Chii-Shyang Kuo, Vincent S. C. Chien, Michelle Liou, Philip E. Cheng

Abstract:

Meditation enhances mental abilities and it is an antidote to anxiety. However, very little is known about brain mechanisms and cortico-subcortical interactions underlying meditation-induced anxiety relief. In this study, the changes of phase-amplitude coupling (PAC) in which the amplitude of the beta frequency band were modulated in phase with delta rhythm were investigated after eight-week of meditation training. The study hypothesized that through a concentrate but relaxed mental training the delta-beta coupling in the frontal regions is attenuated. The delta-beta coupling analysis was applied to within and between maximally-independent component sources returned from the extended infomax independent components analysis (ICA) algorithm on the continuous EEG data during mediation. A unique meditative concentration task through relaxing body and mind was used with a constant level of moderate mental effort, so as to approach an ‘emptiness’ meditative state. A pre-test/post-test control group design was used in this study. To evaluate cross-frequency phase-amplitude coupling of component sources, the modulation index (MI) with statistics to calculate circular phase statistics were estimated. Our findings reveal that a significant delta-beta decoupling was observed in a set of frontal regions bilaterally. In addition, beta frequency band of prefrontal component were amplitude modulated in phase with the delta rhythm of medial frontal component.

Keywords: phase-amplitude coupling, ICA, meditation, EEG

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Authors: Farhad Nouparast

Abstract:

For more production we need more capital formation. Capital formation in each country should be based on comparative advantages in different economic sectors due to the different production possibility curves. In regional planning, recognizing the relative advantages and consequently investing in more production requires identifying areas with the necessary capabilities and location of each region compared to other regions. In this article, ranking of Iran's provinces is done according to the specific and given variables as the best investment position in agricultural activity. So we can provide the necessary background for investment analysis in different regions of the country to formulate national and regional planning and execute investment projects. It is used factor analysis technique and numerical taxonomy analysis to do this in thisarticle. At first, the provinces are homogenized and graded according to the variables using cross-sectional data obtained from the agricultural census and population and housing census of Iran as data matrix. The results show that which provinces have the most potential for capital formation in agronomy sub-sector. Taxonomy classifies organisms based on similar genetic traits in biology and botany. Numerical taxonomy using quantitative methods controls large amounts of information and get the number of samples and categories and take them based on inherent characteristics and differences indirectly accommodates. Numerical taxonomy is related to multivariate statistics.

Keywords: Capital Formation, Factor Analysis, Multivariate statistics, Numerical Taxonomy Analysis, Production, Ranking, Spatial Planning

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Authors: Catalina Sau Man Ng

Abstract:

Workplace bullying is generally defined as a form of direct and indirect maltreatment at work including harassing, offending, socially isolating someone or negatively affecting someone’s work tasks. Workplace bullying is unfortunately commonplace around the world, which makes it a social phenomenon worth researching. However, the measurements and estimation methods of workplace bullying seem to be diverse in different studies, leading to dubious results. Hence, this paper attempts to examine the prevalence of workplace bullying in Hong Kong using the latent class analysis approach. It is often argued that the traditional classification of workplace bullying into the dichotomous 'victims' and 'non-victims' may not be able to fully represent the complex phenomenon of bullying. By treating workplace bullying as one latent variable and examining the potential categorical distribution within the latent variable, a more thorough understanding of workplace bullying in real-life situations may hence be provided. As a result, this study adopts a latent class analysis method, which was tested to demonstrate higher construct and higher predictive validity previously. In the present study, a representative sample of 2814 employees (Male: 54.7%, Female: 45.3%) in Hong Kong was recruited. The participants were asked to fill in a self-reported questionnaire which included measurements such as Chinese Workplace Bullying Scale (CWBS) and Chinese Version of Depression Anxiety Stress Scale (DASS). It is estimated that four latent classes will emerge: 'non-victims', 'seldom bullied', 'sometimes bullied', and 'victims'. The results of each latent class and implications of the study will also be discussed in this working paper.

Keywords: latent class analysis, prevalence, survey, workplace bullying

Procedia PDF Downloads 315

Authors: Bongs Lainjo

Abstract:

The evolution and escalation of bike-sharing programs (BSP) continue unabated. Since the sixties, many countries have introduced different models and strategies of BSP. These include variations ranging from dockless models to electronic real-time monitoring systems. Reasons for using this BSP include recreation, errands, work, etc. And there is all indication that complex, and more innovative rider-friendly systems are yet to be introduced. The objective of this paper is to analyze current variables established by different operators and streamline them identifying the most compelling ones using analytics. Given the contents of available databases, there is a lack of uniformity and common standard on what is required and what is not. Two factors appear to be common: user type (registered and unregistered, and duration of each trip). This article uses historical data provided by one operator based in the greater Washington, District of Columbia, USA area. Several variables including categorical and continuous data types were screened. Eight out of 18 were considered acceptable and significantly contribute to determining a useful and reliable predictive model. Bike-sharing systems have become popular in recent years all around the world. Although this trend has resulted in many studies on public cycling systems, there have been few previous studies on the factors influencing public bicycle travel behavior. A bike-sharing system is a computer-controlled system in which individuals can borrow bikes for a fee or free for a limited period. This study has identified unprecedented useful, and pragmatic parameters required in improving BSP ridership dynamics.

Keywords: sharing program, historical data, parameters, ridership dynamics, trip duration

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Authors: Sheikh Shams Azam, Manoj Raju, Venkatesh Pagidimarri, Vamsi Kasivajjala

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Over the past decade, there has been a steep rise in the data-driven analysis in major areas of medicine, such as clinical decision support system, survival analysis, patient similarity analysis, image analytics etc. Most of the data in the field are well-structured and available in numerical or categorical formats which can be used for experiments directly. But on the opposite end of the spectrum, there exists a wide expanse of data that is intractable for direct analysis owing to its unstructured nature which can be found in the form of discharge summaries, clinical notes, procedural notes which are in human written narrative format and neither have any relational model nor any standard grammatical structure. An important step in the utilization of these texts for such studies is to transform and process the data to retrieve structured information from the haystack of irrelevant data using information retrieval and data mining techniques. To address this problem, the authors present Q-Map in this paper, which is a simple yet robust system that can sift through massive datasets with unregulated formats to retrieve structured information aggressively and efficiently. It is backed by an effective mining technique which is based on a string matching algorithm that is indexed on curated knowledge sources, that is both fast and configurable. The authors also briefly examine its comparative performance with MetaMap, one of the most reputed tools for medical concepts retrieval and present the advantages the former displays over the latter.

Keywords: information retrieval, unified medical language system, syntax based analysis, natural language processing, medical informatics

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Authors: Khin Mar Yee, Mu Mu Than, Kyi Lint, Aye Aye Oo, Chan Mya Hmway, Khin Zar Chi Winn

Abstract:

The dynamic changes of Land Use and Land Cover (LULC) changes in Yangon have generally resulted the improvement of human welfare and economic development since the last twenty years. Making map of LULC is crucially important for the sustainable development of the environment. However, the exactly data on how environmental factors influence the LULC situation at the various scales because the nature of the natural environment is naturally composed of non-homogeneous surface features, so the features in the satellite data also have the mixed pixels. The main objective of this study is to the calculation of accuracy based on change detection of LULC changes by Support Vector Machines (SVMs). For this research work, the main data was satellite images of 1996, 2006 and 2015. Computing change detection statistics use change detection statistics to compile a detailed tabulation of changes between two classification images and Support Vector Machines (SVMs) process was applied with a soft approach at allocation as well as at a testing stage and to higher accuracy. The results of this paper showed that vegetation and cultivated area were decreased (average total 29 % from 1996 to 2015) because of conversion to the replacing over double of the built up area (average total 30 % from 1996 to 2015). The error matrix and confidence limits led to the validation of the result for LULC mapping.

Keywords: land use and land cover change, change detection, image processing, support vector machines

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Authors: Taufik Hidayat, Yudha Nurhantari, Bambang U. D. Rianto

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Introduction: The examination of the Short Tandem Repeats (STR) locus on nuclear DNA is very useful in solving the paternity cases. The purpose of this study is to know the description of paternity cases and paternity index/probability of paternity analysis based on Indonesian allele frequency at Sardjito Hospital Yogyakarta. Method: This was an observational study with cross-sectional analytic method. Population and sample were all cases of disputed paternity from January 2011 to June 2015 that fulfill the inclusion and exclusion criteria and were examined at Forensic Medicine Unit of Sardjito Hospital, Medical Faculty of Gadjah Mada University. The paternity index was calculated with EasyDNA Program by Fung (2013). Analysis of the study was conducted by comparing the results through unpaired categorical test using Kolmogorov-Smirnov test. This study was designed with 95% confidence interval (CI) with α = 5% and significance level is p < 0,05. Results: From 42 disputed paternity cases we obtained trio paternity cases were 32 cases (76.2%) and duo without a mother was 10 cases (23.8%). The majority of the fathers' estimated ages were 21-30 years (33.3%) and the mother's age was 31-40 years (38.1%). The majority of the ages of children examined for paternity were under 12 months (47.6%). The majority of ethnic clients are Javanese. Conclusion of inclusion was 57.1%, and exclusion was 42.9%. The Kolmogorov-Smirnov test obtained p-value = 0.673. Conclusion: There is no significant difference between paternity index/probability of paternity based on Indonesian allele frequency between trio and duo of paternity.

Keywords: disputed paternity, paternity index, probability of paternity, short tandem

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

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

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

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