Search results for: Statistical%20package%20IBM%20SPSS%2020

Authors: F. Berna Benli, Özgür Keskin

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Lately, many mathematicians have been studied the statistical convergence of a sequence of fuzzy numbers. We know that Lambda-statistically convergence is a kind of convergence between ordinary convergence and statistical convergence. In this paper, we will introduce the new kind of convergence such as λ-levelwise statistical convergence. Then, we will define the concept of the λ-levelwise statistical cluster and limit points of a sequence of fuzzy numbers. Also, we will discuss the relations between the sets of λ-levelwise statistical cluster points and λ-levelwise statistical limit points of sequences of fuzzy numbers. This work has been extended in this paper, where some relations have been considered such that when lambda-statistical limit inferior and lambda-statistical limit superior for lambda-statistically convergent sequences of fuzzy numbers are equal. Furthermore, lambda-statistical boundedness condition for different sequences of fuzzy numbers has been studied.

Keywords: fuzzy number, λ-levelwise statistical cluster points, λ-levelwise statistical convergence, λ-levelwise statistical limit points, λ-statistical cluster points, λ-statistical convergence, λ-statistical limit points

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Authors: Jack S. Pullman, Daniel Wen, Avinash Sharma, Bert Van Der Werf, Richard Martin

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Background: New Zealand (NZ) melanoma incidence rates are amongst the highest in the world. Previous studies investigating the incidence of melanoma in NZ were performed for the periods 1995 – 1999 and 2000 – 2004 and suggested increasing melanoma incidence rates. Aim: The aim of the study is to provide an up-to-date review of trends in cutaneous melanoma in NZ from the New Zealand Cancer Registry (NZCR) 2010 – 2020. Methods: De-identified data were obtained from the NZCR, and relevant demographic and histopathologic information was extracted. Statistical analyses were conducted to calculate age-standardized incidence rates for invasive melanoma (IM) and melanoma in situ (MIS). Secondary results included Breslow thickness and melanoma subtype analysis. Results: There was a decline in the IM age-standardized incidence rate from 30.4 to 23.9 per 100,000 person-years between 2010 to 2020, alongside an increase in MIS incidence rate from 37.1 to 50.3 per 100,000 person-years. Men had a statistically significant higher IM incidence rate (p <0.001) and Breslow thickness (p <0.001) compared with women. Increased age was associated with a higher incidence of IM, presentation with melanoma of greater Breslow thickness and more advanced T stage. Conclusion: The incidence of IM in NZ has decreased in the last decade and was associated with an increase in MIS incidence over the same period. This can be explained due to earlier detection, dermoscopy, the maturity of prevention campaigns and/or a change in skin protection behavior.

Keywords: melanoma, incidence, epidemiology, New Zealand

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Authors: Rino Gubiani, Gianfranco Pergher

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The work focused on the statistical analysis of accidents in the forestry sector (2000-2020) in Friuli-Venezia Giulia region, located in the North-East of Italy. The aim of the work was to analyse the evolution of the casualties throughout time and to evaluate possible improvements in the sector. It was shown that even nowadays the rate of accidents in forestry work is higher compared with all the other sectors, including agriculture; moreover, it was highlighted that some accidents remained present throughout the whole analysed range, such as slipping on the soil, being hit by trees and falling down from the plants. The results showed that an increase in forestry exploitation could even increase the total number of accidents, if advanced technological machines, such as cable cranes, would not implemented, given the fact that there is also a significant number of old people (above 50 years old) working in the sector.

Keywords: safety, forestry work, accidents, risk analysis, casualties, statistical analysis

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Authors: Petros Roussos

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The present study focused on students' statistical reasoning related to Null Hypothesis Statistical Testing and p-values. Its objective was to test the hypothesis that neither the place (classroom, at a distance, online) nor the medium that actually supports the learning (ICT, internet, books) has an effect on understanding of statistical concepts. In addition, it was expected that students' attitudes towards statistics would not predict understanding of statistical concepts. The sample consisted of 385 undergraduate and postgraduate students from six state and private universities (five in Greece and one in Cyprus). Students were administered two questionnaires: a) the Greek version of the Survey of Attitudes Toward Statistics, and b) a short instrument which measures students' understanding of statistical significance and p-values. Results suggest that attitudes towards statistics do not predict students' understanding of statistical concepts, whereas the medium did not have an effect.

Keywords: attitudes towards statistics, blended learning, e-learning, statistical reasoning

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Authors: Eglė Bilevičiūtė, Vidmantas Egidijus Kurapka, Snieguolė Matulienė, Sigutė Stankevičiūtė

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The Council of European Union (EU Council) has stressed on several occasions the need for a concerted, comprehensive and effective solution to delinquency problems in EU communities. In the context of establishing a European Forensic Science Area and the development of forensic science infrastructure in Europe, EU Council believes that forensic science can significantly contribute to the efficiency of law enforcement, crime prevention and combating crimes. Lithuanian scientists have consolidated to implement a project named “Conception of the vision for European Forensic Science 2020 implementation in Lithuania” (the project is funded for the period of 1 March 2014 - 31 December 2016) with the objective to create a conception of implementation of the vision for European Forensic Science 2020 in Lithuania by 1) evaluating the current status of Lithuania’s forensic system and opportunities for its improvement; 2) analysing achievements and knowledge in investigation of crimes listed in conclusions of EU Council on the vision for European Forensic Science 2020 including creation of a European Forensic Science Area and the development of forensic science infrastructure in Europe: trafficking in human beings, organised crime and terrorism; 3) analysing conceptions of criminalistics, which differ in different EU member states due to the variety of forensic schools, and finding means for their harmonization. Apart from the conception of implementation of the vision for European Forensic Science 2020 in Lithuania, the project is expected to suggest provisions that will be relevant to other EU countries as well. Consequently, the presented conception of implementation of vision for European Forensic Science 2020 in Lithuania could initiate a project for a common vision of European Forensic Science and contribute to the development of the EU as an area of freedom, security and justice. The article presents main ideas of the project of the conception of the vision for European Forensic Science 2020 of EU Council and analyses its legal background, as well as prospects of and challenges for its implementation in Lithuania and the EU.

Keywords: EUROVIFOR, standardization, vision for European Forensic Science 2020, Lithuania

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Authors: Jagannath P. Tegar

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The new National Education Policy (NEP) 2020 of Govt. of India has envisaged a major overhaul of the education system of India, in particular, the revamping of the Curriculum of Higher Education. In this process, the faculty members of the Indian universities and institutions have a challenging role in developing the curriculum, which is a shift from the traditional (content-based) curriculum to a student-centric- outcome-based Curriculum (SC-OBC) to be implemented in all of the Universities and institutions. The efforts and initiatives on the design and implementation of SC-OBC are remarkable in the engineering and technical education landscape of the country, but it is still in its early stages and many more steps are needed for the successful adaptation in every level of Higher Education. The premier institute of Govt. of India (NITTTR, Bhopal) has trained and developed the capacity and capability among the teachers of Polytechnics on the design and development of Student Centric - Outcome Based Curriculum and also providing academic consultancy for reforming curriculum in line of NEP- 2020 envisions for the states such as Chhattisgarh, Bihar and Maharashtra to make them responsibly ready for such a new shift in Higher Education. This research-based paper is on three main aspects: 1) the level of acceptance and preparedness of teachers /faculty towards NEP-2020 and student-centred outcome-based learning. 2) the extent of implementing NEP-2020 and student-centered outcome-based learning at Indian institutions/ universities and 3) the challenges of implementing NEP-2020 and student-centered outcome-based learning outcome-based education in the Indian context. The paper content will inspire curriculum designers and developers to prepare SC-OBC that meets the specific needs of industry and society at large, which is intended in the NEP-2020 of Govt. of India

Keywords: outcome based curriculum, student centric learning, national education policy -2020, implementation of nep-2020. outcome based learning, higher education curriculum

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Authors: Soroush Pakniyat-Jahromi, Jessica Bucciarelli, Souparno Mitra, Neda Motamedi, Ralph Amazan, Samuel Rothman, Jose Tiburcio, Douglas Reich, Vicente Liz

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Violence is defined as an act of physical force that is intended to cause harm and may lead to physical and/or psychological damage. Violence toward healthcare workers (HCWs) is more common in psychiatric settings, emergency departments, and nursing homes; however, healthcare workers in medical setting are not spared from such events. Workplace violence has a huge burden in the healthcare industry and has a major impact on the physical and mental wellbeing of staff. The purpose of this study is to compare the prevalence of patient agitation and violence in medical-surgical settings in BronxCare Hospital (BCH) Bronx, New York, one year before and during the COVID-19 pandemic. Data collection occurred between June 2021 and August 2021, while the sampling time was from 2019 to 2021. The data were separated into two separate time categories: pre-COVID-19 (03/2019-03/2020) and COVID-19 (03/2020-03/2021). We created frequency tables for 19 variables. We used a chi-square test to determine a variable's statistical significance. We tested all variables against “restraint type”, determining if a patient was violent or became violent enough to restrain. The restraint types were “chemical”, “physical”, or both. This analysis was also used to determine if there was a statistical difference between the pre-COVID-19 and COVID-19 timeframes. Our data shows that there was an increase in incidents of violence in COVID-19 era (03/2020-03/2021), with total of 194 (62.8%) reported events, compared to pre COVID-19 era (03/2019-03/2020) with 115 (37.2%) events (p: 0.01). Our final analysis, completed using a chi-square test, determined the difference in violence in patients between pre-COVID-19 and COVID-19 era. We then tested the violence marker against restraint type. The result was statistically significant (p: 0.01). This is the first paper to systematically review the prevalence of violence in medical-surgical units in a hospital in New York, pre COVID-19 and during the COVID-19 era. Our data is in line with the global trend of increased prevalence of patient agitation and violence in medical settings during the COVID-19 pandemic. Violence and its management is a challenge in healthcare settings, and the COVID-19 pandemic has brought to bear a complexity of circumstances, which may have increased its incidence. It is important to identify and teach healthcare workers the best preventive approaches in dealing with patient agitation, to decrease the number of restraints in medical settings, and to create a less restrictive environment to deliver care.

Keywords: COVID-19 pandemic, patient agitation, restraints, violence

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Authors: Arkaprabha Bhattacharyya, Makarand Hastak

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

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

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Authors: Phawichsak Prapassornpitaya, Wanida Jinsart

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Daily monitoring PM₁₀ and PM₂.₅ data from 2007 to 2017 were analyzed to provide baseline data for prediction of the air pollution in Bangkok in the period of 2018 -2020. Two statistical models, Autoregressive Integrated Moving Average model (ARIMA) were used to evaluate the trends of pollutions. The prediction concentrations were tested by root means square error (RMSE) and index of agreement (IOA). This evaluation of the traffic PM₂.₅ and PM₁₀ were studied in association with the regulatory control and emission standard changes. The emission factors of particulate matter from diesel vehicles were decreased when applied higher number of euro standard. The trends of ambient air pollutions were expected to decrease. However, the Bangkok smog episode in February 2018 with temperature inversion caused high concentration of PM₂.₅ in the air environment of Bangkok. The impact of traffic pollutants was depended upon the emission sources, temperature variations, and metrological conditions.

Keywords: fine particulate matter, ARIMA, RMSE, Bangkok

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Authors: Neha Bhardwaj

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In this paper, we consider positive linear operators and study the Voronovskaya type result of the operator then obtain an error estimate in terms of the higher order modulus of continuity of the function being approximated and its A-statistical convergence. Also, we compute the corresponding rate of A-statistical convergence for the linear positive operators.

Keywords: Poisson distribution, Voronovskaya, modulus of continuity, a-statistical convergence

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Authors: Lukanda Kalobo

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In South Africa, the High School Mathematics Curriculum provides teachers with specific aims and skills to be developed which involves the understanding about the measures of central tendency. The exploration begins with the definitions of statistical literacy, measurement of central tendency and a discussion on why statistical literacy is essential today. It furthermore discusses the statistical literacy basics involved in understanding the concepts of measures of central tendency. The statistical literacy test on the measures of central tendency, was used to collect data which was administered to 78 first year students direct from high schools. The results indicated that students seemed to have forgotten about the statistical literacy in understanding the concepts of measure of central tendency after completing their high school study. The authors present inferences regarding the alignment between statistical literacy and the understanding of the concepts about the measures of central tendency, leading to the conclusion that there is a need to provide in-service and pre-service training.

Keywords: conceptual understanding, mean, median, mode, statistical literacy

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Authors: Ahmad Masduki Bin Selamat, Kang Chia Yang

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The International Standard Organization (ISO) is an international consensus on good management practice. It is derived from the Greek word “isos” meaning equal. ISO is aimed to give organization guidelines on what bring quality management system that leads to continuous improvement. The need of quality product is essential these days, especially in the manufacturing and service sectors. The requirement to produce good product is demanded, hence the certification of ISO enables the company to gain the trust from the public. Due to this, organizations whether government or private sectors in Malaysia are going for the ISO certification. However recently there has been an introduction of Islamic standard known as Islamic Standard Institute 2020 (ISI 2020). The ISI standards emphasize more on values that should be in the employees’ mind. By possessing good values, employees will work only for the betterment of the company. Currently only the feelings of being paid for the job exist in the employees’ mind. The non-Malays like Chinese and others, which comprise 40% of the sample size, are not aware about the existence of any Islamic quality system. As for the Malay managers, they support the Islamic quality systems. For them such values are encouraged by religion. By imitating religion, Allah promises a better life in this world and hereafter. Even though ISI 2020 is still new but the majority of Malays would support the need of Islamic quality system. Our findings suggest that integration of these two-quality systems running parallel would bring a better result.

Keywords: International Standard Organization (ISO), Islamic standard, quality, ISI 2020

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Authors: Eszter Siposne Nandori

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The paper describes how the subjective interpretation of poverty changed during the COVID-19 pandemic. The results of data collection at the end of 2020 are compared to the results of a similar survey from 2019. The methods of systematic data collection are used to collect data about the beliefs of the population about poverty. The analysis is carried out in Borsod-Abaúj-Zemplén County, one of the most backward areas in Hungary. The paper concludes that poverty is mainly linked to material values, and it did not change from 2019 to 2020. Some slight changes, however, highlight the effect of the pandemic: poverty is increasingly seen as a generational problem in 2020, and another important change is that isolation became more closely related to poverty.

Keywords: Hungary, interpretation of poverty, pandemic, systematic data collection, subjective poverty

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Authors: Abul Quasem Al-Amin, Md. Hasanuzzaman, Mohammad Nurul Azam, Walter Leal Filho

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With regard to the future energy strategy and vision, this study aimed to find the drawbacks of proposed energy diversification policy for 2020. To have a clear picture of the drawback and competitive alternative, this study has explored two scenarios, namely Scenario a and Scenario b. The Scenario a indicates that in the year 2020 the GHG emissions would be 823,498.00 million tons (Mt) with a 2020 final demand and proposed fuel mix such as by the Five-Fuel Diversification Strategy. In contrast, as an alternative, the Scenario b with biofuel potentials indicates that the substitution of coal energy by 5%, 10%, and 15%, respectively, with biofuel, would reduce the GHG emissions from 374,551.00, 405,118.00, and 823,498.00 million tons to 339,964.00, 329,834.00, and 305,288.00 million tons, respectively, by the present fuel mix, business-as-usual fuel mix, and proposed fuel mix up to the year 2020. Therefore, this study has explored a healthy alternative by introducing biofuel renewable energy option instead of conventional energy utilization in the power generation with environmental aspect in minds. This study effort would lessen the gap between GHG mitigation and future sustainable development and would useful to formulate effective renewable energy strategy in Malaysia.

Keywords: energy, environmental impacts, renewable energy, biofuel, energy policy

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Authors: Tin Thongthammachart, Wanida Jinsart

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Atmospheric particulate matter particles with a diameter less than 10 microns (PM₁₀) and less than 2.5 microns (PM₂.₅) have adverse health effect. The impact from PM was studied from both health and regulatory perspective. Ambient PM data was collected over ten years in Bangkok and vicinity areas of Thailand from 2007 to 2017. Statistical models were used to forecast PM concentrations from 2018 to 2020. Monitoring monthly data averaged concentration of PM₁₀ and PM₂.₅ were used as input to forecast the monthly average concentration of PM. The forecasting results were validated by root means square error (RMSE). The predicted results were used to determine hazard risk for the carcinogenic disease. The health risk values were interpolated with GIS with ordinary kriging technique to create hazard maps in Bangkok and vicinity area. GIS-based maps illustrated the variability of PM distribution and high-risk locations. These evaluated results could support national policy for the sake of human health.

Keywords: PM₁₀, PM₂.₅, statistical models, atmospheric particulate matter

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Authors: Vladimir S. Timofeev

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In this article the problem of distributional moments estimation is considered. The new approach of moments estimation based on usage of the characteristic function is proposed. By statistical simulation technique, author shows that new approach has some robust properties. For calculation of the derivatives of characteristic function there is used numerical differentiation. Obtained results confirmed that author’s idea has a certain working efficiency and it can be recommended for any statistical applications.

Keywords: characteristic function, distributional moments, robustness, outlier, statistical estimation problem, statistical simulation

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Authors: Ryan Brading

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The results of Taiwan’s presidential election, which took place on 11 January 2020, were alarming for the Kuomintang (KMT). A party that was once the pillar of Taiwan’s institutional apparatus is now losing its direction. Since 2016, the inability of KMT to construct a winning presidential election campaign strategy has made its Chinese ancestry an obstacle in Taiwan’s vibrant and transparent democracy. The appearance of the little-known legislator Han Kuo-yu as the leadership alternative opened the possibility of reigniting the party. Han’s victory in the Kaohsiung mayoral election in November 2018 provided hope that Han could also win the presidency. Wrongly described as a populist, Han, however, was defeated in the January 2020 presidential race. This article analyses why Han is not a populist, his triumph in Kaohsiung, humiliation in running for the presidency and suffering a complete ‘loss of face’ when Kaohsiungers democratically ousted him from the mayoral post on 6 June 2020.

Keywords: populism, 1992 consensus, youth vote, Taiwan, recall

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Authors: Authors: A. Lakhal, M. Bahalou, A. Khattabi

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Introduction: Tuberculosis is one of the world's deadliest infectious diseases. In Morocco, a total of 30,636 cases of Tuberculosis, all forms combined, were reported in 2015, representing an incidence of 89 cases per 100,000 population. The number of deaths from tuberculosis (TB) was 656 cases. In the prefecture of Meknes, its incidence remains high compared to the national level. The objective of this work is to describe the epidemiological profile of tuberculosis in the prefecture of Meknes. Methods: It is a descriptive analysis of TB cases reported between 2016 and 2020 at the regional diagnostic center of tuberculosis and respiratory diseases. We performed analysis by using Microsoft Excel and EpiInfo 7. Results: Epidemiological data from 2016 to 2020 report a total of 4100 new cases of all forms of tuberculosis, with an average of 820 new cases per year. The median age is 32 years. There is a clear male predominance, on average 58% of cases are male and 42% female. The incidence rate of bacteriologically confirmed tuberculosis per 100,000 inhabitants has increased from 35 cases per 100,000 inhabitants in 2016 to 39.4 cases per 100,000 inhabitants in 2020. The confirmation rate for pulmonary tuberculosis decreased from 84% in 2016 to 75% in 2020. Pulmonary involvement predominates by an average of 46%, followed by lymph node involvement 29%and pleural involvement by an average of 10%. Digestive, osteoarticular, genitourinary, and meningeal involvement occurs in 8% of cases. Primary tuberculosis infection occurs in an average of 0.5% of cases. The proportion of HIV-TB co-infections was 2.8 in 2020. Conclusion: The incidence of tuberculosis in Meknes remains high compared to the national level. Thus, it is imperative to reinforce the earlier detection; improve the contact tracing, detection methods of cases for their confirmation and treatment, and to reduce the proportion of the lost to follow up as well.

Keywords: tuberculosis, epidemiological profile, meknes, morocco

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Authors: Petar Sarajcev, Josip Vasilj, Damir Jakus

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This paper presents a novel statistical description of the counterpoise effective length due to lightning surges, where the (impulse) effective length had been obtained by means of regressive formulas applied to the transient simulation results. The effective length is described in terms of a statistical distribution function, from which median, mean, variance, and other parameters of interest could be readily obtained. The influence of lightning current amplitude, lightning front duration, and soil resistivity on the effective length has been accounted for, assuming statistical nature of these parameters. A method for determining the optimal counterpoise length, in terms of the statistical impulse effective length, is also presented. It is based on estimating the number of dangerous events associated with lightning strikes. Proposed statistical description and the associated method provide valuable information which could aid the design engineer in optimising physical lengths of counterpoises in different grounding arrangements and soil resistivity situations.

Keywords: counterpoise, grounding conductor, effective length, lightning, Monte Carlo method, statistical distribution

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Authors: Jihye Jeon

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This paper analyzes the conceptual framework of three statistical methods, multiple regression, path analysis, and structural equation models. When establishing research model of the statistical modeling of complex social phenomenon, it is important to know the strengths and limitations of three statistical models. This study explored the character, strength, and limitation of each modeling and suggested some strategies for accurate explaining or predicting the causal relationships among variables. Especially, on the studying of depression or mental health, the common mistakes of research modeling were discussed.

Keywords: multiple regression, path analysis, structural equation models, statistical modeling, social and psychological phenomenon

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Authors: Berger Saintius, Edna Ariste, Djeamsly Salomon

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Background: Maternal mortality is a preventable global health problem that affects developed, developing, and underdeveloped countries alike. Globally, maternal mortality rates have declined since 1990, but 830 women die every day from pregnancy and childbirth-related causes that are often preventable. Haiti, with a number of 529 maternal deaths per 100,000 live births, is one of the countries with the highest maternal mortality rate in the Caribbean. This study consists of analyzing maternal death surveillance data in Haiti from 2017-2020. Method : A descriptive study was conducted; data were extracted from the National Epidemiological Surveillance Network of maternal deaths from 2017 to 2020. Sociodemographic variables were analyzed. Excel and Epi Info 7.2 were used for data analysis. Frequency and proportion measurements were calculated. Results: 756 deaths were recorded for the study period: 42 (6%) in 2017, 168 (22%) in 2018, 265 (35%) in 2019, and 281 (37%) in 2020. The North Department recorded the highest number of deaths, 167 (22%). 83(11%) in Les Cayes. 96% of these deaths are people aged between 15 and 49. Conclusion. Maternal mortality is a major health problem in Haiti. Mobilization, participation, and involvement of communities, increase in obstetric care coverage and promotion of Family Planning are among the strategies to fight this problem.

Keywords: epidemiology, maternal death, hospital, Haiti

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Authors: Theodore Gautier Le Jeune Bikoko, Jean Claude Tchamba, Sofiane Amziane

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This study focuses on the problem of collapsed buildings within the city of Douala over the past ten years, and more precisely, within the period from 2011 to 2020. It was carried out in a bid to ascertain the real causes of this phenomenon, which has become recurrent in the leading economic city of Cameroon. To achieve this, it was first necessary to review some works dealing with construction materials and technology as well as some case histories of structural collapse within the city. Thereafter, a statistical study was carried out on the results obtained. It was found that the causes of building collapses in the city of Douala are: Neglect of administrative procedures, use of poor quality materials, poor composition and confectioning of concrete, lack of Geotechnical study, lack of structural analysis and design, corrosion of the reinforcement bars, poor maintenance in buildings, and other causes. Out of the 46 cases of structural failure of buildings within the city of Douala, 7 of these were identified to have had no geotechnical study carried out, giving a percentage of 15.22%. It was also observed that out of the 46 cases of structural failure, 6 were as a result of lack of proper structural analysis and design, giving a percentage of 13.04%. Subsequently, recommendations and suggestions are made in a bid to placing particular emphasis on the choice of materials, the manufacture and casting of concrete, as well as the placement of the required reinforcements. All this guarantees the stability of a building.

Keywords: collapse buildings, Douala, structural collapse, Cameroon

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Authors: Kristyna Hrabova, Sabina Hüblova, Tomas Vymazal

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Structural design of concrete structure has the result in qualities of structural safety and serviceability, together with durability, robustness, sustainability and resilience. A sustainable approach is at the heart of the research agenda around the world, and the Fibrillation Commission is also working on a new model code 2020. Now it is clear that the effects of mechanical, environmental load and even social coherence need to be reflected and included in the designing and evaluating structures. This study aimed to present the methodology for the sustainability assessment of various concrete mixtures.

Keywords: concrete, cement, sustainability, Model Code 2020

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Authors: Chi T. L. Pham, L. Vu, Hoang T. Le, Huong T. T. Le, Quyen T. T. Bui

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Burning joss paper and incense during religious and cultural ceremonies is common in Vietnam. This study aims to measure the impact of burning joss paper and incense during Vu Lai festival (full moon of July) in Vietnam. Data of Hanoi air quality in year 2020 was used. Interrupted time series analysis was employed to examine the changes in pattern of various air quality indicators before and after the festival period. The results revealed that burning joss paper and incense led to an immediate increase of 15.94 units in the air quality index on the first day, which gradually rose to 47.4 units by the end of the full moon period. Regarding NO2, PM10, and PM25, there was no significant immediate change at the start of the intervention period (August 29th, 2020). However, significant increases in levels and an upward trend were observed during the intervention time, followed by substantial decreases after the intervention period ended (September 3rd, 2020). This analysis did not find a significant impact on CO, SO2, and O3 due to burning joss paper and incense. These findings provide valuable insights for policymakers and stakeholders involved in managing and enhancing air quality in regions where such practices are prevalent.

Keywords: air pollution, incense, ITSA, joss paper, religious activities

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

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Authors: Queen Suraajini Rajendran, Sai Hung Cheung

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Statistical down scaling models are required to connect the global climate model outputs and the local weather variables for climate change impact prediction. For reliable climate change impact studies, the uncertainty associated with the model including natural variability, uncertainty in the climate model(s), down scaling model, model inadequacy and in the predicted results should be quantified appropriately. In this work, a new approach is developed by the authors for statistical classification, statistical down scaling and uncertainty assessment and is applied to Singapore rainfall. It is a robust Bayesian uncertainty analysis methodology and tools based on coupling dependent modeling error with classification and statistical down scaling models in a way that the dependency among modeling errors will impact the results of both classification and statistical down scaling model calibration and uncertainty analysis for future prediction. Singapore data are considered here and the uncertainty and prediction results are obtained. From the results obtained, directions of research for improvement are briefly presented.

Keywords: statistical downscaling, global climate model, climate change, uncertainty

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Authors: Rishikesh Yadav, Ramakanta Meher, Vishnu Narayan Mishra

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The main aim of this article is to investigate the statistical convergence of the summation of integral type operators and to obtain the weighted statistical convergence. The rate of statistical convergence by means of modulus of continuity and function belonging to the Lipschitz class are also studied. We discuss the convergence of the defined operators by graphical representation and put a better rate of convergence than the Szasz-Mirakjan-Kantorovich operators. In the last section, we extend said operators into bivariate operators to study about the rate of convergence in sense of modulus of continuity and by means of Lipschitz class by using function of two variables.

Keywords: The Szasz-Mirakjan-Kantorovich operators, statistical convergence, modulus of continuity, Peeters K-functional, weighted modulus of continuity

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Authors: Sincy Wilson

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This article focuses on the data scattered throughout the 2020 Report on migration for a variety of reasons. Despite the fact that climate migrants are no longer recognized on an international or national level, their situation remains unchanged, and many countries have already encountered the problem of people entering their country without permission. With the information presented in the paper, researchers are focusing on climate-induced displacement rather than conflict-related migration. The author finishes by stating that there is no time to waste in recognizing climate migrants.

Keywords: climate refugees, climatological factors, migration, slow-onset migration

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Authors: Ari Prasetyo, Taufik Faturohman

Abstract:

The COVID-19 pandemic in Indonesia is part of the ongoing worldwide pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was confirmed to have spread to Indonesia on 2 March 2020. Moreover, the government of Indonesia has been conducting a local lockdown to limit people's movement from one city to another city. Therefore, this situation has impact on business operation, especially on highway companies listed on the Indonesia stock exchange. This study evaluates and measures three companies’ financial performance and health conditions before and during the COVID-19 pandemic from 2016 – 2020. The measurement is conducted by using financial ratio analysis and the Altman Z-score method. The ratio used to measure the financial ratio analysis is taken from the decree of the Ministry of SOE’s KEP-100/MBU/2002 about the company’s health level condition. From the decree, there are eight financial ratios used such as return on equity (ROE), return on investment (ROI), current ratio, cash ratio, collection period, inventory turnover, total asset turnover, and total equity to total asset. Altman Z-score is used to calculate the financial distress condition. The result shows that the highway companies for the period 2016 – 2020 are as follows: PT Jasa Marga (Persero) Tbk (AA, BB, BB, BB, C), PT Citra Marga Nusaphala Persada Tbk (BB, AA, BB, BBB, C), and PT Nusantara Infrastructure Tbk (BB, BB, AA, BBB, C). In addition, the Altman Z-score assessment performed in 2016-2020 shows that PT Jasa Marga (Persero) Tbk was in the grey zone area for 2015-2018 and in the distress zone for 2019-2020. PT Citra Marga Nusaphala Persada Tbk was in the grey zone area for 2015-2019 and in the distress zone for 2020. PT Nusantara Infrastructure Tbk was in the grey zone area for 2015-2018 and in the distress zone for 2019-2020.

Keywords: financial performance, financial ratio, Altman Z-score, financial distress, highway company

Procedia PDF Downloads 151

Authors: Smah Almotiri

Abstract:

One of the most common fields of natural language processing (NLP) is sentimental analysis. The inferred feeling in the text can be successfully mined for various events using sentiment analysis. Twitter is viewed as a reliable data point for sentimental analytics studies since people are using social media to receive and exchange different types of data on a broad scale during the COVID-19 epidemic. The processing of such data may aid in making critical decisions on how to keep the situation under control. The aim of this research is to look at how sentimental states differed in a single geographic region during the lockdown at two different times.1162 tweets were analyzed related to the COVID-19 pandemic lockdown using keywords hashtags (lockdown, COVID-19) for the first sample tweets were from March 23, 2020, until April 23, 2020, and the second sample for the following year was from March 1, 2020, until April 4, 2020. Natural language processing (NLP), which is a form of Artificial intelligence, was used for this research to calculate the sentiment value of all of the tweets by using AFINN Lexicon sentiment analysis method. The findings revealed that the sentimental condition in both different times during the region's lockdown was positive in the samples of this study, which are unique to the specific geographical area of New Zealand. This research suggests applying machine learning sentimental methods such as Crystal Feel and extending the size of the sample tweet by using multiple tweets over a longer period of time.

Keywords: sentiment analysis, Twitter analysis, lockdown, Covid-19, AFINN, NodeJS

Procedia PDF Downloads 149