Search results for: statistics and probability

Authors: Ibrahim Turfanda, Soniya Rai, Karan Vadher

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Objectives— The study aims to compare real-world adherence to and persistence with dulaglutide and liraglutide in patients with type 2 diabetes (T2D) initiating treatment in UAE. Methods— This was a retrospective, non-interventional study (observation period: 01 March 2017–31 August 2019) using the UAE Dubai e-Claims database. Included: adult patients initiating dulaglutide/liraglutide 01 September 2017–31 August 2018 (index period) with: ≥1 claim for T2D in the 6 months before index date (ID); ≥1 claim for dulaglutide/liraglutide during index period; and continuous medical enrolment for ≥6 months before and ≥12 months after ID. Key endpoints, assessed 3/6/12 months after ID: adherence to treatment (proportion of days covered [PDC; PDC ≥80% considered ‘adherent’], per-group mean±standard deviation [SD] PDC); and persistence (number of continuous therapy days from ID until discontinuation [i.e., >45 days gap] or end of observation period). Patients initiating dulaglutide/liraglutide were propensity score matched (1:1) based on baseline characteristics. Between-group comparison of adherence was analysed using the McNemar test (α=0.025). Persistence was analysed using Kaplan–Meier estimates with log-rank tests (α=0.025) for between-group comparisons. This study presents 12-month outcomes. Results— Following propensity score matching, 263 patients were included in each group. Mean±SD PDC for all patients at 12 months was significantly higher in the dulaglutide versus the liraglutide group (dulaglutide=0.48±0.30, liraglutide=0.39±0.28, p=0.0002). The proportion of adherent patients favored dulaglutide (dulaglutide=20.2%, liraglutide=12.9%, p=0.0302), as did the probability of being adherent to treatment (odds ratio [97.5% CI]: 1.70 [0.99, 2.91]; p=0.03). Proportion of persistent patients also favoured dulaglutide (dulaglutide=15.2%, liraglutide=9.1%, p=0.0528), as did the probability of discontinuing treatment 12 months after ID (p=0.027). Conclusions— Based on the UAE Dubai e-Claims database data, dulaglutide initiators exhibited significantly greater adherence in terms of mean PDC versus liraglutide initiators. The proportion of adherent patients and the probability of being adherent favored the dulaglutide group, as did treatment persistence.

Keywords: adherence, dulaglutide, effectiveness, liraglutide, persistence

Procedia PDF Downloads 105

Authors: Katejarinporn Chaiya, Jarumon Nookong, Nutthapat Kaewrattanapat

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The purposes of this research were to develop and find users’ satisfaction after using the Decision Support System for Examination Selection. This research presents the design of information systems. In order to find the necessary examination of the statistics. Based on the examination of the candidate and then taking the easy difficulty setting statistics applied to the test. In addition, research has also made performance appraisals from experts and user satisfaction. By results of analysis showed that the performance appraisals from experts on the system as a whole and at a good level. mean was 3.44 and S.D. was 0.55 and user satisfaction per system as a whole and the good level mean was 3.37 and S.D. was 0.42 can conclude that effective systems are in a good level. Work has been completed in accordance with the scope of work. The website used developing this project is PHP, MySQL.5.0.45 for database.

Keywords: secision support system, examination, PHP, information systems

Procedia PDF Downloads 427

Authors: Kwaku Damoah

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This paper presents a methodology and software application (App) designed to empower users in accessing, retrieving, and comparatively exploring data within the hierarchical network framework of the Government Finance Statistics (GFS) system. It explores the ease of navigating the GFS system and identifies the gaps filled by the new methodology and App. The GFS, embodies a complex Hierarchical Network Classification (HNC) structure, encapsulating institutional units, revenues, expenses, assets, liabilities, and economic activities. Navigating this structure demands specialized knowledge, experience, and skill, posing a significant challenge for effective analytics and fiscal policy decision-making. Many professionals encounter difficulties deciphering these classifications, hindering confident utilization of the system. This accessibility barrier obstructs a vast number of professionals, students, policymakers, and the public from leveraging the abundant data and information within the GFS. Leveraging R programming language, Data Science Analytics and Machine Learning, an efficient methodology enabling users to access, navigate, and conduct exploratory comparisons was developed. The machine learning Fiscal Analytics App (FLOWZZ) democratizes access to advanced analytics through its user-friendly interface, breaking down expertise barriers.

Keywords: data science, data wrangling, drilldown analytics, government finance statistics, hierarchical network classification, machine learning, web application.

Procedia PDF Downloads 48

Authors: K. Y. Chen, H. Chua, C. W. Kan

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Environmental investment is an important issue in many countries. In this study, we will first review the environmental issues related to India and their effect on the economical development. Secondly, economic data would be collected from government yearly statistics. The statistics would also include the environmental investment information of India. Finally, we would co-relate the data in order to find out the relationship between environmental investment and sustainable development in India. Therefore, in the paper, we aim to analyse the effect of an environmental investment on the sustainable development in India. Based on the economic data collected, India is in development status with fast population and GDP growth speed. India is facing the environment problems due to its high-speed development. However, the environment investment could give a positive impact on the sustainable development in India. The environmental investment is keeping in the same growth rate with GDP. Acknowledgment: Authors would like to thank the financial support from the Hong Kong Polytechnic University for this work.

Keywords: India, environmental investment, sustainable development, analysis

Procedia PDF Downloads 297

Authors: Haj Najafi Leila, Tehranizadeh Mohsen

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Dependencies between diverse factors involved in probabilistic seismic loss evaluation are recognized to be an imperative issue in acquiring accurate loss estimates. Dependencies among component damage costs could be taken into account considering two partial distinct states of independent or perfectly-dependent for component damage states; however, in our best knowledge, there is no available procedure to take account of loss dependencies in story level. This paper attempts to present a method called "modal cost superposition method" for decoupling story damage costs subjected to earthquake ground motions dealt with closed form differential equations between damage cost and engineering demand parameters which should be solved in complex system considering all stories' cost equations by the means of the introduced "substituted matrixes of mass and stiffness". Costs are treated as probabilistic variables with definite statistic factors of median and standard deviation amounts and a presumed probability distribution. To supplement the proposed procedure and also to display straightforwardness of its application, one benchmark study has been conducted. Acceptable compatibility has been proven for the estimated damage costs evaluated by the new proposed modal and also frequently used stochastic approaches for entire building; however, in story level, insufficiency of employing modification factor for incorporating occurrence probability dependencies between stories has been revealed due to discrepant amounts of dependency between damage costs of different stories. Also, more dependency contribution in occurrence probability of loss could be concluded regarding more compatibility of loss results in higher stories than the lower ones, whereas reduction in incorporation portion of cost modes provides acceptable level of accuracy and gets away from time consuming calculations including some limited number of cost modes in high mode situation.

Keywords: dependency, story-cost, cost modes, engineering demand parameter

Procedia PDF Downloads 160

Authors: Deepti Kohli, Meeta Keswani Mehra

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The paper develops a theoretical model of electoral competition with purely opportunistic candidates and a uni-dimensional policy using the probability voting approach while focusing on the aspect of lobby formation to analyze the inherent complex interactions between centripetal and centrifugal forces and their effects on equilibrium policy platforms. There exist three types of agents, namely, Left-wing, Moderate and Right-wing who comprise of the total voting population. Also, it is assumed that the Left and Right agents are free to initiate a lobby of their choice. If initiated, these lobbies generate donations which in turn can be contributed to one (or both) electoral candidates in order to influence them to implement the lobby’s preferred policy. Four different lobby formation scenarios have been considered: no lobby formation, only Left, only Right and both Left and Right. The equilibrium policy platforms, amount of individual donations by agents to their respective lobbies and the contributions offered to the electoral candidates have been solved for under each of the above four cases. Since it is assumed that the agents cannot coordinate each other’s actions during the lobby formation stage, there exists a probability with which a lobby would be formed, which is also solved for in the model. The results indicate that the policy platforms of the two electoral candidates converge completely under the cases of no lobby and both (extreme) formations but diverge under the cases of only one (Left or Right) lobby formation. This is because in the case of no lobby being formed, only the centripetal forces (emerging from the election-winning aspect) are present while in the case of both extreme (Left-wing and Right-wing) lobbies being formed, centrifugal forces (emerging from the lobby formation aspect) also arise but cancel each other out, again resulting in a pure policy convergence phenomenon. In contrast, in case of only one lobby being formed, both centripetal and centrifugal forces interact strategically, leading the two electoral candidates to choose completely different policy platforms in equilibrium. Additionally, it is found that in equilibrium, while the donation by a specific agent type increases with the formation of both lobbies in comparison to when only one lobby is formed, the probability of implementation of the policy being advocated by that lobby group falls.

Keywords: electoral competition, equilibrium policy platforms, lobby formation, opportunistic candidates

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Authors: Ali Ocholi

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The study was conducted to analyze the impact of agro-allied industries on rural dwellers in Benue state, Nigeria. Stratified random sampling technique was used to select the respondents for the study. Primary data were collected through the use of structured questionnaires administered on 366 respondents from the selected communities; the data were analyzed using both descriptive and inferential statistics. The result of Mann-Whitney (U) statistics showed that water availability (14350) and good road network (15082.00) were the only social impact derived from the industries by the rural dwellers. The study recommended that right and proper policies and programmes should be put in place by the government to mandate all private and public agro-allied industries to embark on projects that would be in favour of the rural dwellers where the agro-allied industries are situated.

Keywords: agriculture, agro-allied industry, rural dwellers, Benue state

Procedia PDF Downloads 229

Authors: Peyman Sheikholharam Mashhadi

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Difficulties in analyzing real world images in classical image processing and machine vision framework have motivated researchers towards considering the biology-based vision. It is a common belief that mammalian visual cortex has been adapted to the statistics of the real world images through the evolution process. There are two well-known successful models of mammalian visual cortical cells: Independent Component Analysis (ICA) and Independent Subspace Analysis (ISA). In this paper, we statistically analyze the dependencies which remain in the components after applying these models to the natural images. Also, we investigate the response of feature detectors to gratings with various parameters in order to find optimal parameters of the feature detectors. Finally, the selectiveness of feature detectors to phase, in both models is considered.

Keywords: statistics, independent component analysis, independent subspace analysis, phase, natural images

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Authors: Shivdayal Patel, Suhail Ahmad

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Safety assurance and failure prediction of composite material component of an offshore structure due to low velocity impact is essential for associated risk assessment. It is important to incorporate uncertainties associated with material properties and load due to an impact. Likelihood of this hazard causing a chain of failure events plays an important role in risk assessment. The material properties of composites mostly exhibit a scatter due to their in-homogeneity and anisotropic characteristics, brittleness of the matrix and fiber and manufacturing defects. In fact, the probability of occurrence of such a scenario is due to large uncertainties arising in the system. Probabilistic finite element analysis of composite plates due to low-velocity impact is carried out considering uncertainties of material properties and initial impact velocity. Impact-induced damage of composite plate is a probabilistic phenomenon due to a wide range of uncertainties arising in material and loading behavior. A typical failure crack initiates and propagates further into the interface causing de-lamination between dissimilar plies. Since individual crack in the ply is difficult to track. The progressive damage model is implemented in the FE code by a user-defined material subroutine (VUMAT) to overcome these problems. The limit state function is accordingly established while the stresses in the lamina are such that the limit state function (g(x)>0). The Gaussian process response surface method is presently adopted to determine the probability of failure. A comparative study is also carried out for different combination of impactor masses and velocities. The sensitivity based probabilistic design optimization procedure is investigated to achieve better strength and lighter weight of composite structures. Chain of failure events due to different modes of failure is considered to estimate the consequences of failure scenario. Frequencies of occurrence of specific impact hazards yield the expected risk due to economic loss.

Keywords: composites, damage propagation, low velocity impact, probability of failure, uncertainty modeling

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Authors: Cornelius Michael Ekenta

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The research made a gender comparative analysis of the influence of sources of information on the adoption of tenera improved oil palm technology. Purposive, stratified and random sampling techniques were used to sample a total of 292 farmers (155 males and 137 females) for the study. Structured questionnaire was used to obtain primary data used for analysis. Obtained data were analyzed with descriptive statistics and Logit regressions analysis. Findings revealed that radio, extension office, television and farmers’ group were the most preferred sources of information by the farmers both male and female. Also, males perceived information from radio (92%) and farmers’ group (84%) to be available and information from Research Institutes as credible (95%). Similarly, the female perceived information from Research Institutes to be reliable (70%). The study showed that 38% of men adopted the variety, 25% of the women adopted the variety while 32% of both men and women adopted the variety in the study area. Regressions analysis indicated that radio, extension office, television, farmers’ group and research institute were significant at 0.5% of probability for men and female farmers. The study concluded that the adoption of tenera improved oil palm technology was low among male and female farmers though men adopted more than the women. It was recommended therefore that Agricultural Development Programme (ADP) in other states of the country should partner with their state radio and television stations to broadcast agricultural programmes periodically to ensure efficient dissemination of agricultural information to the farmers.

Keywords: analysis, Edo, gender, influence, information, sources, tenera

Procedia PDF Downloads 86

Authors: Ramin Vafadary, Maryam Khanbaghi

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Forecasting electricity load is important for various purposes like planning, operation, and control. Forecasts can save operating and maintenance costs, increase the reliability of power supply and delivery systems, and correct decisions for future development. This paper compares various time series methods to forecast 24 hours ahead of electricity load. The methods considered are the Holt-Winters smoothing, SARIMA Modeling, LSTM Network, Fbprophet, and Tensorflow probability. The performance of each method is evaluated by using the forecasting accuracy criteria, namely, the mean absolute error and root mean square error. The National Renewable Energy Laboratory (NREL) residential energy consumption data is used to train the models. The results of this study show that the SARIMA model is superior to the others for 24 hours ahead forecasts. Furthermore, a Bagging technique is used to make the predictions more robust. The obtained results show that by Bagging multiple time-series forecasts, we can improve the robustness of the models for 24 hours ahead of electricity load forecasting.

Keywords: bagging, Fbprophet, Holt-Winters, LSTM, load forecast, SARIMA, TensorFlow probability, time series

Procedia PDF Downloads 79

Authors: Chiung-Hui Chen

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The Internet of Things (IoT) was designed for widespread convenience. With the smart tag and the sensing network, a large quantity of dynamic information is immediately presented in the IoT. Through the internal communication and interaction, meaningful objects provide real-time services for users. Therefore, the service with appropriate decision-making has become an essential issue. Based on the science of human behavior, this study employed the environment model to record the time sequences and locations of different behaviors and adopted the probability module of the hierarchical Hidden Markov Model for the inference. The statistical analysis was conducted to achieve the following objectives: First, define user behaviors and predict the user behavior routes with the environment model to analyze user purposes. Second, construct the hierarchical Hidden Markov Model according to the logic framework, and establish the sequential intensity among behaviors to get acquainted with the use and activity fabric of the intelligent environment. Third, establish the intensity of the relation between the probability of objects’ being used and the objects. The indicator can describe the possible limitations of the mechanism. As the process is recorded in the information of the system created in this study, these data can be reused to adjust the procedure of intelligent design services.

Keywords: behavior, big data, hierarchical hidden Markov model, intelligent object

Procedia PDF Downloads 219

Authors: M. Bahari Mehrabani, Hua-Peng Chen

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Management and maintenance of coastal defence structures during the expected life cycle have become a real challenge for decision makers and engineers. Accurate evaluation of the current condition and future performance of flood defence structures is essential for effective practical maintenance strategies on the basis of available field inspection data. Moreover, as coastal defence structures age, it becomes more challenging to implement maintenance and management plans to avoid structural failure. Therefore, condition inspection data are essential for assessing damage and forecasting deterioration of ageing flood defence structures in order to keep the structures in an acceptable condition. The inspection data for flood defence structures are often collected using discrete visual condition rating schemes. In order to evaluate future condition of the structure, a probabilistic deterioration model needs to be utilised. However, existing deterioration models may not provide a reliable prediction of performance deterioration for a long period due to uncertainties. To tackle the limitation, a time-dependent condition-based model associated with a transition probability needs to be developed on the basis of condition grade scheme for flood defences. This paper presents a probabilistic method for predicting future performance deterioration of coastal flood defence structures based on condition grading inspection data and deterioration curves estimated by expert judgement. In condition-based deterioration modelling, the main task is to estimate transition probability matrices. The deterioration process of the structure related to the transition states is modelled according to Markov chain process, and a reliability-based approach is used to estimate the probability of structural failure. Visual inspection data according to the United Kingdom Condition Assessment Manual are used to obtain the initial condition grade curve of the coastal flood defences. The initial curves then modified in order to develop transition probabilities through non-linear regression based optimisation algorithms. The Monte Carlo simulations are then used to evaluate the future performance of the structure on the basis of the estimated transition probabilities. Finally, a case study is given to demonstrate the applicability of the proposed method under no-maintenance and medium-maintenance scenarios. Results show that the proposed method can provide an effective predictive model for various situations in terms of available condition grading data. The proposed model also provides useful information on time-dependent probability of failure in coastal flood defences.

Keywords: condition grading, flood defense, performance assessment, stochastic deterioration modelling

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Authors: Erindi Allaj

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This paper studies arbitrage pricing theory in financial markets with transaction costs. We extend the existing theory to include the more realistic possibility that the price at which the investors trade is dependent on the traded volume. The investors in the market always buy at the ask and sell at the bid price. Transaction costs are composed of two terms, one is able to capture the implicit transaction costs and the other the price impact. Moreover, a new definition of a self-financing portfolio is obtained. The self-financing condition suggests that continuous trading is possible, but is restricted to predictable trading strategies which have left and right limit and finite quadratic variation. That is, predictable trading strategies of infinite variation and of finite quadratic variation are allowed in our setting. Within this framework, the existence of an equivalent probability measure is equivalent to the absence of arbitrage opportunities, so that the first fundamental theorem of asset pricing (FFTAP) holds. It is also proved that, when this probability measure is unique, any contingent claim in the market is hedgeable in an L2-sense. The price of any contingent claim is equal to the risk-neutral price. To better understand how to apply the theory proposed we provide an example with linear transaction costs.

Keywords: arbitrage pricing theory,
transaction costs, fundamental theorems of arbitrage, financial markets

Procedia PDF Downloads 342

Authors: Qaisara Parveen, M. Imran Yousuf

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The purpose of this study was to find the effectiveness of the use of advance organizer model for enhancing meta-cognition of students in the subject of science. It was hypothesized that the students of experimental group taught through advance organizer model would show the better cognition than the students of control group taught through traditional teaching. The population of the study consisted of all secondary school students studying in government high school located in Rawalpindi. The sample of the study consisted of 50 students of 9th class of humanities group. The sample was selected on the basis of their pretest scores through matching, and the groups were randomly assigned for the treatment. The experimental group was taught through advance organizer model while the control group was taught through traditional teaching. The self-developed achievement test was used for the purpose of pretest and posttest. After collecting the pre-test score and post-test score, the data was analyzed and interpreted by use of descriptive statistics as mean and standard deviation and inferential statistics t-test. The findings indicate that students taught using advance organizers had a higher level of meta-cognition as compared to control group. Further, meta cognition level of boys was found higher than that of girls students. This study also revealed the fact that though the students at different meta-cognition level approached learning situations in a different manner, Advance organizer model is far superior to Traditional method of teaching.

Keywords: descriptive, experimental, humanities, meta-cognition, statistics, science

Procedia PDF Downloads 291

Authors: Arti Devi, Parthasarthi Choudhury

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Extreme rainfall frequency analysis for Meteorological Sub-Division 4 of India was analysed using L-moments approach. Serial Correlation and Mann Kendall tests were conducted for checking serially independent and stationarity of the observations. The discordancy measure for the sites was conducted to detect the discordant sites. The regional homogeneity was tested by comparing with 500 generated homogeneous regions using a 4 parameter Kappa distribution. The best fit distribution was selected based on ZDIST statistics and L-moments ratio diagram from the five extreme value distributions GPD, GLO, GEV, P3 and LP3. The LN3 distribution was selected and regional rainfall frequency relationship was established using index-rainfall procedure. A regional mean rainfall relationship was developed using multiple linear regression with latitude and longitude of the sites as variables.

Keywords: L-moments, ZDIST statistics, serial correlation, Mann Kendall test

Procedia PDF Downloads 425

Authors: Ratu Khabiba, Qisha Quarina

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This study aims to analyse the effect of married couples’ assortative educational attainments on the division of economic activities among themselves in the household. This study contributes to the literature on women’s participation in employment, especially among married women, to see whether the traditional values about gender roles in the household still continue to shape the employment participation among married women in Indonesia, despite increasing women’s human capital through education. This study utilizes the Indonesian National Socioeconomic Survey (SUSENAS) 2016 and estimates the results using the multinomial logit model. Our results show that compared to high-educated educational homogamy couples, educational heterogamy couples, especially hypergamy, have a higher probability of being a single-worker type. Moreover, the high-educated educational homogamy couples have the highest probability of being a dual-worker type. Thus, we found evidence that the traditional values of gender role segregation seem to still play a significant role in married women’s employment decision in Indonesia, particularly for couples’ with educational heterogamy and low-educated educational homogamy couples.

Keywords: assortative education, dual-worker, hypergamy, homogamy, traditional values, women labor participation

Procedia PDF Downloads 103

Authors: L. Aparecida Bastos, J. Leige Lopes, J. Crepaldi, R. Monteiro da Silva

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The objective of this study is to analyze the evolution of some social and economic indicators of Mercosur´s economies from 1980 to 2012, based on the statistics of the Latin American Integration Association (LAIA). The objective is to observe if after the accession of these economies to Mercosur (the first accessions occurred in 1994) these indicators showed better performance, in order to demonstrate if economic integration contributed to improved trade, macroeconomic performance, and level of social and economic development of member countries. To this end, the methodologies used will be a literature review and descriptive statistics. The theoretical framework that guides the work are the theories of Integration: Classical Liberal, Marxist and structural-proactive. The results reveal that most social and economic indicators showed better performance in those economies that joined Mercosur after 1994. This work is the result of an investigation already completed.

Keywords: economic integration, Mercosur, social indicators, economic indicators

Procedia PDF Downloads 279

Authors: Boumesbah Asma, Chergui Mohamed El-amine

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Since it has been shown that the multi-objective minimum spanning tree problem (MOST) is NP-hard even with two criteria, we propose in this study a hybrid NSGA-II algorithm with an exact mutation operator, which is only used with low probability, to find an approximation to the Pareto front of the problem. In a connected graph G, a spanning tree T of G being a connected and cycle-free graph, if k edges of G\T are added to T, we obtain a partial graph H of G inducing a reduced size multi-objective spanning tree problem compared to the initial one. With a weak probability for the mutation operator, an exact method for solving the reduced MOST problem considering the graph H is then used to give birth to several mutated solutions from a spanning tree T. Then, the selection operator of NSGA-II is activated to obtain the Pareto front approximation. Finally, an adaptation of the VNS metaheuristic is called for further improvements on this front. It allows finding good individuals to counterbalance the diversification and the intensification during the optimization search process. Experimental comparison studies with an exact method show promising results and indicate that the proposed algorithm is efficient.

Keywords: minimum spanning tree, multiple objective linear optimization, combinatorial optimization, non-sorting genetic algorithm, variable neighborhood search

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Authors: Urvee B. Trivedi, U. D. Dalal

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As wireless communication services grow quickly; the seriousness of spectrum utilization has been on the rise gradually. An emerging technology, cognitive radio has come out to solve today’s spectrum scarcity problem. To support the spectrum reuse functionality, secondary users are required to sense the radio frequency environment, and once the primary users are found to be active, the secondary users are required to vacate the channel within a certain amount of time. Therefore, spectrum sensing is of significant importance. Once sensing is done, different prediction rules apply to classify the traffic pattern of primary user. Primary user follows two types of traffic patterns: periodic and stochastic ON-OFF patterns. A cognitive radio can learn the patterns in different channels over time. Two types of classification methods are discussed in this paper, by considering edge detection and by using autocorrelation function. Edge detection method has a high accuracy but it cannot tolerate sensing errors. Autocorrelation-based classification is applicable in the real environment as it can tolerate some amount of sensing errors.

Keywords: cognitive radio (CR), probability of detection (PD), probability of false alarm (PF), primary user (PU), secondary user (SU), fast Fourier transform (FFT), signal to noise ratio (SNR)

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Authors: J. Jarolímek, P. Urban, P. Pavlínek, D. Dzúrová

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The industry constitutes a dominant economic sector in Czechia. The automotive industry represents the most important industrial sector in terms of gross value added and the number of employees. The objective of this study was to analyse the occurrence of occupational diseases (OD) in the automotive industry in Czechia during the 2001-2014 period. Whereas the occurrence of OD in other sectors has generally been decreasing, it has been increasing in the automotive industry, including growing spatial discrepancies. Data on OD cases were retrieved from the National Registry of Occupational Diseases. Further, we conducted a survey in automotive companies with a focus on occupational health services and positions of the companies in global production networks (GPNs). An analysis of OD distribution in the automotive industry was performed (age, gender, company size and its role in GPNs, regional distribution of studied companies, and regional unemployment rate), and was accompanied by an assessment of the quality and range of occupational health services. The employees older than 40 years had nearly 2.5 times higher probability of OD occurrence compared with employees younger than 40 years (OR 2.41; 95% CI: 2.05-2.85). The OD occurrence probability was 3 times higher for women than for men (OR 3.01; 95 % CI: 2.55-3.55). The OD incidence rate was increasing with the size of the company. An association between the OD incidence and the unemployment rate was not confirmed.

Keywords: occupational diseases, automotive industry, health geography, unemployment

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Authors: Md. Arifur Rahman, Ummya Salma, Nazrul Islam

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Private sector banking business is one of the leading businesses of Bangladesh as it is profitable and directly attached with the economic development of the country. Training has got very high importance in this sector for increasing the performance of the banks. It has a long term impact on a number of aspects of the bank employees and their performances. It is an investment of the organization that is permanent in nature. Study shows that there are positive relationships between training and the employee commitment, job retention, job satisfaction and company performance. Training is also concerned with promotion, compensation, work-life policies, career development, task and contextual performance of the employees. As such, this paper aims at identifying the impact of training on employee commitment, job retention, job satisfaction and the performance of the private sector banks in Bangladesh. Both primary and secondary data were used to conduct the study. Data were collected from the bank officers who were trained in their banks. Both descriptive and inferential statistics were used to analyze the data. Descriptive statistics were used to describe the present situation of the banks and their employees. Inferential statistics were used to identify the factors and their significance concerned with training. Results show that there is a significant relationship between the performance and the training of the employees. It also shows that the training can motivate employees and encourage them to work hard. However, this study did not find any relationship between the commitment of the employees and the training. This study suggests that for increasing the performance of the banks, training is a must which is to be given deliberately for improving the specific skills of the bank employees.

Keywords: training, promotion, compensation, work-life policies

Procedia PDF Downloads 268

Authors: Luksanaporn Krungkraipetch

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Epidemic keratoconjunctivitis is an acute infection caused by the adenovirus symptoms of eye irritation, tearing an incubation period of 7-9 days from the respiratory tract into the eye and often cohesion in the community who work in the school's pool as well as a shopping mall. After infection can cause symptoms within 1-2 days chance to infect others up to two weeks. In some cases when red-eye better they had potential complications of the eye, inflammation occurs 7-10 days after conjunctivitis. It could be for several more months to recover. This study is a cross-sectional study with one hundred and eleven beach venders, and purpose of the research was to assess the knowledge, that knowledge has improved much. By comparing before and after the knowledge of the use of questionnaires and test your knowledge. The statistics used for data analysis percent, arithmetic mean and T-test. The statistics used to analyze data at the level of statistical p ≤ 0.05. Result of this study; mostly female (83.8%), most age 19-35 years (42.3%). Hometown is mostly in Chonburi 74.8%. 20.7% had epidemic keratoconjunctivitis within one year. Compared between before and after gave knowledge; after gave knowledge is better than before gave knowledge p=0.00.

Keywords: knowledge, epidemic keratoconjunctivitis, conjunctivitis, beach vender

Procedia PDF Downloads 252

Authors: Etienne Gatera

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Many studies have been conducted on SDT. Most of them focus on developed countries because of influencing factors such as; education, health, labor force, female labor force participation, industrialization, urbanization and migration. However, this thesis project paper aims to assess the impact of the total fertility rate (TFR) on the trends of the SDR in Rwanda. We will mainly be based in Rwanda after the 1994 genocide. Rwanda is located in East Africa, with approximately 13 million inhabitants. Thus, after the 1994 Tutsi genocide. The population growth rate exploded out of control with 6.17 children per woman in 1995. However, it's declined to 4.2 in 2014-2015 and declining to 4.1% in 2019-2020. Respectively with 3.4 children per woman in urban areas and 4.3 in rural areas. According to the National Institute of Statistics of Rwanda. Rwanda's population is expected to continue to grow for the rest of the century and reach 33.35 million people in 2099, with 2.1 children per woman in 2050. However, this project document aims to demonstrate the impact of the TFR on SDT trends in Rwanda. Thus, the decline in the TFR in Rwanda began with the introduction of family planning practices, which now account for 47.5% in 2019. Childbearing with three children for rural women compared to two children in the city, the increase in Divorce and separation caused by the behavior called "Kuza n'ijoro" or "coming at night" similar to cohabitation in developed countries. The decline in remarriage is caused by single mothers behavior who prefer to raise their children rather than remarry. Therefore, the study used probability sampling with (Stratified random sampling) method with a survey questionnaire of 1067 respondents in the 5 Districts (3 in rural areas and two in urban areas), with the target group of women Age between 15-49. The study demonstrated that the age of marriage in rural areas is two years higher than in urban areas. Divorce is more common in urban is with 6.2% with 5.2% in rural areas. However, separation is more common in rural areas than in urban areas, with a lower rate of 3%, due to the higher system called "Kuza n'ijoro" or "come at night", similar to cohabitation in developed countries. The study revealed that more than 85% of divorced people prefer to remain single, which confirms the low remarriage rate. Childbearing has started to decrease, especially for young singles in urban areas, due to the economic situation, with national statistics showing that unemployment in the youth community is still 16% higher. Therefore, the study concluded by confirming the hypothesis based on the results of the TFR indicators such as marriage, remarriage, divorce, separation, divorce, Kuza n'ijoro, childbearing] and abortion. The study consists of four sections, an introduction and background, a review of the literature, a description of the data and methodology, an analysis of the data, discussion results and a conclusion.

Keywords: Kuza n'ijoro, Rwanda, second demographic transition (SDT), total fertility rate (TFR)

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Authors: E. Gouya Bozorg

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The issue of ranking of sports teams, in particular soccer teams is of primary importance in the professional sports. However, it is still based on classical statistics and models outside of area of mathematics. Rigorous mathematics and then statistics despite the expectation held of them have not been able to effectively engage in the issue of ranking. It is something that requires serious pathology. The purpose of this study is to change the approach to get closer to mathematics proper for using in the ranking. We recommend using theoretical mathematics as a good option because it can hermeneutically obtain the theoretical concepts and criteria needful for the ranking from everyday language of a League. We have proposed a framework that puts the issue of ranking into a new space that we have applied in soccer as a case study. This is an experimental and theoretical study on the issue of ranking in a professional soccer league based on theoretical mathematics, followed by theoretical statistics. First, we showed the theoretical definition of constant number Є = 1.33 or ‘golden number’ of a soccer league. Then, we have defined the ‘efficiency of a team’ by this number and formula of μ = (Pts / (k.Є)) – 1, in which Pts is a point obtained by a team in k number of games played. Moreover, K.Є index has been used to show the theoretical median line in the league table and to compare top teams and bottom teams. Theoretical coefficient of σ= 1 / (1+ (Ptx / Ptxn)) has also been defined that in every match between the teams x, xn, with respect to the ability of a team and the points of both of them Ptx, Ptxn, and it gives a performance point resulting in a special ranking for the League. And it has been useful particularly in evaluating the performance of weaker teams. The current theory has been examined for the statistical data of 4 major European Leagues during the period of 1998-2014. Results of this study showed that the issue of ranking is dependent on appropriate theoretical indicators of a League. These indicators allowed us to find different forms of ranking of teams in a league including the ‘special table’ of a league. Furthermore, on this basis the issue of a record of team has been revised and amended. In addition, the theory of ranking can be used to compare and classify the different leagues and tournaments. Experimental results obtained from archival statistics of major professional leagues in the world in the past two decades have confirmed the theory. This topic introduces a new theory for ranking of a soccer league. Moreover, this theory can be used to compare different leagues and tournaments.

Keywords: efficiency of a team, ranking, special table, theoretical mathematic

Procedia PDF Downloads 401

Authors: Iqbal Pramukti, Mamat Lukman, Hasniatisari Harun, Kusman Ibrahim

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Introduction: People living with HIV had a higher risk of osteoporotic fracture than the general population. The purpose of this study was to predict the 10-year risk of fracture among people living with HIV (PLWH) using FRAX™ and to identify characteristics related to the fracture risk. Methodology: This study consisted of 75 subjects. The ten-year probability of major osteoporotic fractures (MOF) and hip fractures was assessed using the FRAX™ algorithm. A cross-tabulation was used to identify the participant’s characteristics related to fracture risk. Results: The overall mean 10-year probability of fracture was 2.4% (1.7) for MOF and 0.4% (0.3) for hip fractures. For MOF score, participants with parents’ hip fracture history, smoking behavior and glucocorticoid use showed a higher MOF score than those who were not (3.1 vs. 2.5; 4.6 vs 2.5; and 3.4 vs 2.5, respectively). For HF score, participants with parents’ hip fracture history, smoking behavior and glucocorticoid use also showed a higher HF score than those who were not (0.5 vs. 0.3; 0.8 vs. 0.3; and 0.5 vs. 0.3, respectively). Conclusions: The 10-year risk of fracture was higher among PLWH with several factors, including the parent’s hip. Fracture history, smoking behavior and glucocorticoid used. Further analysis on determining factors using multivariate regression analysis with a larger sample size is required to confirm the factors associated with the high fracture risk.

Keywords: HIV, PLWH, osteoporotic fractures, hip fractures, 10-year risk of fracture, FRAX

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Authors: I. M. L. Nadeesha Jayaweera, Adao Alex Trindade

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In choosing a candidate model in likelihood-based modeling via an information criterion, the practitioner is often faced with the difficult task of deciding just how far up the ranked list to look. Motivated by this pragmatic necessity, we construct an uncertainty band for a generalized (model selection) information criterion (GIC), defined as a criterion for which the limit in probability is identical to that of the normalized log-likelihood. This includes common special cases such as AIC & BIC. The method starts from the asymptotic normality of the GIC for the joint distribution of the candidate models in an independent and identically distributed (IID) data framework and proceeds by deriving the (asymptotically) exact distribution of the minimum. The calculation of an upper quantile for its distribution then involves the computation of multivariate Gaussian integrals, which is amenable to efficient implementation via the R package "mvtnorm". The performance of the methodology is tested on simulated data by checking the coverage probability of nominal upper quantiles and compared to the bootstrap. Both methods give coverages close to nominal for large samples, but the bootstrap is two orders of magnitude slower. The methodology is subsequently extended to two other commonly used model structures: regression and time series. In the regression case, we derive the corresponding asymptotically exact distribution of the minimum GIC invoking Lindeberg-Feller type conditions for triangular arrays and are thus able to similarly calculate upper quantiles for its distribution via multivariate Gaussian integration. The bootstrap once again provides a default competing procedure, and we find that similar comparison performance metrics hold as for the IID case. The time series case is complicated by far more intricate asymptotic regime for the joint distribution of the model GIC statistics. Under a Gaussian likelihood, the default in most packages, one needs to derive the limiting distribution of a normalized quadratic form for a realization from a stationary series. Under conditions on the process satisfied by ARMA models, a multivariate normal limit is once again achieved. The bootstrap can, however, be employed for its computation, whence we are once again in the multivariate Gaussian integration paradigm for upper quantile evaluation. Comparisons of this bootstrap-aided semi-exact method with the full-blown bootstrap once again reveal a similar performance but faster computation speeds. One of the most difficult problems in contemporary statistical methodological research is to be able to account for the extra variability introduced by model selection uncertainty, the so-called post-model selection inference (PMSI). We explore ways in which the GIC uncertainty band can be inverted to make inferences on the parameters. This is being attempted in the IID case by pivoting the CDF of the asymptotically exact distribution of the minimum GIC. For inference one parameter at a time and a small number of candidate models, this works well, whence the attained PMSI confidence intervals are wider than the MLE-based Wald, as expected.

Keywords: model selection inference, generalized information criteria, post model selection, Asymptotic Theory

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Authors: Abdullahi Yahaya Musa, Harun Rann Bakari

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The study examined the determinants of food security among households in Maiduguri, Metropolis, Borno State, Nigeria. The objectives of the study are to: examine the determinants of food security among households; identify the coping strategies employed by food-insecure households in Maiduguri, Metropolis, Borno State, Nigeria. The population of the study is 843,964 respondents out of which 400 respondents were sampled. The study used a self-developed questionnaire to collect data from four hundred (400) respondents. Four hundred (400) copies of questionnaires were administered and all were retrieved, making 100% return rate. The study employed descriptive and inferential statistics for data analysis. Descriptive statistics (frequency counts and percentages) was used to analyze the socio-economic characteristics of the respondents and objective four, while inferential statistics (logit regression analysis) was used to analyze one. Four hundred (400) copies of questionnaires were administered and all the four hundred (400) were retrieved, making a 100% return rate. The results were presented in tables and discussed according to the research objectives. The study revealed that HHA, HHE, HHSZ, HHSX, HHAS, HHI, HHFS, HHFE, HHAC and HHCDR were the determinants of food security in Maiduguri Metropolis. Relying on less preferred foods, purchasing food on credit, limiting food intake to ensure children get enough, borrowing money to buy foodstuffs, relying on help from relatives or friends outside the household, adult family members skipping or reducing a meal because of insufficient finances and ration money to household members to buy street food were the coping strategies employed by food-insecure households in Maiduguri metropolis. The study recommended that Nigeria Government should intensify the fight against the Boko haram insurgency. This will put an end to Boko Haram Insurgency and enable farmers to return to farming in Borno state.

Keywords: internally displaced persons, food security, coping strategies, descriptive statistics, logistics regression model, odd ratio

Procedia PDF Downloads 123

Authors: Habte Tadesse Likassa, Bacha Edosa

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Customer’s satisfaction was very important thing that is required for the existence of banks to be more productive and success in any organization and business area. The main goal of the study is assessing and identifying factors that influence customer’s satisfaction in West Shoa Zone of Commercial Bank of Ethiopia (Holeta, Ginchi, Ambo, Gedo and Bako). Stratified random sampling procedure was used in the study and by using simple random sampling (lottery method) 520 customers were drawn from the target population. By using Probability Proportional Size Techniques sample size for each branch of banks were allocated. Both descriptive and inferential statistics methods were used in the study. A binary logistic regression model was fitted to see the significance of factors affecting customer’s satisfaction in this study. SPSS statistical package was used for data analysis. The result of the study reveals that the overall level of customer’s satisfaction in the study area is low (38.85%) as compared those who were not satisfied (61.15%). The result of study showed that all most all factors included in the study were significantly associated with customer’s satisfaction. Therefore, it can be concluded that based on the comparison of branches on their customers satisfaction by using odd ratio customers who were using Ambo and Bako are less satisfied as compared to customers who were in Holeta branch. Additionally, customers who were in Ginchi and Gedo were more satisfied than that of customers who were in Holeta. Since the level of customers satisfaction was low in the study area, it is more advisable and recommended for concerned body works cooperatively more in maximizing satisfaction of their customers.

Keywords: customers, satisfaction, binary logistic, complain handling process, waiting time

Procedia PDF Downloads 444

Authors: Lejla Mušić

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Gender dimension of migration analyzes the intersection in between the world statistics on male and female migrations, around the world, involving the questions of youth migrations. Comparative analyses of world migration statistics as methodology offer the insight into the position of women in labor market around world. There are different forms of youth debris in contemporary world. The main problems are illegal migration, feminization of poverty, kidnapping the girls in Nigeria, femicides in Juarez and Mexico. Illegal migrations involve forced labor, rape and prostitution. Transgender youth share ideas through the online media (anti-bullying videos) and develop their own styles such as anarcho-punk, rave, or rock. Therefore, the stronger gender equality laws and laws for protection of women on work should be enforced.

Keywords: hyperfeminisation, rape, gangs of girls, rent boys masculinities, Varoç in Istanbul, forced labor, rape and prostitution, illegal emigrations

Procedia PDF Downloads 241