Search results for: automation impact regression

Authors: Apollinaire Barme, Simon Tamayo, Arthur Gaudron

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This paper presents a statistical approach to identify explanatory variables linearly related to e-commerce sales. The proposed methodology allows specifying a regression model in order to quantify the relevance between openly available data (economic and demographic) and national e-commerce sales. The proposed methodology consists in collecting data, preselecting input variables, performing regressions for choosing variables and models, testing and validating. The usefulness of the proposed approach is twofold: on the one hand, it allows identifying the variables that influence e- commerce sales with an accessible approach. And on the other hand, it can be used to model future sales from the input variables. Results show that e-commerce is linearly dependent on 11 economic and demographic indicators.

Keywords: e-commerce, statistical modeling, regression, empirical research

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Authors: Simon Strande Henriksen

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When a city and country decide to undertake an Olympic Games, they do so with the notion that hosting the Olympics will provide direct financial benefits to the city, country, and national companies. Like many activities, the Olympic Games tend to be more popular when it is warm, and the athletes are known, and therefore this paper will only focus on the two latest Olympic Summer Games. Cities and countries continue to invest billions of dollars in infrastructure to secure the role of being Olympic hosts. The multiple investments expect to provide both economic growth and a lasting legacy for the citizens. This study aims to determine whether host country companies experience superior economic impact from the Olympics. Building on existing work within the Olympic field of research, it asks: Do companies in host countries of the Olympic Summer Games experience a superior increase in operating revenue and return on assets compared to other comparable countries? In this context, comparable countries are the two candidates following the host city in the bidding procedure. Based on methods used by scholars, a panel data regression was conducted on revenue growth rate and return on assets, to determine if host country companies see a positive relation with hosting the Olympic Games. Combined with an analysis of motivation behind hosting the Olympics, the regression showed no significant positive relations across all analyses, besides in one instance. Indications of a relationship between company performance and economic motivation were found to be present. With the results indicating a limited effect on company growth, it is recommended that prospective host cities and countries carefully consider possible implications the role of being an Olympic host might have on national companies.

Keywords: cross-country analysis, mega-event, multiple regression, quantitative analysis

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Authors: Koffi Sodokin

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Financing microstructures are increasingly seen as a means of financial inclusion and improving overall well-being in developing countries. In practice, digital transformation in finance can accelerate the optimal functioning of financing microstructures, such as access by households to microfinance and microinsurance. Large households' access to finance can lead to a reduction in income inequality and an overall improvement in well-being. This paper explores the impact of access to digital finance and financing microstructures on household well-being and the reduction of income inequality. To this end, we use the propensity score matching, the double difference, and the smooth instrumental quantile regression as estimation methods with two periods of survey data. The paper uses the FinScope consumer data (2016) and the Harmonized Living Standards Measurement Study (2018) from Togo in a comparative perspective. The results indicate that access to digital finance, as a cultural game changer, and to financing microstructures improves overall household well-being and contributes significantly to reducing income inequality.

Keywords: financing microstructure, microinsurance, microfinance, digital finance, well-being, income inequality

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Authors: Ange Meghane Hakizimana, Landry Ndikuriyo

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Retention of employees in the hospitality industry is a recurrent agenda in the organization involving all the combined efforts to maintain the best available laborer. The general objective of this research is to assess the impact of effective employee retention strategies on the success of the hotel industry at Galileo Hotel, Huye District in Rwanda, for the period of 2019-2021. Herzberg Two Factor Theory and Equity Theory were used. The study adopted a descriptive research design. Descriptive research design allowed us to study the elements in their natural form without making any alterations to them. Secondary data and primary data and the data collected were sorted and entered into the statistical packages for social sciences for analysis (SPSS) version 26. Frequencies, descriptive statistics and percentages were used to analyze and establish extent to which employee retention strategies impact the success of the hotel industry of Rwanda and this was analyzed using regression and correlation analysis. The results revealed that employee training and development had an influence of 24.8% on the success of the hotel industry in Rwanda. According to the results of our study, the employee reward system contributes 20.7% to the success of the hotel industry in Rwanda, the value of t is 3.475 and this is greater than the standard t value score of 1.96, p-value is 0.002. Therefore the employee reward system has a great positive impact on the success of the hotel industry in Rwanda. The results also show that 15.7% of the success of the hospitality industry in Rwanda is due to the work environment of employees. With a t-value of 4.384 and a p-value of 0.000, the above statistics show a positive impact of the employees' working environment on success of the hospitality industry in Rwanda. A priority to the retention of their employees should be given by the hotel industry and its managers because it has already been proven that it is an effective approach to offering good customer service. In addition, employee retention reduces expenses associated with employee recruitment and turnover.

Keywords: success, hotel industry, training and development, employee reward system, employee work environment

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Authors: Sandipika Gupta

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Objective: Due to admirably low 30-day mortality rates for paediatric cardiac surgery, it is now pertinent to turn towards more intermediate-length outcomes such as morbidities closely associated with these surgeries. One such morbidity, major adverse events (MAE) comprises a group of adverse outcomes associated with paediatric cardiac surgery (e.g. cardiac arrest, major haemorrhage). Methods: This is a retrospective study that analysed the incidence and impact of MAE which was the primary outcome in the UK population. The data was collected in 5 centres between October 2015 and June 2017, amassing 3090 surgical episodes. The incidence and risk factors for MAE, were assessed through descriptive statistical analyses and multivariate logistic regression. The secondary outcomes of life status at 6 months and the length of hospital stay were also evaluated to understand the impact of MAE on patients. Results: Out of 3090 episodes, 134 (4.3%) had a postoperative MAE. The majority of the episodes were in: neonates (47%, P<0.001), high-risk cardiac diagnosis groups (20.1%, P<0.001), episodes with longer 5mes on the bypass (72.4%, P<0.001) and urgent surgeries (57.9%, P<0.001). Episodes reporting MAE also reported longer lengths of stay in hospital (29 days vs 9 days, P<0.001). Furthermore, patients experiencing MAE were at a higher risk of mortality at the 6-month life status check (mortality rates: 29.2% vs 2%, P<0.001).Conclusions: Key risk factors were identified. An important negative impact of MAE was found for patients. The identified risk factors could be used to profile and flag at-risk patients. Monitoring of MAE rates and closer investigation into the care pathway before and after individual MAEs in children’s heart units may lead to a reduction in these terrible events.

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Authors: Julide Yildirim, Nadir Ocal

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Even though there are many studies investigating the extent and determinants of poverty, there is paucity of research investigating the issue of energy poverty in Turkey. The aim of this paper is threefold: First to investigate the extend of energy poverty in Turkey by using Household Budget Survey datasets belonging to 2005 - 2016 period. Second, to examine the risk factors for energy poverty. Finally, to assess the impact of social assistance program participation on energy poverty. Existing literature employs alternative methods to measure energy poverty. In this study energy poverty is measured by employing expenditure approach, where people are considered as energy poor if they disburse more than 10 per cent of their income to meet their energy requirements. Empirical results indicate that energy poverty rate is around 20 per cent during the time period under consideration. Since Household Budget Survey panel data is not available for 2005 - 2016 period, a pseudo panel has been constructed. Panel logistic regression method is utilized to determine the risk factors for energy poverty. The empirical results demonstrate that there is a statistically significant impact of work status and education level on energy poverty likelihood. In the final part of the paper the impact of social transfers on energy poverty has been examined by utilizing panel biprobit model, where social transfer participation and energy poverty incidences are jointly modeled. The empirical findings indicate that social transfer program participation reduces energy poverty. The negative association between energy poverty and social transfer program participation is more pronounced in urban areas compared with the rural areas.

Keywords: energy poverty, social transfers, panel data models, Turkey

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Authors: Hepinda Fajari Nuharini, Sugiarti A. Musabiq

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Background: Various and continuous pressures that exceed individual resources can cause first-year undergraduate college students to experience psychological distress. Psychological distress can occur when individuals use rumination as cognitive coping strategies. Rumination is one of the cognitive coping strategies that can be used by individuals to respond to psychological distress that causes individuals to think about the causes and consequences of events that have occurred. Rumination had two subtypes, such as brooding and reflective. Therefore, the purpose of this study was determining the role of brooding and reflective as subtypes of rumination toward psychological distress in University of Indonesia first-year undergraduate students. Methods: Participants of this study were 403 University of Indonesia first-year undergraduate students aged between 18 and 21 years old. Psychological distress measured using self reporting questionnaire (SRQ-20) and brooding and reflective as subtypes of rumination measured using Ruminative Response Scale - Short Version (RRS - Short Version). Results: Binary logistic regression analyses showed that 22.8% of the variation in psychological distress could be explained by the brooding and reflective as subtypes of rumination, while 77.2% of the variation in psychological distress could be explained by other factors (Nagelkerke R² = 0,228). The results of the binary logistic regression analysis also showed rumination subtype brooding is a significant predictor of psychological distress (b = 0,306; p < 0.05), whereas rumination subtype reflective is not a significant predictor of psychological distress (b = 0,073; p > 0.05). Conclusion: The findings of this study showed a positive relationship between brooding and psychological distress indicates that a higher level of brooding will predict higher psychological distress. Meanwhile, a negative relationship between reflective and psychological distress indicates a higher level of reflective will predict lower psychological distress in University of Indonesia first-year undergraduate students. Added Values: The psychological distress among first-year undergraduate students would then have an impact on student academic performance. Therefore, the results of this study can be used as a reference for making preventive action to reduce the percentage and impact of psychological distress among first-year undergraduate students.

Keywords: brooding as subtypes of rumination, first-year undergraduate students, psychological distress, reflective as subtypes of rumination

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Authors: Heba Abdelmotaal

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This paper explores the impact of the extent of a company's environmental, social, and governance (ESG) disclosure on credit rating and capital structure. The analysis is based on a sample of 202 firms from the 350 FTSE firms over the period of 2008-2013. ESG disclosure score is measured using Proprietary Bloomberg score based on the extent of a company's Environmental, Social, and Governance (ESG) disclosure. The credit rating is measured by The QuiScore, which is a measure of the likelihood that a company will become bankrupt in the twelve months following the date of calculation. The Capital Structure is measured by long term debt ratio. Two hypotheses are test using panel data regression. The results suggested that the higher degree of ESG disclosure leads to better credit rating. There is significant negative relationship between ESG disclosure and the long term debit percentage. The paper includes implications for the transparency which is resulting of the ESG disclosure could support the Monitoring Function. The monitoring role of disclosure is the increasing in the transparency of the credit rating agencies, also it could affect on managers’ actions. This study provides empirical evidence on the material of ESG disclosure on credit ratings changes and the firms’ capital decision making.

Keywords: capital structure, credit rating agencies, ESG disclosure, panel data regression

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Authors: Suvimon Wajeetongratana, Prateep Wajeetongratana

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The purpose of this research will study the organizational behavior including self-efficacy, hope, optimism, and resiliency that affect to the work motivation in the Dusit workplace and the sample consisted of the production workers in a private company in Dusit area for four hundred workers with approximately 10,000 employees and in this study will provide the multiple regression analysis was used to analyze the questionnaire survey data. The results of the analysis indicate the latent core confidence factor derived from the four components of self-efficacy, hope, optimism, and resiliency provided a significant positive impact on performance. The impact of the integrated latent core confidence factor was, in fact, more effective than derived from any one individual component, as well as any core trait-like self-evaluations such as self-esteem, general efficacy, internal locus of control, and emotional stability.

Keywords: firm performance effectiveness, organizational behavior, work motivation, Dusit workplace

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Authors: Dileep Kumar Gupta, Rajendra Prasad, Pradeep Kumar, Varun Narayan Mishra, Ajeet Kumar Vishwakarma, Prashant K. Srivastava

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An approach was evaluated for the retrieval of soil moisture of bare soil surface using bistatic scatterometer data in the angular range of 200 to 700 at VV- and HH- polarization. The microwave data was acquired by specially designed X-band (10 GHz) bistatic scatterometer. The linear regression analysis was done between scattering coefficients and soil moisture content to select the suitable incidence angle for retrieval of soil moisture content. The 250 incidence angle was found more suitable. The support vector regression analysis was used to approximate the function described by the input-output relationship between the scattering coefficient and corresponding measured values of the soil moisture content. The performance of support vector regression algorithm was evaluated by comparing the observed and the estimated soil moisture content by statistical performance indices %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE). The values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 2.9451, 1.0986, and 0.9214, respectively at HH-polarization. At VV- polarization, the values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 3.6186, 0.9373, and 0.9428, respectively.

Keywords: bistatic scatterometer, soil moisture, support vector regression, RMSE, %Bias, NSE

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Authors: Uyen Tran Tu

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The decision on capital structure is one of the most important and sophisticated decisions in financial management in order to improve firm performance. This article would study the two-way impact between capital structure and firm performance. The study use EVIEWS 6.0 software to determine a two-way relationship between the capital structure and firm performance based on two-stage regression (2SLS - Two-Stage Least Squares). The findings are: capital structure has the opposite effect on the business efficiency and vice versa, factors that effect on business efficiency include Size and Opportunities. Factors effects on the capital structure are size; liquidity. These factors also affect the ratio of capital structure (total debt/ total asset) of companies. In particular, liquidity has the opposite effect; and the size of the business has the same impact. The results of the study are in line with the theory and empirical studies presented, and the results of the study are unchanged for all three years 2015-2017.

Keywords: capital structure, firm performance, factors, two-way relationship

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Authors: Jonathan Iworiso

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Forecasting the equity premium out-of-sample is a major concern to researchers in finance and emerging markets. The quest for a superior model that can forecast the equity premium with significant economic gains has resulted in several controversies on the choice of variables and suitable techniques among scholars. This research focuses mainly on the application of Regression Training (RT) techniques to forecast monthly equity premium out-of-sample recursively with an expanding window method. A broad category of sophisticated regression models involving model complexity was employed. The RT models include Ridge, Forward-Backward (FOBA) Ridge, Least Absolute Shrinkage and Selection Operator (LASSO), Relaxed LASSO, Elastic Net, and Least Angle Regression were trained and used to forecast the equity premium out-of-sample. In this study, the empirical investigation of the RT models demonstrates significant evidence of equity premium predictability both statistically and economically relative to the benchmark historical average, delivering significant utility gains. They seek to provide meaningful economic information on mean-variance portfolio investment for investors who are timing the market to earn future gains at minimal risk. Thus, the forecasting models appeared to guarantee an investor in a market setting who optimally reallocates a monthly portfolio between equities and risk-free treasury bills using equity premium forecasts at minimal risk.

Keywords: regression training, out-of-sample forecasts, expanding window, statistical predictability, economic significance, utility gains

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Authors: Leo Carlo B. Rondina

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Self-image is an important factor to improve the self-esteem of the personnel. The purpose of the study is to determine the self-image of the police. The respondents were the 503 policemen assigned in different Police Station in Davao City, and they were chosen with the used of random sampling. With the used of Exploratory Factor Analysis (EFA), latent construct variables of police image were identified as follows; professionalism, obedience, morality and justice and fairness. Further, ordinal regression indicates statistical characteristics on ages 21-40 which means the age of the respondent statistically improves self-image.

Keywords: police image, exploratory factor analysis, ordinal regression, Galatea effect

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Authors: Mehdi Moeinaddini, Zohreh Asadi-Shekari, Muhammad Zaly Shah, Amran Hamzah

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Currently, planners try to have more green travel options to decrease economic, social and environmental problems. Therefore, this study tries to find significant urban travel factors to be used to increase the usage of alternative urban travel modes. This paper attempts to identify the relationship between prominent urban mobility indicators and daily trips by public transport in 30 cities from various parts of the world. Different travel modes, infrastructures and cost indicators were evaluated in this research as mobility indicators. The results of multi-linear regression analysis indicate that there is a significant relationship between mobility indicators and the daily usage of public transport.

Keywords: green travel modes, urban travel indicators, daily trips by public transport, multi-linear regression analysis

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Authors: A. Ishag Mohamed, A. A. Rabah

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The objective of this research is to develop a generalized correlation for the prediction of thermal conductivity of n-Alkanes and Alkenes. There is a minority of research and lack of correlation for thermal conductivity of liquids in the open literature. The available experimental data are collected covering the groups of n-Alkanes and Alkenes.The data were assumed to correlate to temperature using Filippov correlation. Nonparametric regression of Grace Algorithm was used to develop the generalized correlation model. A spread sheet program based on Microsoft Excel was used to plot and calculate the value of the coefficients. The results obtained were compared with the data that found in Perry's Chemical Engineering Hand Book. The experimental data correlated to the temperature ranged "between" 273.15 to 673.15 K, with R2 = 0.99.The developed correlation reproduced experimental data that which were not included in regression with absolute average percent deviation (AAPD) of less than 7 %. Thus the spread sheet was quite accurate which produces reliable data.

Keywords: N-Alkanes, N-Alkenes, nonparametric, regression

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Authors: Elizabeth Malebogo Mosepele

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Road transport has become increasingly common in the world; people rely on road networks for transportation purpose on a daily basis. However, environmental impact of roads on surrounding landscapes extends their potential effects even further. This study investigates the impact of road network on natural vegetation. The study will provide baseline knowledge regarding roadside vegetation and would be helpful in future for conservation of biodiversity along the road verges and improvements of road verges. The general hypothesis of this study is that the amount and condition of road side vegetation could be explained by road network conditions. Remote sensing techniques were used to analyze vegetation conditions. Landsat 8 OLI image was used to assess vegetation cover condition. NDVI image was generated and used as a base from which land cover classes were extracted, comprising four categories viz. healthy vegetation, degraded vegetation, bare surface, and water. The classification of the image was achieved using the supervised classification technique. Road networks were digitized from Google Earth. For observed data, transect based quadrats of 50*50 m were conducted next to road segments for vegetation assessment. Vegetation condition was related to road network, with the multinomial logistic regression confirming a significant relationship between vegetation condition and road network. The null hypothesis formulated was that 'there is no variation in vegetation condition as we move away from the road.' Analysis of vegetation condition revealed degraded vegetation within close proximity of a road segment and healthy vegetation as the distance increase away from the road. The Chi Squared value was compared with critical value of 3.84, at the significance level of 0.05 to determine the significance of relationship. Given that the Chi squared value was 395, 5004, the null hypothesis was therefore rejected; there is significant variation in vegetation the distance increases away from the road. The conclusion is that the road network plays an important role in the condition of vegetation.

Keywords: Chi squared, geographic information system, multinomial logistic regression, remote sensing, road side vegetation

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Authors: Rahmat Irawan, Mundhir Hanifsyam Harahap, Andar Ristabet Hesda

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As a public sector organization in Indonesia, Directorate General of State Asset Management (DGSAM) which is a unit under the Ministry of Finance of The Republic of Indonesia, has many constraints in managing its employees. While private organizations are able to conduct a human resource management as the best practice, DGSAM is limited by many regulations, especially about punishment and lay off policy for under-performance employees. Therefore, since 2015, DGSAM tries to implement a new and uncommon approach considering employees’ preference to encourage the motivation and performance of employees. DGSAM’s employees may propose the job places, and DGSAM considers them in deciding employees deployment. This study tries to determine the impact of preference-based approach toward employees’ satisfaction and organizational performance. This study uses quantitative approaches by regression analysis to measure the impact of deployment toward satisfaction of deployed employees and performance change of related units in DGSAM. The result of this study shows that preference-based approach significantly improves employees’ satisfaction and performance of related units as well. Based on the results of this study, it can be suggested that the approach is able to be implemented in the wider scope of the Ministry of Finance of The Republic of Indonesia and whole public sector organization in Indonesia. However, this study only focuses on short term measurement, so it is suggested to do further study to analyze the long-term impact.

Keywords: employee deployment, employee satisfaction, human resource management, organizational performance, preference-based approach

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Authors: Prabhashini Wijewantha

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This study looks at the impact of protean career attitude of employees on their career success and next it looks at the mediation effect of career insights on the above relationship. Career success is defined as the accomplishment of desirable work related outcomes at any point in person’s work experiences over time and it comprises of two sub variables, namely, career satisfaction and perceived employability. Protean career attitude was measured using the eight items from the Self Directedness subscale of the Protean Career Attitude scale developed by Briscoe and Hall, where as career satisfaction was measured by the three item scale developed by Martine, Eddleston, and Veiga. Perceived employability was also evaluated using three items and career insight was measured using fourteen items that were adapted and used by De Vos and Soens. Data were collected from a sample of 300 mid career executives in Sri Lanka deploying the survey strategy and data were analyzed using the SPSS and AMOS software version 20.0. A preliminary analysis of data was initially performed where data were screened and reliability and validity were ensured. Next a simple regression analysis was performed to test the direct impact of protean career attitude on career success and the hypothesis was supported. The Baron and Kenney’s four steps, three regressions approach for mediator testing was used to calculate the mediation effect of career insight on the above relationship and a partial mediation was supported by the data. Finally theoretical and practical implications are discussed.

Keywords: career success, career insight, mid career MBAs, protean career attitude

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Authors: Lakhoua Najeh

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Aims of the work: After a presentation of the functionality of an example of a mechatronic system which is a paint mixer system, we present the concepts of modeling and safe operation. This paper briefly discusses how to model and protect the functioning of a mechatronic system relying mainly on functional analysis and safe operation techniques. Methods: For the study of an example of a mechatronic system, we use methods for external functional analysis that illustrate the relationships between a mechatronic system and its external environment. Thus, we present the Safe-Structured Analysis Design Technique method (Safe-SADT) which allows the representation of a mechatronic system. A model of operating safety and automation is proposed. This model enables us to use a functional analysis technique of the mechatronic system based on the GRAFCET (Graphe Fonctionnel de Commande des Etapes et Transitions: Step Transition Function Chart) method; study of the safe operation of the mechatronic system based on the Safe-SADT method; automation of the mechatronic system based on a software tool. Results: The expected results are to propose a model and safe operation of a mechatronic system. This methodology enables us to analyze the relevance of the different models based on Safe-SADT and GRAFCET in relation to the control and monitoring functions and to study the means allowing exploiting their synergy. Conclusion: In order to propose a general model of a mechatronic system, a model of analysis, safety operation and automation of a mechatronic system has been developed. This is how we propose to validate this methodology through a case study of a paint mixer system.

Keywords: mechatronic systems, system modeling, safe operation, Safe-SADT

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Authors: Tsegahun Milkesa

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This study investigates the implementation of Power-Line Communications (PLC) as a sustainable solution for home automation in Ethiopia. With the country's growing technological landscape and the quest for efficient energy use, this research explores the potential of PLC to facilitate smart home systems, aiming to enhance connectivity and energy management. The primary objective is to assess the feasibility and effectiveness of PLC in Ethiopian residences, considering factors such as infrastructure compatibility, reliability, and scalability. By analyzing existing PLC technologies and their adaptability to local contexts, this study aims to propose optimized solutions tailored to the Ethiopian environment. The research methodology involves a combination of literature review, field surveys, and experimental setups to evaluate PLC's performance in transmitting data and controlling various home appliances. Additionally, socioeconomic implications, including affordability and accessibility, are examined to ensure the technology's inclusivity in diverse Ethiopian households. The findings will contribute insights into the viability of PLC for sustainable connectivity in Ethiopian homes, shedding light on its potential to revolutionize energy-efficient and interconnected living spaces. Ultimately, this study seeks to pave the way for accessible and eco-friendly smart home solutions in Ethiopia, aligning with the nation's aspirations for technological advancement and sustainability.

Keywords: sustainable connectivity, power-line communications (PLC), home automation, Ethiopia, smart homes, energy efficiency, connectivity solutions, infrastructure development, sustainable living

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Authors: S. Bangphan, P. Bangphan, C. Ketsombun, T. Sammana

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Optimization of response surface methodology (RSM) was employed to study the effects of three factor (rubber of clearance, spindle of speed, and rice of moisture) in brown rice peeling machine of the optimal good rice yield (99.67, average of three repeats). The optimized composition derived from RSM regression was analyzed using Regression analysis and Analysis of Variance (ANOVA). At a significant level α=0.05, the values of Regression coefficient, R2 adjust were 96.55% and standard deviation were 1.05056. The independent variables are initial rubber of clearance, spindle of speed and rice of moisture parameters namely. The investigating responses are final rubber clearance, spindle of speed and moisture of rice.

Keywords: brown rice, response surface methodology (RSM), peeling machine, optimization, paddy husker

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Authors: A. Mostafa

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This paper presents a numerical study on determination of ballistic limit velocity (V₅₀) of stainless steel 304 (SS 304) used in manufacturing security screens. The simulated ballistic impact tests were conducted on clamped sheets with different thicknesses using ABAQUS/Explicit nonlinear finite element (FE) package. The ballistic limit velocity was determined using three approaches, namely: numerical tests based on material properties, FE calculated residual velocities and FE calculated residual energies. Johnson-Cook plasticity and failure criterion were utilized to simulate the dynamic behaviour of the SS 304 under various strain rates, while the well-known Lambert-Jonas equation was used for the data regression for the residual velocity and energy model. Good agreement between the investigated numerical methods was achieved. Additionally, the dependence of the ballistic limit velocity on the sheet thickness was observed. The proposed approaches present viable and cost-effective assessment methods of the ballistic performance of SS 304, which will support the development of robust security screen systems.

Keywords: ballistic velocity, stainless steel, numerical approaches, security screen

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Authors: Reza Hadjiaghaie Vafaie, Sevda Givtaj

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Automation and control of biological samples and solutions at the microscale is a major advantage for biochemistry analysis and biological diagnostics. Despite the known potential of miniaturization in biochemistry and biomedical applications, comparatively little is known about fluid automation and control at the microscale. Here, we study the electric field effect inside a fluidic channel and proper electrode structures with different patterns proposed to form forward, reversal, and rotational flows inside the channel. The simulation results confirmed that the ac electro-thermal flow is efficient for the control and automation of high-conductive solutions. In this research, the fluid pumping and mixing effects were numerically studied by solving physic-coupled electric, temperature, hydrodynamic, and concentration fields inside a microchannel. From an experimental point of view, the electrode structures are deposited on a silicon substrate and bonded to a PDMS microchannel to form a microfluidic chip. The motions of fluorescent particles in pumping and mixing modes were captured by using a CCD camera. By measuring the frequency response of the fluid and exciting the electrodes with the proper voltage, the fluid motions (including pumping and mixing effects) are observed inside the channel through the CCD camera. Based on the results, there is good agreement between the experimental and simulation studies.

Keywords: microfluidic, nano/micro actuator, AC electrothermal, Reynolds number, micropump, micromixer, microfabrication, mass transfer, biomedical applications

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Authors: Habshah Midi, Mohammed A. Mohammed, Sohel Rana

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Multicollinearity occurs when two or more independent variables in a multiple linear regression model are highly correlated. The ridge regression is the commonly used method to rectify this problem. However, the ridge regression cannot handle the problem of multicollinearity which is caused by high leverage collinearity enhancing observation (HLCEO). Since high leverage points (HLPs) are responsible for inducing multicollinearity, the effect of HLPs needs to be reduced by using Generalized M estimator. The existing GM6 estimator is based on the Minimum Volume Ellipsoid (MVE) which tends to swamp some low leverage points. Hence an improvised GM (MGM) estimator is presented to improve the precision of the GM6 estimator. Numerical example and simulation study are presented to show how HLPs can cause multicollinearity. The numerical results show that our MGM estimator is the most efficient method compared to some existing methods.

Keywords: identification, high leverage points, multicollinearity, GM-estimator, DRGP, DFFITS

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Authors: Girish Chavadappanavar

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The impact of climate on agriculture could result in problems with food security and may threaten the livelihood activities upon which much of the population depends. In the present study, the development of a statistical yield forecast model has been carried out for sugarcane production over Belagavi district, Karnataka using weather variables of crop growing season and past observed yield data for the period of 1971 to 2010. The study shows that this type of statistical yield forecast model could efficiently forecast yield 5 weeks and even 10 weeks in advance of the harvest for sugarcane within an acceptable limit of error. The performance of the model in predicting yields at the district level for sugarcane crops is found quite satisfactory for both validation (2007 and 2008) as well as forecasting (2009 and 2010).In addition to the above study, the climate variability of the area has also been studied, and hence, the data series was tested for Mann Kendall Rank Statistical Test. The maximum and minimum temperatures were found to be significant with opposite trends (decreasing trend in maximum and increasing in minimum temperature), while the other three are found in significant with different trends (rainfall and evening time relative humidity with increasing trend and morning time relative humidity with decreasing trend).

Keywords: climate impact, regression analysis, yield and forecast model, sugar models

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Authors: Jong Won, Park, Sung Hyun, Kim

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The kinetic energy to pass subjected to shock and chisel reciprocating piston hydraulic power supplied by the excavator using for the purpose of crushing the rock, and roads, buildings, etc., hydraulic breakers blow. Impact frequency, efficiency measurement of the impact energy, hydraulic breakers, to demonstrate the ability of hydraulic breaker manufacturers and users to a very important item. And difficult in order to confirm the initial performance degradation in the life of the hydraulic breaker has been thought to be a problem.In this study, we measure the efficiency of hydraulic breaker, Impact energy and Impact frequency, the degradation analysis of research to predict the life.

Keywords: impact energy, impact frequency, hydraulic breaker, life prediction

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Authors: Seyed M. Khatami, H. Naderpour, R. Vahdani, R. C. Barros

Abstract:

Many previous studies have been carried out to calculate the impact force and the dissipated energy between two neighboring buildings during seismic excitation, when they collide with each other. Numerical studies are an important part of impact, which several researchers have tried to simulate the impact by using different formulas. Estimation of the impact force and the dissipated energy depends significantly on some parameters of impact. Mass of bodies, stiffness of spring, coefficient of restitution, damping ratio of dashpot and impact velocity are some known and unknown parameters to simulate the impact and measure dissipated energy during collision. Collision is usually shown by force-displacement hysteresis curve. The enclosed area of the hysteresis loop explains the dissipated energy during impact. In this paper, the effect of using different types of impact models is investigated in order to calculate the impact force. To increase the accuracy of impact model and to optimize the results of simulations, a new damping equation is assumed and is validated to get the best results of impact force and dissipated energy, which can show the accuracy of suggested equation of motion in comparison with other formulas. This relation is called "n-m". Based on mathematical relation, an initial value is selected for the mentioned coefficients and kinetic energy loss is calculated. After each simulation, kinetic energy loss and energy dissipation are compared with each other. If they are equal, selected parameters are true and, if not, the constant of parameters are modified and a new analysis is performed. Finally, two unknown parameters are suggested to estimate the impact force and calculate the dissipated energy.

Keywords: impact force, dissipated energy, kinetic energy loss, damping relation

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Authors: Abisola Akinola, Akinsulere Femi

Abstract:

The stock market has continually been a source of economic development in most developing countries. This study examined the relationship between investors’ ratio analysis and profitability of quoted companies in Nigeria using secondary data obtained from the annual reports of forty-two (42) companies. The study employed the multiple regression technique to analyze the relationship between investors’ ratio analysis (measured by dividend per share and earning per share) and profitability (measured by the return on equity). The results from the analysis show that investors’ ratio analysis, when measured by earnings per share, have a positive and significant impact on profitability. However, the study noted that investors’ ratio analysis, when measured by dividend per share, tend to have a positive impact on profitability but it is statistically insignificant. By implication, investors and other stakeholders that are interested in investing in stocks can predict the earning capacity of listed firms in the stock market.

Keywords: dividend per share, earnings per share, profitability, return on equity

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Authors: Hatim Elhag

Abstract:

Banking and Financial Service Institutions are possibly the most advanced in terms of technology adoption and use it as a key differentiator. With high levels of business process automation, maturity in the functional portfolio, straight through processing and proven technology outsourcing benefits, Banking sector stand to benefit significantly from Cloud computing capabilities. Additionally, with complex Compliance and Regulatory policies, combined with expansive products and geography coverage, the business impact is even greater. While the benefits are exponential, there are also significant challenges in adopting this model– including Legal, Security, Performance, Reliability, Transformation complexity, Operating control and Governance and most importantly proof for the promised cost benefits. However, new architecture designed should be implemented to align this approach.

Keywords: security, cloud, banking sector, cloud computing

Procedia PDF Downloads 475

Authors: S. M. Ashikur Elahee, Md. Zahidur Rahman, Md. Shofiqur Rahman

Abstract:

This study evaluated the impact of different water interventions under WASH program on access of household's to safe drinking water. Following survey method, the study was carried out in two Upazila of South-west coastal region of Bangladesh namely Koyra from Khulna and Shymnagar from Satkhira district. Being an explanatory study, a total of 200 household's selected applying random sampling technique were interviewed using a structured interview schedule. The predicted probability suggests that around 62 percent household's are out of year-round access to safe drinking water whereby, only 25 percent household's have access at SPHERE standard (913 Liters/per person/per year). Besides, majority (78 percent) of the household's have not accessed at both indicators simultaneously. The distance from household residence to the water source varies from 0 to 25 kilometer with an average distance of 2.03 kilometers. The study also reveals that the increase in monthly income around BDT 1,000 leads to additional 11 liters (coefficient 0.01 at p < 0.1) consumption of safe drinking water for a person/year. As expected, lining up time has significant negative relationship with dependent variables i.e., for higher lining up time, the probability of getting access for both SPHERE standard and year round access variables becomes lower. According to ordinary least square (OLS) regression results, water consumption decreases at 93 liters for per person/year of a household if one member is added to that household. Regarding water consumption intensity, ordered logistic regression (OLR) model shows that one-minute increase of lining up time for water collection tends to reduce water consumption intensity. On the other hand, as per OLS regression results, for one-minute increase of lining up time, the water consumption decreases by around 8 liters. Considering access to Deep Tube Well (DTW) as a reference dummy, in OLR, the household under Pond Sand Filter (PSF), Shallow Tube Well (STW), Reverse Osmosis (RO) and Rainwater Harvester System (RWHS) are respectively 37 percent, 29 percent, 61 percent and 27 percent less likely to ensure year round access of water consumption. In line of health impact, different type of water born diseases like diarrhea, cholera, and typhoid are common among the coastal community caused by microbial impurities i.e., Bacteria, Protozoa. High turbidity and TDS in pond water caused by reduction of water depth, presence of suspended particle and inorganic salt stimulate the growth of bacteria, protozoa, and algae causes affecting health hazard. Meanwhile, excessive growth of Algae in pond water caused by excessive nitrate in drinking water adversely effects on child health. In lieu of ensuring access at SPHERE standard, we need to increase the number of water interventions at reasonable distance, preferably a half kilometer away from the dwelling place, ensuring community peoples involved with its installation process where collectively owned water intervention is found more effective than privately owned. In addition, a demand-responsive approach to supply of piped water should be adopted to allow consumer demand to guide investment in domestic water supply in future.

Keywords: access, impact, safe drinking water, Sphere standard, water interventions

Procedia PDF Downloads 194