Search results for: moderating variables

Authors: Shymaa S. Zaher, Hesham M. Abd El-Fatah, Dina M. Ali

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Burullus Lagoon is the second largest lake, along the Mediterranean seashore. It exposed to over nutrient enrichment from fish farming and agricultural drainage wastes. This study assesses the present status phytoplankton response to different flow events, including domestic, agricultural, industrial, and fish farms discharge in the three main sectors of Burullus Lagoon, to focus on the influence of environmental variables on phytoplankton species composition inhabiting the Lagoon. Twelve sites representing the eastern, central, and western basin were selected during winter and summer 2018. Among the most abundant group, Chlorophyceae came in the first rank by 37.9% of the total phytoplankton densities, Bacillariophyceae (29.31%), Cyanophyceae (20.7%), Euglenophyceae (8.63%) and Dinophyceae (3.4%). Cyclotella menenghiana was the most abundant diatoms, while Scenedesmus quadricauda, S. acuminatus, and S. bijuga were highly recorded nearby the drains (in the middle sector). Phytoplankton in Burullus Lagoon attained the lowest values during the winter season and the highest ones during the summer season. The total count of phytoplankton in the middle and western basin of the lake was higher than that of the eastern part. Excessive use of chemical fertilizers, pesticides, and washing out of nutrients loaded to the drainage water, leading to a significant pronounced decrease in community composition and standing crop of phytoplankton in Burullus Lake from year to year, hold the danger of shifting the lagoon ecosystem.

Keywords: Burullus Lagoon, environmental variables, phytoplankton, water pollution

Procedia PDF Downloads 124

Authors: Imalka Wasana Rathnayaka, Rasheda Khanam, Mohammad Mafizur Rahman

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TheCOVID-19 pandemic has created unprecedented challenges to both the health and economic states in countries around the world. This study aims to evaluate the effectiveness of governments' decisions to mitigate the risks of COVID-19 through proposing policy directions to reduce its magnitude. The study is motivated by the ongoing coronavirus outbreaks and comprehensive policy responses taken by countries to mitigate the spread of COVID-19 and reduce death rates. This study contributes to filling the knowledge by exploiting the long-term efficacy of extensive plans of governments. This study employs a Panel autoregressive distributed lag (ARDL) framework. The panels incorporate both a significant number of variables and fortnightly observations from22 countries. The dependent variables adopted in this study are the fortnightly death rates and the rates of the spread of COVID-19. Mortality rate and the rate of infection data were computed based on the number of deaths and the number of new cases per 10000 people.The explanatory variables are fortnightly values of indexes taken to investigate the efficacy of government interventions to control COVID-19. Overall government response index, Stringency index, Containment and health index, and Economic support index were selected as explanatory variables. The study relies on the Oxford COVID-19 Government Measure Tracker (OxCGRT). According to the procedures of ARDL, the study employs (i) the unit root test to check stationarity, (ii) panel cointegration, and (iii) PMG and ARDL estimation techniques. The study shows that the COVID-19 pandemic forced immediate responses from policymakers across the world to mitigate the risks of COVID-19. Of the four types of government policy interventions: (i) Stringency and (ii) Economic Support have been most effective and reveal that facilitating Stringency and financial measures has resulted in a reduction in infection and fatality rates, while (iii) Government responses are positively associated with deaths but negatively with infected cases. Even though this positive relationship is unexpected to some extent in the long run, social distancing norms of the governments have been broken by the public in some countries, and population age demographics would be a possible reason for that result. (iv) Containment and healthcare improvements reduce death rates but increase the infection rates, although the effect has been lower (in absolute value). The model implies that implementation of containment health practices without association with tracing and individual-level quarantine does not work well. The policy implication based on containment health measures must be applied together with targeted, aggressive, and rapid containment to extensively reduce the number of people infected with COVID 19. Furthermore, the results demonstrate that economic support for income and debt relief has been the key to suppressing the rate of COVID-19 infections and fatality rates.

Keywords: COVID-19, infection rate, deaths rate, government response, panel data

Procedia PDF Downloads 76

Authors: Chechen Liao, Pui-Lai To, Chuang-Chun Liu

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Online shopping has become very popular recently. In today’s highly competitive online retail environment, retaining existing customers is a necessity for online retailers. This study focuses on the antecedents and consequences of Internet buyer regret and satisfaction in the online consumer purchasing process. This study examines the roles that online consumer’s purchasing process evaluations (i.e., search experience difficulty, service-attribute evaluations, product-attribute evaluations and post-purchase price perceptions) and alternative evaluation (i.e., alternative attractiveness) play in determining buyer regret and satisfaction in e-commerce. The study also examines the consequences of regret, satisfaction and habit in regard to repurchase intention. In addition, this study attempts to investigate the moderating role of habit in attaining a better understanding of the relationship between repurchase intention and its antecedents. Survey data collected from 431 online customers are analyzed using structural equation modeling (SEM) with partial least squares (PLS) and support provided for the hypothesized links. These results indicate that online consumer’s purchasing process evaluations (i.e., search experience difficulty, service-attribute evaluations, product-attribute evaluations and post-purchase price perceptions) have significant influences on regret and satisfaction, which in turn influences repurchase intention. In addition, alternative evaluation (i.e., alternative attractiveness) has a significant positive influence on regret. The research model can provide a richer understanding of online customers’ repurchase behavior and contribute to both research and practice.

Keywords: online shopping, purchase evaluation, regret, satisfaction

Procedia PDF Downloads 283

Authors: Aaditya U. Jhamb

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Due to the current energy crisis that many countries are battling, energy-efficient buildings are the subject of extensive research in the modern technological era because of growing worries about energy consumption and its effects on the environment. The paper explores 8 factors that help determine energy efficiency for a building: (relative compactness, surface area, wall area, roof area, overall height, orientation, glazing area, and glazing area distribution), with Tsanas and Xifara providing a dataset. The data set employed 768 different residential building models to anticipate heating and cooling loads with a low mean squared error. By optimizing these characteristics, machine learning algorithms may assess and properly forecast a building's heating and cooling loads, lowering energy usage while increasing the quality of people's lives. As a result, the paper studied the magnitude of the correlation between these input factors and the two output variables using various statistical methods of analysis after determining which input variable was most closely associated with the output loads. The most conclusive model was the Decision Tree Regressor, which had a mean squared error of 0.258, whilst the least definitive model was the Isotonic Regressor, which had a mean squared error of 21.68. This paper also investigated the KNN Regressor and the Linear Regression, which had to mean squared errors of 3.349 and 18.141, respectively. In conclusion, the model, given the 8 input variables, was able to predict the heating and cooling loads of a residential building accurately and precisely.

Keywords: energy efficient buildings, heating load, cooling load, machine learning models

Procedia PDF Downloads 96

Authors: Stamatis Zoras, Vasilis Evagelopoulos, Theodoros Staurakas

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The association between elevated air pollution levels and extreme climate conditions (temperature, particulate matter, ozone levels, etc.) and mental consequences has been, recently, the focus of significant number of studies. It varies depending on the time of the year it occurs either during the hot period or cold periods but, specifically, when extreme air pollution and weather events are observed, e.g. air pollution episodes and persistent heatwaves. It also varies spatially due to different effects of air quality and climate extremes to human health when considering metropolitan or rural areas. An air pollutant concentration and a climate extreme are taking a different form of impact if the focus area is countryside or in the urban environment. In the built environment the climate extreme effects are driven through the formed microclimate which must be studied more efficiently. Variables such as biological, age groups etc may be implicated by different environmental factors such as increased air pollution/noise levels and overheating of buildings in comparison to rural areas. Gridded air quality and climate variables derived from the land surface observations network of West Macedonia in Greece will be analysed against mortality data in a spatial format in the region of West Macedonia. Artificial intelligence (AI) tools will be used for data correction and prediction of health deterioration with climatic conditions and air pollution at local scale. This would reveal the built environment implications against the countryside. The air pollution and climatic data have been collected from meteorological stations and span the period from 2000 to 2009. These will be projected against the mortality rates data in daily, monthly, seasonal and annual grids. The grids will be operated as AI-based warning models for decision makers in order to map the health conditions in rural and urban areas to ensure improved awareness of the healthcare system by taken into account the predicted changing climate conditions. Gridded data of climate conditions, air quality levels against mortality rates will be presented by AI-analysed gridded indicators of the implicated variables. An Al-based gridded warning platform at local scales is then developed for future system awareness platform for regional level.

Keywords: air quality, artificial inteligence, climatic conditions, mortality

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Authors: Robert Ab Butarbutar, Sutan Musa Buyana

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Purpose: The purpose of this study is to empirically test the correlation between several variables: perceived quality, overall customer satisfaction and brand attitude to brand loyalty on Maxim magazine in Indonesia. Since the room of adult magazine in Indonesia is restricted, the study of this category has became so interesting to reveal how those variables occur. Design/ methodology/ approach: The combination of exploratory, descriptive and causal research design used in this study. Non-probability sampling, specifically purposive sampling used to determine 160 respondents. Path analysis used to examine the contribution of antecedents variables, perceived quality, overall satisfaction and brand attitude in contribution to brand loyalty. Additional respondents serve for in-depth interview to enrich findings from questionnaire that directly distributed. Findings: The research shows that perceived quality positively contribute to overall satisfaction and brand attitude. Overall satisfaction also positively influence brand attitude and brand loyalty. Finally, brand attitude directly impact to brand loyalty. Despite the hypothesis testing, qualitative research also shows specific behavior of Indonesian customer in consuming adult magazine. Research limitation/implication: This research limited to adult male (18 years at minimum) and who live in big city as Jakarta. Broader geographical coverage is advisable for further research. This study also serves a call for additional empirical research into different product category that targeted to adult male, Since the research of this segment is quite scarce. Managerial Implications: Since findings show perceived quality positively impact and strong contribute to overall satisfaction and brand attitude, it implies for adult magazine to be driven by quality of content. The selection of model, information of current lifestyle of urban male became prioritizes in developing perceived quality. Differentiation also emerges as critical issues since consumer difficult to differentiate significantly one magazine to another. The way magazine deliver its content toward distinctive communication is highly recommended. Furthermore, brand loyalty faces big challenge. Interactivity toward events and social media become critically important. Originality/ value: perceived quality plays as prerequisite to develop overall satisfaction and brand attitude. Finding shows customer difficult to differentiate among adult magazines. Therefore, brand loyalty become a big challenge for company.

Keywords: perceived quality, overall satisfaction, brand attitude, adult magazine

Procedia PDF Downloads 408

Authors: Tesfaldet Mekonnen Estifanos, Chen Hui, Afewerki Weldezgi

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Background: Youth in general and young females in particular, remain at the center of the HIV/AIDS epidemic. Sexual risk-taking among young unmarried women is relatively high and are the most vulnerable and highly exposed to HIV/AIDS. Improvements in the status of HIV/AIDS knowledge and acceptance attitude towards people living with HIV (PLWHIV) plays a great role in averting the incidence of HIV/AIDS. Thus, the aim of the study was to explore the level and correlates of HIV/AIDS knowledge and accepting attitude toward PLWHIV. Methods: A cross-sectional study was conducted using data from the Uganda Demographic Health Survey 2016 (UDHS-2016). National level representative household surveys using a multistage cluster probability sampling method, face to face interviews with standard questionnaires were performed. Unmarried women aged 15-24 years with a sample size of 2019 were selected from the total sample of 8674 women aged 15-49 years and were analyzed using SPSS version 23. Independent variables such as age, religion, educational level, residence, and wealth index were included. Two binary outcome variables (comprehensive HIV/AIDS knowledge and acceptance attitude toward PLWHIV) were utilized. We used the chi-square test as well as multivariate regression analysis to explore correlations of explanatory variables with the outcome variables. The results were reported by odds ratios (OR) with 95% confidence interval (95% CI), taking a p-value less than 0.05 as significant. Results: Almost all (99.3%) of the unmarried women aged 15-24 years were aware of HIV/AIDS, but only 51.2% had adequate comprehensive knowledge on HIV/AIDS. Only 69.4% knew both methods: using a condom every time had sex, and having only one faithful uninfected partner can prevent HIV/AIDS transmission. About 66.6% of the unmarried women reject at least two common local misconceptions about HIV/AIDS. Moreover, an alarmingly few (20.3%) of the respondents had a positive acceptance attitude to PLWHIV. On multivariate analysis, age (20-24 years), living in urban, being educated and wealthier, were predictors of having adequate comprehensive HIV/AIDS knowledge. On the other hand, research participants with adequate comprehensive knowledge about HIV/AIDS were highly likely (OR, 1.94 95% CI, 1.52-2.46) to have a positive acceptance attitude to PLWHIV than those with inadequate knowledge. Respondents with no education, Muslim, and Pentecostal religion were emerged less likely to have a positive acceptance attitude to PLWHIV. Conclusion: This study found out the highly accepted level of awareness, but the knowledge and positive acceptance attitude are not encouraging. Thus, expanding access to comprehensive sexuality and strengthening educational campaigns on HIV/AIDS in communities, health facilities, and schools is needed with a greater focus on disadvantaged women having low educational level, poor socioeconomic status, and those residing in rural areas. Sexual risk behaviors among the most affected people - young women have also a role in the spread of HIV/AIDS. Hence, further research assessing the significant contributing factors for sexual risk-taking might have a positive impact on the fight against HIV/AIDS.

Keywords: acceptance attitude, HIV/AIDS, knowledge, unmarried women

Procedia PDF Downloads 152

Authors: Pholosho M. Kgopa, Phatu W. Mashela, Alen Manyevere

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Increasing incidents of drought spells in most Sub-Saharan Africa call for using alternative sources of water for irrigation in arid and semi-arid regions. A study was conducted to investigate chemical composition of borehole and treated wastewater from different sampling disposal sites at University of Limpopo Experimental Farm (ULEF). A 4 × 5 factorial experiment, with the borehole as a reference sampling site and three other sampling sites along the wastewater disposal system was conducted over five months. Water samples were collected at four sites namely, (a) exit from Pond 16 into the furrow, (b) entry into night-dam, (c) exit from night dam to irrigated fields and (d) exit from borehole to irrigated fields. Water samples were collected in the middle of each month, starting from July to November 2016. Samples were analysed for pH, EC, Ca, Mg, Na, K, Al, B, Zn, Cu, Cr, Pb, Cd and As. The site × time interactions were highly significant for Ca, Mg, Zn, Cu, Cr, Pb, Cd, and As variables, but not for Na and K. Sampling site was highly significant on all variables, with sampling period not significant for K and Na. Relative to water from the borehole, Na concentration in wastewater samples from the night-dam exit, night-dam entry and Pond16 exit were lower by 69, 34 and 55%, respectively. Relative to borehole water, Al was higher in wastewater sampling sites. In conclusion, both sampling site and period affected the chemical composition of treated wastewater.

Keywords: irrigation water quality, spatial effects, temporal effects, water reuse, water scarcity

Procedia PDF Downloads 238

Authors: Etienne Provencal, David L. St-Pierre

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A facility exploiting only electronic gambling machines (EGMs) opened in 2007 in Quebec City, Canada under the name of Salons de Jeux du Québec (SdjQ). This facility is one of the first worldwide to rely on that business model. This paper models the performance of such EGMs. The interest from a managerial point of view is to identify the variables that can be controlled or influenced so that a comprehensive model can help improve the overall performance of the business. The EGM individual performance model contains eight different variables under study (Game Title, Progressive jackpot, Bonus Round, Minimum Coin-in, Maximum Coin-in, Denomination, Slant Top and Position). Using data from Quebec City’s SdjQ, a linear regression analysis explains 90.80% of the EGM performance. Moreover, results show a behavior slightly different than that of a casino. The addition of GameTitle as a factor to predict the EGM performance is one of the main contributions of this paper. The choice of the game (GameTitle) is very important. Games having better position do not have significantly better performance than games located elsewhere on the gaming floor. Progressive jackpots have a positive and significant effect on the individual performance of EGMs. The impact of BonusRound on the dependent variable is significant but negative. The effect of Denomination is significant but weakly negative. As expected, the Language of an EGMS does not impact its individual performance. This paper highlights some possible improvements by indicating which features are performing well. Recommendations are given to increase the performance of the EGMs performance.

Keywords: EGM, linear regression, model prediction, slot operations

Procedia PDF Downloads 255

Authors: Gaurav Gupta, Jitendra Mahakud

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This study focuses on the significance of internal financing constraints on the determination of corporate fixed investments in the case of Indian manufacturing companies. Financing constraints companies which have less internal fund or retained earnings face more transaction and borrowing costs due to imperfections in the capital market. The period of study is 1999-2000 to 2013-2014 and we consider 618 manufacturing companies for which the continuous data is available throughout the study period. The data is collected from PROWESS data base maintained by Centre for Monitoring Indian Economy Pvt. Ltd. Panel data methods like fixed effect and random effect methods are used for the analysis. The Likelihood Ratio test, Lagrange Multiplier test, and Hausman test results conclude the suitability of the fixed effect model for the estimation. The cash flow and liquidity of the company have been used as the proxies for the internal financial constraints. In accordance with various theories of corporate investments, we consider other firm specific variable like firm age, firm size, profitability, sales and leverage as the control variables in the model. From the econometric analysis, we find internal cash flow and liquidity have the significant and positive impact on the corporate investments. The variables like cost of capital, sales growth and growth opportunities are found to be significantly determining the corporate investments in India, which is consistent with the neoclassical, accelerator and Tobin’s q theory of corporate investment. To check the robustness of results, we divided the sample on the basis of cash flow and liquidity. Firms having cash flow greater than zero are put under one group, and firms with cash flow less than zero are put under another group. Also, the firms are divided on the basis of liquidity following the same approach. We find that the results are robust to both types of companies having positive and negative cash flow and liquidity. The results for other variables are also in the same line as we find for the whole sample. These findings confirm that internal financing constraints play a significant role for determination of corporate investment in India. The findings of this study have the implications for the corporate managers to focus on the projects having higher expected cash inflows to avoid the financing constraints. Apart from that, they should also maintain adequate liquidity to minimize the external financing costs.

Keywords: cash flow, corporate investment, financing constraints, panel data method

Procedia PDF Downloads 241

Authors: Libena Cernohorska

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The goal of this paper is to specify factors influencing the profitability of selected banks. Next, a model will be created to help establish variables that have a demonstrable influence on the development of the selected banks' profitability ratios. Czech banks and their international parent companies were selected for analyzing profitability. Banks categorized as large banks (according to the Czech National Bank's system, which ranks banks according to balance sheet total) were selected to represent the Czech banks. Two ratios, the return on assets ratio (ROA) and the return on equity ratio (ROE) are used to assess bank profitability. Six endogenous and four external indicators were selected from among other factors that influence bank profitability. The data analyzed were for the years 2001 – 2013. First, correlation analysis, which was supposed to eliminate correlated values, was conducted. A large number of correlated values were established on the basis of this analysis. The strongly correlated values were omitted. Despite this, the subsequent regression analysis of profitability for the individual banks that were selected did not confirm that the selected variables influenced their profitability. The studied factors' influence on bank profitability was demonstrated only for Československá Obchodní Banka and Société Générale using regression analysis. For Československá Obchodní Banka, it was demonstrated that inflation level and the amount of the central bank's interest rate influenced the return on assets ratio and that capital adequacy and market concentration influenced the return on equity ratio for Société Générale.

Keywords: banks, profitability, regression analysis, ROA, ROE

Procedia PDF Downloads 254

Authors: Chechen Liao, Pui-Lai To, Yi-Hui Wang

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Recently location-based augmented reality games (LBS+AR) have become increasingly popular as a major form of entertainment. Location-based augmented reality games have provided a lot of opportunities for face-to-face interaction among players. Prior studies also indicate that the social side of location-based augmented reality games are one of the major reasons for players to engage in the games. However, the impact of the usage of location-based augmented reality games has not been well explored. The study examines how interpersonal interaction affects social capital and health through playing location-based augmented reality games. The study also investigates how social capital mediates the relationships between interpersonal interaction and health. The study uses survey method to collect data. Six-hundred forty-seven questionnaires are collected. Structural equation modeling is used to investigate the relationships among variables. The causal relationships between variables in the research model are tested. The results of the study indicated that four interpersonal attraction attributes, including ability, proximity, similarity, and familiarity, are identified by ways of factor analysis. Interpersonal attraction is important for location-based augmented reality game-players to develop bonding and bridging social capital. Bonding and bridging social capital have a positive impact on the mental and social health of game-players. The results of the study provide academic and practical implications for future growth of location-based augmented reality games.

Keywords: health, interpersonal interaction, location-based augmented reality games, social capital

Procedia PDF Downloads 258

Authors: Hsin-Yi Kathy Cheng, Yan-Ying JU, Wann-Yun Shieh, Chin-Man Wang

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Although the coordination of swallowing and respiration has been discussed widely, the influence of the positioning angle on swallowing and respiration during feeding has rarely been investigated. This study aimed to investigate the timing and coordination of swallowing and respiration in different seat inclination angles, with liquid and bolus, to provide suggestions and guidelines for the design and develop a feedback-controlled seat angle adjustment device for the back-adjustable wheelchair. Twenty-six participants aged between 15-30 years old without any signs of swallowing difficulty were included. The combination of seat inclinations and food types was randomly assigned, with three repetitions in each combination. The trunk inclination angle was adjusted by a commercialized positioning wheelchair. A total of 36 swallows were done, with at least 30 seconds of rest between each swallow. We used a self-developed wearable device to measure the submandibular muscle surface EMG, the movement of the thyroid cartilage, and the respiratory status of the nasal cavity. Our program auto-analyzed the onset and offset of duration, and the excursion and strength of thyroid cartilage when it was moving, coordination between breathing and swallowing were also included. Variables measured include the EMG duration (DsEMG), swallowing apnea duration (SAD), total excursion time (TET), duration of 2nd deflection, FSR amplitude, Onset latency, DsEMG onset, DsEMG offset, FSR onset, and FSR offset. These measurements were done in four-seat inclination angles (5。, 15。, 30。, 45。) and three food contents (1ml water, 10ml water, and 5ml pudding bolus) for each subject. The data collected between different contents were compared. Descriptive statistics were used to describe the basic features of the data. Repeated measure ANOVAs were used to analyze the differences for the dependent variables in different seat inclination and food content combinations. The results indicated significant differences in seat inclination, mostly between 5。 and 45。, in all variables except FSR amplitude. It also indicated significant differences in food contents almost among all variables. Significant interactions between seat inclination and food contents were only found in FSR offsets. The same protocol will be applied to participants with disabilities. The results of this study would serve as clinical guidance for proper feeding positions with different food contents. The ergonomic data would also provide references for assistive technology professionals and practitioners in device design and development. In summary, the current results indicated that it is easier for a subject to lean backward during swallowing than when sitting upright and swallowing water is easier than swallowing pudding. The results of this study would serve as the clinical guidance for proper feeding position (such as wheelchair back angle adjustment) with different food contents. The same protocol can be applied to elderly participants or participants with physical disabilities. The ergonomic data would also provide references for assistive technology professionals and practitioners in device design and development.

Keywords: swallowing, positioning, assistive device, disability

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Authors: Sajjad Rezaei, Mahdieh Molanouri Shamsi, Azadeh Jamali

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Background and purpose: Surfactant protein D (SP-D) is a lung-specific protein that is detectable in human plasma. Effect of exercise training on SP-D levels as well as its relation to metabolic indices is not known. The present study then aimed to investigate the effects of 10 weeks of aerobic training on serum levels of SP-D and insulin resistance in women with type 2 diabetes. Materials and methods: Twenty-two overweight women with type 2 diabetes mellitus were recruited through deliberate sampling and randomly assigned to intervention and control groups (11 in each group). The intervention group underwent a progressive aerobic training program for 10 weeks, 3 days per week, 30-55 min/day at 50-75% heart rate reserve (HRR). Control group continued with its everyday routine. Blood samples were obtained before and after training for biochemical analysis. Within-group and between-group differences were analyzed with paired and independent t-tests in spss software, respectively, and the relation between variables was analyzed with Pearson’s correlation coefficient (all at P = 0.05). Results: Significant differences were observed between groups in leptin, glucose, waist circumference and VO2 max after training. SP-D was decreased and VO2 max was increased significantly in intervention group. However, no significant correlation was observed between SP-D and other variables. Conclusion: Since there was no corresponding decrease in insulin resistance with decreased levels of SP-D, it seems unlikely for SP-D to mediate the association between obesity and insulin resistance in type 2 diabetics.

Keywords: exercise training, SP-D, insulin resistance, type 2 diabetes

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Authors: Sifriyani Sifriyani, I Nyoman Budiantara, Sri Haryatmi, Gunardi Gunardi

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East Java Province has a first rank as a province that has the most counties and cities in Indonesia and has the largest population. In 2015, the population reached 38.847.561 million, this figure showed a very high population growth. High population growth is feared to lead to increase the levels of unemployment. In this study, the researchers mapped and modeled the unemployment rate with 6 variables that were supposed to influence. Modeling was done by nonparametric geographically weighted regression methods with truncated spline approach. This method was chosen because spline method is a flexible method, these models tend to look for its own estimation. In this modeling, there were point knots, the point that showed the changes of data. The selection of the optimum point knots was done by selecting the most minimun value of Generalized Cross Validation (GCV). Based on the research, 6 variables were declared to affect the level of unemployment in eastern Java. They were the percentage of population that is educated above high school, the rate of economic growth, the population density, the investment ratio of total labor force, the regional minimum wage and the ratio of the number of big industry and medium scale industry from the work force. The nonparametric geographically weighted regression models with truncated spline approach had a coefficient of determination 98.95% and the value of MSE equal to 0.0047.

Keywords: East Java, nonparametric geographically weighted regression, spatial, spline approach, unemployed rate

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Authors: Huseyin Guler, Cigdem Kosar

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The aim of this study is to propose Bridge estimator for seasonal unit root tests. Seasonality is an important factor for many economic time series. Some variables may contain seasonal patterns and forecasts that ignore important seasonal patterns have a high variance. Therefore, it is very important to eliminate seasonality for seasonal macroeconomic data. There are some methods to eliminate the impacts of seasonality in time series. One of them is filtering the data. However, this method leads to undesired consequences in unit root tests, especially if the data is generated by a stochastic seasonal process. Another method to eliminate seasonality is using seasonal dummy variables. Some seasonal patterns may result from stationary seasonal processes, which are modelled using seasonal dummies but if there is a varying and changing seasonal pattern over time, so the seasonal process is non-stationary, deterministic seasonal dummies are inadequate to capture the seasonal process. It is not suitable to use seasonal dummies for modeling such seasonally nonstationary series. Instead of that, it is necessary to take seasonal difference if there are seasonal unit roots in the series. Different alternative methods are proposed in the literature to test seasonal unit roots, such as Dickey, Hazsa, Fuller (DHF) and Hylleberg, Engle, Granger, Yoo (HEGY) tests. HEGY test can be also used to test the seasonal unit root in different frequencies (monthly, quarterly, and semiannual). Another issue in unit root tests is the lag selection. Lagged dependent variables are added to the model in seasonal unit root tests as in the unit root tests to overcome the autocorrelation problem. In this case, it is necessary to choose the lag length and determine any deterministic components (i.e., a constant and trend) first, and then use the proper model to test for seasonal unit roots. However, this two-step procedure might lead size distortions and lack of power in seasonal unit root tests. Recent studies show that Bridge estimators are good in selecting optimal lag length while differentiating nonstationary versus stationary models for nonseasonal data. The advantage of this estimator is the elimination of the two-step nature of conventional unit root tests and this leads a gain in size and power. In this paper, the Bridge estimator is proposed to test seasonal unit roots in a HEGY model. A Monte-Carlo experiment is done to determine the efficiency of this approach and compare the size and power of this method with HEGY test. Since Bridge estimator performs well in model selection, our approach may lead to some gain in terms of size and power over HEGY test.

Keywords: bridge estimators, HEGY test, model selection, seasonal unit root

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Authors: Wasfi Al Salamat, Shaker Al-Kharouf

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This study aims to examine the determinants of financial stability for 13 commercial banks listed on the Amman stock exchange (ASE) over the period (2007-2016) after controlling for the independent variables: return on equity (ROE), return on assets (ROA), earnings per share (EPS), growth in gross domestic product (GDP), inflation rate and debt ratio to measure the financial stability by three main variables: capital adequacy, non-performing loans and the number of returned checks. The balanced panel data statistical approach has been used for data analysis. Results are estimated by using multiple regression models. The empirical results suggested that there is statistically significant negative effect of inflation rate and debt ratio on the capital adequacy while there is statistically significant positive effect of growth in gross domestic product on capital adequacy. In contrast, there is statistically significant negative effect of return on equity and growth in gross domestic product on the non-performing loans while there is statistically significant positive effect of inflation rate on non-performing loans. Finally, there is statistically significant negative effect of growth in gross domestic product on the number of returned checks while there is statistically significant positive effect of inflation rate on the number of returned checks.

Keywords: capital adequacy, financial stability, non-performing loans, number of returned checks, ASE

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Authors: Soha Saad, Jean Bigeon, Florence Ossart, Etienne Sourdille

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Developing better solutions for train rescheduling problems has been drawing the attention of researchers for decades. Most researches in this field deal with minor incidents that affect a large number of trains due to cascading effects. They focus on timetables, rolling stock and crew duties, but do not take into account infrastructure limits. The present work addresses electric infrastructure incidents that limit the power available for train traction, and hence the transportation capacity of the railway system. Rescheduling is needed in order to optimally share the available power among the different trains. We propose a rescheduling process based on dynamic multiphysics railway simulations that include the mechanical and electrical properties of all the system components and calculate physical quantities such as the train speed profiles, voltage along the catenary lines, temperatures, etc. The optimization problem to solve has a large number of continuous and discrete variables, several output constraints due to physical limitations of the system, and a high computation cost. Our approach includes a phase of sensitivity analysis in order to analyze the behavior of the system and help the decision making process and/or more precise optimization. This approach is a quantitative method based on simulation statistics of the dynamic railway system, considering a predefined range of variation of the input parameters. Three important settings are defined. Factor prioritization detects the input variables that contribute the most to the outputs variation. Then, factor fixing allows calibrating the input variables which do not influence the outputs. Lastly, factor mapping is used to study which ranges of input values lead to model realizations that correspond to feasible solutions according to defined criteria or objectives. Generalized Sobol indexes are used for factor prioritization and factor fixing. The approach is tested in the case of a simple railway system, with a nominal traffic running on a single track line. The considered incident is the loss of a feeding power substation, which limits the power available and the train speed. Rescheduling is needed and the variables to be adjusted are the trains departure times, train speed reduction at a given position and the number of trains (cancellation of some trains if needed). The results show that the spacing between train departure times is the most critical variable, contributing to more than 50% of the variation of the model outputs. In addition, we identify the reduced range of variation of this variable which guarantees that the output constraints are respected. Optimal solutions are extracted, according to different potential objectives: minimizing the traveling time, the train delays, the traction energy, etc. Pareto front is also built.

Keywords: optimization, rescheduling, railway system, sensitivity analysis, train timetable

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Authors: Lovro Štefan

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The main purpose of the present study was to investigate the associations between the overweight/obesity status and lifestyle factors. In this cross-sectional study, participants were 1950 urban secondary-school students (54.7% of female students) aged 17-18 years old. Dependent variable was body-mass index status derived from self-reported height and weight. The outcome was binarised, where participants with value <25 kg/m2 were collapsed into „normal“, while those ≥25 kg/m2 into „overweight/obesity“ category. Independent variables were gender, type of school, physical activity, sedentary behaviour, self-rated health, self-perceived socioeconomic status and psychological distress. The associations between the dependent and independent variables were analyzed by using multiple logistic regression analysis. In the univariate model, being overweight/obese was significantly associated with being a male student (OR 0.31; 95% CI 0.23 to 0.42), attending a vocational school (OR 1.87; 95% CI 1.42 to 2.48), not meeting the recommendations for moderate-to-vigorous physical activity (OR 0.44; 95% CI 0.22 to 0.88), more time spending in sedentary behaviour (OR 1.53; 95% CI 1.07 to 2.19), poor self-rated health (OR 0.35, 95% CI 0.20 to 0.56) and lower socioeconomic status (OR 0.63; 95% CI 0.48 to 0.84). In the multivariate model, the same associations occured between the dependent and independent variable. In both models, psychological distress was not associated with being overweight/obese. In conclusion, our findings suggest, that lifestyle factors are independently associated with body-mass index

Keywords: body mass index, secondary-school students, Croatia, physical activity, sedentary behaviour, logistic regression

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Authors: Shivaram P. Arunachalam, Mustafa Y. Sir, Andy Boggust, David M. Nestler, Thomas R. Hellmich, Kalyan S. Pasupathy

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Emergency departments (EDs) provide urgent care to patients throughout the day in a complex and chaotic environment. Real-time location systems (RTLS) are increasingly being utilized in healthcare settings, and have shown to improve safety, reduce cost, and increase patient satisfaction. Radio Frequency Identification Device (RFID) data in an ED has been shown to compute variables such as patient-provider contact time, which is associated with patient outcomes such as 30-day hospitalization. These variables can provide avenues for improving ED operational efficiency. A major challenge with ED financial operations is under-coding of critical care services due to physicians’ difficulty reporting accurate times for critical care provided under Current Procedural Terminology (CPT) codes 99291 and 99292. In this work, the authors propose a framework to optimize ED critical care billing using RFID data. RFID estimated physician-patient contact times could accurately quantify direct critical care services which will help model a data-driven approach for ED critical care billing. This paper will describe the framework and provide insights into opportunities to prevent under coding as well as over coding to avoid insurance audits. Future work will focus on data analytics to demonstrate the feasibility of the framework described.

Keywords: critical care billing, CPT codes, emergency department, RFID

Procedia PDF Downloads 131

Authors: N. R. Badurally Adam, S. R. Monebhurrun, M. Z. Dauhoo, A. Khoodaruth

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Transport energy demand is vital for the economic growth of any country. Globalisation and better standard of living plays an important role in transport energy demand. Recently, transport energy demand in Mauritius has increased significantly, thus leading to an abuse of natural resources and thereby contributing to global warming. Forecasting the transport energy demand is therefore important for controlling and managing the demand. In this paper, we develop a model to predict the transport energy demand. The model developed is based on a system of five stochastic differential equations (SDEs) consisting of five endogenous variables: fuel price, population, gross domestic product (GDP), number of vehicles and transport energy demand and three exogenous parameters: crude birth rate, crude death rate and labour force. An interval of seven years is used to avoid any falsification of result since Mauritius is a developing country. Data available for Mauritius from year 2003 up to 2009 are used to obtain the values of design variables by applying genetic algorithm. The model is verified and validated for 2010 to 2012 by substituting the values of coefficients obtained by GA in the model and using particle swarm optimisation (PSO) to predict the values of the exogenous parameters. This model will help to control the transport energy demand in Mauritius which will in turn foster Mauritius towards a pollution-free country and decrease our dependence on fossil fuels.

Keywords: genetic algorithm, modeling, particle swarm optimization, stochastic differential equations, transport energy demand

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Authors: Sandeep Thakur, Ismail Mondal, Phani Bhusan Ghosh, Papita Das, Tarun Kumar De

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Sundarbans Reserve forest of India has been undergoing major transformations in the recent past owing to population pressure and related changes. This has brought about major changes in the spatial landscape of the region especially in the western parts. This study attempts to assess the impacts of the Landcover changes on the mangrove habitats. Time series imageries of Landsat were used to analyze the Normalized Differential Vegetation Index (NDVI) patterns over the western parts of Indian Sundarbans forest in order to assess the heath of the mangroves in the region. The images were subjected to Land use Land cover (LULC) classification using sub-pixel classification techniques in ERDAS Imagine software and the changes were mapped. The spatial proliferation of aquaculture farms during the study period was also mapped. A multivariate regression analysis was carried out between the obtained NDVI values and the LULC classes. Similarly, the observed meteorological data sets (time series rainfall and minimum and maximum temperature) were also statistically correlated for regression. The study demonstrated the application of NDVI in assessing the environmental status of mangroves as the relationship between the changes in the environmental variables and the remote sensing based indices felicitate an efficient evaluation of environmental variables, which can be used in the coastal zone monitoring and development processes.

Keywords: aquaculture farms, LULC, Mangrove, NDVI

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Authors: John Michael Russo

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Honeybees are important to our food system and continue to suffer from high rates of colony loss. Precision feed has brought many benefits to livestock cultivation and these should transfer to apiculture. However, apiculture has unique challenges. The objective of this research is to understand how principles of precision agriculture, applied to apiculture and feed specifically, might effectively improve state-of-the-art cultivation. The methodology surveys apicultural practice to build a model for assessment. First, a review of apicultural motivators is made. Feed method is then evaluated. Finally, precision feed methods are examined as accelerants with potential to advance the effectiveness of feed practice. Six important motivators emerge: colony loss, disease, climate change, site variance, operational costs, and competition. Feed practice itself is used to compensate for environmental variables. The research finds that the current state-of-the-art in apiculture feed focuses on critical challenges in the management of feed schedules which satisfy requirements of the bees, preserve potency, optimize environmental variables, and manage costs. Many of the challenges are most acute when feed is used to dispense medication. Technology such as RNA treatments have even more rigorous demands. Precision feed solutions focus on strategies which accommodate specific needs of individual livestock. A major component is data; they integrate precise data with methods that respond to individual needs. There is enormous opportunity for precision feed to improve apiculture through the integration of precision data with policies to translate data into optimized action in the apiary, particularly through automation.

Keywords: precision agriculture, precision feed, apiculture, honeybees

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Authors: Ka C. Lam, Oluwafunmibi S. Idowu

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Uncertainty in cost is a major factor affecting performance of construction projects. To our knowledge, several conceptual cost models have been developed with varying degrees of accuracy. Incorporating conceptual quantities into conceptual cost models could improve the accuracy of early predesign cost estimates. Hence, the development of quantity models for estimating conceptual quantities of framed reinforced concrete structures using supervised machine learning is the aim of the current research. Using measured quantities of structural elements and design variables such as live loads and soil bearing pressures, response and predictor variables were defined and used for constructing conceptual quantities models. Twenty-four models were developed for comparison using a combination of non-parametric support vector regression, linear regression, and bootstrap resampling techniques. R programming language was used for data analysis and model implementation. Gross soil bearing pressure and gross floor loading were discovered to have a major influence on the quantities of concrete and reinforcement used for foundations. Building footprint and gross floor loading had a similar influence on beams and slabs. Future research could explore the modelling of other conceptual quantities for walls, finishes, and services using machine learning techniques. Estimation of conceptual quantities would assist construction planners in early resource planning and enable detailed performance evaluation of early cost predictions.

Keywords: bootstrapping, conceptual quantities, modelling, reinforced concrete, support vector regression

Procedia PDF Downloads 206

Authors: Mahjabeen Akbar

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Dental aesthetics and its associated psychosocial influence have a significant impact on individuals. Correcting malocclusions is a key motivating factor for majority patients; however, psychosocial factors have been rarely incorporated in evaluating malocclusions. Therefore, it is necessary to study the psychosocial influence of malocclusion in patients. The study aimed to determine the psychosocial influence of dental aesthetics in dental students by the ‘Psychosocial Impact of Dental Aesthetics Questionnaire’ and self-rated Aesthetic Component of the Index of Orthodontic Treatment Need (IOTN). This was a quantitative study using a cross-sectional study design. One hundred twenty dental students (71 females and 49 males; mean age 24.5) were selected via purposive sampling from July to August 2019. Dental students with no former orthodontic treatment were requested to fill out the ‘Psychosocial Impact of Dental Aesthetics Questionnaire.’ Variables including; self-confidence/insecurity, social influence, psychological influence and self-perception of the need of an orthodontic treatment were evaluated by a sequence of statements, while dental aesthetics were evaluated by using the IOTN Aesthetic Component. To determine the significance, the Kruskal-Wallis test was utilized. The results show that all four variables measuring psychosocial impact indicated significant correlations with the perceived malocclusions with a p-value of less than 0.01. The results conclude there is a strong psychological and social influence of altered dental aesthetics on an individual. Moreover, the relationship between the IOTN-AC grading with the psychosocial wellbeing of an individual stands proven, indicating that the perception of altered dental aesthetics is as important as a factor in treatment need as the amount of malocclusion.

Keywords: dental aesthetics, malocclusion, psychosocial influence, dental students

Procedia PDF Downloads 152

Authors: Camila Amin-Puello, Lina Vasco-Diaz, Juan Ramirez-Arias, Claudia Munoz, Carlos Gonzalez-Calderon

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Operational flexibility is a fundamental aspect in the field of airlines because although demand is constantly changing, it is the duty of companies to provide a service to users that satisfies their needs in an efficient manner without sacrificing factors such as comfort, safety and other perception variables. The objective of this research is to understand the factors that describe and explain operational flexibility by implementing advanced analytical methods such as exploratory factor analysis and structural equation modeling, examining multiple levels of operational flexibility and understanding how these variable influences users' decision-making when choosing an airline and in turn how it affects the airlines themselves. The use of a hybrid model and latent variables improves the efficiency and accuracy of airline performance prediction in the unpredictable Colombian market. This pioneering study delves into traveler motivations and their impact on domestic flight demand, offering valuable insights to optimize resources and improve the overall traveler experience. Applying the methods, it was identified that low-cost airlines are not useful for flexibility, while users, especially women, found airlines with greater flexibility in terms of ticket costs and flight schedules to be more useful. All of this allows airlines to anticipate and adapt to their customers' needs efficiently: to plan flight capacity appropriately, adjust pricing strategies and improve the overall passenger experience.

Keywords: hybrid choice model, airline, business travelers, domestic flights

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Authors: Funmilola Ajani, I. A. Ayodele, O.A. Filade

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Tourism has direct, indirect and induced impacts on economic development and the industry is one of the most crucial tradable sectors in the world. The study was therefore carried out to assess the potentials of ecotourism to nature conservation and its contributions to the improvement of the livelihood of Oke- Ila Orangun community. One hundred and fifty residents were chosen by stratified random sampling as respondents. Respondents awareness of ecotourism was assessed using an 8-point scale while respondents acceptance of ecotourism was assessed using a 14-point scale. Contributions to improvement of livelihood of residents and perceived constraints identified by residents to the development of the water fall and socio-economic variables among others were also obtained. Also, in-depth interview was conducted with the king of Ayikunnugba. The data was analyzed using descriptive statistics such as frequency count, mean and percentages. Correlation analysis was used to determine whether or not a relationship exists between two variables at 0.05 level of significance. Perception of respondents based on the awareness of ecotourism and contributions to livelihood development was high (78.3%). A significant relationship exists between acceptance of ecotourism and its contributions to peoples’ livelihood. Also, relationship between constraints encountered by respondents and its contributions to peoples livelihood is highly significant(r =0.546; P =0.00). Majority (71.3%) of the respondents believed that the development of the area will not lead to environmental pollution. Public- Private- Partnership (PPP) is therefore recommended so as to enable the recreation site to meet international standard in terms of development and management.

Keywords: Ayikunnugba water fall, ecotourism constraints, nature conservation, awareness

Procedia PDF Downloads 158

Authors: Jiraporn Prommaha

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The purpose of this research is to study the development of Thailand Brand Identity and the perception of its image in order to find any guidelines for the identity development and the image perception of Thailand Brand in Health and Wellness Tourism. The paper is conducted through mixed methods research, both the qualitative and quantitative researches. The qualitative focuses on the in-depth interview of executive administrations from public and private sectors involved scholars and experts in identity and image issue, main 11 people. The quantitative research was done by the questionnaires to collect data from foreign tourists 800; Chinese tourists 400 and UK tourists 400. The technique used for this was the Exploratory Factor Analysis (EFA), this was to determine the relation between the structures of the variables by categorizing the variables into group by applying the Varimax rotation technique. This technique showed recognition the Thailand brand image related to the 2 countries, China and UK. The results found that guidelines for brand identity development and image perception of health and wellness tourism in Thailand; as following (1) Develop communication in order to understanding of the meaning of the word 'Health and beauty tourism' throughout the country, (2) Develop human resources as a national agenda, (3) Develop awareness rising in the conservation and preservation of natural resources of the country, (4) Develop the cooperation of all stakeholders in Health and Wellness Businesses, (5) Develop digital communication throughout the country and (6) Develop safety in Tourism.

Keywords: brand identity, image perception, nation branding, health and wellness tourism, mixed methods research

Procedia PDF Downloads 200

Authors: Bongs Lainjo

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

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

Procedia PDF Downloads 138

Authors: Bakr Gomaa, Hana Awad

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A stuffy room is one of the indicators of poor indoor air quality. Through working in an educational building in Alexandria, it is noticed that one of the rooms is smelly. A field study is conducted in a private university building in Alexandria to achieve indoor sustainable educational environment. Additionally, the indoor air quality is empirically assessed, and thermal comfort is identified in educational buildings, in studio halls specifically during lecture hours. The current research uses qualitative and quantitative methods in the form of literature review, investigation and test measurements. At a similar time that the teachers and students fill in a questionnaire regarding the concept of indoor climate, thermal comfort variables are determined. The indoor thermal conditions of the studio are assessed through three variables including Fanger’s comfort indicators (calculated using PMV, predicted mean vote and PPD, predicted percentage of dissatisfied people), the actual people clothing and metabolic rate. Actual measurements of air quality are obtained in a case study in an architectural building. Results have proved that indoor climatic conditions as air flow and temperature are inconvenient to inhabitants. Regarding questionnaire results, occupants appear to be uncomfortable in both seasons, with result percentages out of the acceptable range. Finally, further researches will center on how to preserve thermal comfort in school buildings since it has a vital influence on the student’s knowledge.

Keywords: educational buildings, Indoor air quality, productivity, thermal comfort

Procedia PDF Downloads 195