Search results for: climatic variables

Authors: Vanessa H. S. Zago, Ana Maria H. de Avila, Paula P. Costa, Welington Corozolla, Liriam S. Teixeira, Eliana C. de Faria

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Objectives: The outcome of cardiovascular disease is affected by environment and climate. This study evaluated the possible relationships between climatic and environmental changes and the occurrence of biological rhythms in serum lipids and lipoproteins in a large population sample in the city of Campinas, State of Sao Paulo, Brazil. In addition, it determined the temporal variations of death due to atherosclerotic events in Campinas during the time window examined. Methods: A large 8-year retrospective study was carried out to evaluate the lipid profiles of individuals attended at the University of Campinas (Unicamp). The study population comprised 27.543 individuals of both sexes and of all ages. Normolipidemic and dyslipidemic individuals classified according to Brazilian guidelines on dyslipidemias, participated in the study. For the same period, the temperature, relative humidity and daily brightness records were obtained from the Centro de Pesquisas Meteorologicas e Climaticas Aplicadas a Agricultura/Unicamp and frequencies of death due to atherosclerotic events in Campinas were acquired from the Brazilian official database DATASUS, according to the International Classification of Diseases. Statistical analyses were performed using both Cosinor and ARIMA temporal analysis methods. For cross-correlation analysis between climatic and lipid parameters, cross-correlation functions were used. Results: Preliminary results indicated that rhythmicity was significant for LDL-C and HDL-C in the cases of both normolipidemic and dyslipidemic subjects (n =respectively 11.892 and 15.651 both measures increasing in the winter and decreasing in the summer). On the other hand, for dyslipidemic subjects triglycerides increased in summer and decreased in winter, in contrast to normolipidemic ones, in which triglycerides did not show rhythmicity. The number of deaths due to atherosclerotic events showed significant rhythmicity, with maximum and minimum frequencies in winter and summer, respectively. Cross-correlation analyzes showed that low humidity and temperature, higher thermal amplitude and dark cycles are associated with increased levels of LDL-C and HDL-C during winter. In contrast, TG showed moderate cross-correlations with temperature and minimum humidity in an inverse way: maximum temperature and humidity increased TG during the summer. Conclusions: This study showed a coincident rhythmicity between low temperatures and high concentrations of LDL-C and HDL-C and the number of deaths due to atherosclerotic cardiovascular events in individuals from the city of Campinas. The opposite behavior of cholesterol and TG suggest different physiological mechanisms in their metabolic modulation by climate parameters change. Thus, new analyses are underway to better elucidate these mechanisms, as well as variations in lipid concentrations in relation to climatic variations and their associations with atherosclerotic disease and death outcomes in Campinas.

Keywords: atherosclerosis, climatic variations, lipids and lipoproteins, associations

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Authors: Nadia Elouaer

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Tax revenue is the main state resource and one of the important variables in tax policy. Nevertheless, this resource is continually decreasing, so it is important to focus on the reasons for this decline. Several studies show that the taxpayer is reluctant to pay taxes, especially in countries at risk or in countries in transition, including Tunisia. This study focuses on the tax evasion behavior of a Tunisian taxpayer under the influence of his political beliefs, as well as the influence of different tax compliance variables. Using a questionnaire, a sample of 500 Tunisian taxpayers is used to examine the relationship between political beliefs and taxpayer affiliations and tax compliance variables, as well as the study of the causal link between political beliefs and fraudulent behavior. The data were examined using correlation, factor, and regression analysis and found a positive and statistically significant relationship between the different tax compliance variables and the tax evasion behavior. There is also a positive and statistically significant relationship between tax evasion and political beliefs and affiliations. The study of the relationship between political beliefs and compliance variables shows that they are closely related. The conclusion is to admit that tax evasion and political beliefs are closely linked, and the government should update its tax policy and modernize its administration in order to strengthen the credibility and disclosure of information in order to restore a relationship of trust between public authorities and the taxpayer.

Keywords: fiscal policy, political beliefs, tax evasion, taxpayer behavior

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Authors: Hitham Yami

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This study will focus primarily on assessing the availability requirements of the electronic management of oil companies in Libya, and the mean objectives of the research applying electronic management and make recommendations and steps to approach electronic management. There are limited research and statistical analysis to support electronic management in Libyan companies. The groundwork for the proposed approach is to develop independent variables and the dependent variables to be restructured after it Alntra side of the field and the side to get the data to achieve the desired results and solving the problem faced by the Libyan Oil Corporation. All these strategies are proposed to achieve the goal, and solving Libyan oil installations.

Keywords: oil company’s revenue, independent variables, electronic management, Libyan oil corporation

Procedia PDF Downloads 259

Authors: Roshanak Afrakhteh, Abdolrasoul Salman Mahini, Mahdi Motagh, Hamidreza Kamyab

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Urban Heat Islands (UHIs) are distinctive urban areas characterized by densely populated central cores surrounded by less densely populated peripheral lands. These areas experience elevated temperatures, primarily due to impermeable surfaces and specific land use patterns. The consequences of these temperature variations are far-reaching, impacting the environment and society negatively, leading to increased energy consumption, air pollution, and public health concerns. This paper emphasizes the need for simplified approaches to comprehend UHI temperature dynamics and explains how urban development patterns contribute to land surface temperature variation. To illustrate this relationship, the study focuses on the Guilan Plain, utilizing techniques like principal component analysis and generalized additive models. The research centered on mapping land use and land surface temperature in the low-lying area of Guilan province. Satellite data from Landsat sensors for three different time periods (2002, 2012, and 2021) were employed. Using eCognition software, a spatial unit known as a "city block" was utilized through object-based analysis. The study also applied the normalized difference vegetation index (NDVI) method to estimate land surface radiance. Predictive variables for urban land surface temperature within residential city blocks were identified categorized as intrinsic (related to the block's structure) and neighboring (related to adjacent blocks) variables. Principal Component Analysis (PCA) was used to select significant variables, and a Generalized Additive Model (GAM) approach, implemented using R's mgcv package, modeled the relationship between urban land surface temperature and predictor variables.Notable findings included variations in urban temperature across different years attributed to environmental and climatic factors. Block size, shared boundary, mother polygon area, and perimeter-to-area ratio were identified as main variables for the generalized additive regression model. This model showed non-linear relationships, with block size, shared boundary, and mother polygon area positively correlated with temperature, while the perimeter-to-area ratio displayed a negative trend. The discussion highlights the challenges of predicting urban surface temperature and the significance of block size in determining urban temperature patterns. It also underscores the importance of spatial configuration and unit structure in shaping urban temperature patterns. In conclusion, this study contributes to the growing body of research on the connection between land use patterns and urban surface temperature. Block size, along with block dispersion and aggregation, emerged as key factors influencing urban surface temperature in residential areas. The proposed methodology enhances our understanding of parameter significance in shaping urban temperature patterns across various regions, particularly in Iran.

Keywords: urban heat island, land surface temperature, LST modeling, GAM, Gilan province

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Authors: Zhidong Zhang, Zhi-Chao Zhang, Georgianna Duarte

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This study investigated the attention problems with the instrument of Achenbach System of Empirically Based Assessment (ASEBA). Two thousand eight hundred and ninety-four adolescents were surveyed by using a stratified sampling method. We examined the relationships between relevant background variables and attention problems. Multiple regression models were applied to analyze the data. Relevant variables such as sports activities, hobbies, age, grade and the number of close friends were included in this study as predictive variables. The analysis results indicated that educational environments and extracurricular activities are important factors which influence students’ attention problems.

Keywords: adolescents, ASEBA, attention problems, educational environments, stratified sampling

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Authors: Marina Sofia, Alexios Giannakopoulos, Antonia Touloudi, Dimitris C Chatzopoulos, Zoi Athanasakopoulou, Vassiliki Spyrou, Charalambos Billinis

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Fertility of dairy cattle can be affected by heat stress when the ambient temperature increases above 30°C and the relative humidity ranges from 35% to 50%. The present study was conducted on dairy cattle farms during summer months in Greece and aimed to identify the serological profile against pathogens that could affect fertility and to associate the positive serological results at herd level with temperature factors. A total of 323 serum samples were collected from clinically healthy dairy cows of 8 herds, located in Central and Northern Greece. ELISA tests were performed to detect antibodies against selected pathogens that affect fertility, namely Chlamydophila abortus, Coxiella burnetii, Neospora caninum, Toxoplasma gondii and Infectious Bovine Rhinotracheitis Virus (IBRV). Eleven climatic variables were derived from the WorldClim version 1.4. and ArcGIS V.10.1 software was used for analysis of the spatial information. Five different MaxEnt models were applied to associate the temperature variables with the locations of seropositive Chl. abortus, C. burnetii, N. caninum, T. gondii and IBRV herds (one for each pathogen). The logistic outputs were used for the interpretation of the results. ROC analyses were performed to evaluate the goodness of fit of the models’ predictions. Jackknife tests were used to identify the variables with a substantial contribution to each model. The seropositivity rates of pathogens varied among the 8 herds (0.85-4.76% for Chl. abortus, 4.76-62.71% for N. caninum, 3.8-43.47% for C. burnetii, 4.76-39.28% for T. gondii and 47.83-78.57% for IBRV). The variables of annual temperature range, mean diurnal range and maximum temperature of the warmest month gave a contribution to all five models. The regularized training gains, the training AUCs and the unregularized training gains were estimated. The mean diurnal range gave the highest gain when used in isolation and decreased the gain the most when it was omitted in the two models for seropositive Chl.abortus and IBRV herds. The annual temperature range increased the gain when used alone and decreased the gain the most when it was omitted in the models for seropositive C. burnetii, N. caninum and T. gondii herds. In conclusion, antibodies against Chl. abortus, C. burnetii, N. caninum, T. gondii and IBRV were detected in most herds suggesting circulation of pathogens that could cause infertility. The results of the spatial analyses demonstrated that the annual temperature range, mean diurnal range and maximum temperature of the warmest month could affect positively the possible pathogens’ presence. Acknowledgment: This research has been co‐financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH–CREATE–INNOVATE (project code: T1EDK-01078).

Keywords: dairy cows, seropositivity, spatial analysis, temperature factors

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Authors: Ndeye Tiguida Sarr, Onur Akpinar

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The tourism industry, being the sector that includes all the activities related to the organization and satisfaction of tourists during their trip, also has a very important role in the national economy of the host country. In order to measure the stakes of tourism on the economy, microeconomic and macroeconomic factors are elements of analysis. While microeconomics is limited to an individual perspective, macroeconomics extends to a global perspective and treats the economy as a whole by focusing on social and economic actors in general. It is in this context that this study focuses on macroeconomic variables in order to determine the factors that influence the financial performance of tourism firms in Turkey, which is one of the world's major destinations. The aim of the study is to demonstrate the relationship between macroeconomic variables and the financial performance of tourism firms. Data from 2011 to 2020 are collected, from a sample of 16 companies that represent the tourism sector in Borsa Istanbul. Tobin’s Q ratio, Market to Book ratio, Return on Invested Capital, and Return on Assets as the financial performance indicators were dependent variables of the study. Gross Domestic Products, Inflation, Interest Rates, and Unemployment as macroeconomic indicators were independent variables. Again, Size, Liquidity, Leverage, and Age were control variables of the study. According to the results, value indicators, which are Tobin’s Q ratio and Market to Book ratio, have a statistically significant relationship with Inflation, Interest Rates, and Unemployment. A negative relationship is found between value indicators and Interest rates and a positive relationship between value indicators and Unemployment and Inflation. On the other hand, there is no significant relationship between profit indicators (Return on Invested Capital and Return on Assets) and macroeconomic variables. Accordingly, Interest rates negatively affect the financial performance of tourism firms and stand out as a factor that decreases the value.

Keywords: financial performance, macroeconomic variables, panel data, Tobin Q

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Authors: Paola Utreras, Yazmina Olmos, Loreto Sanhueza

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This work shows how the learning of physics is enriched with scientific inquiry practices, achieving learning that results in the use of higher-level cognitive skills. The activities, which were carried out with students of the 3rd semester of the courses of the Faculty of Sciences of the Engineering of the Austral University of Chile, focused on the understanding of the nature of the thermodynamic variables and how they relate to each other. This, through the analysis of atmospheric data obtained in the meteorological station Miraflores, located on the campus. The proposed activities consisted of the elaboration of time series, linear analysis of variables, as well as the analysis of frequencies and periods. From their results, the students reached conclusions associated with the nature of the thermodynamic variables studied and the relationships between them, to finally make public their results in a report using scientific writing standards. It is observed that introducing topics that are close to them, interesting and which affect their daily lives allows a better understanding of the subjects, which is reflected in higher levels of approval and motivation for the subject.

Keywords: basic sciences, inquiry-based learning, scientific inquiry, thermodynamics

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Authors: Sonali Agarwal

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The investor perception about investment avenues is affected to a great degree by the current happenings, within the country, and on the global stage. The influencing events can range from government policies, bilateral trade agreements, election agendas, to changing exchange rates, appreciation and depreciation of currency, recessions, meltdowns, bankruptcies etc. The current research attempts to discover and unravel the effect of various macroeconomic variables (crude oil price, gold price, silver price and USD exchange rate) on the Indian mutual fund industry in general and the chosen funds (Axis Gold Fund, BSL Gold Fund, Kotak Gold Fund & SBI gold fund) in particular. Cointegration tests and Vector error correction equations prove that the chosen variables have strong effect on the NAVs (net asset values) of the mutual funds. However, the greatest influence is felt from the fund’s own past and current information and it is found that when an innovation of fund’s own lagged NAVs is given, variance caused is high that changes the current NAVs markedly. The study helps to highlight the interplay of macroeconomic variables and their repercussion on mutual fund industry.

Keywords: cointegration, Granger causality, impulse response, macroeconomic variables, mutual funds, stationarity, unit root test, variance decomposition, VECM

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Authors: Bry X., Trottier C., Mortier F., Cornu G., Verron T.

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We address component-based regularization of a Multivariate Generalized Linear Model (MGLM). A set of random responses Y is assumed to depend, through a GLM, on a set X of explanatory variables, as well as on a set T of additional covariates. X is partitioned into R conceptually homogeneous blocks X1, ... , XR , viewed as explanatory themes. Variables in each Xr are assumed many and redundant. Thus, Generalised Linear Regression (GLR) demands regularization with respect to each Xr. By contrast, variables in T are assumed selected so as to demand no regularization. Regularization is performed searching each Xr for an appropriate number of orthogonal components that both contribute to model Y and capture relevant structural information in Xr. We propose a very general criterion to measure structural relevance (SR) of a component in a block, and show how to take SR into account within a Fisher-scoring-type algorithm in order to estimate the model. We show how to deal with mixed-type explanatory variables. The method, named THEME-SCGLR, is tested on simulated data.

Keywords: Component-Model, Fisher Scoring Algorithm, GLM, PLS Regression, SCGLR, SEER, THEME

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Authors: Somesh Kumar Sharma, Sunanad Gupta

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The contribution of aviation to society and economy is undisputedly significant. The aviation industry drives economic and social progress by contributing prominently to tourism, commerce and improved quality of life. Identifying the amount of fuel consumed by an aircraft while moving in both airspace and ground networks is critical to air transport economics. Aviation fuel is a major operating cost parameter of the aviation industry and at the same time it is prone to various constraints. This article aims to develop a model for fuel consumption of aviation product. The paper tailors the information for the fuel consumption optimization in terms of information development, information evaluation and information refinement. The information is evaluated and refined using statistical package R and Factor Analysis which is further validated with neural networking. The study explores three primary dimensions which are finally summarized into 23 influencing variables in contrast to 96 variables available in literature. The 23 variables explored in this study should be considered as highly influencing variables for fuel consumption which will contribute significantly towards fuel optimization.

Keywords: fuel consumption, civil aviation industry, neural networking, optimization

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Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

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Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

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Authors: Zubda Zia, Zainab Masood

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This study has investigated the relationship between renewable energy, urbanization, industrialization, and economic growth in Pakistan, through the years 1990-2016. All the three explanatory variables play a pivotal role in their contribution to growth in any economy, especially a developing one such as Pakistan. Auto-regressive distributive lag (ARDL) model has been used to determine the co-integration and relationship between the variables. The empirical results indicate that there exists a positive and significant relationship between all the three variables and economic growth and that there is a stable, long-run relationship among them. Policy suggestions that incorporate the results include having a larger share of renewable energy in the energy sector, using urbanization as a means to remove the big city trend and move towards, smaller sustainable cities, etc.

Keywords: economic growth, energy crisis, industrialization, renewable energy, SGDs, urbanization

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Authors: Roikhan Mochamad Aziz

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This study aims to analze the interdependence of several variables simultaneously in order to simplify the form of the relationship between some of the variables studied a number of factors less than the variable studied which means it can also describe the data structure of a research. Based 100 respondents from the public, such as the people of South Tangerang, this study used factor analysis tool. The results of this study indicate that the studied variables being formed into nine factors, namely faith factors, community factors, factors of social care, confidence factor, factor income, educational factors, self-satisfaction factors, factors work, and knowledge factor. Total variance of the 9 factors is 67,30% means that all nine of these factors are factors that can contribute too paying zakat of muzakki consciousness of 67,30% while the remaining 32,70% is supported by other factors outside the 9 factors.

Keywords: zakat, analysis factor, faith, education, knowledge

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Authors: Antonio Oliveira, Rute F. Meneses, Nuno Trigueiros-Cunha

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Tinnitus is commonly defined as an aberrant perception of sound without external stimulus. It is a chronic condition, with consequences on the QOL. The coping strategies used were not always effective and coping was identified as a predictor of QOL in individuals with tinnitus, which reinforces the idea that in health the use of effective coping styles should be promoted. This work intend to verify relations between coping strategies assessed by BriefCope in subjects with tinnitus and variables such as gender, age and severity of tinnitus measured by THI and the Visual Analogue Scale and also hearing and hyperacusis. The results indicate that there are any statistically significant relationships between the variables assessed in relation to the results of BriefCope except in the Visual Analogue Scale. These results, indicating no relationship between almost all variables, reinforce the need for further study of coping strategies use by these patients.

Keywords: Brief Cope, coping strategies, quality of live, THI, Tinnitus

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Authors: Yo-Seph Byun, Gyu-Phil Lee, Young-Bin Park, Gye-Chun Cho, Seong-Won Lee

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In Korea, a study on Limit State Design (LSD) for underground structures is being conducted in order to perform more effective design. In this study, as a result of MCS (Monte-Carlo Simulation) technique, failure probabilities of the structure during normal and earthquake are estimated in reliability analysis. Target reliability indexes are determined depending on load combinations for underground structure, and then, design variables such as load and material factors in LSD are decided. As a result, through the research in order to determine more reliable design variables, a specification of LSD for underground structures is able to be developed.

Keywords: design variable, limit state design, target reliability index, underground structure

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Authors: Christina Kalogirou

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Investigating the integration of bioclimatic design into vernacular architecture could lead to interesting results regarding the preservation of cultural heritage while enhancing the energy efficiency of historic buildings. Furthermore, these recognized principles and systems of bioclimatic design in vernacular settlements could be applied to modern architecture and thus to new buildings in such areas. This study introduces an approach to categorizing distinct technologies and design principles of bioclimatic design based on a thoughtful approach to various climatic zones and environment in Greece (mountainous areas, islands and lowlands). For this purpose, various types of dwellings are evaluated for their response to climate, regarding the layout of the buildings (orientation, floor plans’ shape, semi-open spaces), the site planning, the openings (size, position, protection), the building envelope (walls: construction materials-thickness, roof construction detailing) and the migratory living pattern according to seasonal needs. As a result, various passive design principles (that could be adapted to current architectural practice in such areas, in order to optimize the relationship between site, building, climate and energy efficiency) are proposed.

Keywords: bioclimatic design, buildings physics, climatic zones, energy efficiency, vernacular architecture

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Authors: Chien-Jen Liu, Shu Ching Yang

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Using the technology acceptance model (TAM), this study examined the external variables of technological complexity (TC) to acquire a better understanding of the factors that influence the acceptance of computer application courses by learners at Active Aging Universities. After the learners in this study had completed a 27-hour Facebook course, 44 learners responded to a modified TAM survey. Data were collected to examine the path relationships among the variables that influence the acceptance of Facebook-mediated community learning. The partial least squares (PLS) method was used to test the measurement and the structural model. The study results demonstrated that attitudes toward Facebook use directly influence behavioral intentions (BI) with respect to Facebook use, evincing a high prediction rate of 58.3%. In addition to the perceived usefulness (PU) and perceived ease of use (PEOU) measures that are proposed in the TAM, other external variables, such as TC, also indirectly influence BI. These four variables can explain 88% of the variance in BI and demonstrate a high level of predictive ability. Finally, limitations of this investigation and implications for further research are discussed.

Keywords: technology acceptance model (TAM), technological complexity, partial least squares (PLS), perceived usefulness

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Authors: Carolina Senabre, Sergio Valero, Miguel Lopez, Antonio Gabaldon

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This paper presents a comprehensive survey of the short-term load forecasting (STLF). Since the behavior of consumers and producers continue changing as new technologies, it is an ongoing process, and moreover, new policies become available. The results of a research study for the Spanish Transport System Operator (REE) is presented in this paper. It is presented the improvement of the forecasting accuracy in the Balearic Islands considering the introduction of meteorological variables, such as temperature to reduce forecasting error. Variables analyzed for the forecasting in terms of overall accuracy are cloudiness, solar radiation, and wind velocity. It has also been analyzed the type of days to be considered in the research.

Keywords: short-term load forecasting, power demand, neural networks, load forecasting

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Authors: S. Benbellil-Tafoughalt, J. M. Koene

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Growth strategies are often plastic and influenced by environmental conditions. Terrestrial gastropods are particularly affected by seasonal and climatic variables, and growth rate and size at maturity are key traits in their life history. Therefore, we investigated juvenile growth of Helix aperta snails under four combinations of temperature and photoperiod using two sets of young snails, born in the laboratory from adults collected in either the autumn (aestivating snails) or spring (active snails). Parental snails were collected from Bakaro (Northeastern Algeria). Higher temperature increased adult size and reduced time to reproduction. Long day photoperiod also increased the final body weight, but had no effect on the length of the growth period. The season of birth had significant effects on length of the growth period and weight of hatchings, whereas this weight difference disappeared by adulthood. The spring snails took less time to develop and reached similar adult body weight as the autumn snails. These differences may be due to differences in egg size or quality between the snails from different seasons. More rapid growth in spring snails results in larger snails entering aestivation, a period with size-related mortality in this species.

Keywords: growth, Hélix aperta, photoperiod, temperature

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Authors: E. Bensaci, M. Saheb, Y. Nouidjem, A. Zoubiri, A. Bouzegag, M. Houhamdi

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The Greater flamingo is considered the flagship species of wetlands across semi-arid and Saharan regions of Africa, especially Chotts and Sebkhas, which also concentrate significant numbers of bird species. Flamingos have different status (wintering and breeder) which vary between sites in different parts of Algeria. We conducted surveys and recorded banded flamingos across distinct regions within two climatic belts: semi-arid (Hauts Plateaux) and arid (Sahara), showing the importance of these sites in the migratory flyways particularly the relation between West Mediterranean and West Africa populations. The distribution of Greater flamingos varied between sites and seasons, where the concentrations mainly were in the wide, lees deep and salt lakes. Many of the sites (17) in the surveyed area were regularly supporting at least 1% of the regional population during winter. The analysis of Greater flamingos behaviour in different climatic regions in relation showed that the feeding is the dominant diurnal activity with rates exceeding 60% of the time. While feeding varies between seasons, and showed a negative relationship with the degree of disturbance.

Keywords: Algeria, greater flamingo, Phoenicopterus roseus, Sahara, semi-arid

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Authors: Emma Serwaa Obobisaa, Haibo Chen

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International trade and outward foreign direct investment are important factors which are generally recognized in the economic growth and development. Though several scholars have struggled to reveal the influence of trade and outward foreign direct investment (FDI) on economic growth, most studies utilized common econometric models such as vector autoregression and aggregated the variables, which for the most part prompts, however, contradictory and mixed results. Thus, there is an exigent need for the precise study of the trade and FDI effect of economic growth while applying strong econometric models and disaggregating the variables into its separate individual variables to explicate their respective effects on economic growth. This will guarantee the provision of policies and strategies that are geared towards individual variables to ensure sustainable development and growth. This study, therefore, seeks to examine the causal effect of China-Africa trade and Outward Foreign Direct Investment on the economic growth of Africa using a robust and recent econometric approach such as system dynamics model. Our study impanels and tests an ensemble of a group of vital variables predominant in recent studies on trade-FDI-economic growth causality: Foreign direct ınvestment, international trade and economic growth. Our results showed that the system dynamics method provides accurate statistical inference regarding the direction of the causality among the variables than the conventional method such as OLS and Granger Causality predominantly used in the literature as it is more robust and provides accurate, critical values.

Keywords: economic growth, outward foreign direct investment, system dynamics model, international trade

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Authors: Anwar Hasan Abdullah Othman, Ahamed Kameel, Hasanuddeen Abdul Aziz

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In this study, an attempt has been made to investigate the relationship specifically the causal relation between fund unit prices of Islamic equity unit trust fund which measure by fund NAV and the selected macro-economic variables of Malaysian economy by using VECM causality test and Granger causality test. Monthly data has been used from Jan, 2006 to Dec, 2012 for all the variables. The findings of the study showed that industrial production index, political election and financial crisis are the only variables having unidirectional causal relationship with fund unit price. However, the global oil prices is having bidirectional causality with fund NAV. Thus, it is concluded that the equity unit trust fund industry in Malaysia is an inefficient market with respect to the industrial production index, global oil prices, political election and financial crisis. However, the market is approaching towards informational efficiency at least with respect to four macroeconomic variables, treasury bill rate, money supply, foreign exchange rate and corruption index.

Keywords: fund unit price, unit trust industry, Malaysia, macroeconomic variables, causality

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Authors: Minseo Jo

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The purpose of this paper is to examine the factors in the hedonic price models, that has significance impact in determining the price of apartments. There are many variables employed in the hedonic price models and their effectiveness vary differently according to the researchers and the regions they are analysing. In order to consider various conditions, the meta-regression analysis has been selected for the study. In this paper, four meta-independent variables, from the 65 hedonic price models to analysis. The factors that influence the prices of apartments, as well as including factors that influence the prices of apartments, regions, which are divided into two of the research performed, years of research performed, the coefficients of the functions employed. The covariance between the four meta-variables and p-value of the coefficients and the four meta-variables and number of data used in the 65 hedonic price models have been analyzed in this study. The six factors that are most important in deciding the prices of apartments are positioning of apartments, the noise of the apartments, points of the compass and views from the apartments, proximity to the public transportations, companies that have constructed the apartments, social environments (such as schools etc.).

Keywords: hedonic price model, housing price, meta-regression analysis, characteristics

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Authors: Hye Rim Lee, Eui Jun Jeong, Ji Hye Yoo

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This study makes an integrated investigation on how life satisfaction is associated with the Korean game users' psychological variables (self-esteem, game and life self- efficacy), social variables (bonding and bridging social capital), and demographic variables (age, gender). The data used for the empirical analysis came from a representative sample survey conducted in South Korea. Results show that self-esteem and game efficacy were an important antecedent to the degree of users’ life satisfaction. Both bonding social capital and bridging social capital enhance the level of the users’ life satisfaction. The importance of perspectives as well as their implications for the game users and further associated research, are explored.

Keywords: life satisfaction, self-esteem, game efficacy, life-efficacy, social capital

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Authors: Redouane Tlemsani, Redouane, Belkacem Kouninef, Abdelkader Benyettou

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In this paper, our system is a Markovien system which we can see it like a Dynamic Bayesian Networks. One of the major interests of these systems resides in the complete training of the models (topology and parameters) starting from training data. The Bayesian Networks are representing models of dubious knowledge on complex phenomena. They are a union between the theory of probability and the graph theory in order to give effective tools to represent a joined probability distribution on a set of random variables. The representation of knowledge bases on description, by graphs, relations of causality existing between the variables defining the field of study. The theory of Dynamic Bayesian Networks is a generalization of the Bayesians networks to the dynamic processes. Our objective amounts finding the better structure which represents the relationships (dependencies) between the variables of a dynamic bayesian network. In applications in pattern recognition, one will carry out the fixing of the structure which obliges us to admit some strong assumptions (for example independence between some variables).

Keywords: Arabic on line character recognition, dynamic Bayesian network, pattern recognition, networks

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Authors: K. Bencherif, M. Bellifa

Abstract:

The expected climatic changes in North Africa are the increase of both intensity and frequencies of the summer droughts and a reduction in water availability during growing season. The exiting coppices and forest formations in the national park of Tlemcen are dominated by holm oak, zen oak and cork oak. These opened-fragmented structures don’t seem enough strong so to hope durable protection against climate change. According to the observed climatic tendency, the objective is to analyze the climatic context and its evolution taking into account the eventual behaving of the oak species during the next 20-30 years on one side and the landscaped context in relation with the most adequate sylvicultural models to choose and especially in relation with human activities on another side. The study methodology is based on Climatic synthesis and Floristic and spatial analysis. Meteorological data of the decade 1989-2009 are used to characterize the current climate. An another approach, based on dendrochronological analysis of a 120 years sample Aleppo pine stem growing in the park, is used so to analyze the climate evolution during one century. Results on the climate evolution during the 50 years obtained through climatic predictive models are exploited so to predict the climate tendency in the park. Spatially, in each forest unit of the Park, stratified sampling is achieved so to reduce the degree of heterogeneity and to easily delineate different stands using the GPS. Results from precedent study are used to analyze the anthropogenic factor considering the forecasts for the period 2025-2100, the number of warm days with a temperature over 25°C would increase from 30 to 70. The monthly mean temperatures of the maxima’s (M) and the minima’s (m) would pass respectively from 30.5°C to 33°C and from 2.3°C to 4.8°C. With an average drop of 25%, precipitations will be reduced to 411.37 mm. These new data highlight the importance of the risk fire and the water stress witch would affect the vegetation and the regeneration process. Spatial analysis highlights the forest and the agricultural dimensions of the park compared to the urban habitat and bare soils. Maps show both fragmentation state and forest surface regression (50% of total surface). At the level of the park, fires affected already all types of covers creating low structures with various densities. On the silvi cultural plan, Zen oak form in some places pure stands and this invasion must be considered as a natural tendency where Zen oak becomes the structuring specie. Climate-related changes have nothing to do with the real impact that South-Mediterranean forests are undergoing because human constraints they support. Nevertheless, hardwoods stand of oak in the national park of Tlemcen will face up to unexpected climate changes such as changing rainfall regime associated with a lengthening of the period of water stress, to heavy rainfall and/or to sudden cold snaps. Faced with these new conditions, management based on mixed uneven aged high forest method promoting the more dynamic specie could be an appropriate measure.

Keywords: global warming, mediterranean forest, oak shrub-lands, Tlemcen

Procedia PDF Downloads 387

Authors: Malay Kumar Pramanik

Abstract:

Climate change induced sea level rise increases storm surge, erosion, and inundation, which are stirred by an intricate interplay of physical environmental components at the coastal region. The Mumbai coast is much vulnerable to accelerated regional sea level change due to its highly dense population, highly developed economy, and low topography. To determine the significant causes behind coastal vulnerability, this study analyzes four different iterations of CVI by incorporating the pixel-based differentially weighted rank values of the selected five geological (CVI5), three physical (CVI8 with including geological variables), and four socio-economic variables (CVI4). However, CVI5 and CVI8 results yielded broadly similar natures, but after including socio-economic variables (CVI4), the results CVI (CVI12) has been changed at Mumbai and Kurla coastal portion that indicates the study coastal areas are mostly sensible with socio-economic variables. Therefore, the results of CVI12 show that out of 274.1 km of coastline analyzed, 55.83 % of the coast is very low vulnerable, 60.91 % of the coast is moderately vulnerable while 50.75 % is very high vulnerable. Finding also admits that in the context of growing urban population and the increasing rate of economic activities, socio-economic variables are most important variable to use for validating and testing the CVI. Finally, some recommendations are presented for concerned decision makers and stakeholders to develop appropriate coastal management plans, nourishment projects and mitigation measures considering socio-economic variables.

Keywords: coastal vulnerability index, sea level change, Mumbai coast, geospatial approach, coastal management, climate change

Procedia PDF Downloads 127

Authors: Farooq A. Al-Sheikh, Ali Elkamel, William A. Anderson

Abstract:

A fluidized catalytic cracking unit (FCCU) is one of the effective units in many refineries. Modeling and optimization of FCCU were done by many researchers in past decades, but in this research, comparison between post- and oxy-combustion was studied in the regenerator-FCCU. Therefore, a simplified mathematical model was derived by doing mass/heat balances around both reactor and regenerator. A state space analysis was employed to show effects of the flow rates variables such as air, feed, spent catalyst, regenerated catalyst and flue gas on the output variables. The main aim of studying dynamic responses is to figure out the most influencing variables that affect both reactor/regenerator temperatures; also, finding the upper/lower limits of the influencing variables to ensure that temperatures of the reactors and regenerator work within normal operating conditions. Therefore, those values will be used as side constraints in the optimization technique to find appropriate operating regimes. The objective functions were modeled to be maximizing the energy in the reactor while minimizing the energy consumption in the regenerator. In conclusion, an oxy-combustion process can be used instead of a post-combustion one.

Keywords: FCCU modeling, optimization, oxy-combustion, post-combustion

Procedia PDF Downloads 206

Authors: Lu Ren, You-Liang Fang, Yan-Gang Zhao

Abstract:

In recent years, the application of BIM (Building Information Modelling) to construction schedule plan has been the focus of more and more researchers. In order to assess the reasonable level of the BIM-based construction schedule plan, that is whether the schedule can be completed on time, some researchers have introduced reliability theory to evaluate. In the process of evaluation, the uncertain factors affecting the construction schedule plan are regarded as random variables, and probability distributions of the random variables are assumed to be normal distribution, which is determined using two parameters evaluated from the mean and standard deviation of statistical data. However, in practical engineering, most of the uncertain influence factors are not normal random variables. So the evaluation results of the construction schedule plan will be unreasonable under the assumption that probability distributions of random variables submitted to the normal distribution. Therefore, in order to get a more reasonable evaluation result, it is necessary to describe the distribution of random variables more comprehensively. For this purpose, cubic normal distribution is introduced in this paper to describe the distribution of arbitrary random variables, which is determined by the first four moments (mean, standard deviation, skewness and kurtosis). In this paper, building the BIM model firstly according to the design messages of the structure and making the construction schedule plan based on BIM, then the cubic normal distribution is used to describe the distribution of the random variables due to the collecting statistical data of the random factors influencing construction schedule plan. Next the reliability analysis of the construction schedule plan based on BIM can be carried out more reasonably. Finally, the more accurate evaluation results can be given providing reference for the implementation of the actual construction schedule plan. In the last part of this paper, the more efficiency and accuracy of the proposed methodology for the reliability analysis of the construction schedule plan based on BIM are conducted through practical engineering case.

Keywords: BIM, construction schedule plan, cubic normal distribution, reliability analysis

Procedia PDF Downloads 138