The purpose of this study is to investigate the effect of using Bicarbonate and Calcium parameters as alternatives to the lithostratigraphic units covered the catchment area, on water quality index (WQI) values that h...The purpose of this study is to investigate the effect of using Bicarbonate and Calcium parameters as alternatives to the lithostratigraphic units covered the catchment area, on water quality index (WQI) values that have been implemented with GIS technique at Wadi Al-Arab Dam. The analyzed results (by WQI method) have been used to depict water quality for the two approaches. Based on physico-chemical parameters, the calculated values for WQI over the 3-year for study period were 169, 168, and 157, respectively. While the WQI values were 184, 183 and 172, respectively, as a result of incorporated Bicarbonate and Calcium parameters in WQI calculations that significantly contributed to increasing the WQI. The elevated values may be attributed to the influence of carbonate stone dissolution and mechanical erosion under weathering conditions that are prevalent during winter season in the catchment area. As a consequence of lithostratigraphic unites product and GIS technique integration and normalization processes, most of water quality ranks are good and only autumn season has poor water quality in the 2012 and 2013, while in 2014 it has good water quality in the same season. The WQI values increase in general trend from winter to autumn seasons during the study period that may be referred to outflow by daily consumption, evaporation rising, and seepage water. The analysis shows that the modified water quality values of the Wadi Al-Arab Dam Reservoir (WADR) vary after using Bicarbonate and Calcium parameters by constant value. Generally, the results signify that the WADR is not polluted based on the physical and chemical characteristics of water.展开更多
In this paper, three rock types including Sandstone, Mudstone, and Crystalline Gypsum were part of a laboratory study conducted to develop a dataset for predicting the unconfined compressive strength of UAE intact sed...In this paper, three rock types including Sandstone, Mudstone, and Crystalline Gypsum were part of a laboratory study conducted to develop a dataset for predicting the unconfined compressive strength of UAE intact sedimentary rock specimens. Four hundred nineteen rock samples from various areas along the coastal region of the UAE were collected and tested for the development of this dataset and evaluation of models. From the statistical analysis of the data, regression equations were established among rock parameters and correlations were expressed and compared by the ones proposed in literature.展开更多
To categorize the nations to reflect the development status, to date, there are many conceptual frameworks. The Human Development index (HDI) that is published by the United Nations Development Programme is widely acc...To categorize the nations to reflect the development status, to date, there are many conceptual frameworks. The Human Development index (HDI) that is published by the United Nations Development Programme is widely accepted and practiced by many people such as academicians, politicians, and donor organizations. However, though the development of HDI has gone through many revisions since its formulation in 1990, even the current version of the index formulation published in 2016 needs research to better understand and to gap-fill the knowledge base that can enhance the index formulation to facilitate the direction of attention such as release of funds. Therefore, in this paper, based on principal component analysis and K-means clustering algorithm, the data that reflect the measures of life expectancy index (LEI), education index (EI), and income index (II) are analyzed to categorize and to rank the member states of the UN using R statistical software package, an open source extensible programming language for statistical computing and graphics. The outcome of the study shows that the proportion of total eigen value (i.e., proportion of total variance) explained by PCA-1 (i.e., first principal component) accounts for more than 85% of the total variation. Moreover, the proportion of total eigen value explained by PCA-1 increases with time (i.e., yearly) though the amount of increase with time is not significant. However, the proportions of total eigen value explained by PCA-2 and PCA-3 decrease with time. Therefore, the loss of information in choosing PCA-1 to represent the chosen explanatory variables (i.e., LEI, EI, and II) may diminish with time if the trend of increasing pattern of proportion of total eigen value explained by PCA-1 with time continues in the future as well. On the other hand, the correlation between EI and PCA-1 increases with time although the magnitude of increase is not that significant. This same trend is observed in II as well. However, in contrast to these observations, the correlation between PCA-1 and LEI decreases with time. These findings imply that the contributions of EI and II to PCA-1 increase with time, but the contribution of LEI to PCA-1 decreases with time. On top of these, as per Hopkins statistic, the clusterability of the information conveyed by PCA-1 alone is far better than the clusterability of the information conveyed by PCA scores (i.e., PCA-1, PCA-2, and PCA-3) and the explanatory variables. Therefore, choosing PCA-1 to represent the chosen explanatory variables is becoming more concrete.展开更多
文摘The purpose of this study is to investigate the effect of using Bicarbonate and Calcium parameters as alternatives to the lithostratigraphic units covered the catchment area, on water quality index (WQI) values that have been implemented with GIS technique at Wadi Al-Arab Dam. The analyzed results (by WQI method) have been used to depict water quality for the two approaches. Based on physico-chemical parameters, the calculated values for WQI over the 3-year for study period were 169, 168, and 157, respectively. While the WQI values were 184, 183 and 172, respectively, as a result of incorporated Bicarbonate and Calcium parameters in WQI calculations that significantly contributed to increasing the WQI. The elevated values may be attributed to the influence of carbonate stone dissolution and mechanical erosion under weathering conditions that are prevalent during winter season in the catchment area. As a consequence of lithostratigraphic unites product and GIS technique integration and normalization processes, most of water quality ranks are good and only autumn season has poor water quality in the 2012 and 2013, while in 2014 it has good water quality in the same season. The WQI values increase in general trend from winter to autumn seasons during the study period that may be referred to outflow by daily consumption, evaporation rising, and seepage water. The analysis shows that the modified water quality values of the Wadi Al-Arab Dam Reservoir (WADR) vary after using Bicarbonate and Calcium parameters by constant value. Generally, the results signify that the WADR is not polluted based on the physical and chemical characteristics of water.
文摘In this paper, three rock types including Sandstone, Mudstone, and Crystalline Gypsum were part of a laboratory study conducted to develop a dataset for predicting the unconfined compressive strength of UAE intact sedimentary rock specimens. Four hundred nineteen rock samples from various areas along the coastal region of the UAE were collected and tested for the development of this dataset and evaluation of models. From the statistical analysis of the data, regression equations were established among rock parameters and correlations were expressed and compared by the ones proposed in literature.
文摘To categorize the nations to reflect the development status, to date, there are many conceptual frameworks. The Human Development index (HDI) that is published by the United Nations Development Programme is widely accepted and practiced by many people such as academicians, politicians, and donor organizations. However, though the development of HDI has gone through many revisions since its formulation in 1990, even the current version of the index formulation published in 2016 needs research to better understand and to gap-fill the knowledge base that can enhance the index formulation to facilitate the direction of attention such as release of funds. Therefore, in this paper, based on principal component analysis and K-means clustering algorithm, the data that reflect the measures of life expectancy index (LEI), education index (EI), and income index (II) are analyzed to categorize and to rank the member states of the UN using R statistical software package, an open source extensible programming language for statistical computing and graphics. The outcome of the study shows that the proportion of total eigen value (i.e., proportion of total variance) explained by PCA-1 (i.e., first principal component) accounts for more than 85% of the total variation. Moreover, the proportion of total eigen value explained by PCA-1 increases with time (i.e., yearly) though the amount of increase with time is not significant. However, the proportions of total eigen value explained by PCA-2 and PCA-3 decrease with time. Therefore, the loss of information in choosing PCA-1 to represent the chosen explanatory variables (i.e., LEI, EI, and II) may diminish with time if the trend of increasing pattern of proportion of total eigen value explained by PCA-1 with time continues in the future as well. On the other hand, the correlation between EI and PCA-1 increases with time although the magnitude of increase is not that significant. This same trend is observed in II as well. However, in contrast to these observations, the correlation between PCA-1 and LEI decreases with time. These findings imply that the contributions of EI and II to PCA-1 increase with time, but the contribution of LEI to PCA-1 decreases with time. On top of these, as per Hopkins statistic, the clusterability of the information conveyed by PCA-1 alone is far better than the clusterability of the information conveyed by PCA scores (i.e., PCA-1, PCA-2, and PCA-3) and the explanatory variables. Therefore, choosing PCA-1 to represent the chosen explanatory variables is becoming more concrete.
