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Niaz R, Iqbal N, Al-Ansari N, Hussain I, Elsherbini Elashkar E, Shamshoddin Soudagar S, Gani SH, Mohamd Shoukry A, Sh. Sammen S. A new spatiotemporal two-stage standardized weighted procedure for regional drought analysis. PeerJ 2022; 10:e13249. [PMID: 35529495 PMCID: PMC9070328 DOI: 10.7717/peerj.13249] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 03/21/2022] [Indexed: 01/13/2023] Open
Abstract
Drought is a complex phenomenon that occurs due to insufficient precipitation. It does not have immediate effects, but sustained drought can affect the hydrological, agriculture, economic sectors of the country. Therefore, there is a need for efficient methods and techniques that properly determine drought and its effects. Considering the significance and importance of drought monitoring methodologies, a new drought assessment procedure is proposed in the current study, known as the Maximum Spatio-Temporal Two-Stage Standardized Weighted Index (MSTTSSWI). The proposed MSTTSSWI is based on the weighting scheme, known as the Spatio-Temporal Two-Stage Standardized Weighting Scheme (STTSSWS). The potential of the weighting scheme is based on the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and the steady-state probabilities. Further, the STTSSWS computes spatiotemporal weights in two stages for various drought categories and stations. In the first stage of the STTSSWS, the SPI, SPEI, and the steady-state probabilities are calculated for each station at a 1-month time scale to assign weights for varying drought categories. However, in the second stage, these weights are further propagated based on spatiotemporal characteristics to obtain new weights for the various drought categories in the selected region. The STTSSWS is applied to the six meteorological stations of the Northern area, Pakistan. Moreover, the spatiotemporal weights obtained from STTSSWS are used to calculate MSTTSSWI for regional drought characterization. The MSTTSSWI may accurately provide regional spatiotemporal characteristics for the drought in the selected region and motivates researchers and policymakers to use the more comprehensive and accurate spatiotemporal characterization of drought in the selected region.
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Affiliation(s)
- Rizwan Niaz
- Statistics, Quaid-i-Azam University, Islamabad, Punjab, Pakistan
| | - Nouman Iqbal
- Statistics, Quaid-i-Azam University, Islamabad, Punjab, Pakistan,Knowledge unit of business Economics accountancy and Commerce (KUBEAC), University of management and technology Sialkot campus, Sialkot, Pakistan
| | - Nadhir Al-Ansari
- Department of Civil, Environmental and Natural Resources Engineering, Lulea University of Technology, Lulea, Sweden
| | - Ijaz Hussain
- Statistics, Quaid-i-Azam University, Islamabad, Punjab, Pakistan
| | | | - Sadaf Shamshoddin Soudagar
- College of Business Administration, King Saud University Riyadh, Riyadh, Saudi Arabia, Riyadh, Saudi Arabia
| | - Showkat Hussain Gani
- Business Administration, College of Business Administration, King Saud University Riyadh, Saudi Arabia, Riyadh, Riyadh, Saudi Arabia
| | - Alaa Mohamd Shoukry
- Arriyadh Community College, King Saud University, Riyadh, Saudi Arabia,Workers University, KSA, Nsar, Egypt, Egypt
| | - Saad Sh. Sammen
- Department of Civil Engineering, Coolege of Engineering, University of Diyala, Diyala Governorate, Iraq
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Dong D, Malik HA, Liu Y, Elashkar EE, Shoukry AM, Khader JA. Battling for Consumer's Positive Purchase Intention: A Comparative Study Between Two Psychological Techniques to Achieve Success and Sustainability for Digital Entrepreneurships. Front Psychol 2021; 12:665194. [PMID: 34054669 PMCID: PMC8160311 DOI: 10.3389/fpsyg.2021.665194] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Accepted: 03/22/2021] [Indexed: 01/21/2023] Open
Abstract
This research focuses on students' online purchase intentions in Pakistan toward different products available for sale on numerous e-business websites. This study's main objective is to determine which methodology is better to enhance customer online purchase intention. It also aims to discover how to improve perceived benefits and lower perceived risks associated with any available online product and entrepreneurship. AMOS 24 has been used to deal with the mediation in study design with bootstrap methodology. The study was conducted on 250 students from different educational institutes in Pakistan using a simple random sampling technique. A finding of this study suggests that both methods positively impact online purchase intention of consumers and sustainable digital economy. But social media advertisement is more effective through enhancing the perceived benefits of products. In contrast, product content factors are more effective at lowering the perceived risks associated with available online products.
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Affiliation(s)
- Dandan Dong
- School of Journalism and Communication, Nanjing University, Nanjing, China
| | - Haider Ali Malik
- FAST School of Management, National University of Computer and Emerging Sciences, Islamabad, Pakistan
| | - Yaoping Liu
- Department of Business Administration, Rajamangala University of Technology Krungthep, Bangkok, Thailand
- Department of Business Administration, Mahidol University, Salaya, Thailand
| | - Elsayed Elsherbini Elashkar
- Administrative Sciences Department, Community College, King Saud University, Riyadh, Saudi Arabia
- Applied Statistics Department, Faculty of Commerce, Mansoura University, Mansoura, Egypt
| | - Alaa Mohamd Shoukry
- Arriyadh Community College, King Saud University, Riyadh, Saudi Arabia
- Department of Business Administration, KSA Workers University, Nsar, Egypt
| | - J. A. Khader
- College of Business Administration, King Saud University Muzahimiyah, Al-Muzahmiyya, Saudi Arabia
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Shaukat MH, Hussain I, Faisal M, Al-Dousari A, Ismail M, Shoukry AM, Elashkar EE, Gani S. Monthly drought prediction based on ensemble models. PeerJ 2020; 8:e9853. [PMID: 33194356 PMCID: PMC7485508 DOI: 10.7717/peerj.9853] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Accepted: 08/11/2020] [Indexed: 11/20/2022] Open
Abstract
Drought is a natural hazard, which is a result of a prolonged shortage of precipitation, high temperature and change in the weather pattern. Drought harms society, the economy and the natural environment, but it is difficult to identify and characterize. Many areas of Pakistan have suffered severe droughts during the last three decades due to changes in the weather pattern. A drought analysis with the incorporation of climate information has not yet been undertaken in this study region. Here, we propose an ensemble approach for monthly drought prediction and to define and examine wet/dry events. Initially, the drought events were identified by the short term Standardized Precipitation Index (SPI-3). Drought is predicted based on three ensemble models i.e., Equal Ensemble Drought Prediction (EEDP), Weighted Ensemble Drought Prediction (WEDP) and the Conditional Ensemble Drought Prediction (CEDP) model. Besides, two weighting procedures are used for distributing weights in the WEDP model, such as Traditional Weighting (TW) and the Weighted Bootstrap Resampling (WBR) procedure. Four copula families (i.e., Frank, Clayton, Gumbel and Joe) are used to explain the dependency relation between climate indices and precipitation in the CEDP model. Among all four copula families, the Joe copula has been found suitable for most of the times. The CEDP model provides better results in terms of accuracy and uncertainty as compared to other ensemble models for all meteorological stations. The performance of the CEDP model indicates that the climate indices are correlated with a weather pattern of four meteorological stations. Moreover, the percentage occurrence of extreme drought events that have appeared in the Multan, Bahawalpur, Barkhan and Khanpur are 1.44%, 0.57%, 2.59% and 1.71%, respectively, whereas the percentage occurrence of extremely wet events are 2.3%, 1.72%, 0.86% and 2.86%, respectively. The understanding of drought pattern by including climate information can contribute to the knowledge of future agriculture and water resource management.
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Affiliation(s)
| | - Ijaz Hussain
- Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan
| | - Muhammad Faisal
- Faculty of Health Studies, University of Bradford, Bradford, United Kingdom.,Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, United Kingdom
| | | | - Muhammad Ismail
- Department of Statistics, COMSATS University Islamabad, Lahore Campus, Lahore, Pakistan
| | - Alaa Mohamd Shoukry
- Arriyadh Community College, King Saud University, Riyadh, Saudi Arabia.,KSA, Workers University Egypt, Nasr, Egypt
| | - Elsayed Elsherbini Elashkar
- Administrative Sciences Department, Community College, King Saud University, Riyadh, Saudi Arabia.,Applied Statistics Department, Faculty of Commerce, Mansoura University, Mansoura, Egypt
| | - Showkat Gani
- College of Business Administration, King Saud University, Muzahimiyah, Saudi Arabia
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Shaukat MH, Al-Dousari A, Hussain I, Faisal M, Ismail M, Mohamd Shoukry A, Elashkar EE, Gani S. Evaluation of wet and dry event's trend and instability based on the meteorological drought index. PeerJ 2020; 8:e9729. [PMID: 32904207 PMCID: PMC7451013 DOI: 10.7717/peerj.9729] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Accepted: 07/24/2020] [Indexed: 11/20/2022] Open
Abstract
A temporal imbalance in the water availability, which is consistently below average or more than average rainfall, can lead to extremely dry or wet conditions. This impacts on agricultural yields, water resources and human activities. Weather instabilities and trends of wet/dry events have not yet been explored in Pakistan. In this study, we have two-fold objectives: (1) evaluate the weather instabilities, and (2) the trend of dry/wet events of selected stations of Pakistan. To observe weather instabilities, we used Mean Marginal Hilbert Spectrum (MMHS) and Continuous Wavelet Power Spectrum (CWPS) as meteorological series are mostly non-linear and non-stationary. We used Ensemble Empirical Mode Decomposition (EEMD) for the analysis of temporal characteristics of dry/wet events. We found that all stations are facing severe weather instabilities during the short period of 5 and 10 months using MMHS method and CWPS has shown the weather instabilities during 4 to 32 months of periodicity for all stations. Ultimately, the achieved short-term weather instabilities indicated by MMHS is consistent with CWPS. In summary, these findings might be useful for water resource management and policymakers.
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Affiliation(s)
| | | | - Ijaz Hussain
- Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan
| | - Muhammad Faisal
- Faculty of Health Studies, University of Bradford, Bradford, United Kingdom.,Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Muhammad Ismail
- Department of Statistics, COMSATS University Islamabad, Lahore Campus, Lahore, Pakistan
| | - Alaa Mohamd Shoukry
- Arriyadh Community College, King Saud University, Riyadh, Saudi Arabia.,KSA workers University, Nsar, Egypt
| | - Elsayed Elsherbini Elashkar
- Administrative Sciences Department, Community College, King Saud University, Riyadh, Saudi Arabia.,Applied Statistics Department, Faculty of Commerce, Mansoura University, Mansoura, Egypt
| | - Showkat Gani
- College of Business Administration, King Saud University, Muzahimiyah, Saudi Arabia
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Nazir HM, Hussain I, Faisal M, Elashkar EE, Shoukry AM. Improving the prediction accuracy of river inflow using two data pre-processing techniques coupled with data-driven model. PeerJ 2019; 7:e8043. [PMID: 31871832 PMCID: PMC6921981 DOI: 10.7717/peerj.8043] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Accepted: 10/16/2019] [Indexed: 11/20/2022] Open
Abstract
River inflow prediction plays an important role in water resources management and power-generating systems. But the noises and multi-scale nature of river inflow data adds an extra layer of complexity towards accurate predictive model. To overcome this issue, we proposed a hybrid model, Variational Mode Decomposition (VMD), based on a singular spectrum analysis (SSA) denoising technique. First, SSA his applied to denoise the river inflow data. Second, VMD, a signal processing technique, is employed to decompose the denoised river inflow data into multiple intrinsic mode functions (IMFs), each with a relative frequency scale. Third, Empirical Bayes Threshold (EBT) is applied on non-linear IMF to smooth out. Fourth, predicted models of denoised and decomposed IMFs are established by learning the feature values of the Support Vector Machine (SVM). Finally, the ensemble predicted results are formulated by adding the predicted IMFs. The proposed model is demonstrated using daily river inflow data from four river stations of the Indus River Basin (IRB) system, which is the largest water system in Pakistan. To fully illustrate the superiority of our proposed approach, the SSA-VMD-EBT-SVM hybrid model was compared with SSA-VMD-SVM, VMD-SVM, Empirical Mode Decomposition (EMD) based i.e., EMD-SVM, SSA-EMD-SVM, Ensemble EMD (EEMD) based i.e., EEMD-SVM and SSA-EEMD-SVM. We found that our proposed hybrid SSA-EBT-VMD-SVM model outperformed than others based on following performance measures: the Nash-Sutcliffe Efficiency (NSE), Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE). Therefore, SSA-VMD-EBT-SVM model can be used for water resources management and power-generating systems using non-linear time series data.
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Affiliation(s)
| | - Ijaz Hussain
- Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan
| | - Muhammad Faisal
- Faculty of Health Studies, University of Bradford, Bradford, United Kingdom
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, United Kingdom
| | | | - Alaa Mohamd Shoukry
- Arriyadh Community College, King Saud University, Riyadh, Saudi Arabia
- KSA workers University, Egypt, KSA, Egypt
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