Offline printed Sindhi optical text recognition: survey

Optical Charter Recognition (OCR) applications are becoming more intensive than before and show great prospective for rapid data entry, but has limited success when applied to the Sindhi language. This paper summarize the general topic of optical character recognition and highlights the characteristics of Sindhi script. It also presents an historical review of the Sindhi text recognition systems. More this paper underlines the capabilities of different OCT=R systems, and then introduce a five stage model for off-line printed Sindhi text recognition system and classify research work according to this mode

Revised and extended social commerce technology adoption in e-business of Pakistan

Social commerce is a new perspective change in modern electronic business procedures bringing together individuals on social media sites and opens up another electronic social marketing channel to establish business. In developing countries like Pakistan, e-business can help organizations using social commerce and social marketing intelligently on particular social network sites to grasp their business clients while they are interacting with their online community on the social media sites. This study investigated consumers’ behavior towards adoption of social commerce and introduced a revised and extended social commerce technology model. The investigation proved the proposed model is valid by confirming loading factor, Kaiser-Mayer-Olkin (KMO), reliability analysis, and structural equation modeling approach for hypotheses tests. The study found Perceived Ease of Use (PEU), Perceived Usefulness (PU), Social Media Influence (SMI), and Risk (RI) have significant impact on social commerce adoption in e-business of Pakistan. More, Trust (TR) and Web experience (WXP) were insignificant that revealed the preventive behavior towards adoption of social commerce in e-business of Pakistan

Overview of Disaster Preparedness and Response Strategies Regarding COVID-19 Crisis Control for Public Safety and Health Protection

The ongoing Coronavirus Disease 2019 (COVID-19) outbreak has incurred tremendous human, social, and economic costs, globally. Major economies across all continents are struggling to contain the COVID-19 pandemic and to flatten the infected curve.  This study focuses on critically reviewing the strategies opted globally to control COVID-19. The main objective of this paper is to overview the pandemic conditions, responses of the public, and actions of the governments with  the  aim to  highlight  the  importance  of  public health  preparedness  and  risk  management  strategies. The current study    uses    an    organized    method    of    locating,    assembling, summarizing, and evaluating the literature on COVID-19 control strategies adopted in different countries. It overviews the conditions of the COVID-19 pandemic in the countries hardest hit by it. The study uses the systemic literature review method to overview, summarize, and organize the literature regarding COVID-19 spread control strategies. A comprehensive Disaster Management and Response System (DMRS) strategy can be productive in limiting the pandemic spread and may also help to flatten the curve. The current study,  based  on  the  experiences of different  countries,  frames  a DMRS  strategy  to  contain  COVID-19  which  includes immediate government intervention, early recognition of the crisis, removal of cognitive  and confirmation biases,  political  and  religious biases, consensus development,  establishment  of a central  command  and control   center,   public   engagement,   integration   of   institutional functioning  using  ICT,  maintaining the medical  supply  chain, limiting  public  mobility  and  mass  gathering,  practicing  social distancing,    quarantining    and    isolation,    clear    and    effective communication for information dissemination, massive testing, and the use of ICT for information sharing, alerting, contact tracing and surveillance

Evaluating and Prioritizing the Green Infrastructure Finance Risks for Sustainable Development in China

China has become a global leader in green infrastructure finance, investing heavily in renewable energy, sustainable transportation, and green buildings. However, there are multiple risks and challenges that impede the development of green infrastructure finance. Thus, this study analyzes and prioritizes the risks associated with green infrastructure finance in China and proposes policy plans to mitigate these risks. A Fuzzy analytical hierarchy process (AHP) is used to identify the main risks associated with green infrastructure finance. The main risks are further decomposed into sub-risks. After, the Fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method is used to prioritize the key policy plans to mitigate risks and sub-risks. The results of Fuzzy AHP show that policy and regulations are the most significant risk associated with green infrastructure finance in China, followed by financial risks, and technical risks. The results of Fuzzy VIKOR reveal that increasing the availability of financing options is the most crucial policy plan to mitigate the risks and sub-risks for green infrastructure finance. The developed standardized technical guidelines and procedures and a legal and regulatory framework are ranked second and third are the most effective and feasible policy plans

The selection of wind power project location in the Southeastern Corridor of Pakistan: A factor analysis, AHP, and fuzzy-TOPSIS application

Pakistan has sufficient wind energy potential across various locations of the country. However, so far, wind energy development has not attained sufficient momentum matching its potential. Amongst various other challenges, the site selection for wind power development has always been a primary concern of the decision-makers. Principally, wind project site selection decisions are driven by various multifaceted criteria. As such, in this study, a robust research framework comprising of factor analysis (FA) of techno-economic and socio-political factors, and a hybrid analytical hierarchy process (AHP) and fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) have been used for the prioritization of sites in the southeastern region of Pakistan. The results of this study reveal economic and land acquisition as the most significant criteria and sub-criteria, respectively. From the eight different sites considered, Jamshoro has been prioritized as the most suitable location for wind project development followed by Hyderabad, Nooriabad, Gharo, Keti Bandar, Shahbandar, Sajawal, and Talhar. This study provides a comprehensive decision support framework comprising of FA and a hybrid AHP and Fuzzy TOPSIS for the systematic analysis to prioritize suitable sites for the wind project development in Pakistan

Analysis of the Impact of Economic Policy Uncertainty on Environmental Sustainability in Developed and Developing Economies

The literature on the impact of policy uncertainty on climate change has grown rapidly in recent years as policymakers and researchers have become increasingly concerned about the potential adverse effects of policy uncertainty on environmental sustainability. This study aims to investigate the impact of economic policy uncertainty (EPU), GDP per capita, renewable energy consumption (REC), and foreign direct investment (FDI) on environmental sustainability from the perspectives of the environmental Kuznets curve (EKC) and pollution halo/haven hypotheses. The research employs panel data analysis techniques, including panel corrected standard errors (PCSE) and generalized least squares (GLS), to analyze the data from a panel of 19 developed and developing countries from 2001 to 2019. The results reveal that EPU, GDP per capita, REC, and FDI significantly impact GHG emissions, contributing to climate change. The results of the study confirm a U-shaped EKC and pollution haven hypothesis in the selected economies. The findings of this study provide valuable insights for policymakers, as they highlight the need to consider the interplay between economic growth, foreign investment, and environmental policy in addressing climate change. The results also suggest that reducing policy uncertainty and promoting sustainable economic growth can mitigate the effects of climate change and ensure environmental sustainability

Sustainable and Special Economic Zone Selection under Fuzzy Environment: A Case of Pakistan

The establishment of Special Economic Zones (SEZs) is a lengthy, expensive, and long-term orientated endeavor. Proper selection of SEZs is indispensable to meet the objectives of export-led growth and value up-gradation. Consideration of sustainability issues in such planning under the Zone 3.0 paradigm is critical to achieve Sustainable Development Goals (SDGs) by 2030. Multiple key factors such as location, linkages, labor force, suitability of industries, incentives and facilitation, and market orientation are important in decision-making process of establishing SEZs. Furthermore, environmental conditions and resource availability need to be considered in the planning and policy making processes to keep symmetry in the natural environment and ecosystem of the areas under consideration for SEZs. The present study uses Multi-Criteria Decision Analysis (MCDA) methods in the perspectives of green industrial zone planning and development in Pakistan under the flagship project of China-Pakistan Economic Corridor (CPEC) of China’s Belt and Road Initiative (BRI). This research uses Delphi method, Analytical Hierarchy Process (AHP), and the Fuzzy Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR). The Delphi method has been used to identify the main criteria, sub-criteria, and their weights for 3 SEZs under consideration. The results of AHP analysis unfolded that the majority of the experts believe the location and land aspect is the most pivotal criteria in setting SEZs followed by linkages, subsidies, and facilities criteria. Finally, the results of Fuzzy VIKOR analysis considering environmental sustainability reveals that Faisalabad SEZ is the best suited under given criteria and sub-criteria

Examining and prioritizing the effect of sustainable energy on the job market to advance China's green workforce

China, the world's greatest emitter of greenhouse gases, has committed to reaching peak carbon dioxide emissions by 2030 and carbon neutrality by 2060. One strategy to accomplish this aim is switching to a low-carbon economy via advancing renewable energy (RE) projects. Therefore, this study focuses on solar, wind, biomass, and hydropower and examines the beneficial employment effects of RE projects in China. The study uses fuzzy-based Multi-Criteria Decision Making (MCDM) methodologies, such as the Analytical Hierarchy Process (AHP) and Weighted Aggregated Sum Product Assessment (WASPAS), to evaluate numerous employment effect criteria and sub-criteria. Based on these evaluations, the report prioritizes four main types of RE projects. According to the fuzzy AHP technique results, direct employment, skill requirements, and local employment are the most crucial employment effect factors. The study then employed the fuzzy WASPAS approach to assessing various RE initiatives' employment prospects. According to the findings, hydropower is the best choice for creating jobs, followed by wind and solar power initiatives. In recent years, the hydro, wind, and solar power industries have experienced rapid expansion, creating numerous job possibilities in production, installation, operation, and maintenance. Additionally, creating RE projects can boost regional economic growth and lessen poverty

The Selection of Wind Power Project Location in the Southeastern Corridor of Pakistan: A Factor Analysis, AHP, and Fuzzy-TOPSIS Application

Pakistan has sufficient wind energy potential across various locations of the country. However, so far, wind energy development has not attained sufficient momentum matching its potential. Amongst various other challenges, the site selection for wind power development has always been a primary concern of the decision-makers. Principally, wind project site selection decisions are driven by various multifaceted criteria. As such, in this study, a robust research framework comprising of factor analysis (FA) of techno-economic and socio-political factors, and a hybrid analytical hierarchy process (AHP) and fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) have been used for the prioritization of sites in the southeastern region of Pakistan. The results of this study reveal economic and land acquisition as the most significant criteria and sub-criteria, respectively. From the eight different sites considered, Jamshoro has been prioritized as the most suitable location for wind project development followed by Hyderabad, Nooriabad, Gharo, Keti Bandar, Shahbandar, Sajawal, and Talhar. This study provides a comprehensive decision support framework comprising of FA and a hybrid AHP and Fuzzy TOPSIS for the systematic analysis to prioritize suitable sites for the wind project development in Pakistan

Off-Grid Solar PV Power Generation System in Sindh, Pakistan: A Techno-Economic Feasibility Analysis

The off-grid solar photovoltaic (PV) system is a significant step towards electrification in the remote rural regions, and it is the most convenient and easy to install technology. However, the strategic problem is in identifying the potential of solar energy and the economic viability in particular regions. This study, therefore, addresses this problem by evaluating the solar energy potential and economic viability for the remote rural regions of the Sindh province, Pakistan. The results recommended that the rural regions of Sindh have suitable solar irradiance to generate electricity. An appropriate tilt angle has been computed for the selected rural regions, which significantly enhances the generation capacity of solar energy. Moreover, economic viability has been undertaken in this study and it was revealed that the off-grid solar PV power generation system provides electricity at the cost of Pakistani Rupees (PKR) 6.87/kWh and is regarded as much cheaper than conventional energy sources, i.e., around PKR 20.79/kWh. Besides, the off-grid solar PV power generation system could mitigate maximum CO2 annually on the condition that all of the selected remote rural regions adopt the off-grid solar PV system. Therefore, this study shall help the government to utilize the off-grid solar PV power generation system in the remote rural regions of Pakistan