Analysis the Gap Between Existing and Required Facilities of Health and Education in District Tharparker

Tharparkar, situated within the arid regions of Sindh province, faces significant challenges as a result of its arid conditions and shifting climate patterns. These changes represent substantial threats to the well-being and livelihoods of the local community. This study attempts to investigate the disparity between existing and required health and education facilities in district Tharparker. The study delves into the challenges faced by the region in meeting the growing needs of its population in terms of healthcare and education services. Data was collected from recent Census reports i.e. Pakistan Bureau of Statistics 2017 and through key informant interviews. Through data analysis, the research sheds light on the factors contributing to the gap and proposes potential solutions to bridge the divide. Results of the study show that there is low enrollment of students in schools and present health facilities and staff isn’t enough to serve the existing population of district Tharparker. The findings underscore the importance of addressing these gaps to enhance the overall well-being and development of Tharparker's residents. This study is significant in a way that it will provide a way forward to government authorities and other supporting agencies in formulating effective plans for addressing the deficiencies (regarding health and education facilities

Investigating the Normality of Data Set Collected to Resolve the Accessibility Issues of Badin Sub-Region, Sindh, Pakistan

To highlight the accessibility issues of rural households, the data were collected from the rural subregion of Badin, Sindh, Pakistan. The purpose of the data-collection was to offer policy proposal?s inputs, as concerned planning agencies could be able to know the ground realities and implement their planned decisions accordingly. Therefore, the aim of this study was to investigate about the normality of the data, collected through the questionnaire survey from the sampled population of the study area. Total hundred questionnaires were completed from sampled rural households. Mostly, the household?s demographic and socioeconomic aspects were targeted in this regard, including travel- time and distance characteristics. The data were successfully analyzed in SPSS-17.0 and results were generated accordingly. The results exhibited the symmetry in household-size aspect due to clustering; whereas, household income, traveldistance and time depicted enormous variations

Public Sector Education Institution's Analysis: A Way Forward to Curtail Rural-Regional Education Accessibility Problems

The availability of accessible educational facilities is essential for the better rural education. However, because of the huge population, lack of resources and absence of proper policy plans; the distance between educational facilities and rural communities is mounting as time progresses. These sorts of problematic circumstances put damaging effects on education standards and become responsible for the declining literacy rate. Hence, the goal of this research is to investigate the lack of educational institutions with respect to indigenous standards. Therefore, in this study, the dearth of education institutions was determined for the one of the most deprived sub-regions of Pakistan, i.e. Badin. The data were collected through observations, questionnaire survey, and from secondary sources, like census report and other pertinent public sector documents. The outcome of this study can be taken as an input to develop policy plans, targeting the education accessibility issues of backward communities. This research could show a guiding-path to local planning agencies, as these can come-up with the policy plans to trounce the education accessibility issues from the bucolic sub-regions of developing countrie

Attribute Hierarchy of Conflicts in Construction Projects: A Case Study of Sindh

Conflicts seem to arise throughout the life cycle of the construction project and in result, these may lead to several other issues such as project cost overrun, time overrun, productivity loss, loss of profit and above all damage of business relationships in general and specifically in construction industry. Hence, this paper focuses on various direct and indirect causes leading to conflicts in construction industry of Sindh, Pakistan. Detailed literature review and interviews have been carried out to identify several direct and indirect causes of conflicts and finally, a set of questionnaire has been designed and distributed to get expert opinion on the significance of these causes in this sector. The data has been analyzed by RIW (Relative Importance Weight) method. The outcome of this study shows that payment delay is the major direct cause of conflicts in the construction projects followed by contractual claims, public interruption, poor communication and site conditions. Thus, it is suggested that proper attention should be given to the above mentioned concerns so as to have a uniform flow of construction project life cycle without any interruption

Use of the Analytic Hierarchy Process Technique for Land-use Analysis

The AHP (Analytic Hierarchy Process) is a useful tool in decision making method for land-use planning. Hillside development often contains environmental constraints because of hilly topography. Planners and decision makers have a limited opportunity to implement innovative approaches in land-use planning decision making process. This paper discusses on a possible MCDA (Multi Criteria Decision Analysis) method of land suitability analysis for sustainable hillside development. A hierarchical structure model is developed for the land suitability analysis. Land-use planners can get benefit from MCDA techniques for hillside development projects and various kinds of land-use planning problems. Criteria are prioritized by the experts and a number of sub-criteria are set in order to select the best alternatives for sustainable hillside development by using AHP method. Various techniques and modules are available that can check uncertainty of a computed final decision by experts. CR (Consistency Ratio) method is used to examine the uncertainty in decision obtained by the experts. If CR is more than required CR standards that it can revise weights with minor changes in criteria judgements to check uncertainty in decision-making of land suitability analysis. The AHP steps can be used by using the EC (Expert Choice) decision support software automatically or manually. This paper intends to introduce MCDA as a policy design tool for planners and decision makers like an AHP application in land-use plannin

Integrated GIS-Based Site Selection of Hillside Development for Future Growth of Urban Areas

Urbanization is a challenging issue for developing countries, like Malaysia. Penang Island is one of the states of Malaysia selected as a study area where limited flat land exists. As a result, this would create urban environmental problems, such as unstable slopes and landslides due to uneven topography. The purpose of this study was to develop land suitability model for hillside development. Hence, this research aims land suitability analysis modelling for hillside development by using integrated GIS (Geographic Information System) based MCDM (Multi-Criteria Decision Making approach. The hill land portion of Penang Island was selected for hillside site development using GIS and AHP (Analytic Hierarchy Process) as a MCDM method for sustainable hillside development. This study found that 15% of land was highly suitable, 27% moderately suitable, 41% less suitable, and 17% not suitable. Therefore, this research can be consistently used by the concerned authorities for sustainable hillside urban planning and development. This approach can be used as a policy tool in decision making of urban planning and development

Public Intentions to Purchase Electric Vehicles in Pakistan

Electric vehicles (EVs) have the potential to lead the transition in road transportation from traditional petroleum mobility to electric mobility. Despite many environmental benefits, the market penetration rate of EVs is still low in most developing countries. Recently, Pakistan formulated its first EV policy for 2020–2025 to accelerate EV adoption. This study aims to explore the factors, including environmental concerns, perceived ease of use, effort expectancy, social influence, and perceived facilitating conditions, affecting individuals’ behavioral intentions to purchase EVs in Pakistan. The hypotheses were developed based on the literature, and an online questionnaire survey was conducted in Lahore, Pakistan, to collect the relevant data. The partial least square path modeling approach of structural equation modeling was used to test the hypothesis. The results confirmed that the environmental concerns, perceived ease of use, and effort expectancy positively affect the public’s intentions to use EVs in the future. However, social influence and facilitating conditions did not significantly contribute to EV adoption in the present study. The findings suggest that the EV manufacturers aiming to accelerate EV adoption should develop marketing strategies to disseminate information regarding the environmental benefits of EVs and enhance clarity about EVs’ performance and usage

ML-Based Detection of DDoS Attacks Using Evolutionary Algorithms Optimization

The escalating reliance of modern society on information and communication technology has rendered it vulnerable to an array of cyber-attacks, with distributed denial-of-service (DDoS) attacks emerging as one of the most prevalent threats. This paper delves into the intricacies of DDoS attacks, which exploit compromised machines numbering in the thousands to disrupt data services and online commercial platforms, resulting in significant downtime and financial losses. Recognizing the gravity of this issue, various detection techniques have been explored, yet the quantity and prior detection of DDoS attacks has seen a decline in recent methods. This research introduces an innovative approach by integrating evolutionary optimization algorithms and machine learning techniques. Specifically, the study proposes XGB-GA Optimization, RF-GA Optimization, and SVM-GA Optimization methods, employing Evolutionary Algorithms (EAs) Optimization with Tree-based Pipelines Optimization Tool (TPOT)-Genetic Programming. Datasets pertaining to DDoS attacks were utilized to train machine learning models based on XGB, RF, and SVM algorithms, and 10-fold cross-validation was employed. The models were further optimized using EAs, achieving remarkable accuracy scores: 99.99% with the XGB-GA method, 99.50% with RF-GA, and 99.99% with SVM-GA. Furthermore, the study employed TPOT to identify the optimal algorithm for constructing a machine learning model, with the genetic algorithm pinpointing XGB-GA as the most effective choice. This research significantly advances the field of DDoS attack detection by presenting a robust and accurate methodology, thereby enhancing the cybersecurity landscape and fortifying digital infrastructures against these pervasive threats

Data Preparation for GIS based Land Suitability Modelling: A Stepped Approach

The land suitability analysis of any facility has become a complex affair. Each aspect of the landscape has inherent properties that are, to some extent, appropriate or inappropriate for planned activities. Compliance with government guidelines, installation guidelines and customer needs has made this task more complex. Land-use suitability analysis is identifying the most suitable spatial pattern for future land uses according to specific requirements, preferences, or predictors of some activity. Land-use suitability can mean different things to different experts depending on the purpose. Geographic Information System (GIS) has proven to be a key tool in addressing these land compatibility issues. GIS is a science of analysing position information that can count several numbers of these parameters at the same time, and it can be used to identify and analyse earth compatibility for all types of physical planning. A spatial aptitude model generally corresponds to the scientific question “Where is the best location for a particular facility or business? Therefore, this paper aims to provide an intensified approach to prepare datasets and layers for such land suitability problems using GIS. This paper will be valuable to land managers in land-use planning for any facility