Development of Multiple Linear Regression Model and Rule Based Decision Support System to Improve Supply Chain Management of Road Construction Projects in Disaster Regions

Supply chain operations of construction industry including road projects in disaster regions results in exceeding project budget and timelines. In road construction projects, supply chain with poor performance can affect efficiency and completion time of the project. This is also the case of the road projects in disaster areas. Disaster areas consider both natural and man-made disasters. Few examples of disaster zones are; Pakistan, Afghanistan, Iraq, Sri Lanka, India, Japan, Haiti and many other countries with similar environments. The key factors affecting project performance and execution are insecurity, uncertainties in demand and supply, poor communication and technology, poor infrastructure, lack of political and government will, unmotivated organizational staff, restricted accessibility to construction materials, legal hitches, multiple challenges of hiring labour force and exponential construction rates due to high risk environment along with multiple other factors. The managers at all tiers are facing challenges of overrunning time and budget of supply chain operations during planning as well as execution phase of development projects. The aim of research is to develop a Multiple Linear Regression Model (MLRM) and a Rule Based Decision Support System by incorporating various factors affecting supply chain management of road projects in disaster areas in the order of importance. This knowledge base (KB) (importance / coefficient of each factor) will assist infrastructure managers (road projects) and practitioners in disaster regions in decision making to minimize the effect of each factor which will further help them in project improvement. Conduct of Literature Review in the fields of disaster areas, supply chain operational environments of road project, statistical techniques, Artificial Intelligence (AI) and types of research approaches has provided deep insights to the researchers. An initial questionnaire was developed and distributed amongst participants as pilot project and consequently results were analysed. The results’ analysis enabled the researcher to extract key variables impacting supply chain performance of road project. The results of questionnaire analysis will facilitate development of Multiple Linear Regression Model, which will eventually be verified and validated with real data from actual environments. The development of Multiple Linear Regression Model and Rule Based Decision Support System incorporating all factors which affect supply chain performance of road projects in disastrous regions is the most vital contribution to the research. The significance and novelty of this research is the methodology developed that is the integration of those different methods which will be employed to measure the SCM performance of road projects in disaster areas

Numerical Study on The Out-of-Plane Behaviour of Brick Masonry Walls Strengthened with Cement Sand Mortar

Masonry, as a building material, has a long history of usage in construction. The utilization of brick masonry in conjunction with mortar has been widely adopted due to its ease of implementation and structural durability. However, it has been observed that masonry structures exhibit significant vulnerabilities in the face of lateral loads, particularly regarding bending and shear. As seismic activity continues to pose a growing threat, the need for effective methods of strengthening masonry structures against earthquakes is becoming increasingly imperative. In this research, the Finite Element method is employed to assess the influence of the thickness of cement-sand (CS) mortar on the flexural capacity of cement-clay interlocking brick (CCIB) masonry walls through numerical modeling. In this study, three models of CCIB masonry walls with varying thicknesses of cement-sand (CS) mortar are analyzed. The models comprised of CCIB masonry walls with a one-sided application of CS mortar layers of 10mm and 20mm thickness. The findings indicate that the flexural capacity of the CCIB masonry walls can be improved by increasing the thickness of the CS mortar layer

Hemodynamic Comparison between modified saddle block and subarachnoid block for Transurethral Resection of Prostate

BACKGROUND:   Spinal anesthesia is often the mode of anesthesia in transurethral resection of prostate (TURP) albeit with risk of hypotension. However, hemodynamic derangement is often less pronounced in saddle block. This study was conducted to compare the mean fall in Mean arterial Pressure (MAP) and Heart rate (HR) between modified saddle block and subarachnoid block for TURP.  OBJECTIVE:   To compare the mean fall in MAP and HR between modified saddle block and subarachnoid block for TURP.  METHODS:   In this randomized controlled trial 120 patients undergoing elective TURP were included and divided into two groups. Group A Patients received subarachnoid block and Group B received modified saddle block. Baseline hemodynamics were recorded before and then at 5 minutes after anesthesia. All the collected data was entered into SPSS version 22 and analyzed. Quantitative data like age, BMI, ASA-PS score, duration of surgery and baseline hemodynamics were presented as means and standard deviations. The fall of mean arterial pressure (MAP) & heart rate (HR) were compared among groups by independent t test and P value < 0.05 was considered as statistically significant.   RESULTS:  Mean fall in MAP was 8.98±1.28 mmHg and 3.13±0.68 mmHg (p<0.001) in group A and B, respectively. Mean fall in HR was 7.17±0.98 and 2.78±0.59 (p<0.001) in group A and group B, respectively.  CONCLUSION:   Modified saddle block resulted in significantly decreased fall in MAP and HR as compared with subarachnoid block for TURP.  KEY WORDS:   Modified Saddle Block; Subarachnoid Block; Mean Arterial Pressure &nbsp

Effect of time pressure and human judgment on decision making in three public sector organizations of Pakistan

This study attempts to widen the effect of time pressure and human judgment on decision making. A census of three organizations named Project Management Organization (PMO), Accountant General Pakistan Revenues (AGPR) and Controller General of Accountant (CGA) was occupied. To demeanor this study a questionnaire tagged Decision Making, Time Pressure and Human Judgment was used for the assortment of data. The questionnaire was predominantly designed to accomplish the objectives of the study. The total number of observations was eighty two and the Arithmetic Mean Score of decision making, time pressure and human judgment were 2.532, 2.527 and 2.395 respectively. The significance level of the model was 0.000 which illustrates maximum significant level. As p-value is less than .05 so it can be assumed that the variables elected for the study are decidedly significant

The Relationship between Poverty, Income Inequality and Unemployment: Evidence from ARDL and Bound Testing Approach

The paper explores the impact of development expenditure, military expenditure, debt, political stability, foreign direct investment and inflation on poverty, income inequality and unemployment in the context of Pakistan. Time series uninterrupted data is used for the period 1980 to 2014. Income inequality is havoc by which income gap increases between rich and poor of society. Pakistan has an alarming situation of income inequality, poverty and unemployment rate as compared to other developing nations. The empirical findings confirm that increase in development expenditure causes a decrease in poverty and unemployment but inequality increases due to capitalism. There is a negative relationship between military expenditure inequality and unemployment. Foreign direct investment decreases inequality and unemployment. Results also show that political stability is responsible for increasing poverty and unemployment

Geoelectrical Survey for the Exploration of Ground Water using Vertical Electrical Sounding: A Case Study of Androt District Rawlakot, Azad Jammu & Kashmir

Vertical Electrical Sounding (VES) method has been widely used to depict the subsurface lithology, thickness and structure based on resistivity of layered media with the ultimate objective of evaluating groundwater potential. In this investigation, VES was used to outline subsurface geology to produce a 2D subsurface resistivity model based on the resistivity contrast of layered rocks, for evaluating the accessibility of groundwater in the Siwaliks group of Androt District Rawlakot, Azad Jammu and Kashmir (AJ&K). The Schlumberger electrode configuration was used with spacing arrangement of current electrode (AB/2) going from 1.5 to 250 meters and potential electrode (MN) 1 to 50 meters. The VES data was qualitatively analyzed by using iteration software (IPI2win) which showed that the area is composed of clay, shale, fractured sandstone with intercalation of clay based on resistivity contrast. At depth of 40m-100m along VES indicates good prospects for ground water potential, associated with sandstone beds of Siwaliks group. The resistivity depth section maps at potential depth of 30m, 40m, 60m and 80m are prepared for the demarcation of potential reservoir beds at various depth. The interpreted sounding curves are interpreted qualitatively and pseudo section, Resistivity section and geological log are prepared based on resistivity contrast which shows agreement with geology and hydrological condition of the area. The favorable reservoir rock as an aquifer demarcated in the study area is fractured sandstone with intercalation of clay beds, with apparent resistivity range of 80Ωm to 100Ωm and thickness of 20m to 50m at different sites. The apparent resistivity sections revealed that the North East (NE) and North West (NW) regions are comparatively good potential reservoir for ground water

The Relationship between Poverty, Income Inequality and Unemployment: Evidence from ARDL and Bound Testing Approach

The paper explores the impact of development expenditure, military expenditure, debt, political stability, foreign direct investment and inflation on poverty, income inequality and unemployment in the context of Pakistan. Time series uninterrupted data is used for the period 1980 to 2014. Income inequality is havoc by which income gap increases between rich and poor of society. Pakistan has an alarming situation of income inequality, poverty and unemployment rate as compared to other developing nations. The empirical findings confirm that increase in development expenditure causes a decrease in poverty and unemployment but inequality increases due to capitalism. There is a negative relationship between military expenditure inequality and unemployment. Foreign direct investment decreases inequality and unemployment. Results also show that political stability is responsible for increasing poverty and unemployment