A Novel Study of the Relation Between Students Navigational Behavior on Blackboard and their Learning Performance in an Undergraduate Networking Course

This paper provides an overview of students behavior analysis on a learning management system (LMS), Blackboard (Bb) Learn for a core data communications course of the Undergraduate IT program in the Information Sciences and Technology (IST) Department at George Mason University (GMU). This study is an attempt to understand the navigational behavior of students on Blackboard Learn which can be further attributed to the overall performance of the students. In total, 160 undergraduate students participated in the study. Vast amount of students activities data across all four sections of the course were collected. All sections have similar content, assessment design and instruction methods. A correlation analysis between the different assessment methods and various key variables such as total student time, total number of logins and various other factors were performed, to evaluate students engagement on Blackboard Learn. Our findings can help instructors to efficiently identify students strengths or weaknesses and fine-tune their courses for better student engagement and performance

Impact of Working Capital Management Approaches (Aggressive/Conservative) on the Profitability and Shareholder’s Worth: Comparative Analysis of Cement and Sugar Industry

This study investigates that how sugar and cement companies listed at Karachi stock exchange manage the working capital approaches (aggressive/conservative) mix. Sample of 18 cement and 31 sugar companies used in this thesis. In this study impact of working capital approaches namely aggressive investment policy and aggressive financing policy is checked on the profitability and shareholder’s worth. All the companies selected from sugar and cement sector are listed at Karachi stock exchange and have active status. The time period for this study is from 2006 to 2012. Regression analysis is use to analyze the impact of working capital investment and financing policies. Regression analysis is supported by SPSS software. The result of this study indicate that if companies follow the aggressive investment and financing policies then they will not be able to yield more profit as both these policies yields negative effect on the profitability and shareholder’ worth. There is inverse relationship between degree of aggressiveness with profitability and shareholder’ worth. Keywords: Working capital efficiency, aggressive investment policy, working capital financing policy, firm’ profitability, shareholder’s worth, Cement industry, sugar industr

Impact of Working Capital Management Approaches (Aggressive/Conservative) on the Profitability and Shareholder’s Worth: Comparative Analysis of Cement and Sugar Industry

This study investigates that how sugar and cement companies listed at Karachi stock exchange manage the working capital approaches (aggressive/conservative) mix. Sample of 18 cement and 31 sugar companies used in this thesis. In this study impact of working capital approaches namely aggressive investment policy and aggressive financing policy is checked on the profitability and shareholder’s worth. All the companies selected from sugar and cement sector are listed at Karachi stock exchange and have active status. The time period for this study is from 2006 to 2012. Regression analysis is use to analyze the impact of working capital investment and financing policies. Regression analysis is supported by SPSS software. The result of this study indicate that if companies follow the aggressive investment and financing policies then they will not be able to yield more profit as both these policies yields negative effect on the profitability and shareholder’ worth. There is inverse relationship between degree of aggressiveness with profitability and shareholder’ worth. Keywords: Working capital efficiency, aggressive investment policy, working capital financing policy, firm’ profitability, shareholder’s worth, Cement industry, sugar industr

Videoprompter: an ensemble of foundational models for zero-shot video understanding

Vision-language models (VLMs) classify the query video by calculating a similarity score between the visual features and text-based class label representations. Recently, large language models (LLMs) have been used to enrich the text-based class labels by enhancing the descriptiveness of the class names. However, these improvements are restricted to the text-based classifier only, and the query visual features are not considered. In this paper, we propose a framework which combines pre-trained discriminative VLMs with pre-trained generative video-to-text and text-to-text models. We introduce two key modifications to the standard zero-shot setting. First, we propose language-guided visual feature enhancement and employ a video-to-text model to convert the query video to its descriptive form. The resulting descriptions contain vital visual cues of the query video, such as what objects are present and their spatio-temporal interactions. These descriptive cues provide additional semantic knowledge to VLMs to enhance their zeroshot performance. Second, we propose video-specific prompts to LLMs to generate more meaningful descriptions to enrich class label representations. Specifically, we introduce prompt techniques to create a Tree Hierarchy of Categories for class names, offering a higher-level action context for additional visual cues, We demonstrate the effectiveness of our approach in video understanding across three different zero-shot settings: 1) video action recognition, 2) video-to-text and textto-video retrieval, and 3) time-sensitive video tasks. Consistent improvements across multiple benchmarks and with various VLMs demonstrate the effectiveness of our proposed framework. Our code will be made publicly available

Do financial development and energy efficiency ensure green environment? Evidence from R.C.E.P. economies

The issue of climate change and environmental degradation has been prevailing for the last few decades. Yet economies are further expanding due to free trade agreement which accelerates the trade of energy and carbon intensive commodities across the regions. A prominent example of such free trade is the Regional Comprehensive Economic Partnership (R.C.E.P.), which mostly remains ignored. The current research study explores the influence of financial development (F.D.) and energy efficiency (E.N.E.F.) on carbon emissions in the R.C.E.P. economies. Also, this study analyses the role of economic growth and renewable energy on environmental quality during the period from 1990 to 2020. Panel data approaches such as slope heterogeneity, crosssection dependence, and the second-generation panel unit root test are used. The non-normally distributed variables are found cointegrated. Therefore, a novel method of moments quantile regression is used. The results demonstrate that F.D. and economic growth are positively associated with CO2 emissions. At the same time, E.N.E.F. and renewable energy consumption (R.E.C.) significantly reduce the emissions level and promote a green environment in all quantiles. The environmental Kuznets curve is found valid in the R.C.E.P. economies. These results are robust as validated by Fully-Modified Ordinary Least Square – a parametric approach. A two-way significant causal association exists between carbon-economic growth, carbon-F.D., carbon- R.E.C., and carbon-E.N.E.F.. The findings suggest an enhancement in R.E.C., improvement in the E.N.E.F. approaches, and implications for green F.D. in the region

In vitro and in vivo evaluation of different measures to control Ascochyta blight in chickpea

Ascochyta blight, an infection caused by Ascochyta rabiei is a destructive disease in many chickpea growing regions and it caused significant yield losses. To minimize the impact of Ascochyta blight, 5 fungicides viz., Aliette, Cabrio Top, Thiovit Jet, Cymoxanil and Difenoconazole, 5 plants extracts namely Azadirachta indica, Azadirachta azedarach, Datura stramonium, Chenopodium album and Allium sativum L. and two strains T-22 and E58 of bio-control agents (BCAs) Trichoderma viride and Aspergillus flavus were evaluated on the growth of A. rabiei under in vitro conditions by using the food poison technique. The colony growth of Ascochyta rabiei was inhibited at all concentrations of fungicides @ 0.07, 0.15, 0.21%, plants extracts @ 4, 6, 9% and bio-control agents @ 105, 106 and 107 conidia ml-1 respectively. Among all applied treatments, maximum inhibition colony growth of pathogen was recorded in the case of Aliette (83.4%), followed by Cabrio Top (74.3%), Azadirachta indica (50.3%) and Trichoderma viride (60.3%) at their high concentrations. Field trials showed that Aliette and Cabario Top significantly reduced the disease severity to 10 % and 24% respectively, followed by Azadirachta indica and Allium sativum which reduced the disease severity to 40% and 50% respectively. Bio-control agent Trichoderma viride proved less effective in controlling Ascochyta bight severity under field conditions. The present study showed that systemic and sulphur containing fungicides, plant extracts and bio-control agents (BCAs) have the potential to control Ascochyta blight in both in vitro and in vivo conditions

Convective Heat Transfer Study of ZnO Nanofluids and a Comparison with the Conventional Coolant Water

In this era, the utilization of automobiles is increasing rapidly. So, it is a task for the automobile industries to yield well-ordered cooling system, which is actually responsible to carry waste heat of engine to atmosphere for effective working of an internal combustion engines. In this research, car radiator was tested by the water based Nano fluids to increase its heat transfer capacity and new experimental results were reported. Zinc Oxide nanofluids were prepared and tested by adding their nanoparticles in water with different volume fractions (0.1, 0.2, 0.3 and 0.4)%. Experimentally, effect of these concentrations were observed by varying a fluid flow rate from 4 liter per minute to 1 liter per minute and inlet temperature of fluid entering in radiator was kept constant at 80oC and enhancement in heat transfer was observed  from 46% to 70% by using ZnO Nano Fluid having volumetric concentration 0.2%. Increase in volumetric concentration had shown the enhancement of heat transfer but up to 0.2% and it was seen that further increase in concentration was been reduced the heat transfer capacity.