ASSESSING THE EFFECTIVENESS OF ONLINE EDUCATION FROM THE STUDENTS' PERSPECTIVE

In this paper the researchers have investigated students' perceptions about theeffectiveness of their online education. The sample consisted of 180 participants of theVirtual University (VU) of Pakistan, and already developed instruments were used tomeasures dependent and independent variables. Through using correlation matrix andregression analysis, it was found that the following areas are important for studentsabout the effectiveness of online education; Instructor competence, Course structure,and level of technology. The results of our research showed that faculty iat VU isdelivering online education that meets the students' needs in regard to course structureand instructor competence. Moreover, results also indicated that students think thatcourse structure and instructor competence are more important for the effectiveness ofonline education than the current level of technology

Environment Friendly Products: Factors that Influence the Green Purchase Intentions of Pakistani Consumers

This study examines the influence of various factors on the green purchase intentions of Pakistani consumers. To this end, a conceptual model has been proposed and subjected to empirical verification with the use of a survey. The survey results obtained in two major Pakistani cities provide reasonable support for the validity of the proposed model. Specifically, the findings from the correlation matrix, simple regression followed by multiple regression analysis confirm the influence of OGI, EK, EC and PPP&Q on consumers purchase intentions toward green products. The OGI, EK and EC, in turn, also seem to affect consumers green purchase intentions via the moderating role of PPP&Q of a green product. Although the present findings provide a better understanding of the process and significant antecedents of green purchasing intentions, this also highlights one area for more thorough investigation. This is the significant moderating role of PPP&Q variables in consumers’ green purchasing process. As the findings suggest that respondents have a high positive attitude regarding green products and are ready to buy green products more often, but as for as the product price and quality are concerned, green products must perform competitively just like the traditional products. This study also discusses how the present findings may help the Pakistani government and green marketers to fine-tune their environmental programs

A Data Mining Technique to Improve Configuration Prioritization Framework for Component-based Systems: An Empirical Study

In the current application development strategies, families of products are developed with personalized configurations to increase stakeholders’ satisfaction. Product lines have the ability to address several requirements due to their reusability and configuration properties. The structuring and prioritizing of configuration requirements facilitate the development processes, whereas it increases the conflicts and inadequacies. This results in increasing human effort, reducing user satisfaction, and failing to accommodate a continuous evolution in configuration requirements. To address these challenges, we propose a framework for managing the prioritization process considering heterogeneous stakeholders priority semantically. Features are analyzed, and mined configuration priority using the data mining method based on frequently accessed and changed configurations. Firstly, priority is identified based on heterogeneous stakeholder’s perspectives using three factors functional, experiential, and expressive values. Secondly, the mined configuration is based on frequently accessed or changed configuration frequency to identify the new priority for reducing failures or errors among configuration interaction. We evaluated the performance of the proposed framework with the help of an experimental study and by comparing it with analytical hierarchical prioritization (AHP) and Clustering. The results indicate a significant increase (more than 90 percent) in the precision and the recall value of the proposed framework, for all selected cases

Transparent conductive oxide films for high-performance dye-sensitized solar cells

In this paper, atmospheric pressure chemical vapor deposition of fluorine-doped tin oxide (FTO) thin films of various thicknesses and dopant levels is reported. The deposited coatings are used to fabricate dye-sensitized solar cells, which exhibited reproducible power conversion efficiencies in excess of 10%. No surface texturing of FTOs or any additional treatment of dye-covered films is applied. In comparison, the use of commercial FTOs showed a lower cell efficiency of 7.11%. Detailed analysis showed that the cell efficiencies do not simply depend on the resistivity of FTOs but instead rely on a combination of carrier concentration, thickness, and surface roughness properties

Effect of thermally treated barley dietary fiber against hypercholesterolemia

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Linguistic Features and Bi-LSTM for Identification of Fake News

With the spread of Internet technologies, the use of social media has increased exponentially. Although social media has many benefits, it has become the primary source of disinformation or fake news. The spread of fake news is creating many societal and economic issues. It has become very critical to develop an effective method to detect fake news so that it can be stopped, removed or flagged before spreading. To address the challenge of accurately detecting fake news, this paper proposes a solution called Statistical Word Embedding over Linguistic Features via Deep Learning (SWELDL Fake), which utilizes deep learning techniques to improve accuracy. The proposed model implements a statistical method called “principal component analysis” (PCA) on fake news textual representations to identify significant features that can help identify fake news. In addition, word embedding is employed to comprehend linguistic features and Bidirectional Long Short-Term Memory (Bi-LSTM) is utilized to classify news as true or fake. We used a benchmark dataset called SWELDL Fake to validate our proposed model, which has about 72,000 news articles collected from different benchmark datasets. Our model achieved a classification accuracy of 98.52% on fake news, surpassing the performance of state-of-the-art deep learning and machine learning models

Molecular probing of Aflatoxigenic fungi in rice grains collected from local markets of Lahore, Pakistan

Background: Aflatoxigenic Aspergillus strains have emerged as a serious threat to food safety and quality assurance. The objective of this study was to identify the aflatoxigenic Aspergillus sp. by targeting the amplification of aflatoxigenic genes i.e., aflR, nor1, omt1, ver1, in different fugal strains isolated from the rice grains being marketed in local markets of Lahore city, Pakistan.Methods: Total eleven (11) Aspergillus strains were isolated from rice grains and aflatoxigenic genes i.e., aflR, nor1, omt1, ver1 were amplified to differentiate between aflatoxin producing and non-producing strains.Results: Four (04) out of total eleven (11) strains showed the presence of aflatoxins producing genes, indicating the possible contamination of aflatoxins in rice grains being sold in local markets of Lahore.Conclusion: This research provides the basis for the quantification of aflatoxins; a significant threat to the quality of foodstuffs and consumers. The situation demands the attention of rice growers, processors as well as government officials to tackle the problem to assure the safety of rice eaters.Keywords: Aflatoxins; Aspergillus; Cereal grains; Contamination; Mycotoxigenic

Understanding nanomechanical and surface ellipsometry of optical F-doped SnO2 thin films by in-line APCVD

In this paper, a production-type chemical vapour deposition (CVD) is utilized to deposit fluorine doped tin oxide thin films of different thicknesses and dopant levels. Deposited films showed a preferred orientation along the (200) plane of a tetragonal structure due to the formation of halogen rich polar molecules during the process. A holistic approach studying elastic modulus and hardness of resulting films by a high-throughput atmospheric-pressure CVD process is described. The hardness values determined lie between 8 - 20 GPa. For a given load, the modulus generally increased slightly with the thickness. The average elastic recovery for the coatings was found to be between 45 – 50 %. Refractive index and thickness values derived from the fitted ellipsometry data were in excellent agreement with independent calculations from transmission and reflection data

Quantitative determination of the effects of He–Ne laser irradiation on seed thermodynamics, germination attributes and metabolites of Safflower (Carthamus tinctorius L) in relation with the activities of germination enzymes

The present investigation was undertaken to assess the effects of different doses (100, 300, and 500 mJ) of low power He–Ne laser (632.8 nm) irradiation on seed germination and thermodynamics attributes and activities of potential germinating enzymes in relation with changes in seed metabolites. He–Ne laser seed irradiation increased the amylase (Amy), protease (Pro) and glucosidase (Gluco) activities, with a significant improvement in seed thermodynamics and seed germination attributes. A fast increase was found in free fatty acids (FFA), free amino acids (FAA), chlorophyll (Chl), carotenoids (Car), total soluble sugars (TSS) and reducing sugars (RS) in laser treated seeds in parallel with fast decline in seed oil contents and total soluble proteins (TSP). Significant positive correlations were recorded in laser-induced enhanced seed energy levels, germination, activities of germination enzymes with levels of FAA, FFA, Chl, TSS and RS, but a negative correlation with the levels of TSP and oil. In conclusion, the seed treatment with 100 and 300 mJ He–Ne laser was more effective to improve the seed germination potential associated with an improvement in seed energy levels due to increased activities of germination enzymes due to the speedy breakdown of seed reserves to simple metabolites as building blocks