Relationship of Self-Efficacy and Obstacles of E-Learning Towards Online Method in IR4. 0

In IR4.0 situation, online method and e-learning been considered as a part to be implemented. Self-efficacy and obstacles in e-learning are the elements to be concerned in the learning process. The ultimate objective of this research is to identify self-efficacy and obstacles in e-learning experienced by students. Further, this research determines the relationships among self-efficacy and obstacles in e-learning. There are 202 students in year 2 and year 3 in Faculty of Technology Management and Business (FPTP) were chosen as respondents of this study. Self-efficacy refers to how confident an individual feels about handling particular tasks, challenges and context given by the lecturer. Obstacles were defined as the resistance faced by students that bringing negative effects to them in using e-how. This research used questionnaires and quantitative methods for data collection method. The relationships among self-efficacy in e-learning and obstacles in e-learning is very weak. This research has been carried out to accomplish the objectives set by the researchers to identify the self-efficacy in using e-learning and obstacles in e-learning. The findings show that the students have e-learning self-efficacy (mean= 3.8201). Four elements of obstacles (factors) emerged, that include personality, organization, situational and technological obstacles. Organizational obstacles were the most prevalent (mean= 3.3020), followed by personality obstacles (mean= 3.2855), and situation obstacles (mean= 3.281). Technology obstacles (mean= 2.7723) were the least common. To conclude the research for identifying the relationship between self-efficacy and obstacles in e-learning experience, one hypothesis was tested and accepted

Factors that Influenced the Quality Inspection on the Production Line in Manufacturing Industry

The quality of a product is the main concern for customers. Hence, the objectives of this research are to determine factor that affect the inline quality inspection and improvement solutions of the quality inspection standard in the production process. Meanwhile, the scopes of the research are studying of all the factors that influence inline quality inspection and techniques to improve quality inspection standard. Hence, interviews had been carried out towards the respondents who work under the Quality Assurance Department and in charge of inline quality inspection. Through analyzing the chosen products which were cot sheet and latex cap, it can be said that worker, material, and machine are the most common factors that cause defects on the products. Therefore, the result of this research shows that the worker’s training, maintenance and checking procedure of incoming raw materials are the main influence factors to overcome the problems occurred

Factors that Influenced the Quality Inspection on the Production Line in Manufacturing Industry

The quality of a product is the main concern for customers. Hence, the objectives of this research are to determine factor that affect the inline quality inspection and improvement solutions of the quality inspection standard in the production process. Meanwhile, the scopes of the research are studying of all the factors that influence inline quality inspection and techniques to improve quality inspection standard. Hence, interviews had been carried out towards the respondents who work under the Quality Assurance Department and in charge of inline quality inspection. Through analyzing the chosen products which were cot sheet and latex cap, it can be said that worker, material, and machine are the most common factors that cause defects on the products. Therefore, the result of this research shows that the worker’s training, maintenance and checking procedure of incoming raw materials are the main influence factors to overcome the problems occurred

Extensive Genetic Diversity of HIV-1 in Incident and Prevalent Infections among Malaysian Blood Donors: Multiple Introductions of HIV-1 Genotypes from Highly Prevalent Countries - Fig 3

<p><b>Sub-region neighbour joining tree analyses of the 1.6kb partial <i>gag-pol</i> genes sequenced in two clusters of (A) subtype B'/C and (B) B'/G recombinants characterised in the population.</b> Based on the informative sites analyses, recombination breakpoints were estimated for each strain and the partial <i>gag-pol</i> sequences (HXB2:1753–3440) were then sub-divided into different regions for phylogenetic reconstruction. Putative HIV-1 parental reference genotypes used in bootscan were 90THCM235 (CRF01_AE), CNRL42 (subtype B' of Thai origin), 95IN21068 (subtype C) and 01NGPL0674 (subtype G). Incident or prevalent HIV-1 infections for each strain, as determined using a limiting antigen avidity enzyme immunoassay (LAg-Avidity EIA) were identified by orange triangles or red circles, respectively. Bootstrap values of greater than 70% were indicated on the branch nodes. The scale bar represents 1% genetic distance (0.01 substitutions per site).</p

Phylogenetic reconstruction of 136 partial <i>gag-pol</i> gene sequences of 1.6kb amplified among the blood donors in Kuala Lumpur, Malaysia between 2013 and 2014.

<p>HIV-1 incidence was estimated using a limiting antigen avidity enzyme immunoassay (LAg-Avidity EIA) to identify recent (incident) and long-standing (prevalent) infections as indicated where available. Neighbour-joining tree was constructed in MEGA 5.05 [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0161853#pone.0161853.ref022" target="_blank">22</a>] using Kimura 2-parameter method of nucleotide substitutions and the reliability of the branching nodes were assessed by bootstrap analysis of 1000 replicates. Eleven partial <i>gag</i>-PR (834bp) and two RT gene sequences (966bp) were genotyped separately using similar methods and their prevalence was reported in this study (figures not shown for clarity). Relevant HIV-1 reference genotypes in Southeast Asia include subtype B, CRF01_AE, CRF33_01B, CRF34_01B, CRF48_01B, CRF52_01B, CRF53_01B, CRF54_01B, CRF58_01B and CRF74_01B. Reference sequences of other genotypes prevalent in China (CRF07_BC, CRF08_BC and other recently-described B'/C CRFs) and Africa (subtype G, CRF02_AG and CRF45_cpx) were also included in the analysis. The reference sequences were labelled in the following order: genotype, country of origin, isolate name and GenBank accession number. A well-supported cluster of Malaysian subtype G strains was also highlighted as G_MY within the subtype G clade of African reference strains. All 12 unique recombinant forms were denoted by closed diamonds and labelled according to incident or prevalent infection status. Clusters of novel B'/C recombinants (strains 13MYNBB108, 14MYNBB084, 14MYNBB090 and 14MYNBB164) and B'/G recombinants (13MYNBB064 and 13MYNBB065) were highlighted in the tree. Simian immunodeficiency virus (SIVcpz) reference strains were included as outgroup. Bootstrap values of greater than 70% were indicated on the branch nodes. The scale bar represents 1% genetic distance (0.01 substitutions per site).</p

HIV-1 genotype distribution of incident and prevalent infections among 127 blood donors in Kuala Lumpur.

<p>A limiting-antigen avidity enzyme immunoassay (LAg-Avidity EIA) was used to distinguish incident from prevalent HIV-1 infections. Out of 179 samples available for incidence assay testing, 70.9% (n = 127) were successfully genotyped and comprised of 29 (22.8%) incident HIV-1 infections.</p