A hybrid group-based movie recommendation framework with overlapping memberships.

Recommender Systems (RS) are widely used to help people or group of people in finding their required information amid the issue of ever-growing information overload. The existing group recommender approaches consider users to be part of a single group only, but in real life a user may be associated with multiple groups having conflicting preferences. For instance, a person may have different preferences in watching movies with friends than with family. In this paper, we address this problem by proposing a Hybrid Two-phase Group Recommender Framework (HTGF) that takes into consideration the possibility of users having simultaneous membership of multiple groups. Unlike the existing group recommender systems that use traditional methods like K-Means, Pearson correlation, and cosine similarity to form groups, we use Fuzzy C-means clustering which assigns a degree of membership to each user for each group, and then Pearson similarity is used to form groups. We demonstrate the usefulness of our proposed framework using a movies data set. The experiments were conducted on MovieLens 1M dataset where we used Neural Collaborative Filtering to recommend Top-k movies to each group. The results demonstrate that our proposed framework outperforms the traditional approaches when compared in terms of group satisfaction parameters, as well as the conventional metrics of precision, recall, and F-measure.

Redesign and validation of a computer programming course using Inductive Teaching Method.

Inductive Teaching Method (ITM) promotes effective learning in technological education (Felder & Silverman, 1988). Students prefer ITM more as it makes the subject easily understandable (Goltermann, 2011). The ITM motivates the students to actively participate in class activities and therefore could be considered a better approach to teach computer programming. There has been little research on implementing ITM in computer science courses despite its potential to improve effective learning. In this research, an existing computer programming lab course is taught using a traditional Deductive Teaching Method (DTM). The course is redesigned and taught by adopting the ITM instead. Furthermore, a comprehensive plan has been devised to deliver the course content in computer labs. The course was evaluated in an experiment consisting of 81 undergraduate students. The students in the Experimental Group (EG) (N = 45) were taught using the redesigned ITM course, whereas the students in the Control Group (CG) (N = 36) were taught using the DTM course. The performance of both groups was compared in terms of the marks obtained by them. A pre-test conducted to compare pre-course mathematical and analytical abilities showed that CG was better in analytical reasoning with no significant differences in mathematical abilities. Three post-tests were used to evaluate the groups theoretical and practical competence in programming and showed EG improved performance with large, medium, and small effect sizes as compared to CG. The results of this research could help computer programming educators to implement inductive strategies that could improve the learning of the computer programming.

Fighting adult illiteracy with the help of the environmental print material.

Adult illiteracy is a major problem worldwide especially in developing countries. Adult Basic Education (ABE) programs working in this context are not very effective due to lack of motivation for the people who are not literate. The reason is inadequate learning content and content delivery methods. This situation calls for developing novel learning content and a learner-directed content delivery approach. This paper presents an exploratory study investigating the use of the Environmental Print Material (EPM) as learning content for the non-literate population of Pakistan. The EPM content is presented to the adult non-literate population in two ethnographic studies. The most frequently recognized content is selected and utilized as learning content in a Computer Assisted Learning (CAL) application. An empirical study is conducted upon two groups with 107 participants to compare the EPM-based learning content with Traditional Learning Content (TLC). As many as 54 participants participated in the experimental group (presented with EPM-based learning content), whereas 53 participants took part in the control group (presented with TLC content). The results reveal that the experimental group performed significantly better compared to the control group in recognition, pronunciation, and recall of the presented content. The meta-analysis of the results shows a large effect size of (1.05) with confidence interval in the range (0.798-1.315). The results claim that the EPM has potential to be considered as learning content in the ABE programs.

Rapid detection of HCV genotyping 1a, 1b, 2a, 3a, 3b and 6a in a single reaction using two-melting temperature codes by a real-time PCR-based assay.

The genotype of the hepatitis C virus (HCV) is an important indicator for antiviral therapeutic response. We hereby described development of a rapid HCV genotyping approach that enabled the identification of the six most common HCV subtypes of Asia, i.e., 1a, 1b, 2a, 3a, 3b, and 6a, in a single reaction. Using two dual-labeled, self-quenched probes that target the core region of the HCV genome, the exact subtype could be accurately identified by two-melting temperature codes determined from the two respective probes in a real-time PCR assay. Analytical sensitivity studies using armored RNA samples representing each of the six HCV subtypes showed that 5 copies/reaction of HCV RNA could be detected. The assay was evaluated using 244 HCV-positive serum samples and the results were compared with sequencing analysis. Of the 224 samples, subtype 3a (127, 52.3%) was the dominant, followed by 1b (51, 20.9%), 3b (47, 19.3%), 2a (8, 3.3%), 6a (4, 1.6%) and the least was subtype 1a (1, 0.4%). Moreover, 6 (2.5%) mixed infection samples were also detected. These results were fully concordant with sequencing analysis. We concluded that this real-time PCR-based assay could provide a rapid and reliable tool for routine HCV genotyping in most Asian countries.

Computer Aided Screening of Phytochemicals from Garcinia against the Dengue NS2B/NS3 Protease.

Dengue virus NS2/NS3 protease because of its ability to cleave viral proteins is considered as an attractive target to screen antiviral agents. Medicinal plants contain a variety of phytochemicals that can be used as drug against different diseases and infections. Therefore, this study was designed to uncover possible phytochemical of different classes (Aromatic, Carbohydrates, Lignin, Saponins, Steroids, Tannins, Terpenoids, Xanthones) that could be used as inhibitors against the NS2B/NS3 protease of DENV. With the help of molecular docking, Garcinia phytochemicals found to be bound deeply inside the active site of DENV NS2B/NS3 protease among all tested phytochemicals and had interactions with catalytic triad (His51, Asp75, Ser135). Thus, it can be concluded from the study that these Gracinia phytochemicals could serve as important inhibitors to inhibit the viral replication inside the host cell. Further in-vitro investigations require confirming their efficacy.