Visualization and centrality measurement of social network analysis

Social networks have increased in popularity and play an important role in people's life nowadays. Hundreds of millions of people participate in social networks and the number is growing day by day. Social networks have become a useful tool and help people in every field of life such as in education, politics and business. Social networks give people the idea of knowing and interacting with each other, experiencing the power of sharing and being connected with people from different places and countries. The purpose of this study is to analyse the behaviour of actors in a network, the graph and the relationship between actors in social networks. The researcher expects to use the technique of Social Network Analysis with Organisation Risk Analyser (ORA) tool to analyse the data. Three different types of dataset are analysed in the form of network visualisation and centrality measurement. The results reveal the hidden relationships and clusters in the network, and indicate which nodes provide better performance for each centrality measur

Critical Thinking Session (CTS)

CTS in Physics course provides quantitative and analytic skills needed for analysing data and solving problems in the sciences area. It involves crafting a learning environment where students can explore on their own and understand how the physical world works, and to connect complex scientific concepts to their daily lives. This activity requires students to work as a team

Evaluation of DPPH Free Radical Scavenging, α-Glucosidase Inhibitory, and Antimicrobial Activities of Aquilaria malaccensis Leaf Extracts

Herbs and medicinal plants are major ingredients in traditional or folk medicine for many countries of the world, including Malaysia. This study evaluated the potential of the leaf extract in different solvent polarities and drying methods of Aquilaria malaccensis, in scavenging free radicals and inhibiting the enzyme α-glucosidase as well as antimicrobial activities. Both methanol and ethanol extracts in oven dry method were efficient solvents to extract the antioxidant constituents of A. malaccensis. To analyze α-glucosidase inhibitory activity, the methanol extracts of A. malaccensis in air dry method exhibited the highest activity with an IC50 value of 196.31 μg/mL. In addition, for the antimicrobial activity, each extract was tested by a serial two-fold dilution method against selected Gram-positive bacteria and Gram-negative bacteria, and this suggested that hexane in oven dry method possessed the maximum antimicrobial activity against the gram-positive bacteria tested. It is suggested that the antioxidant and antidiabetic properties were exhibited most in a polar solvent (MEOH) whether in air dry or oven dry method with no significant difference. In contrary with antimicrobial which was efficient in a non-polar solvent (HEX) in oven dry method. These results indicate that A. malaccensis is a promising source as herbal medicine

Media exposure, attitude, anxiety and practices among university students during the COVID-19 pandemic

The coronavirus disease 2019 (COVID-19) pandemic, which originated from China, went global within weeks. At the time of writing, almost 300 million people around the world have been infected by this potent and fast-spreading disease, which in many cases has paralysed economies and normal daily activities. University students are among the people that have been badly affected by the pandemic, as the movement control order (MCO) has resulted in university closure. Hence, many students are unable to proceed with their regular studies and have to be extra vigilant in dealing with the pandemic. During the MCO period, they rely heavily on media for guidance and information. This study was conducted to examine media exposure, attitude, anxiety, and practices towards COVID-19 amongst the students of Universiti Pendidikan Sultan Idris (UPSI), Perak, Malaysia. A quantitative research design was used to achieve the research objective. A total of 505 respondents answered an online survey and the findings revealed that respondents were highly dependent on various media for updated information about the pandemic, with the majority of them anxious about their safety. These findings are useful for higher education institutions in developing a better learning environment for students and understand the impact of the pandemic on students

Removal of cu2+ using utricularia aurea as a biosorbent in synthetic industrial wastewater/ Nor Azliza Akbar

Biosorption of copper ions (Cu2+) using Utricularia Aurea has been investigated as a function of pH, contact time and particle size of the biosorbent. A series of batch equilibrium adsorption study was conducted to determine the effect of varied pH from pH 2, 4, 7, and 9, contact time at 30, 60, 90 and 120 minutes, biosorbent particle size ranging from 150 µm, 300 µm, 450 µm and 600 µm at an agitation speed of 125 rpm using Utricularia aurea (U. Aurea). Based on the optimization study, it was found that the optimum removal of Cu2+ (>90%) occurred at pH4, contact time of 40 minutes and particle size of 450µm. Atomic Absorption Spectrometer was used to analyse the concentration of Cu2+ in the sample. A kinetic study on Cu2+ adsorption onto U.Aurea was analysed using pseudo-first order and pseudo second order kinetic models. Based on the kinetic study analysis, the adsorption of Cu2+ followed pseudo- second order kinetic which r2 was greater than 0.99 rather than pseudo- first order kinetic models. Thus, Utricularia Aurea can be an alternative as a new adsorbent media in treating heavy metals contaminated for industrial wastewater

E-learning and social media motivation factor model

The aims of this study are to probe into the motivational factors toward the usage of e-learning and social media among educational technology postgraduate students in the Faculty of Education, Universiti Teknologi Malaysia. This study had involved 70 respondents via the means of a questionnaire. Four factors have been studied, named, the factor of technology, exposure, content and social influence. Via Structural Equation Modeling (SEM), this research uncovers that respondents usage of e-learning is being motivated by the factor of technology and content. The respondents use of social media was found to be motivated by the factor of technology and social influence. A strong positive relationship exists between the usage of e-learning and social media suggesting that social media can be manipulated as supporting material for e-learning. Yet, the finding may not be generalized to all Malaysian educational technology postgraduate students

Developing and measuring an assessment instrument for media literacy among digital natives using Digital Intelligence (DQ) framework

The emergence of digitalisation focusing on media literacy is becoming more prevalent and thus forcing educators to embrace innovations as our digital natives are now shifting their attention to digital technologies. This study aimed to develop and measure an assessment instrument for media literacy focusing on knowledge, skills, and values for digital natives in Malaysia. Adopting the digital intelligence (DQ) framework, we have constructed the assessment instrument relevant to our digital natives of secondary school students and distributed it across schools in eleven states and one Federal Territory of Malaysia. We received a complete set of instruments from 1,276 respondents of Form Two and Form Four students and analyse the data by using descriptive and statistical analysis through SPSS. The findings of the study contribute to a more holistic assessment instrument that recognises the increasingly complex areas of knowledge, values, and skills for digital natives living in diverse, digitally-mediated environments

A review of knowledge graph embedding methods of TransE, TransH and TransR for missing links

Knowledge representation and reasoning require knowledge graph embedding as it is crucial in the area. It involves mapping entities and relationships from a knowledge graph into vectors of lower dimensions that are continuous in nature. This encoding enables machine learning algorithms to effectively reason and make predictions on graph-structured data. This review article offers an overview and critical analysis specifically about the methods of knowledge graph embedding which are TransE, TransH, and TransR. The key concepts, methodologies, strengths, and limitations of these methods, along with examining their applications and experiments conducted by existing researchers have been studied. The motivation to conduct this study is to review the well-known and most applied knowledge embedding methods and compare the features of those methods so that a comprehensive resource for researchers and practitioners interested in delving into knowledge graph embedding techniques is delivered

SYNTHESIS AND CHARACTERIZATION OF LEADFREE PIEZOELECTRIC (K0.5Na0.5) NbO3 PRODUCED WITH IMPROVED CALCINATION TEMPERATURE

Potassium sodium niobate (KNN) is one of the lead free piezoelectric material that catch the attention of researchers and also those in the industrial field because of its stable piezoelectric responses and environmental friendly composition. The recent development of KNN shows that many methods have been used to synthesize the KNN but the stoichiometric Ka0.5Na0.5NbO3 composition is extremely difficult to consolidate. One of the ways to overcome the problem is to precisely pre-calcine and use milling process for proper homogenization followed by natural sintering process. In this paper, attempt has been made to synthesize the KNN produced at 750 oC calcination temperature. The results of 1060oC sintering temperature for 2 hours show a good composition of KNN with orthorhombic crystal structure where the final sintered pellet can reach to a relative density up to 87.13 %