The Impact of Personality Traits Towards the Intention to Adopt Mobile Learning

Mobile devices have become increasingly more common in the digitally connected world. Mobile learning as a model of e-learning refers to the acquisition of knowledge & skills utilizing mobile technologies. The aim of this study is to identify the extrinsic influential factors for the adoption of mobile learning. This study proposes the use of an extended technology acceptance model (TAM) theory that includes variables of personality traits such as perceived enjoyment and computer self-efficiency. The participants of this study were 351 students at University Technology Malaysia who had experiences in e-learning. The study found that perceived usefulness as an extrinsic factor has the highest influence on students’ intention to adopt mobile learning through an investigation of technology acceptance toward mobile learning. Personality traits such as perceived enjoyment and self-efficacy have impact on behavior intention to adopt mobile learning

Quantifying the Emergence of Dengue in Hanoi, Vietnam: 1998–2009

Dengue is the most common vector-borne viral disease of humans, causing an estimated 50 million cases per year. The number of countries affected by dengue has increased dramatically in the last 50 years and dengue is now a major public health problem in large parts of the tropical and subtropical world. It is of considerable importance to understand the factors that determine how dengue becomes newly established in areas where the risk of dengue was previously small. Hanoi in North Vietnam is a large city where dengue appears to be emerging. We analyzed 12 years of dengue surveillance data in order to characterize the temporal and spatial epidemiology of dengue in Hanoi and to establish if dengue incidence has been increasing. After excluding the two major outbreak years of 1998 and 2009 and correcting for changes in population age structure over time, we found there was a significant annual increase in the incidence of notified dengue cases over the period 1999–2008. Dengue cases were concentrated in young adults in the highly urban central areas of Hanoi. This study indicates that dengue transmission is increasing in Hanoi and provides a platform for further studies of the underlying drivers of this emergence

Antifungal activity of extracts and phenolic compounds from Barringtonia racemosa L. (Lecythidaceae)

The antifungal activity of methanolic, ethanolic and boiling water extracts of Barringtonia racemosa leaves, sticks and barks were investigate against Fusarium sp., Tricoderma koningii, Penicillium sp.,Ganoderma tropicum, Ganoderma lucidum, Aspergillus sp. and Rhizopus sp. at concentration of 50 mg/ml. Better antifungal activity was observed with the methanolic extracts in all aerial parts of B.racemosa that showed excellent inhibitory activity against all the fungi tested. The strongest inhibitory activity effect was observed with the methanolic extract of leaf against Fusarium sp. (53.45%), G.lucidum (34.57%), Aspergillus sp. (32.27%) and T. koningii (20.99%). Remarkable are also the specific effects of the boiling water extract of leaf against Fusarium sp. (51.72%) and with the ethanolic extractof bark against Rhizopus sp. (37.50%). None of the boiling water extracts of leaf, stick and bark showed inhibitory activity effect against G. tropicum and T. koningii. Among different fungi tested, Fusarium sp.was found to be more sensitive to B. racemosa extracts when compared to others. The increase in the production of phenolics in the extracts can be correlated with the induction of resistance in treatedplant against phytopathogenic fungi. HPLC analysis of the extract of B. racemosa (leaves, sticks and barks) showed two different phenolic acids (gallic acid and ferrulic acid) and four different flavonoids(naringin, rutin, luteolin and kaempferol). The results of present study provide scientific basis for the use of the plant extract in the future development as antifungal, antibacterial, antioxidant and antiinflammatory agent

FIS-SMED: a fuzzy inference system application for plastic injection mold changeover

Dr. Shingo's SMED (single minute exchange of dies) methodology is the most well-known method for changeover time reduction using both simple methodological solutions and tool/design changes. Simplification and standardization are the main technique of SMED to make the changeover process independent from personal experience. However, in plastic injection molding, process parameter setting after changing the molds totally depends on the varied expertise levels of setup experts. The number of available setup experts in a shift dictates the number of changeover that can be given to the production plan. Due to this dependency, expected benefits of SMED cannot be realized. In this paper, an application of a fuzzy inference system (FIS) is presented for parameter adjustments during changeovers on plastic injection molds. The proposed system captures the highest level of domain expertise and makes it applicable by machine operators. Integrating this system into SMED applications encourages production lot size reduction. Moreover, proposed FIS increases the quality awareness of machine operators and can be used to train new ones