3,975 research outputs found

    Pineapples internal quality inspection approaches and its potential effects in Malaysia

    Get PDF
    Pineapple (Ananas Comosus L. Metil) is a tropical plant under Bromeliaceous family that is grown in American tropics, subtropics, and warmer regions (U. Nations 2012). Pineapple is the second harvest tropical fruit after banana in the world (S. Ndungu 2014). Pineapple has spiny skin that will turn into yellowish brown from green when ripe. Pineapple is a non-climatic fruit that will stop ripping once it is harvested. Pineapple is famous not only because its taste but also its nutrients for health (M. Farid Hossain 2015, p.84). It contains nutriet that can supply suffiecient requirement of calcium, sodium, potassium, fibre, vitamin C, and so on. Those nutrients can help to build up healthy and growth of bone, enhance body immune system, and decrease high blood pressure for body system

    On two-variable guarded fragment logic with expressive local Presburger constraints

    Full text link
    We consider the extension of two-variable guarded fragment logic with local Presburger quantifiers. These are quantifiers that can express properties such as ``the number of incoming blue edges plus twice the number of outgoing red edges is at most three times the number of incoming green edges'' and captures various description logics with counting, but without constant symbols. We show that the satisfiability of this logic is EXP-complete. While the lower bound already holds for the standard two-variable guarded fragment logic, the upper bound is established by a novel, yet simple deterministic graph theoretic based algorithm

    Development of titanium dioxide nanoparticles/nanosolution for photocatalytic activity

    Get PDF
    Biological and chemical contaminants by man-made activities have been serious global issue. Exposure of these contaminants beyond the limits may result in serious environmental and health problem. Therefore, it is important to develop an effective solution that can be easily utilized by mankind. One of the effective ways to overcome this problem is by using titanium dioxide (TiO2). TiO2 is a well-known photocatalyst that widely used for environmental clean-up due to its ability to decompose organic pollutant and kill bacteria. Although it is proven TiO2 has an advantage to solve this concern, its usefulness unfortunately is limited only under UV light irradiation. Therefore, the aim of this work was to investigate the potential of TiO2 that can be activated under visible light by the incorporation of metal ions (Fe, Ag, Zr and Ag-Zr). In this study, sol-gel method was employed for the synthesis of metal ions incorporated TiO2. XRD analysis revealed that all samples content biphasic anatase-brookite TiO2 of size 3 nm to 5 nm. It was found that the incorporation of these metal ions did not change the morphology of TiO2 but the crystallinity and optical properties were affected. The crystallinity of anatase in the biphasic TiO2 was found to be decreased and favored brookite formation. PL analysis showed metal ions incorporation suppressed the recombination of electron-hole pairs while the band gap energy of TiO2 (3.2 eV) was decreased by the incorporation of Fe (2.46 eV) and Ag (2.86 eV). Among this incorporation, Ag-Zr incorporated TiO2 showed highest performance for methyl orange degradation (93%) under fluorescent xxv light irradiation for 10 h. This follows by Zr-TiO2 (82%), Fe-TiO2 (75%) and Ag�TiO2 (43%). Meanwhile, the highest antibacterial performance was exhibited by Ag�TiO2. TEM images showed that E.coli bacterium was killed within 12 h after treated with Ag-TiO2. The results obtained from the fieldwork study established that Ag-Zr incorporation have excellent performances for VOC removal and antibacterial test. The VOC content after treated with Ag-Zr-TiO2 fulfilled the Industry Code of Practice on Indoor Air Quality 2010 which is lower than 3 ppm. In addition, the percentage of microbes also found to be decrease around 45 % within 5 days of monitoring

    Use of SketchBook Pro with Tablet PC (TabSketch™) as a design thinking tool in the teaching and learning of design and technology

    Get PDF
    This paper shares the preliminary findings from the first two phases of an exploratory study on the potential of Tab-Sketch™ as i) a design-thinking tool for design and technology (D&T) teachers and pupils in secondary schools; ii) a teaching and learning tool for D&T teachers; and iii) a platform to document design-thinking in the form of digital design journal. Tab-Sketch is an acronym derived from Tablet PC and SketchBook Pro, a computer software. The study, which is naturalistic in approach, was initiated in Nov 2004 and has evolved into three phases. Phases 1 and 2 were completed. Phase 3 has commenced in Aug 2006 and will end in Dec 2007. The insights and experiences gained from the first two phases include: • the concept of ‘growing ideas’ conveniently and dynamically; • the potential of the software for quick sketches and editing via features like layer and the range of rendering tools available; • Tab-Sketch as a tool for the teacher-designer to dialogue with self and to practise rapid visualisation; • capturing design conversations graphically and digitally between teacher and pupil; and • ease in manipulating images and ideating presentation drawings. These preliminary findings have shaped Phase 3 of the study which is still on-going

    Ensemble candidate classification for the LOTAAS pulsar survey

    Get PDF
    One of the biggest challenges arising from modern large-scale pulsar surveys is the number of candidates generated. Here, we implemented several improvements to the machine learning (ML) classifier previously used by the LOFAR Tied-Array All-Sky Survey (LOTAAS) to look for new pulsars via filtering the candidates obtained during periodicity searches. To assist the ML algorithm, we have introduced new features which capture the frequency and time evolution of the signal and improved the signal-to-noise calculation accounting for broad profiles. We enhanced the ML classifier by including a third class characterizing RFI instances, allowing candidates arising from RFI to be isolated, reducing the false positive return rate. We also introduced a new training data set used by the ML algorithm that includes a large sample of pulsars misclassified by the previous classifier. Lastly, we developed an ensemble classifier comprised of five different Decision Trees. Taken together these updates improve the pulsar recall rate by 2.5 per cent, while also improving the ability to identify pulsars with wide pulse profiles, often misclassified by the previous classifier. The new ensemble classifier is also able to reduce the percentage of false positive candidates identified from each LOTAAS pointing from 2.5 per cent (∼500 candidates) to 1.1 per cent (∼220 candidates)

    A novel wideband dynamic directional indoor channel model based on a Markov process

    Get PDF
    This document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available
    corecore