Evaluation of social personalized adaptive E-Learning environments : end-user point of view

The use of adaptations, along with the social affordances of collaboration and networking, carries a great potential for improving e-learning experiences. However, the review of the previous work indicates current e-learning systems have only marginally explored the integration of social features and adaptation techniques. The overall aim of this research, therefore, is to address this gap by evaluating a system developed to foster social personalized adaptive e-learning experiences. We have developed our first prototype system, Topolor, based on the concepts of Adaptive Educational Hypermedia and Social E-Learning. We have also conducted an experimental case study for the evaluation of the prototype system from different perspectives. The results show a considerably high satisfaction of the end users. This paper reports the evaluation results from end user point of view, and generalizes our method to a component-based evaluation framework

Convective Heat Transfer Enhancement for Electronic Device Applications using Patterned MWCNTs Structures

This article reports on the heat transfer characteristics of columnar Vertically Aligned Multiwall Carbon Nanotubes (VA-MWCNTs) grown on a patterned Si surface. In the first part, we describe the procedure for patterning the silicon (Si) surface and the growth of MWCNTS on these patterned surfaces. The diameter of MWCNTs grown by Chemical Vapor Deposition (CVD) technique was in the range of 30-80 nm. In the second part structures mimicking macroscopic finned heat sinks are used for enhancing forced convective heat transfer on a silicon substrate. Convective heat transfer coefficient has been experimentally measured for silicon substrates with and without MWCNT-based fins on it. The configuration with MWCNTs based fins shows an enhancement in convective heat transfer of 40% and 20%, as maximum and average value respectively, compared to the bare silicon. Experiments have been carried out in a wind tunnel with air as coolant in fully turbulent regime. These encouraging results and the possibility of growing structures directly on silicon can be regarded as a first step

Silicon-mediated mitigation of wounding stress acts by up-regulating the rice antioxidant system

Silicon (Si) is essential for normal growth and development in plants and is also beneficial for their responses to wounding. However, the mechanisms by which Si acts to mitigate the effects of wounding is not fully understood. This effect possibly occurs through a reduction in the oxidative stresses associated with wounding. Here, we tested this possibility by investigating the effects of applying different concentrations of Si (0,5 and 1,0 mM) to rice plants under wounding stress for a period of 6 and 12 h. We found that a higher uptake of Si was signifiacntly associated with an increase in leaf chlorophyll contet. In response to wounding induced oxidative stress, the extent of lipid bilayer peroxidation was reduced in a dose-dependent manner by Si application for 6 or 12 h. Activity of the catalase enzyme was initially lowered by Si treatment; however, at 1.0 mM Si, catalase activity increased significantly after 12h of wounding stress. A similar response was also observed for a peroxidase enzyme. Polyphenol oxidase showed a significant reduction in activity. We conclude that Si application does not only improve leaf chlorophyll content but can also overcome the oxidative stress due wounds or physical injuries

study of carbon nanotubes based polydimethylsiloxane composite films

Thanks to their remarkable characteristics, carbon nanotubes (CNTs) have fields of applications which are growing every day. Among them, the use of CNTs as filler for polymers is one of the most promising. In this work we report on Polydimethylsiloxane (PDMS) composites with different weight percentages (0.0% to 3.0%) of multiwall carbon nanotubes (MWCNTs) having diameter 10?30 nm and length 20?30 ?m. To achieve optimum dispersion of CNTs in PDMS matrix, high speed mechanical stirring and ultrasonication were performed. By using the doctor blade technique, 70 ?m thick uniform films were produced on glass. They were subsequently thermally cured and detached from the glass to get flexible and self standing films. The surface morphological study done by FESEM, shows that CNTs are well dispersed in the PDMS. Raman spectroscopy and FTIR were used to investigate the possible structural changes in the polymer composite. To examine the optical behavior UV-VIS spectroscopy was employed in both specular and diffused modes. A linear increase in absorption coefficient is found with the increasing percentage of CNTs while the transmittance decreases exponentially. The results confirm the dependence of optical limiting effect on the quantity of MWCNTs. Based on optical study, MWCNTs/PDMS composite films can be a promising material to extend performances of optical limiters against laser pulses, which is often required in lasing systems

Search for Intermediate Mass Magnetic Monopoles and Nuclearites with the SLIM experiment

SLIM is a large area experiment (440 m2) installed at the Chacaltaya cosmic ray laboratory since 2001, and about 100 m2 at Koksil, Himalaya, since 2003. It is devoted to the search for intermediate mass magnetic monopoles (107-1013 GeV/c2) and nuclearites in the cosmic radiation using stacks of CR39 and Makrofol nuclear track detectors. In four years of operation it will reach a sensitivity to a flux of about 10-15 cm-2 s-1 sr-1. We present the results of the calibration of CR39 and Makrofol and the analysis of a first sample of the exposed detector.Comment: Presented at the 22nd ICNTS, Barcelona 200

A New Paradigm for Improved Image Steganography by using Adaptive Number of Dominant Discrete Cosine Transform Coefficients

Image steganography camouflages secret messages in images by tampering image contents. There is a natural desire for hiding maximum secret information with the least possible distortions in the host image. This requires an algorithm that intelligently optimizes the capacity keeping the required imperceptibility of the image. This paper presents an image steganography scheme that preserves an adaptively chosen block of dominant coefficients from each Discrete Cosine Transform coefficients, whereas the rest of the coefficients are replaced with normalized secret image pixel values. Secret image pixel value are normalized in an adaptively chosen range. Embedding such kind of normalized data in adaptively chosen non-square L- shaped blocks utilize maximum embedding space available in each block that consequently results in maximizing payload capacity, while maintaining the image quality. This scheme achieved payload capacity up to 21.5 bit per pixel (bpp), while maintaining image quality of 38.24 dB peak signal to noise ratio.Comment: 9 page

growth of vertically aligned multiwall carbon nanotubes columns

Capability of patterning carbon nanotubes (CNTs) growth is of tantamount importance for a number of applications ranging from thermal to electronic. This article reports on the columnar growth of vertically aligned multiwall carbon nanotubes (VA-MWCNTs) on patterned Silicon (Si) surface. We have developed procedures based on negative as well as positive masking approaches which allows the growth of predetermined MWCNTs patterns. We describe in detail the process steps leading to Si surface patterning. As quoted above, patterns are exploited to grow VA-MWCNTs. We have focused in particular on the growth of CNT pillars by chemical vapor despoition (CVD) technique at 850°C with camphor and ferrocene as carbon precursors and catalyst respectively. Field emission scanning electron microscopy (FESEM) is employed at low magnification to verify the correct patterning, and at high magnification to examine the surface morphology of CNTs pillars. The pillars are up to 2 mm high, their height being tailored through the deposition time. The diameter of each MWCNT is in the range 30–70 nm and the length is up to few hundred micrometers. The small CNT pillars produced, have several electrical and thermal applications. For instance they can be very useful for heat transfer systems as the lower thermal conductivity of fluids can be improved by the inclusion of nanotubes thanks to their peculiar 1-dimensional heat transfer characteristics

Search for massive rare particles with the SLIM experiment

The search for magnetic monopoles in the cosmic radiation remains one of the main aims of non-accelerator particle astrophysics. Experiments at high altitude allow lower mass thresholds with respect to detectors at sea level or underground. The SLIM experiment is a large array of nuclear track detectors at the Chacaltaya High Altitude Laboratory (5290 m a.s.l.). The results from the analysis of 171 m$^2$ exposed for more than 3.5 y are here reported. The completion of the analysis of the whole detector will allow to set the lowest flux upper limit for Magnetic Monopoles in the mass range 10$^5$ - 10$^{12}$ GeV. The experiment is also sensitive to SQM nuggets and Q-balls, which are possible Dark Matter candidates.Comment: Presented at the 29-th ICRC, Pune, India (2005

Dense-CaptionNet : a sentence generation architecture for fine-grained description of image semantics

Automatic image captioning, a highly challenging research problem, aims to understand and describe the contents of the complex scene in human understandable natural language. The majority of the recent solutions are based on holistic approaches where the scene is described as a whole, potentially losing the important semantic relationship of objects in the scene. We propose Dense-CaptionNet, a region-based deep architecture for fine-grained description of image semantics, which localizes and describes each object/region in the image separately and generates a more detailed description of the scene. The proposed network contains three components which work together to generate a fine-grained description of image semantics. Region descriptions and object relationships are generated by the first module, whereas the second one generates the attributes of objects present in the scene. The textual descriptions obtained as an output of the two modules are concatenated to feed as an input to the sentence generation module, which works on encoder-decoder formulation to generate a grammatically correct but single line, fine-grained description of the whole scene. The proposed Dense-CaptionNet is trained and tested using Visual Genome, MSCOCO, and IAPR TC-12 datasets. The results establish a new state-of-the-art when compared with the existing top performing methodologies, e.g., Up-Down-Captioner, Show, Attend and Tell, Semstyle, and Neural Talk, especially on complex scenes