Abstract: This paper presents the findings of an
experimental investigation to study the effect of alkali content
in geopolymer mortar specimens exposed to sulphuric acid.
Geopolymer mortar specimens were manufactured from Class F fly
ash by activation with a mixture of sodium hydroxide and sodium
silicate solution containing 5% to 8% Na2O. Durability of specimens
were assessed by immersing them in 10% sulphuric acid solution and
periodically monitoring surface deterioration and depth of
dealkalization, changes in weight and residual compressive strength
over a period of 24 weeks. Microstructural changes in the specimens
were studied with Scanning electron microscopy (SEM) and EDAX.
Alkali content in the activator solution significantly affects the
durability of fly ash based geopolymer mortars in sulphuric acid.
Specimens manufactured with higher alkali content performed better
than those manufactured with lower alkali content. After 24 weeks in
sulphuric acid, specimen with 8% alkali still recorded a residual
strength as high as 55%.
Abstract: The purpose of this study was to assess the value of Second Life among post-secondary instructors with experience using Second Life as an educational tool. Using Everett Rogers-s diffusion of innovations theory, survey respondents (N = 162), were divided into three adopter categories: innovators, early adopters and the early majority. Respondents were from 15 countries and 25 academic disciplines, indicating the considerable potential this innovation has to be adopted across many different borders and in many areas of academe. Nearly 94% of respondents said they plan to use Second Life again as an educational tool. However, no significant differences were found in instructors- levels of satisfaction with Second Life as an educational tool or their perceived effect on student learning across adopter categories. On the other hand, instructors who conducted class fully in Second Life were significantly more satisfied than those who used Second Life as only a small supplement to a real-world class. Overall, personal interest factors, rather than interpersonal communication factors, most influenced respondents- decision to adopt Second Life as an educational tool. In light of these findings, theoretical implications are discussed and practical suggestions are provided.
Abstract: Data mining uses a variety of techniques each of which is useful for some particular task. It is important to have a deep understanding of each technique and be able to perform sophisticated analysis. In this article we describe a tool built to simulate a variation of the Kohonen network to perform unsupervised clustering and support the entire data mining process up to results visualization. A graphical representation helps the user to find out a strategy to optmize classification by adding, moving or delete a neuron in order to change the number of classes. The tool is also able to automatically suggest a strategy for number of classes optimization.The tool is used to classify macroeconomic data that report the most developed countries? import and export. It is possible to classify the countries based on their economic behaviour and use an ad hoc tool to characterize the commercial behaviour of a country in a selected class from the analysis of positive and negative features that contribute to classes formation.
Abstract: This study demonstrates the use of Class F fly ash in
combination with lime or lime kiln dust in the full depth reclamation
(FDR) of asphalt pavements. FDR, in the context of this paper, is a
process of pulverizing a predetermined amount of flexible pavement
that is structurally deficient, blending it with chemical additives and
water, and compacting it in place to construct a new stabilized base
course. Test sections of two structurally deficient asphalt pavements
were reclaimed using Class F fly ash in combination with lime and
lime kiln dust. In addition, control sections were constructed using
cement, cement and emulsion, lime kiln dust and emulsion, and mill
and fill. The service performance and structural behavior of the FDR
pavement test sections were monitored to determine how the fly ash
sections compared to other more traditional pavement rehabilitation
techniques. Service performance and structural behavior were
determined with the use of sensors embedded in the road and Falling
Weight Deflectometer (FWD) tests. Monitoring results of the FWD
tests conducted up to 2 years after reclamation show that the cement,
fly ash+LKD, and fly ash+lime sections exhibited two year resilient
modulus values comparable to open graded cement stabilized
aggregates (more than 750 ksi). The cement treatment resulted in a
significant increase in resilient modulus within 3 weeks of
construction and beyond this curing time, the stiffness increase was
slow. On the other hand, the fly ash+LKD and fly ash+lime test
sections indicated slower shorter-term increase in stiffness. The fly
ash+LKD and fly ash+lime section average resilient modulus values
at two years after construction were in excess of 800 ksi. Additional
longer-term testing data will be available from ongoing pavement
performance and environmental condition data collection at the two
pavement sites.
Abstract: Information on weed distribution within the field is necessary to implement spatially variable herbicide application. Since hand labor is costly, an automated weed control system could be feasible. This paper deals with the development of an algorithm for real time specific weed recognition system based on Histogram Maxima with threshold of an image that is used for the weed classification. This algorithm is specifically developed to classify images into broad and narrow class for real-time selective herbicide application. The developed system has been tested on weeds in the lab, which have shown that the system to be very effectiveness in weed identification. Further the results show a very reliable performance on images of weeds taken under varying field conditions. The analysis of the results shows over 95 percent classification accuracy over 140 sample images (broad and narrow) with 70 samples from each category of weeds.