Abstract: Information and Communication Technologies (ICT) in mathematical education is a very active field of research and innovation, where learning is understood to be meaningful and grasping multiple linked representation rather than rote memorization, a great amount of literature offering a wide range of theories, learning approaches, methodologies and interpretations, are generally stressing the potentialities for teaching and learning using ICT. Despite the utilization of new learning approaches with ICT, students experience difficulties in learning concepts relevant to understanding mathematics, much remains unclear about the relationship between the computer environment, the activities it might support, and the knowledge that might emerge from such activities. Many questions that might arise in this regard: to what extent does the use of ICT help students in the process of understanding and solving tasks or problems? Is it possible to identify what aspects or features of students' mathematical learning can be enhanced by the use of technology? This paper will highlight the interest of the integration of information and communication technologies (ICT) into the teaching and learning of mathematics (quadratic functions), it aims to investigate the effect of four instructional methods on students- mathematical understanding and problem solving. Quantitative and qualitative methods are used to report about 43 students in middle school. Results showed that mathematical thinking and problem solving evolves as students engage with ICT activities and learn cooperatively.
Abstract: The presence of toxic heavy metals in industrial
effluents is one of the serious threats to the environment. Heavy
metals such as Cadmium, Chromium, Lead, Nickel, Zinc, Mercury,
Copper, Arsenic are found in the effluents of industries such as
foundries, electroplating, petrochemical, battery manufacturing,
tanneries, fertilizer, dying, textiles, metallurgical and metal finishing.
Tremendous increase of industrial copper usage and its presence in
industrial effluents has lead to a growing concern about the fate and
effects of Copper in the environment. Percolation of industrial
effluents through soils leads to contamination of ground water and
soils. The transport of heavy metals and their diffusion into the soils
has therefore, drawn the attention of the researchers.
In this study, an attempt has been made to delineate the
mechanisms of transport and fate of copper in terrestrial
environment. Column studies were conducted using perplex glass
square column of dimension side 15 cm and 1.35 m long. The soil
samples were collected from a natural drain near Mohali (India). The
soil was characterized to be poorly graded sandy loam. The soil was
compacted to the field dry density level of about 1.6 g/cm3. Break
through curves for different depths of the column were plotted. The
results of the column study indicated that the copper has high
tendency to flow in the soils and fewer tendencies to get absorbed on
the soil particles. The t1/2 estimates obtained from the studies can be
used for design copper laden wastewater disposal systems.
Abstract: Residue Number System (RNS) is a modular representation and is proved to be an instrumental tool in many digital signal processing (DSP) applications which require high-speed computations. RNS is an integer and non weighted number system; it can support parallel, carry-free, high-speed and low power arithmetic. A very interesting correspondence exists between the concepts of Multiple Valued Logic (MVL) and Residue Number Arithmetic. If the number of levels used to represent MVL signals is chosen to be consistent with the moduli which create the finite rings in the RNS, MVL becomes a very natural representation for the RNS. There are two concerns related to the application of this Number System: reaching the most possible speed and the largest dynamic range. There is a conflict when one wants to resolve both these problem. That is augmenting the dynamic range results in reducing the speed in the same time. For achieving the most performance a method is considere named “One-Hot Residue Number System" in this implementation the propagation is only equal to one transistor delay. The problem with this method is the huge increase in the number of transistors they are increased in order m2 . In real application this is practically impossible. In this paper combining the Multiple Valued Logic and One-Hot Residue Number System we represent a new method to resolve both of these two problems. In this paper we represent a novel design of an OHRNS-based adder circuit. This circuit is useable for Multiple Valued Logic moduli, in comparison to other RNS design; this circuit has considerably improved the number of transistors and power consumption.
Abstract: This paper presents a NDT by infrared thermography with excitation CO2 Laser, wavelength of 10.6 μm. This excitation is the controllable heating beam, confirmed by a preliminary test on a wooden plate 1.2 m x 0.9 m x 1 cm. As the first practice, this method is applied to detecting the defect in CFRP heated by the Laser 300 W during 40 s. Two samples 40 cm x 40 cm x 4.5 cm are prepared, one with defect, another one without defect. The laser beam passes through the lens of a deviation device, and heats the samples placed at a determinate position and area. As a result, the absence of adhesive can be detected. This method displays prominently its application as NDT with the composite materials. This work gives a good perspective to characterize the laser beam, which is very useful for the next detection campaigns.
Abstract: The effects of divers carbon substrates were
investigated for the tabtoxin production of an isolated pathogenic
Pseudomonas syringae pv. tabaci, the causal agent of wildfire of
tobacco and are discussed in relation to the bacterium growth. The
isolated organism was grown in batch culture on Woolley's
medium (28°C, 200 rpm, during 5 days). The growth has been
measured by the optical density (OD) at 620 nm and the tabtoxin
production quantified by Escherichia coli (K-12) bioassay
technique. The growth and the tabtoxin production were both
influenced by the substrates (sugars, amino acids, organic acids)
used, each, as a sole carbon source and as a supplement for the
same amino acids. The most significant quantities of tabtoxin were
obtained in presence of some amino acids used as sole carbon
source and/or as supplement.
Abstract: Cloud Computing is a new technology that helps us to
use the Cloud for compliance our computation needs. Cloud refers to a scalable network of computers that work together like Internet. An
important element in Cloud Computing is that we shift processing, managing, storing and implementing our data from, locality into the
Cloud; So it helps us to improve the efficiency. Because of it is new
technology, it has both advantages and disadvantages that are
scrutinized in this article. Then some vanguards of this technology
are studied. Afterwards we find out that Cloud Computing will have
important roles in our tomorrow life!
Abstract: In this paper we present a noise reduction filter for video processing. It is based on the recently proposed two dimensional steering kernel, extended to three dimensions and further augmented to suit the spatial-temporal domain of video processing. Two alternative filters are proposed - the time symmetric kernel and the time asymmetric kernel. The first reduces the noise on single sequences, but to handle the problems at scene shift the asymmetric kernel is introduced. The performance of both are tested on simulated data and on a real video sequence together with the existing steering kernel. The proposed kernels improves the Rooted Mean Squared Error (RMSE) compared to the original steering kernel method on video material.
Abstract: Although backpropagation ANNs generally predict
better than decision trees do for pattern classification problems, they
are often regarded as black boxes, i.e., their predictions cannot be
explained as those of decision trees. In many applications, it is
desirable to extract knowledge from trained ANNs for the users to
gain a better understanding of how the networks solve the problems.
A new rule extraction algorithm, called rule extraction from artificial
neural networks (REANN) is proposed and implemented to extract
symbolic rules from ANNs. A standard three-layer feedforward ANN
is the basis of the algorithm. A four-phase training algorithm is
proposed for backpropagation learning. Explicitness of the extracted
rules is supported by comparing them to the symbolic rules generated
by other methods. Extracted rules are comparable with other methods
in terms of number of rules, average number of conditions for a rule,
and predictive accuracy. Extensive experimental studies on several
benchmarks classification problems, such as breast cancer, iris,
diabetes, and season classification problems, demonstrate the
effectiveness of the proposed approach with good generalization
ability.
Abstract: In this paper we discuss the problems of the long-term management policy of Lake Peipsi and the roles of natural and anthropogenic factors in the ecological state of the lake. The reduction of the pollution during the last 15 years could not give significant changes of the chemical composition of the water, what implicates the essential role that natural factors have on the ecological state of lake. One of the most important factors having impact on the hydrochemical cycles and ecological state is the hydrological regime which is clearly expressed in L. Peipsi. The absence on clear interrelations of climate cycles and nutrients suggest that complex abiotic and biotic interactions, which take place in the lake ecosystem, plays a significant role in the matter circulation mechanism within lake.
Abstract: The removal of hydrogen sulphide is required for reasons of health, odour problems, safety and corrosivity problems. The means of removing hydrogen sulphide mainly depend on its concentration and kind of medium to be purified. The paper deals with a method of hydrogen sulphide removal from the air by its catalytic oxidation to elemental sulphur with the use of Fe-EDTA complex. The possibility of obtaining fibrous filtering materials able to remove small concentrations of H2S from the air were described. The base of these materials is fibrous ion exchanger with Fe(III)- EDTA complex immobilized on their functional groups. The complex of trivalent iron converts hydrogen sulphide to elemental sulphur. Bivalent iron formed in the reaction is oxidized by the atmospheric oxygen, so complex of trivalent iron is continuously regenerated and the overall process can be accounted as pseudocatalytic. In the present paper properties of several fibrous catalysts based on ion exchangers with different chemical nature (weak acid,weak base and strong base) were described. It was shown that the main parameters affecting the process of catalytic oxidation are:concentration of hydrogen sulphide in the air, relative humidity of the purified air, the process time and the content of Fe-EDTA complex in the fibres. The data presented show that the filtering layers with anion exchange package are much more active in the catalytic processes of hydrogen sulphide removal than cation exchanger and inert materials. In the addition to the nature of the fibres relative air humidity is a critical factor determining efficiency of the material in the air purification from H2S. It was proved that the most promising carrier of the Fe-EDTA catalyst for hydrogen sulphide oxidation are Fiban A-6 and Fiban AK-22 fibres.
Abstract: During the last couple of years, the degree of dependence on IT systems has reached a dimension nobody imagined to be possible 10 years ago. The increased usage of mobile devices (e.g., smart phones), wireless sensor networks and embedded devices (Internet of Things) are only some examples of the dependency of modern societies on cyber space. At the same time, the complexity of IT applications, e.g., because of the increasing use of cloud computing, is rising continuously. Along with this, the threats to IT security have increased both quantitatively and qualitatively, as recent examples like STUXNET or the supposed cyber attack on Illinois water system are proofing impressively. Once isolated control systems are nowadays often publicly available - a fact that has never been intended by the developers. Threats to IT systems don’t care about areas of responsibility. Especially with regard to Cyber Warfare, IT threats are no longer limited to company or industry boundaries, administrative jurisdictions or state boundaries. One of the important countermeasures is increased cooperation among the participants especially in the field of Cyber Defence. Besides political and legal challenges, there are technical ones as well. A better, at least partially automated exchange of information is essential to (i) enable sophisticated situational awareness and to (ii) counter the attacker in a coordinated way. Therefore, this publication performs an evaluation of state of the art Intrusion Detection Message Exchange protocols in order to guarantee a secure information exchange between different entities.
Abstract: As the majority of faults are found in a few of its
modules so there is a need to investigate the modules that are
affected severely as compared to other modules and proper
maintenance need to be done in time especially for the critical
applications. As, Neural networks, which have been already applied
in software engineering applications to build reliability growth
models predict the gross change or reusability metrics. Neural
networks are non-linear sophisticated modeling techniques that are
able to model complex functions. Neural network techniques are
used when exact nature of input and outputs is not known. A key
feature is that they learn the relationship between input and output
through training. In this present work, various Neural Network Based
techniques are explored and comparative analysis is performed for
the prediction of level of need of maintenance by predicting level
severity of faults present in NASA-s public domain defect dataset.
The comparison of different algorithms is made on the basis of Mean
Absolute Error, Root Mean Square Error and Accuracy Values. It is
concluded that Generalized Regression Networks is the best
algorithm for classification of the software components into different
level of severity of impact of the faults. The algorithm can be used to
develop model that can be used for identifying modules that are
heavily affected by the faults.
Abstract: Achievement motivation is believed to promote
giftedness attracting people to invest in many programs to adopt
gifted students providing them with challenging activities.
Intellectual giftedness is founded on the fluid intelligence and
extends to more specific abilities through the growth and inputs from
the achievement motivation. Acknowledging the roles played by the
motivation in the development of giftedness leads to an effective
nurturing of gifted individuals. However, no study has investigated
the direct and indirect effects of the achievement motivation and
fluid intelligence on intellectual giftedness. Thus, this study
investigated the contribution of motivation factors to giftedness
development by conducting tests of fluid intelligence using Cattell
Culture Fair Test (CCFT) and analytical abilities using culture
reduced test items covering problem solving, pattern recognition,
audio-logic, audio-matrices, and artificial language, and self report
questionnaire for the motivational factors. A number of 180 highscoring
students were selected using CCFT from a leading university
in Malaysia. Structural equation modeling was employed using Amos
V.16 to determine the direct and indirect effects of achievement
motivation factors (self confidence, success, perseverance,
competition, autonomy, responsibility, ambition, and locus of
control) on the intellectual giftedness. The findings showed that the
hypothesized model fitted the data, supporting the model postulates
and showed significant and strong direct and indirect effects of the
motivation and fluid intelligence on the intellectual giftedness.
Abstract: Inter-organizational Workflow (IOW) is commonly
used to support the collaboration between heterogeneous and
distributed business processes of different autonomous organizations
in order to achieve a common goal. E-government is considered as an
application field of IOW. The coordination of the different
organizations is the fundamental problem in IOW and remains the
major cause of failure in e-government projects. In this paper, we
introduce a new coordination model for IOW that improves the
collaboration between government administrations and that respects
IOW requirements applied to e-government. For this purpose, we
adopt a Multi-Agent approach, which deals more easily with interorganizational
digital government characteristics: distribution,
heterogeneity and autonomy. Our model integrates also different
technologies to deal with the semantic and technologic
interoperability. Moreover, it conserves the existing systems of
government administrations by offering a distributed coordination
based on interfaces communication. This is especially applied in
developing countries, where administrations are not necessary
equipped with workflow systems. The use of our coordination
techniques allows an easier migration for an e-government solution
and with a lower cost. To illustrate the applicability of the proposed
model, we present a case study of an identity card creation in Tunisia.
Abstract: The use of radar in Quantitative Precipitation Estimation (QPE) for radar-rainfall measurement is significantly beneficial. Radar has advantages in terms of high spatial and temporal condition in rainfall measurement and also forecasting. In Malaysia, radar application in QPE is still new and needs to be explored. This paper focuses on the Z/R derivation works of radarrainfall estimation based on rainfall classification. The works developed new Z/R relationships for Klang River Basin in Selangor area for three different general classes of rain events, namely low (10mm/hr, 30mm/hr) and also on more specific rain types during monsoon seasons. Looking at the high potential of Doppler radar in QPE, the newly formulated Z/R equations will be useful in improving the measurement of rainfall for any hydrological application, especially for flood forecasting.
Abstract: One of the long standing challenging aspect in mobile robotics is the ability to navigate autonomously, avoiding modeled and unmodeled obstacles especially in crowded and unpredictably changing environment. A successful way of structuring the navigation task in order to deal with the problem is within behavior based navigation approaches. In this study, Issues of individual behavior design and action coordination of the behaviors will be addressed using fuzzy logic. A layered approach is employed in this work in which a supervision layer based on the context makes a decision as to which behavior(s) to process (activate) rather than processing all behavior(s) and then blending the appropriate ones, as a result time and computational resources are saved.
Abstract: The recent global financial problem urges government
to play role in stimulating the economy due to the fact that private
sector has little ability to purchase during the recession. A concerned
question is whether the increased government spending crowds out
private consumption and whether it helps stimulate the economy. If
the government spending policy is effective; the private consumption
is expected to increase and can compensate the recent extra
government expense. In this study, the government spending is
categorized into government consumption spending and government
capital spending. The study firstly examines consumer consumption
along the line with the demand function in microeconomic theory.
Three categories of private consumption are used in the study. Those
are food consumption, non food consumption, and services
consumption. The dynamic Almost Ideal Demand System of the three
categories of the private consumption is estimated using the Vector
Error Correction Mechanism model. The estimated model indicates
the substituting effects (negative impacts) of the government
consumption spending on budget shares of private non food
consumption and of the government capital spending on budget share
of private food consumption, respectively. Nevertheless the result
does not necessarily indicate whether the negative effects of changes
in the budget shares of the non food and the food consumption means
fallen total private consumption. Microeconomic consumer demand
analysis clearly indicates changes in component structure of
aggregate expenditure in the economy as a result of the government
spending policy. The macroeconomic concept of aggregate demand
comprising consumption, investment, government spending (the
government consumption spending and the government capital
spending), export, and import are used to estimate for their
relationship using the Vector Error Correction Mechanism model.
The macroeconomic study found no effect of the government capital
spending on either the private consumption or the growth of GDP
while the government consumption spending has negative effect on
the growth of GDP. Therefore no crowding out effect of the
government spending is found on the private consumption but it is
ineffective and even inefficient expenditure as found reducing growth
of the GDP in the context of Thailand.
Abstract: The UML modeling of complex distributed systems often is a great challenge due to the large amount of parallel real-time operating components. In this paper the problems of verification of such systems are discussed. ECPN, an Extended Colored Petri Net is defined to formally describe state transitions of components and interactions among components. The relationship between sequence diagrams and Free Choice Petri Nets is investigated. Free Choice Petri Net theory helps verifying the liveness of sequence diagrams. By converting sequence diagrams to ECPNs and then comparing behaviors of sequence diagram ECPNs and statecharts, the consistency among models is analyzed. Finally, a verification process for an example model is demonstrated.
Abstract: This study investigated a strategy of blending lead-laden sludge and Al-rich precursors to reduce the release of metals from the stabilized products. Using PbO as the simulated lead-laden sludge to sinter with γ-Al2O3 by Pb:Al molar ratios of 1:2 and 1:12, PbAl2O4 and PbAl12O19 were formed as final products during the sintering process, respectively. By firing the PbO + γ-Al2O3 mixtures with different Pb/Al molar ratios at 600 to 1000 °C, the lead transformation was determined through X-ray diffraction (XRD) data. In Pb/Al molar ratio of 1/2 system, the formation of PbAl2O4 is initiated at 700 °C, but an effective formation was observed above 750 °C. An intermediate phase, Pb9Al8O21, was detected in the temperature range of 800-900 °C. However, different incorporation behavior for sintering PbO with Al-rich precursors at a Pb/Al molar ratio of 1/12 was observed during the formation of PbAl12O19 in this system. In the sintering process, both temperature and time effect on the formation of PbAl2O4 and PbAl12O19 phases were estimated. Finally, a prolonged leaching test modified from the U.S. Environmental Protection Agency-s toxicity characteristic leaching procedure (TCLP) was used to evaluate the durability of PbO, Pb9Al8O21, PbAl2O4 and PbAl12O19 phases. Comparison for the leaching results of the four phases demonstrated the higher intrinsic resistance of PbAl12O19 against acid attack.
Abstract: This paper presents the idea of a rough controller with application to control the overhead traveling crane system. The structure of such a controller is based on a suggested concept of a fuzzy logic controller. A measure of fuzziness in rough sets is introduced. A comparison between fuzzy logic controller and rough controller has been demonstrated. The results of a simulation comparing the performance of both controllers are shown. From these results we infer that the performance of the proposed rough controller is satisfactory.