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: This study examines perception of environmental
approach in small and medium-sized enterprises (SMEs) – the
process by which firms integrate environmental concern into
business. Based on a review of the literature, the paper synthesizes
focus on environmental issues with the reflection in a case study in
the Czech Republic. Two themes of corporate environmentalism are
discussed – corporate environmental orientation and corporate
stances toward environmental concerns. It provides theoretical
material on greening organizational culture that is helpful in
understanding the response of contemporary business to
environmental problems. We integrate theoretical predictions with
empirical findings confronted with reality. Scales to measure these
themes are tested in a survey of managers in 229 Czech firms. We
used the process of in-depth questioning. The research question was
derived and answered in the context of the corresponding literature
and conducted research. A case study showed us that environmental
approach is variety different (depending on the size of the firm) in
SMEs sector. The results of the empirical mapping demonstrate
Czech company’s approach to environment and define the problem
areas and pinpoint the main limitation in the expansion of
environmental aspects. We contribute to the debate for recognition of
the particular role of environmental issues in business reality.
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: Magnetic Resonance Imaging play a vital role in the decision-diagnosis process of brain MR images. For an accurate diagnosis of brain related problems, the experts mostly compares both T1 and T2 weighted images as the information presented in these two images are complementary. In this paper, rotational and translational invariant form of Local binary Pattern (LBP) with additional gray scale information is used to retrieve similar slices of T1 weighted images from T2 weighted images or vice versa. The incorporation of additional gray scale information on LBP can extract more local texture information. The accuracy of retrieval can be improved by extracting moment features of LBP and reweighting the features based on users feedback. Here retrieval is done in a single subject scenario where similar images of a particular subject at a particular level are retrieved, and multiple subjects scenario where relevant images at a particular level across the subjects are retrieved.
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: 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: In this paper, in addition to introducing good urban planning and its effects on globalization, some new methodologies in urban management and another urban aspects has been presented. Some new concerns in increasing of urban population , metropolitans and its relations on big problems has been focused in this paper. It is very important matter that future urban planning with based on globalization will be with full of basically changes in its management and perspectives.
Abstract: Fair share is one of the scheduling objectives supported on many production systems. However, fair share has been shown to cause performance problems for some users, especially the users with difficult jobs. This work is focusing on extending goaloriented parallel computer job scheduling policies to cover the fair share objective. Goal-oriented parallel computer job scheduling policies have been shown to achieve good scheduling performances when conflicting objectives are required. Goal-oriented policies achieve such good performance by using anytime combinatorial search techniques to find a good compromised schedule within a time limit. The experimental results show that the proposed goal-oriented parallel computer job scheduling policy (namely Tradeofffs( Tw:avgX)) achieves good scheduling performances and also provides good fair share performance.
Abstract: The dental composites are preferably used as filling
materials due to their esthetic appearances. Nevertheless one of the
major problems, during the application of the dental composites, is
shape change named as “polymerisation shrinkage" affecting clinical
success of the dental restoration while photo-polymerisation.
Polymerisation shrinkage of composites arises basically from the
formation of a polymer due to the monomer transformation which
composes of an organic matrix phase. It was sought, throughout this
study, to detect and evaluate the structural polymerisation shrinkage
of prepared dental composites in order to optimize the effects of
various fillers included in hydroxyapatite (HA)-reinforced dental
composites and hence to find a means to modify the properties of
these dental composites prepared with defined parameters. As a
result, the shrinkage values of the experimental dental composites
were decreased by increasing the filler content of composites and the
composition of different fillers used had effect on the shrinkage of
the prepared composite systems.
Abstract: In over deployed sensor networks, one approach
to Conserve energy is to keep only a small subset of sensors
active at Any instant. For the coverage problems, the monitoring
area in a set of points that require sensing, called demand points, and
consider that the node coverage area is a circle of range R, where R
is the sensing range, If the Distance between a demand point and
a sensor node is less than R, the node is able to cover this point. We
consider a wireless sensor network consisting of a set of sensors
deployed randomly. A point in the monitored area is covered if it is
within the sensing range of a sensor. In some applications, when the
network is sufficiently dense, area coverage can be approximated by
guaranteeing point coverage. In this case, all the points of wireless
devices could be used to represent the whole area, and the working
sensors are supposed to cover all the sensors. We also introduce
Hybrid Algorithm and challenges related to coverage in sensor
networks.
Abstract: In order to alleviate the mental and physical problems
of persons with disabilities, animal-assisted therapy (AAT) is one of
the possible modalities that employs the merit of the human-animal
interaction. Nevertheless, to achieve the purpose of AAT for persons
with severe disabilities (e.g. spinal cord injury, stroke, and
amyotrophic lateral sclerosis), real-time animal language
interpretation is desirable. Since canine behaviors can be visually
notable from its tail, this paper proposes the automatic real-time
interpretation of canine tail language for human-canine interaction in
the case of persons with severe disabilities. Canine tail language is
captured via two 3-axis accelerometers. Directions and frequencies
are selected as our features of interests. The novel fuzzy rules based
on Gaussian-Trapezoidal model and center of gravity (COG)-based
defuzzification method are proposed in order to interpret the features
into four canine emotional behaviors, i.e., agitate, happy, scare and
neutral as well as its blended emotional behaviors. The emotional
behavior model is performed in the simulated dog and has also been
evaluated in the real dog with the perfect recognition rate.
Abstract: This research investigates the suitability of fuel oil in
improving gypseous soil. A detailed laboratory tests were carried-out
on two soils (soil I with 51.6% gypsum content, and soil II with
26.55%), where the two soils were obtained from Al-Therthar site
(Al-Anbar Province-Iraq).
This study examines the improvement of soil properties using the
gypsum material which is locally available with low cost to minimize
the effect of moisture on these soils by using the fuel oil. This study
was conducted on two models of the soil gypsum, from the Tharthar
area. The first model was sandy soil with Gypsum content of (51.6%)
and the second is clayey soil and the content of Gypsum is (26.55%).
The program included tests measuring the permeability and
compressibility of the soil and their collapse properties. The shear
strength of the soil and the amounts of weight loss of fuel oil due to
drying had been found. These tests have been conducted on the
treated and untreated soils to observe the effect of soil treatment on
the engineering properties when mixed with varying degrees of fuel
oil with the equivalent of the water content.
The results showed that fuel oil is a good material to modify the
basic properties of the gypseous soil of collapsibility and
permeability, which are the main problems of this soil and retained
the soil by an appropriate amount of the cohesion suitable for
carrying the loads from the structure.
Abstract: This paper presents an optimal design of linear phase
digital high pass finite impulse response (FIR) filter using Improved
Particle Swarm Optimization (IPSO). In the design process, the filter
length, pass band and stop band frequencies, feasible pass band and
stop band ripple sizes are specified. FIR filter design is a multi-modal
optimization problem. An iterative method is introduced to find the
optimal solution of FIR filter design problem. Evolutionary
algorithms like real code genetic algorithm (RGA), particle swarm
optimization (PSO), improved particle swarm optimization (IPSO)
have been used in this work for the design of linear phase high pass
FIR filter. IPSO is an improved PSO that proposes a new definition
for the velocity vector and swarm updating and hence the solution
quality is improved. A comparison of simulation results reveals the
optimization efficacy of the algorithm over the prevailing
optimization techniques for the solution of the multimodal, nondifferentiable,
highly non-linear, and constrained FIR filter design
problems.
Abstract: This paper provides a framework in order to
incorporate reliability issue as a sign of disruption in distribution
systems and partial covering theory as a response to limitation in
coverage radios and economical preferences, simultaneously into the
traditional literatures of capacitated facility location problems. As a
result we develop a bi-objective model based on the discrete
scenarios for expected cost minimization and demands coverage
maximization through a three echelon supply chain network by
facilitating multi-capacity levels for provider side layers and
imposing gradual coverage function for distribution centers (DCs).
Additionally, in spite of objectives aggregation for solving the model
through LINGO software, a branch of LP-Metric method called Min-
Max approach is proposed and different aspects of corresponds
model will be explored.
Abstract: In this paper a class of numerical methods to solve linear and nonlinear PDEs and also systems of PDEs is developed. The Differential Transform method associated with the Method of Lines (MoL) is used. The theory for linear problems is extended to the nonlinear case, and a recurrence relation is established. This method can achieve an arbitrary high-order accuracy in time. A variable stepsize algorithm and some numerical results are also presented.
Abstract: The essentiality of maintenance assessment and
maintenance optimization in design stage is analyzed, and the existent
problems of conventional maintenance design method are illuminated.
MDMVM (Maintenance Design Method based Virtual Maintenance)
is illuminated, and the process of MDMVM established, and the
MDMVM architecture is given out. The key techniques of MDMVM
are analyzed, and include maintenance design based KBE (Knowledge
Based Engineering) and virtual maintenance based physically
attribute. According to physical property, physically based modeling,
visual object movement control, the simulation of operation force and
maintenance sequence planning method are emphatically illuminated.
Maintenance design system based virtual maintenance is established in
foundation of maintenance design method.
Abstract: Elastic boundary eigensolution problems are converted
into boundary integral equations by potential theory. The kernels of
the boundary integral equations have both the logarithmic and Hilbert
singularity simultaneously. We present the mechanical quadrature
methods for solving eigensolutions of the boundary integral equations
by dealing with two kinds of singularities at the same time. The methods
possess high accuracy O(h3) and low computing complexity. The
convergence and stability are proved based on Anselone-s collective
compact theory. Bases on the asymptotic error expansion with odd
powers, we can greatly improve the accuracy of the approximation,
and also derive a posteriori error estimate which can be used for
constructing self-adaptive algorithms. The efficiency of the algorithms
are illustrated by numerical examples.