Abstract: In this paper, some problem formulations of dynamic object parameters recovery described by non-autonomous system of ordinary differential equations with multipoint unshared edge conditions are investigated. Depending on the number of additional conditions the problem is reduced to an algebraic equations system or to a problem of quadratic programming. With this purpose the paper offers a new scheme of the edge conditions transfer method called by conditions shift. The method permits to get rid from differential links and multipoint unshared initially-edge conditions. The advantage of the proposed approach is concluded by capabilities of reduction of a parametric identification problem to essential simple problems of the solution of an algebraic system or quadratic programming.
Abstract: A method for solving linear and non-linear Goursat
problem is given by using the two-dimensional differential transform
method. The approximate solution of this problem is calculated in
the form of a series with easily computable terms and also the exact
solutions can be achieved by the known forms of the series solutions.
The method can easily be applied to many linear and non-linear
problems and is capable of reducing the size of computational work.
Several examples are given to demonstrate the reliability and the
performance of the presented method.
Abstract: Data mining is an extraordinarily demanding field referring to extraction of implicit knowledge and relationships, which are not explicitly stored in databases. A wide variety of methods of data mining have been introduced (classification, characterization, generalization...). Each one of these methods includes more than algorithm. A system of data mining implies different user categories,, which mean that the user-s behavior must be a component of the system. The problem at this level is to know which algorithm of which method to employ for an exploratory end, which one for a decisional end, and how can they collaborate and communicate. Agent paradigm presents a new way of conception and realizing of data mining system. The purpose is to combine different algorithms of data mining to prepare elements for decision-makers, benefiting from the possibilities offered by the multi-agent systems. In this paper the agent framework for data mining is introduced, and its overall architecture and functionality are presented. The validation is made on spatial data. Principal results will be presented.
Abstract: This paper deals with a power-conscious ANDEXOR- Inverter type logic implementation for a complex class of Boolean functions, namely Achilles- heel functions. Different variants of the above function class have been considered viz. positive, negative and pure horn for analysis and simulation purposes. The proposed realization is compared with the decomposed implementation corresponding to an existing standard AND-EXOR logic minimizer; both result in Boolean networks with good testability attribute. It could be noted that an AND-OR-EXOR type logic network does not exist for the positive phase of this unique class of logic function. Experimental results report significant savings in all the power consumption components for designs based on standard cells pertaining to a 130nm UMC CMOS process The simulations have been extended to validate the savings across all three library corners (typical, best and worst case specifications).
Abstract: Accurate and comprehensive thermodynamic properties of pure and mixture of refrigerants are in demand by both producers and users of these materials. Information about thermodynamic properties is important initially to qualify potential candidates for working fluids in refrigeration machinery. From practical point of view, Refrigerants and refrigerant mixtures are widely used as working fluids in many industrial applications, such as refrigerators, heat pumps, and power plants The present work is devoted to evaluating seven cubic equations of state (EOS) in predicting gas and liquid phase volumetric properties of nine ozone-safe refrigerants both in super and sub-critical regions. The evaluations, in sub-critical region, show that TWU and PR EOS are capable of predicting PVT properties of refrigerants R32 within 2%, R22, R134a, R152a and R143a within 1% and R123, R124, R125, TWU and PR EOS's, from literature data are 0.5% for R22, R32, R152a, R143a, and R125, 1% for R123, R134a, and R141b, and 2% for R124. Moreover, SRK EOS predicts PVT properties of R22, R125, and R123 to within aforementioned errors. The remaining EOS's predicts volumetric properties of this class of fluids with higher errors than those above mentioned which are at most 8%.In general, the results are in favor of the preference of TWU and PR EOS over other remaining EOS's in predicting densities of all mentioned refrigerants in both super and sub critical regions. Typically, this refrigerant is known to offer advantages such as ozone depleting potential equal to zero, Global warming potential equal to 140, and no toxic.
Abstract: Due to their high power-to-weight ratio and low cost,
pneumatic actuators are attractive for robotics and automation
applications; however, achieving fast and accurate control of their
position have been known as a complex control problem. A
methodology for obtaining high position accuracy with a linear
pneumatic actuator is presented. During experimentation with a
number of PID classical control approaches over many operations of
the pneumatic system, the need for frequent manual re-tuning of the
controller could not be eliminated. The reason for this problem is
thermal and energy losses inside the cylinder body due to the
complex friction forces developed by the piston displacements.
Although PD controllers performed very well over short periods, it
was necessary in our research project to introduce some form of
automatic gain-scheduling to achieve good long-term performance.
We chose a fuzzy logic system to do this, which proved to be an
easily designed and robust approach. Since the PD approach showed
very good behaviour in terms of position accuracy and settling time,
it was incorporated into a modified form of the 1st order Tagaki-
Sugeno fuzzy method to build an overall controller. This fuzzy gainscheduler
uses an input variable which automatically changes the PD
gain values of the controller according to the frequency of repeated
system operations. Performance of the new controller was
significantly improved and the need for manual re-tuning was
eliminated without a decrease in performance. The performance of
the controller operating with the above method is going to be tested
through a high-speed web network (GRID) for research purposes.
Abstract: In this paper we present a new approach to detecting a
flaw in T.O.F.D (Time Of Flight Diffraction) type ultrasonic image
based on texture features. Texture is one of the most important
features used in recognizing patterns in an image. The paper
describes texture features based on 2D Gabor functions, i.e.,
Gaussian shaped band-pass filters, with dyadic treatment of the radial
spatial frequency range and multiple orientations, which represent an
appropriate choice for tasks requiring simultaneous measurement in
both space and frequency domains. The most relevant features are
used as input data on a Fuzzy c-mean clustering classifier. The
classes that exist are only two: 'defects' or 'no defects'. The proposed
approach is tested on the T.O.F.D image achieved at the laboratory
and on the industrial field.
Abstract: An implementation of current-mode multiphase sinusoidal oscillators is presented. Using CFTA-based lossy integrators, odd and odd/even phase systems can be realized with following advantages. The condition of oscillation and frequency of oscillation can be orthogonally tuned. The high output impedances facilitate easy driving an external load without additional current buffers. The proposed MSOs provide odd or even phase signals that are equally spaced in phase and equal amplitude. The circuit requires one CFTA, one resistor and one grounded capacitor per phase without additional current amplifier. The results of PSPICE simulations using CMOS CFTA are included to verify theory.
Abstract: In this paper, we propose a new image segmentation approach for colour textured images. The proposed method for image segmentation consists of two stages. In the first stage, textural features using gray level co-occurrence matrix(GLCM) are computed for regions of interest (ROI) considered for each class. ROI acts as ground truth for the classes. Ohta model (I1, I2, I3) is the colour model used for segmentation. Statistical mean feature at certain inter pixel distance (IPD) of I2 component was considered to be the optimized textural feature for further segmentation. In the second stage, the feature matrix obtained is assumed to be the degraded version of the image labels and modeled as Markov Random Field (MRF) model to model the unknown image labels. The labels are estimated through maximum a posteriori (MAP) estimation criterion using ICM algorithm. The performance of the proposed approach is compared with that of the existing schemes, JSEG and another scheme which uses GLCM and MRF in RGB colour space. The proposed method is found to be outperforming the existing ones in terms of segmentation accuracy with acceptable rate of convergence. The results are validated with synthetic and real textured images.
Abstract: This research was conducted to develop a correlation
between microstructure of HSLA steel and the mechanical properties
that occur as a result of both laser and mechanical forming processes
of the metal. The technique of forming flat metals by applying laser
beams is a relatively new concept in the manufacturing industry.
However, the effects of laser energy on the stability of metal alloy
phases have not yet been elucidated in terms of phase
transformations and microhardness. In this work, CO2 laser source
was used to irradiate the surface of a flat metal then the
microstructure and microhardness of the metal were studied on the
formed specimen. The extent to which the microstructure changed
depended on the heat inputs of up to 1000 J/cm2 with cooling rates of
about 4.8E+02 K/s. Experimental results revealed that the irradiated
surface of a HSLA steel had transformed to austenitic structure
during the heating process.
Abstract: Moulded parts contribute to more than 70% of
components in products. However, common defects particularly in
plastic injection moulding exist such as: warpage, shrinkage, sink
marks, and weld lines. In this paper Taguchi experimental design
methods are applied to reduce the warpage defect of thin plate
Acrylonitrile Butadiene Styrene (ABS) and are demonstrated in two
levels; namely, orthogonal arrays of Taguchi and the Analysis of
Variance (ANOVA). Eight trials have been run in which the optimal
parameters that can minimize the warpage defect in factorial
experiment are obtained. The results obtained from ANOVA
approach analysis with respect to those derived from MINITAB
illustrate the most significant factors which may cause warpage in
injection moulding process. Moreover, ANOVA approach in
comparison with other approaches like S/N ratio is more accurate and
with the interaction of factors it is possible to achieve higher and the
better outcomes.
Abstract: Cluster analysis is the name given to a diverse collection of techniques that can be used to classify objects (e.g. individuals, quadrats, species etc). While Kohonen's Self-Organizing Feature Map (SOFM) or Self-Organizing Map (SOM) networks have been successfully applied as a classification tool to various problem domains, including speech recognition, image data compression, image or character recognition, robot control and medical diagnosis, its potential as a robust substitute for clustering analysis remains relatively unresearched. SOM networks combine competitive learning with dimensionality reduction by smoothing the clusters with respect to an a priori grid and provide a powerful tool for data visualization. In this paper, SOM is used for creating a toroidal mapping of two-dimensional lattice to perform cluster analysis on results of a chemical analysis of wines produced in the same region in Italy but derived from three different cultivators, referred to as the “wine recognition data" located in the University of California-Irvine database. The results are encouraging and it is believed that SOM would make an appealing and powerful decision-support system tool for clustering tasks and for data visualization.
Abstract: The paper presents the influence of the conventional
ploughing tillage technology in comparison with the minimum
tillage, upon the soil properties, weed control and yield in the case of
maize (Zea mays L.), soya-bean (Glycine hispida L.) and winter
wheat (Triticum aestivum L.) in a three years crop rotation. A
research has been conducted at the University of Agricultural
Sciences and Veterinary Medicine Cluj-Napoca, Romania. The use of
minimum soil tillage systems within a three years rotation: maize,
soya-bean, wheat favorites the rise of the aggregates hydro stability
with 5.6-7.5% on a 0-20 cm depth and 5-11% on 20-30 cm depth.
The minimum soil tillage systems – paraplow, chisel or rotary grape
– are polyvalent alternatives for basic preparation, germination bed
preparation and sowing, for fields and crops with moderate loose
requirements being optimized technologies for: soil natural fertility
activation and rationalization, reduction of erosion, increasing the
accumulation capacity for water and realization of sowing in the
optimal period. The soil tillage system influences the productivity
elements of cultivated species and finally the productions thus
obtained. Thus, related to conventional working system, the
productions registered in minimum tillage working represented 89-
97% in maize, 103-112% in soya-bean, 93-99% in winter-wheat. The
results of investigations showed that the yield is a conclusion soil
tillage systems influence on soil properties, plant density assurance
and on weed control. Under minimum tillage systems in the case of
winter weat as an option for replacing classic ploughing, the best
results in terms of quality indices were obtained from version worked
with paraplow, followed by rotary harrow and chisel. At variants
worked with paraplow were obtained quality indices close to those of
the variant worked with plow, and protein and gluten content was
even higher. At Ariesan variety, highest protein content, 12.50% and
gluten, 28.6% was obtained for the variant paraplow.
Abstract: The k-nearest neighbors (knn) is a simple but effective method of classification. In this paper we present an extended version of this technique for chemical compounds used in High Throughput Screening, where the distances of the nearest neighbors can be taken into account. Our algorithm uses kernel weight functions as guidance for the process of defining activity in screening data. Proposed kernel weight function aims to combine properties of graphical structure and molecule descriptors of screening compounds. We apply the modified knn method on several experimental data from biological screens. The experimental results confirm the effectiveness of the proposed method.
Abstract: A new voltage-mode triple-input single-output multifunction filter using only two current conveyors is presented. The proposed filter which possesses three inputs and single-output can generate all biquadratic filtering functions at the output terminal by selecting different input signal combinations. The validity of the proposed filter is verified through PSPICE simulations.
Abstract: Web applications have become complex and crucial for many firms, especially when combined with areas such as CRM (Customer Relationship Management) and BPR (Business Process Reengineering). The scientific community has focused attention to Web application design, development, analysis, testing, by studying and proposing methodologies and tools. Static and dynamic techniques may be used to analyze existing Web applications. The use of traditional static source code analysis may be very difficult, for the presence of dynamically generated code, and for the multi-language nature of the Web. Dynamic analysis may be useful, but it has an intrinsic limitation, the low number of program executions used to extract information. Our reverse engineering analysis, used into our WAAT (Web Applications Analysis and Testing) project, applies mutational techniques in order to exploit server side execution engines to accomplish part of the dynamic analysis. This paper studies the effects of mutation source code analysis applied to Web software to build application models. Mutation-based generated models may contain more information then necessary, so we need a pruning mechanism.
Abstract: This study aims to screen out and to optimize the
major nutrients for maximum carotenoid production and
antioxidation characteristics by Rhodotorula rubra. It was found that
supplementary of 10 g/l glucose as carbon source, 1 g/l ammonium
sulfate as nitrogen source and 1 g/l yeast extract as growth factor in
the medium provided the better yield of carotenoid content of 30.39
μg/g cell dry weight the amount of antioxidation of Rhodotorula
rubra by DPPH, ABTS and MDA method were 1.463%, 34.21% and
34.09 μmol/l, respectively.
Abstract: This study explores how the mechanics of learning
paves the way to engineering innovation. Theories related to learning
in the new product/service innovation are reviewed from an
organizational perspective, behavioral perspective, and engineering
perspective. From this, an engineering team-s external interactions
for knowledge brokering and internal composition for skill balance
are examined from a learning and innovation viewpoints. As a result,
an integrated learning model is developed by reconciling the
theoretical perspectives as well as developing propositions that
emphasize the centrality of learning, and its drivers, in the
engineering product/service development. The paper also provides a
review and partial validation of the propositions using the results of a
previously published field study in the aerospace industry.
Abstract: Nondestructive testing in engineering is an inverse
Cauchy problem for Laplace equation. In this paper the problem
of nondestructive testing is expressed by a Laplace-s equation with
third-kind boundary conditions. In order to find unknown values on
the boundary, the method of fundamental solution is introduced and
realized. Because of the ill-posedness of studied problems, the TSVD
regularization technique in combination with L-curve criteria and
Generalized Cross Validation criteria is employed. Numerical results
are shown that the TSVD method combined with L-curve criteria is
more efficient than the TSVD method combined with GCV criteria.
The abstract goes here.
Abstract: Recently, there have been considerable efforts towards the convergence between P2P and Grid computing in order to reach a solution that takes the best of both worlds by exploiting the advantages that each offers. Augmenting the peer-to-peer model to the services of the Grid promises to eliminate bottlenecks and ensure greater scalability, availability, and fault-tolerance. The Grid Information Service (GIS) directly influences quality of service for grid platforms. Most of the proposed solutions for decentralizing the GIS are based on completely flat overlays. The main contributions for this paper are: the investigation of a novel resource discovery framework for Grid implementations based on a hierarchy of structured peer-to-peer overlay networks, and introducing a discovery algorithm utilizing the proposed framework. Validation of the framework-s performance is done via simulation. Experimental results show that the proposed organization has the advantage of being scalable while providing fault-isolation, effective bandwidth utilization, and hierarchical access control. In addition, it will lead to a reliable, guaranteed sub-linear search which returns results within a bounded interval of time and with a smaller amount of generated traffic within each domain.