Abstract: The design of distributed systems involves the
partitioning of the system into components or partitions and the
allocation of these components to physical nodes. Techniques have
been proposed for both the partitioning and allocation process.
However these techniques suffer from a number of limitations. For
instance object replication has the potential to greatly improve the
performance of an object orientated distributed system but can be
difficult to use effectively and there are few techniques that support
the developer in harnessing object replication.
This paper presents a methodological technique that helps
developers decide how objects should be allocated in order to
improve performance in a distributed system that supports
replication. The performance of the proposed technique is
demonstrated and tested on an example system.
Abstract: In this paper we proposed comparison of four content based objective metrics with results of subjective tests from 80 video sequences. We also include two objective metrics VQM and SSIM to our comparison to serve as “reference” objective metrics because their pros and cons have already been published. Each of the video sequence was preprocessed by the region recognition algorithm and then the particular objective video quality metric were calculated i.e. mutual information, angular distance, moment of angle and normalized cross-correlation measure. The Pearson coefficient was calculated to express metrics relationship to accuracy of the model and the Spearman rank order correlation coefficient to represent the metrics relationship to monotonicity. The results show that model with the mutual information as objective metric provides best result and it is suitable for evaluating quality of video sequences.
Abstract: This paper presents the development of a Bayesian
belief network classifier for prediction of graft status and survival
period in renal transplantation using the patient profile information
prior to the transplantation. The objective was to explore feasibility
of developing a decision making tool for identifying the most suitable
recipient among the candidate pool members. The dataset was
compiled from the University of Toledo Medical Center Hospital
patients as reported to the United Network Organ Sharing, and had
1228 patient records for the period covering 1987 through 2009. The
Bayes net classifiers were developed using the Weka machine
learning software workbench. Two separate classifiers were induced
from the data set, one to predict the status of the graft as either failed
or living, and a second classifier to predict the graft survival period.
The classifier for graft status prediction performed very well with a
prediction accuracy of 97.8% and true positive values of 0.967 and
0.988 for the living and failed classes, respectively. The second
classifier to predict the graft survival period yielded a prediction
accuracy of 68.2% and a true positive rate of 0.85 for the class
representing those instances with kidneys failing during the first year
following transplantation. Simulation results indicated that it is
feasible to develop a successful Bayesian belief network classifier for
prediction of graft status, but not the graft survival period, using the
information in UNOS database.
Abstract: In this paper, an experimentation to enhance the
visibility of hot objects in a thermal image acquired with ordinary
digital camera is reported, after the applications of lowpass and
median filters to suppress the distracting granular noises. The
common thresholding and slicing techniques were used on the
histogram at different gray levels, followed by a subjective
comparative evaluation. The best result came out with the threshold
level 115 and the number of slices 3.
Abstract: In this study, a new criterion for determining the number of classes an image should be segmented is proposed. This criterion is based on discriminant analysis for measuring the separability among the segmented classes of pixels. Based on the new discriminant criterion, two algorithms for recursively segmenting the image into determined number of classes are proposed. The proposed methods can automatically and correctly segment objects with various illuminations into separated images for further processing. Experiments on the extraction of text strings from complex document images demonstrate the effectiveness of the proposed methods.1
Abstract: This paper presents the application of a signal intensity
independent similarity criterion for rigid and non-rigid body
registration of binary objects. The criterion is defined as the
weighted ratio image of two images. The ratio is computed on a
voxel per voxel basis and weighting is performed by setting the raios
between signal and background voxels to a standard high value. The
mean squared value of the weighted ratio is computed over the union
of the signal areas of the two images and it is minimized using the
Chebyshev polynomial approximation.
Abstract: Gas Metal Arc Welding (GMAW) processes is an
important joining process widely used in metal fabrication
industries. This paper addresses modeling and optimization of this
technique using a set of experimental data and regression analysis.
The set of experimental data has been used to assess the influence
of GMAW process parameters in weld bead geometry. The
process variables considered here include voltage (V); wire feed
rate (F); torch Angle (A); welding speed (S) and nozzle-to-plate
distance (D). The process output characteristics include weld bead
height, width and penetration. The Taguchi method and regression
modeling are used in order to establish the relationships between
input and output parameters. The adequacy of the model is
evaluated using analysis of variance (ANOVA) technique. In the
next stage, the proposed model is embedded into a Simulated
Annealing (SA) algorithm to optimize the GMAW process
parameters. The objective is to determine a suitable set of process
parameters that can produce desired bead geometry, considering
the ranges of the process parameters. Computational results prove
the effectiveness of the proposed model and optimization
procedure.
Abstract: The paper evaluates the ongoing reform of VAT in the Czech Republic in terms of impacts on individual households. The main objective is to analyse the impact of given changes on individual households. The adopted method is based on the data related to household consumption by individual household quintiles; obtained data are subjected to micro-simulation examining. Results are discussed in terms of vertical tax justice. Results of the analysis reveal that VAT behaves regressively and a sole consolidation of rates at a higher level only increases the regression of this tax in the Czech Republic.
Abstract: Large metal and concrete structures suffer by various kinds of deterioration, and accurate prediction of the remaining life is important. This paper informs about two methods for its assessment. One method, suitable for steel bridges and other constructions exposed to fatigue, monitors the loads and damage accumulation using information systems for the operation and the finite element model of the construction. In addition to the operation load, the dead weight of the construction and thermal stresses can be included into the model. The second method is suitable for concrete bridges and other structures, which suffer by carbonatation and other degradation processes, driven by diffusion. The diffusion constant, important for the prediction of future development, can be determined from the depth-profile of pH, obtained by pH measurement at various depths. Comparison with measurements on real objects illustrates the suitability of both methods.
Abstract: management of medical devices in hospitals includes
the planning of medical equipment acquisition and maintenance. The
presence of critical and non-critical areas together with technological
proliferation render the management of medical devices very
complex. This study creates an easy and objective methodology for
the analysis of medical equipment maintenance, that makes the
management of medical devices more feasible. The study has been
carried out at Florence Hospital Careggi and it aims to help the
clinical engineering department to manage medical equipment by
clarifying the hospital situation through a characterization of the
different areas, technologies and fault typologies.
Abstract: Modeling of the distributed systems allows us to
represent the whole its functionality. The working system instance
rarely fulfils the whole functionality represented by model; usually
some parts of this functionality should be accessible periodically.
The reporting system based on the Data Warehouse concept seams to
be an intuitive example of the system that some of its functionality is
required only from time to time. Analyzing an enterprise risk
associated with the periodical change of the system functionality, we
should consider not only the inaccessibility of the components
(object) but also their functions (methods), and the impact of such a
situation on the system functionality from the business point of view.
In the paper we suggest that the risk attributes should be estimated
from risk attributes specified at the requirements level (Use Case in
the UML model) on the base of the information about the structure of
the model (presented at other levels of the UML model). We argue
that it is desirable to consider the influence of periodical changes in
requirements on the enterprise risk estimation. Finally, the
proposition of such a solution basing on the UML system model is
presented.
Abstract: Trends in business intelligence, e-commerce and
remote access make it necessary and practical to store data in
different ways on multiple systems with different operating systems.
As business evolve and grow, they require efficient computerized
solution to perform data update and to access data from diverse
enterprise business applications. The objective of this paper is to
demonstrate the capability of DTS [1] as a database solution for
automatic data transfer and update in solving business problem. This
DTS package is developed for the sales of variety of plants and
eventually expanded into commercial supply and landscaping
business. Dimension data modeling is used in DTS package to
extract, transform and load data from heterogeneous database
systems such as MySQL, Microsoft Access and Oracle that
consolidates into a Data Mart residing in SQL Server. Hence, the
data transfer from various databases is scheduled to run automatically
every quarter of the year to review the efficient sales analysis.
Therefore, DTS is absolutely an attractive solution for automatic data
transfer and update which meeting today-s business needs.
Abstract: Fuzzy C-means Clustering algorithm (FCM) is a
method that is frequently used in pattern recognition. It has the
advantage of giving good modeling results in many cases, although,
it is not capable of specifying the number of clusters by itself. In
FCM algorithm most researchers fix weighting exponent (m) to a
conventional value of 2 which might not be the appropriate for all
applications. Consequently, the main objective of this paper is to use
the subtractive clustering algorithm to provide the optimal number of
clusters needed by FCM algorithm by optimizing the parameters of
the subtractive clustering algorithm by an iterative search approach
and then to find an optimal weighting exponent (m) for the FCM
algorithm. In order to get an optimal number of clusters, the iterative
search approach is used to find the optimal single-output Sugenotype
Fuzzy Inference System (FIS) model by optimizing the
parameters of the subtractive clustering algorithm that give minimum
least square error between the actual data and the Sugeno fuzzy
model. Once the number of clusters is optimized, then two
approaches are proposed to optimize the weighting exponent (m) in
the FCM algorithm, namely, the iterative search approach and the
genetic algorithms. The above mentioned approach is tested on the
generated data from the original function and optimal fuzzy models
are obtained with minimum error between the real data and the
obtained fuzzy models.
Abstract: This study aimed at assessing whether and to what extent moral judgment and behaviour were: 1. situation-dependent; 2. selectively dependent on cognitive and affective components; 3. influenced by gender and age; 4. reciprocally congruent. In order to achieve these aims, four different types of moral dilemmas were construed and five types of thinking were presented for each of them – representing five possible ways to evaluate the situation. The judgment criteria included selfishness, altruism, sense of justice, and the conflict between selfishness and the two moral issues. The participants were 250 unpaid volunteers (50% male; 50% female) belonging to two age-groups: young people and adults. The study entailed a 2 (gender) x 2 (age-group) x 5 (type of thinking) x 4 (situation) mixed design: the first two variables were betweensubjects, the others were within-subjects. Results have shown that: 1. moral judgment and behaviour are at least partially affected by the type of situations and by interpersonal variables such as gender and age; 2. moral reasoning depends in a similar manner on cognitive and affective factors; 3. there is not a gender polarity between the ethic of justice and the ethic of cure/ altruism; 4. moral reasoning and behavior are perceived as reciprocally congruent even though their congruence decreases with a more objective assessment. Such results were discussed in the light of contrasting theories on morality.
Abstract: A cart-ball system is a challenging system from the
control engineering point of view. This is due to the nonlinearities,
multivariable, and non-minimum phase behavior present in this
system. This paper is concerned with the problem of modeling and
control of such system. The objective of control strategy is to place
the cart at a desired position while balancing the ball on the top of the
arc-shaped track fixed on the cart. A State-Feedback Controller
(SFC) with a pole-placement method will be designed in order to
control the system. At first, the mathematical model of a cart-ball
system in the state-space form is developed. Then, the linearization of
a model will be established in order to design a SFC. The integral
control strategy will be performed as to control the cart position of a
system. Simulation work is then performed using
MATLAB/SIMULINK software in order to study the performance of
SFC when applied to the system.
Abstract: Article is devoted to the problem of Kazakhstan people national values in the conditions of the Republic of Kazakhstan independence. Formation of ethnos national values is viewed as the mandatory constituent of this process in contemporary conditions. The article shows the dynamics of forming socialspiritual basis of Kazakhstan people-s national values. It depicts peculiarities of interethnic relations in poly-ethnic and multiconfessional Kazakhstan. The study reviews in every detail various directions of the state social policy development in the sphere of national values. It is aimed to consolidation of the society to achieve the shared objective, i.e. building democratic and civilized state. The author discloses peculiarities of ethnos national values development using specific sources. It is underlined that renewal and modernization of Kazakhstan society represents new stage in the national value development, and its typical feature is integration process based on peoples- friendship, cultural principles of interethnic communication.
Abstract: The equilibrium chemical reactions taken place in a converter reactor of the Khorasan Petrochemical Ammonia plant was studied using the minimization of Gibbs free energy method. In the minimization of the Gibbs free energy function the Davidon– Fletcher–Powell (DFP) optimization procedure using the penalty terms in the well-defined objective function was used. It should be noted that in the DFP procedure along with the corresponding penalty terms the Hessian matrices for the composition of constituents in the Converter reactor can be excluded. This, in fact, can be considered as the main advantage of the DFP optimization procedure. Also the effect of temperature and pressure on the equilibrium composition of the constituents was investigated. The results obtained in this work were compared with the data collected from the converter reactor of the Khorasan Petrochemical Ammonia plant. It was concluded that the results obtained from the method used in this work are in good agreement with the industrial data. Notably, the algorithm developed in this work, in spite of its simplicity, takes the advantage of short computation and convergence time.
Abstract: Prediction of fault-prone modules provides one way to
support software quality engineering. Clustering is used to determine
the intrinsic grouping in a set of unlabeled data. Among various
clustering techniques available in literature K-Means clustering
approach is most widely being used. This paper introduces K-Means
based Clustering approach for software finding the fault proneness of
the Object-Oriented systems. The contribution of this paper is that it
has used Metric values of JEdit open source software for generation
of the rules for the categorization of software modules in the
categories of Faulty and non faulty modules and thereafter
empirically validation is performed. The results are measured in
terms of accuracy of prediction, probability of Detection and
Probability of False Alarms.
Abstract: The objective of the research was to evaluate the
quality of milk pomade sweet – sherbet packed in different packaging
materials (Multibarrier 60, met.BOPET/PE, Aluthen), by several
packaging technologies – active and modified atmosphere (MAP)
(consisting of 100% CO2), and control – in air ambiance.
Experiments were carried out at the Faculty of Food Technology of
Latvia University of Agriculture. Samples were stored at the room
temperature +21±1 °C. The physiochemical properties – weight
losses, moisture, hardening, colour and changes in headspace
atmosphere concentration (CO2 and O2) of packs were analysed
before packaging and after 2, 4, 6, 8, 10 and 12 storage weeks.
Abstract: Abrasive waterjet is a novel machining process capable of processing wide range of hard-to-machine materials. This research addresses modeling and optimization of the process parameters for this machining technique. To model the process a set of experimental data has been used to evaluate the effects of various parameter settings in cutting 6063-T6 aluminum alloy. The process variables considered here include nozzle diameter, jet traverse rate, jet pressure and abrasive flow rate. Depth of cut, as one of the most important output characteristics, has been evaluated based on different parameter settings. The Taguchi method and regression modeling are used in order to establish the relationships between input and output parameters. The adequacy of the model is evaluated using analysis of variance (ANOVA) technique. The pairwise effects of process parameters settings on process response outputs are also shown graphically. The proposed model is then embedded into a Simulated Annealing algorithm to optimize the process parameters. The optimization is carried out for any desired values of depth of cut. The objective is to determine proper levels of process parameters in order to obtain a certain level of depth of cut. Computational results demonstrate that the proposed solution procedure is quite effective in solving such multi-variable problems.