Abstract: In this paper we present a new method for over-height
vehicle detection in low headroom streets and highways using digital
video possessing. The accuracy and the lower price comparing to
present detectors like laser radars and the capability of providing
extra information like speed and height measurement make this
method more reliable and efficient. In this algorithm the features are
selected and tracked using KLT algorithm. A blob extraction
algorithm is also applied using background estimation and
subtraction. Then the world coordinates of features that are inside the
blobs are estimated using a noble calibration method. As, the heights
of the features are calculated, we apply a threshold to select overheight
features and eliminate others. The over-height features are
segmented using some association criteria and grouped using an
undirected graph. Then they are tracked through sequential frames.
The obtained groups refer to over-height vehicles in a scene.
Abstract: A dynamic risk management framework for software
projects is presented. Currently available software risk management
frameworks and risk assessment models are static in nature and lacks
feedback capability. Such risk management frameworks are not
capable of providing the risk assessment of futuristic changes in risk
events. A dynamic risk management framework for software project
is needed that provides futuristic assessment of risk events.
Abstract: Many high-risk pathogens that cause disease in
humans are transmitted through various food items. Food-borne
disease constitutes a major public health problem. Assessment of the
quality and safety of foods is important in human health. Rapid and
easy detection of pathogenic organisms will facilitate precautionary
measures to maintain healthy food. The Polymerase Chain Reaction
(PCR) is a handy tool for rapid detection of low numbers of bacteria.
We have designed gene specific primers for most common food
borne pathogens such as Staphylococci, Salmonella and E.coli.
Bacteria were isolated from food samples of various food outlets and
identified using gene specific PCRs. We identified Staphylococci,
Salmonella and E.coli O157 using gene specific primers by rapid and
direct PCR technique in various food samples. This study helps us in
getting a complete picture of the various pathogens that threaten to
cause and spread food borne diseases and it would also enable
establishment of a routine procedure and methodology for rapid
identification of food borne bacteria using the rapid technique of
direct PCR. This study will also enable us to judge the efficiency of
present food safety steps taken by food manufacturers and exporters.
Abstract: The aim of this article is to assess the existing
business models used by the banks operating in the CEE countries in
the time period from 2006 till 2011.
In order to obtain research results, the authors performed
qualitative analysis of the scientific literature on bank business
models, which have been grouped into clusters that consist of such
components as: 1) capital and reserves; 2) assets; 3) deposits, and 4)
loans.
In their turn, bank business models have been developed based on
the types of core activities of the banks, and have been divided into
four groups: Wholesale, Investment, Retail and Universal Banks.
Descriptive statistics have been used to analyse the models,
determining mean, minimal and maximal values of constituent
cluster components, as well as standard deviation. The analysis of
the data is based on such bank variable indices as Return on Assets
(ROA) and Return on Equity (ROE).
Abstract: 2007 is a jubilee year: in 1967, programming language SIMULA 67 was presented, which contained all aspects of what was later called object-oriented programming. The present paper contains a description of the development unto the objectoriented programming, the role of simulation in this development and other tools that appeared in SIMULA 67 and that are nowadays called super-object-oriented programming.
Abstract: If organizations like Mellat Bank want to identify its
customer market completely to reach its specified goals, it can
segment the market to offer the product package to the right segment.
Our objective is to offer a segmentation model for Iran banking
market in Mellat bank view. The methodology of this project is
combined by “segmentation on the basis of four part-quality
variables" and “segmentation on the basis of different in means".
Required data are gathered from E-Systems and researcher personal
observation. Finally, the research offers the organization that at first
step form a four dimensional matrix with 756 segments using four
variables named value-based, behavioral, activity style, and activity
level, and at the second step calculate the means of profit for every
cell of matrix in two distinguished work level (levels α1:normal
condition and α2: high pressure condition) and compare the segments
by checking two conditions that are 1- homogeneity every segment
with its sub segment and 2- heterogeneity with other segments, and
so it can do the necessary segmentation process. After all, the last
offer (more explained by an operational example and feedback
algorithm) is to test and update the model because of dynamic
environment, technology, and banking system.
Abstract: Since 2008 a new economic crisis is present is the
entire planet. This crisis affects several domains of the economic but
also of the social life. Consumption decreases due to the lack of
necessary resources of households to increase their expenditures. The
car manufacturing is one of the main industrial activities in European
Union (EU) and the present crisis particularly affects it. The present
study examines the correlations between several socio-economic
indicators and car market in European Union. The target is to find out
the impact of the present economic crisis on the car market in EU.
Abstract: This paper seeks to develop simple yet practical and
efficient control scheme that enables cooperating arms to handle a
flexible beam. Specifically the problem studied herein is that of two
arms rigidly grasping a flexible beam and such capable of generating
forces/moments in such away as to move a flexible beam along a
predefined trajectory. The paper develops a sliding mode control law
that provides robustness against model imperfection and uncertainty.
It also provides an implicit stability proof. Simulation results for two
three joint arms moving a flexible beam, are presented to validate the
theoretical results.
Abstract: In this study we survey the method for fast finding a minimum link path between two arbitrary points within a simple polygon, which can pass only through the vertices, with preprocessing.
Abstract: The study of piezoelectric material in the past was in T-Domain form; however, no one has studied piezoelectric material in the S-Domain form. This paper will present the piezoelectric material in the transfer function or S-Domain model. S-Domain is a well known mathematical model, used for analyzing the stability of the material and determining the stability limits. By using S-Domain in testing stability of piezoelectric material, it will provide a new tool for the scientific world to study this material in various forms.
Abstract: Human-related information security breaches within organizations are primarily caused by employees who have not been made aware of the importance of protecting the information they work with. Information security awareness is accordingly attracting more attention from industry, because stakeholders are held accountable for the information with which they work. The authors developed an Information Security Retrieval and Awareness model – entitled “ISRA" – that is tailored specifically towards enhancing information security awareness in industry amongst all users of information, to address shortcomings in existing information security awareness models. This paper is principally aimed at expounding a prototype for the ISRA model to highlight the advantages of utilizing the model. The prototype will focus on the non-technical, humanrelated information security issues in industry. The prototype will ensure that all stakeholders in an organization are part of an information security awareness process, and that these stakeholders are able to retrieve specific information related to information security issues relevant to their job category, preventing them from being overburdened with redundant information.
Abstract: The concentrations of aliphatic and polycyclic aromatic hydrocarbons (PAH) were determined in atmospheric aerosol samples collected at a rural site in Hungary (K-puszta, summer 2008), a boreal forest (Hyytiälä,
April 2007) and a polluted rural area in Italy (San Pietro Capofiume, Po Valley, April 2008). A clear distinction between “clean" and “polluted" periods was observed. Concentrations obtained for Hyytiälä are significantly lower than those for the other two sites. Source reconciliation was performed using diagnostic parameters, such as the carbon preference index and ratios between PAH. The presence of an unresolved complex mixture of hydrocarbons, especially for the Finnish and Italian samples, is indicative of petrogenic inputs. In K-puszta, the aliphatic hydrocarbons are dominated by leaf wax n-alkanes. The long range transport of anthropogenic pollution contributed to the Finnish aerosol. Industrial activities and vehicular emissions represent major sources in San Pietro Capofiume. PAH in K-puszta consist of both pyrogenic and petrogenic compounds.
Abstract: This paper presents a low cost automatic system for
sampling the electric field in a limited area. The scanning area is a
flat surface parallel to the ground at a selected height. We discuss
in detail the hardware, software and all the arrangements involved
in the system operation. In order to show the system performance
we include a campaign of narrow band measurements with 6017
sample points in the surroundings of a cellular base station. A
commercial isotropic antenna with three orthogonal axes was used
as sampling device. The results are analyzed in terms of its space
average, standard deviation and statistical distribution.
Abstract: With major technological advances and to reduce the
cost of training apprentices for real-time critical systems, it was
necessary the development of Intelligent Tutoring Systems for
training apprentices in these systems. These systems, in general, have
interactive features so that the learning is actually more efficient,
making the learner more familiar with the mechanism in question. In
the home stage of learning, tests are performed to obtain the student's
income, a measure on their use. The aim of this paper is to present a
framework to model an Intelligent Tutoring Systems using the UML
language. The various steps of the analysis are considered the
diagrams required to build a general model, whose purpose is to
present the different perspectives of its development.
Abstract: A study was undertaken to assess the potential of an
Algal Turf Scrubber to remove nitrogen from aquaculture effluent to
reduce environmental pollution. High total ammonia nitrogen
concentrations were introduced to an Algal Turf Scrubber developed
under varying hydraulic surface loading rates of African catfish
(Clarius gariepinus) effluent in a recirculating aquaculture system.
Nutrient removal rates were not affected at total suspended solids
concentration of up to 0.04g TSS/l (P > 0.05). Nitrogen removal
rates 0.93-0.99g TAN/m²/d were recorded at very high loading rates
3.76-3.81 g TAN/m²/d. Total ammonia removal showed ½ order
kinetics between 1.6 to 2.3mg/l Total Ammonia Nitrogen
concentrations. Nitrogen removal increased with its loading, which
increased with hydraulic surface loading rate. Total Ammonia
Nitrogen removal by Algal turf scrubber was higher than reported
values for fluidized bed filters and trickling filters. The algal turf
scrubber also effectively removed nitrate thereby reducing the need
for water exchange.
Abstract: This paper illustrates the use of a combined neural
network model for classification of electrocardiogram (ECG) beats.
We present a trainable neural network ensemble approach to develop
customized electrocardiogram beat classifier in an effort to further
improve the performance of ECG processing and to offer
individualized health care.
We process a three stage technique for detection of premature
ventricular contraction (PVC) from normal beats and other heart
diseases. This method includes a denoising, a feature extraction and a
classification. At first we investigate the application of stationary
wavelet transform (SWT) for noise reduction of the
electrocardiogram (ECG) signals. Then feature extraction module
extracts 10 ECG morphological features and one timing interval
feature. Then a number of multilayer perceptrons (MLPs) neural
networks with different topologies are designed.
The performance of the different combination methods as well as
the efficiency of the whole system is presented. Among them,
Stacked Generalization as a proposed trainable combined neural
network model possesses the highest recognition rate of around 95%.
Therefore, this network proves to be a suitable candidate in ECG
signal diagnosis systems. ECG samples attributing to the different
ECG beat types were extracted from the MIT-BIH arrhythmia
database for the study.
Abstract: Clustering is a very well known technique in data mining. One of the most widely used clustering techniques is the kmeans algorithm. Solutions obtained from this technique depend on the initialization of cluster centers and the final solution converges to local minima. In order to overcome K-means algorithm shortcomings, this paper proposes a hybrid evolutionary algorithm based on the combination of PSO, SA and K-means algorithms, called PSO-SA-K, which can find better cluster partition. The performance is evaluated through several benchmark data sets. The simulation results show that the proposed algorithm outperforms previous approaches, such as PSO, SA and K-means for partitional clustering problem.
Abstract: The design requirements for successful human
accommodation in urban spaces are well known; and the range of
facilities available for meeting urban water quality and quantity
requirements is also well established. Their competing requirements
must be reconciled in order for urban spaces to be successful for
both. This paper outlines the separate human and water imperatives
and their interactions in urban spaces. Stormwater management
facilities- relative potential contributions to urban spaces are
contrasted, and design choices for achieving those potentials are
described. This study uses human success of urban space as the
evaluative criterion of stormwater amenity: human values call on
stormwater facilities to contribute to successful human spaces.
Placing water-s contribution under the overall idea of successful
urban space is an evolution from previous subjective evaluations.
The information is based on photographs and notes from
approximately 1,000 stormwater facilities and urban sites collected
during the last 35 years in North America and overseas, and the
author-s experience on multi-disciplinary design teams. This
conceptual study combines the disciplinary roles of engineering,
landscape architecture, and sociology in effecting successful urban
design.
Abstract: A multi-board run-time reconfigurable (MRTR)
system for evolvable hardware (EHW) is introduced with the aim to
implement on hardware the bidirectional incremental evolution (BIE)
method. The main features of this digital intrinsic EHW solution rely
on the multi-board approach, the variable chromosome length
management and the partial configuration of the reconfigurable
circuit. These three features provide a high scalability to the solution.
The design has been written in VHDL with the concern of not being
platform dependant in order to keep a flexibility factor as high as
possible. This solution helps tackling the problem of evolving
complex task on digital configurable support.
Abstract: Determination of nano particle size is substantial since
the nano particle size exerts a significant effect on various properties
of nano materials. Accordingly, proposing non-destructive, accurate
and rapid techniques for this aim is of high interest. There are some
conventional techniques to investigate the morphology and grain size
of nano particles such as scanning electron microscopy (SEM),
atomic force microscopy (AFM) and X-ray diffractometry (XRD).
Vibrational spectroscopy is utilized to characterize different
compounds and applied for evaluation of the average particle size
based on relationship between particle size and near infrared spectra
[1,4] , but it has never been applied in quantitative morphological
analysis of nano materials. So far, the potential application of nearinfrared
(NIR) spectroscopy with its ability in rapid analysis of
powdered materials with minimal sample preparation, has been
suggested for particle size determination of powdered
pharmaceuticals. The relationship between particle size and diffuse
reflectance (DR) spectra in near infrared region has been applied to
introduce a method for estimation of particle size. Back propagation
artificial neural network (BP-ANN) as a nonlinear model was applied
to estimate average particle size based on near infrared diffuse
reflectance spectra. Thirty five different nano TiO2 samples with
different particle size were analyzed by DR-FTNIR spectrometry and
the obtained data were processed by BP- ANN.