Abstract: In this work a new offline signature recognition system
based on Radon Transform, Fractal Dimension (FD) and Support Vector Machine (SVM) is presented. In the first step, projections of
original signatures along four specified directions have been performed using radon transform. Then, FDs of four obtained
vectors are calculated to construct a feature vector for each
signature. These vectors are then fed into SVM classifier for recognition of signatures. In order to evaluate the effectiveness of
the system several experiments are carried out. Offline signature
database from signature verification competition (SVC) 2004 is used
during all of the tests. Experimental result indicates that the proposed method achieved high accuracy rate in signature recognition.
Abstract: In this paper, a new learning approach for network
intrusion detection using naïve Bayesian classifier and ID3 algorithm
is presented, which identifies effective attributes from the training
dataset, calculates the conditional probabilities for the best attribute
values, and then correctly classifies all the examples of training and
testing dataset. Most of the current intrusion detection datasets are
dynamic, complex and contain large number of attributes. Some of
the attributes may be redundant or contribute little for detection
making. It has been successfully tested that significant attribute
selection is important to design a real world intrusion detection
systems (IDS). The purpose of this study is to identify effective
attributes from the training dataset to build a classifier for network
intrusion detection using data mining algorithms. The experimental
results on KDD99 benchmark intrusion detection dataset demonstrate
that this new approach achieves high classification rates and reduce
false positives using limited computational resources.
Abstract: Most simple nonlinear thresholding rules for
wavelet- based denoising assume that the wavelet coefficients are independent. However, wavelet coefficients of natural images have significant dependencies. This paper attempts to give a recipe for selecting one of the popular image-denoising algorithms based
on VisuShrink, SureShrink, OracleShrink, BayesShrink and BiShrink and also this paper compares different Bivariate models used for image denoising applications. The first part of the paper
compares different Shrinkage functions used for image-denoising.
The second part of the paper compares different bivariate models
and the third part of this paper uses the Bivariate model with modified marginal variance which is based on Laplacian assumption. This paper gives an experimental comparison on six 512x512 commonly used images, Lenna, Barbara, Goldhill,
Clown, Boat and Stonehenge. The following noise powers 25dB,26dB, 27dB, 28dB and 29dB are added to the six standard images and the corresponding Peak Signal to Noise Ratio (PSNR) values
are calculated for each noise level.
Abstract: Perennial ryegrass (Lolium perenne L.) plants are cultivated for lawn constitution and as forage plants. Considerable number of perennial ryegrass genotypes are present in the flora of our country and they present substantial was performed based on a Project supported bu TUBITAK (Project numver : 106O159) and perannial ryegrass genotypes from 8 provinces were collected during 2006. Seeds of perennial ryegrass were collected from 48 different locations. Populations of turfgrass seeds in flowerpots to be 20 and 1 cm deep greenhouse were sown in three replications at 07.07.2007.Then the growth of turfgrass seedlings in the greenhouse in pots showed sufficiently separated from the plants were planted in each population. Plants planted in the garden of the observation scale of 1-9 was evaluated by the quality, 1 = the weakest / worst, 6 = acceptable and 9 = superior or considered as an ideal. Essentially only recognized in assessing the quality of the color of grass, but the color, density, uniformity, texture (texture), illness or environmental stresses are evaluated as a combination reaction. Turfgrass quality 15.11.2007, 19.03.2008, 27.05.2008, 27.11.2008, 07.03.2009 and 02.06.2009 have been 6 times to be in order. Observations made regarding the quality of grass; 3 years according to seasonal environments turf quality genotypes belonging to 14 different populations were found to be 7.5 and above are reserved for future use in breeding works.The number of genotypes belonging to 41 populations in terms of turfgrass quality was determined as 7.9 of 3 year average seasonal. Argıthan between Doğanhisar (Konya) is located 38.09 latitude and 31.40 longitude, altitude 1158 m in the set that population numbered 41.
Abstract: The goal of this study was to disclose the core of the advertising research based on the psychological aspects by acquainting with the nature of advertising research and revealing the importance of psychological aspects of advertising during the advertising research. The growing interest in consumer response to advertisement served as an encouragement to make the analysis of psychological aspects of the advertising research, because the information obtained during the advertising research helps to answer the question how advertising really works. In the research analysis focuses on the nature of advertising research. The place of advertising research in advertisement planning process and the advertising research process are unfolded. Moreover, the importance of psychological aspects in the advertising research is being examined. The certain psychological aspects like the particularities of advertising communication process, psychological process that are active at advertising acceptance and awareness process as well as the advertising effects are analysed in more detail.
Abstract: Segmentation is an important step in medical image
analysis and classification for radiological evaluation or computer
aided diagnosis. This paper presents the problem of inaccurate lung
segmentation as observed in algorithms presented by researchers
working in the area of medical image analysis. The different lung
segmentation techniques have been tested using the dataset of 19
patients consisting of a total of 917 images. We obtained datasets of
11 patients from Ackron University, USA and of 8 patients from
AGA Khan Medical University, Pakistan. After testing the algorithms
against datasets, the deficiencies of each algorithm have been
highlighted.
Abstract: Oxidative stress makes up common incidents in
eukaryotic metabolism. The presence of diverse components
disturbing the equilibrium during oxygen metabolism increases
oxidative damage unspecifically in living cells. Body´s own
ubiquinone (Q10) seems to be a promising drug in defending the
heightened appearance of reactive oxygen species (ROS). Though, its
lipophilic properties require a new strategy in drug formulation to
overcome their low bioavailability. Consequently, the manufacture of
heterogeneous nanodispersions is in focus for medical applications.
The composition of conventional nanodispersions is made up of a
drug-consisting core and a surfactive agent, also named as surfactant.
Long-termed encapsulation of the surfactive components into tissues
might be the consequence of the use during medical therapeutics. The
potential of provoking side-effects is given by their nonbiodegradable
properties. Further improvements during fabrication
process use the incorporation of biodegradable components such as
modified γ-polyglutamic acid which decreases the potential of
prospective side-effects.
Abstract: This paper examines the influence of communication
form on employee uncertainty during mergers and acquisitions
(M&As). Specifically, the author uses narrative theory to analyze
how narrative organizational communication affects the three
components of uncertainty – decreased predictive, explanatory, and
descriptive ability. It is hypothesized that employees whose
organizations use narrative M&A communication will have greater
predictive, explanatory, and descriptive abilities than employees of
organizations using non-narrative M&A communication. This paper
contributes to the stream of research examining uncertainty during
mergers and acquisitions and argues that narratives are an effective
means of managing uncertainty in the mergers and acquisitions
context.
Abstract: This paper presents the results of the authors in designing, experimenting, assessing and transferring an innovative approach to energy education in secondary schools, aimed to enhance the quality of learning in terms of didactic curricula and pedagogic methods. The training is online delivered to youngsters via e-Books and portals specially designed for this purpose or by learning by doing via interactive games. An online educational methodology is available teachers.
Abstract: Vermiculite was used to develop inorganic
carrier-based formulations of fluorescent pseudomonad strains
R62 and R81. The effect of bio-inoculation of fluorescent
pseudomonad strains R62 and R81 (plant growth promoting
and biocontrol agent) on growth responses of Vigna-mungo
under field condition was enumerated. The combined bioinoculation
of these two organisms in a formuation increased
the pods yield by 300% in comparison to the control crop.
There was also significant increment in the other plant growth
responses such as dry root weight, dry shoot weight, shoot
length and number of branches per plant.
Abstract: Supply Chain Management (SCM) is the integration
between manufacturer, transporter and customer in order to form one
seamless chain that allows smooth flow of raw materials, information
and products throughout the entire network that help in minimizing
all related efforts and costs. The main objective of this paper is to
develop a model that can accept a specified number of spare-parts
within the supply chain, simulating its inventory operations
throughout all stages in order to minimize the inventory holding
costs, base-stock, safety-stock, and to find the optimum quantity of
inventory levels, thereby suggesting a way forward to adapt some
factors of Just-In-Time to minimizing the inventory costs throughout
the entire supply chain. The model has been developed using Micro-
Soft Excel & Visual Basic in order to study inventory allocations in
any network of the supply chain. The application and reproducibility
of this model were tested by comparing the actual system that was
implemented in the case study with the results of the developed
model. The findings showed that the total inventory costs of the
developed model are about 50% less than the actual costs of the
inventory items within the case study.
Abstract: This paper provides an introduction into the evolution
of information and communication technology and illustrates its
usage in the work domain. The paper is sub-divided into two parts.
The first part gives an overview over the different phases of
information processing in the work domain. It starts by charting the
past and present usage of computers in work environments and shows
current technological trends, which are likely to influence future
business applications. The second part starts by briefly describing,
how the usage of computers changed business processes in the past,
and presents first Ambient Intelligence applications based on
identification and localization information, which are already used in
the production and retail sector. Based on current systems and
prototype applications, the paper gives an outlook of how Ambient
Intelligence technologies could change business processes in the
future.
Abstract: Using spatial models as a shared common basis of
information about the environment for different kinds of contextaware
systems has been a heavily researched topic in the last years.
Thereby the research focused on how to create, to update, and to
merge spatial models so as to enable highly dynamic, consistent and
coherent spatial models at large scale. In this paper however, we
want to concentrate on how context-aware applications could use this
information so as to adapt their behavior according to the situation
they are in. The main idea is to provide the spatial model
infrastructure with a situation recognition component based on
generic situation templates. A situation template is – as part of a
much larger situation template library – an abstract, machinereadable
description of a certain basic situation type, which could be
used by different applications to evaluate their situation. In this
paper, different theoretical and practical issues – technical, ethical
and philosophical ones – are discussed important for understanding
and developing situation dependent systems based on situation
templates. A basic system design is presented which allows for the
reasoning with uncertain data using an improved version of a
learning algorithm for the automatic adaption of situation templates.
Finally, for supporting the development of adaptive applications, we
present a new situation-aware adaptation concept based on
workflows.
Abstract: This paper presents an approach based on the
adoption of a distributed cognition framework and a non parametric
multicriteria evaluation methodology (DEA) designed specifically to
compare e-commerce websites from the consumer/user viewpoint. In
particular, the framework considers a website relative efficiency as a
measure of its quality and usability. A website is modelled as a black
box capable to provide the consumer/user with a set of
functionalities. When the consumer/user interacts with the website to
perform a task, he/she is involved in a cognitive activity, sustaining a
cognitive cost to search, interpret and process information, and
experiencing a sense of satisfaction. The degree of ambiguity and
uncertainty he/she perceives and the needed search time determine
the effort size – and, henceforth, the cognitive cost amount – he/she
has to sustain to perform his/her task. On the contrary, task
performing and result achievement induce a sense of gratification,
satisfaction and usefulness. In total, 9 variables are measured,
classified in a set of 3 website macro-dimensions (user experience,
site navigability and structure). The framework is implemented to
compare 40 websites of businesses performing electronic commerce
in the information technology market. A questionnaire to collect
subjective judgements for the websites in the sample was purposely
designed and administered to 85 university students enrolled in
computer science and information systems engineering
undergraduate courses.
Abstract: Lactic acid alone and its combined application with
nisin were evaluated for reducing population of naturally occurring
microorganisms on chilled shrimp. Fresh shrimps were dipped in 0,
1.0% and 2.0% (v/v) lactic acid alone and their combined application
with 0.04 (g/L/kg) nisin solution for 10 min. Total plate counts of
aerobic bacteria (TPCs), Psychrotrophic counts, population of
Pseudomonas spp., H2S producing bacteria and Lactic acid bacteria
(LAB) on shrimps were determined during storage at 4 °C. The
results indicated that total plate counts were 2.91 and 2.63 log CFU/g
higher on untreated shrimps after 7 and 14 days of storage,
respectively, than on shrimps treated with 2.0% lactic acid combined
with 0.04 (g/L/kg) nisin. Both concentrations of lactic acid indicated
significant reduction on Pseudomonas counts during storage, while
2.0% lactic acid combined with nisin indicated the highest reduction.
In addition, H2S producing bacteria were more sensitive to high
concentration of lactic acid combined with nisin during storage.
Abstract: In this paper we present a combined
hashing/watermarking method for image authentication. A robust
image hash, invariant to legitimate modifications, but fragile to
illegitimate modifications is generated from the local image
characteristics. To increase security of the system the watermark is
generated using the image hash as a key. Quantized Index
Modulation of DCT coefficients is used for watermark embedding.
Watermark detection is performed without use of the original image.
Experimental results demonstrate the effectiveness of the presented
method in terms of robustness and fragility.
Abstract: The identification and elimination of bad
measurements is one of the basic functions of a robust state estimator
as bad data have the effect of corrupting the results of state
estimation according to the popular weighted least squares method.
However this is a difficult problem to handle especially when dealing
with multiple errors from the interactive conforming type. In this
paper, a self adaptive genetic based algorithm is proposed. The
algorithm utilizes the results of the classical linearized normal
residuals approach to tune the genetic operators thus instead of
making a randomized search throughout the whole search space it is
more likely to be a directed search thus the optimum solution is
obtained at very early stages(maximum of 5 generations). The
algorithm utilizes the accumulating databases of already computed
cases to reduce the computational burden to minimum. Tests are
conducted with reference to the standard IEEE test systems. Test
results are very promising.
Abstract: Protection and proper management of archaeological heritage are an essential process of studying and interpreting the generations present and future. Protecting the archaeological heritage is based upon multidiscipline professional collaboration. This study aims to gather data by different sources (Photogrammetry and Geographic Information System (GIS)) integrated for the purpose of documenting one the of significant archeological sites (Ahl-Alkahf, Jordan). 3D modeling deals with the actual image of the features, shapes and texture to represent reality as realistically as possible by using texture. The 3D coordinates that result of the photogrammetric adjustment procedures are used to create 3D-models of the study area. Adding Textures to the 3D-models surfaces gives a 'real world' appearance to the displayed models. GIS system combined all data, including boundary maps, indicating the location of archeological sites, transportation layer, digital elevation model and orthoimages. For realistic representation of the study area, 3D - GIS model prepared, where efficient generation, management and visualization of such special data can be achieved.
Abstract: We consider linear regression models where both input data (the values of independent variables) and output data (the observations of the dependent variable) are interval-censored. We introduce a possibilistic generalization of the least squares estimator, so called OLS-set for the interval model. This set captures the impact of the loss of information on the OLS estimator caused by interval censoring and provides a tool for quantification of this effect. We study complexity-theoretic properties of the OLS-set. We also deal with restricted versions of the general interval linear regression model, in particular the crisp input – interval output model. We give an argument that natural descriptions of the OLS-set in the crisp input – interval output cannot be computed in polynomial time. Then we derive easily computable approximations for the OLS-set which can be used instead of the exact description. We illustrate the approach by an example.
Abstract: Policies that support entrepreneurship are keys to the
generation of new business. In Brazil, seed capital, installation of
technology parks, programs and zero interest financing, economic
subsidy as Program First Innovative Company (PRIME) are
examples of incentive policies. For the implementation of PRIME, in
particular the Brazilian Innovation Agency (FINEP) decentralized
operationalization so that business incubators could select innovative
projects. This paper analyzes the program PRIME Business Incubator
Center of the State of Sergipe (CISE) after calculating the mean and
standard deviation of the grades obtained by companies in the factors
of innovation, market potential, financial return economic, market
strategy and staff and application of the Mann-Whitney test.