Abstract: Computer worm detection is commonly performed by
antivirus software tools that rely on prior explicit knowledge of the
worm-s code (detection based on code signatures). We present an
approach for detection of the presence of computer worms based on
Artificial Neural Networks (ANN) using the computer's behavioral
measures. Identification of significant features, which describe the
activity of a worm within a host, is commonly acquired from security
experts. We suggest acquiring these features by applying feature
selection methods. We compare three different feature selection
techniques for the dimensionality reduction and identification of the
most prominent features to capture efficiently the computer behavior
in the context of worm activity. Additionally, we explore three
different temporal representation techniques for the most prominent
features. In order to evaluate the different techniques, several
computers were infected with five different worms and 323 different
features of the infected computers were measured. We evaluated
each technique by preprocessing the dataset according to each one
and training the ANN model with the preprocessed data. We then
evaluated the ability of the model to detect the presence of a new
computer worm, in particular, during heavy user activity on the
infected computers.
Abstract: Two-dimensional finite element model was created in this work to investigate the stresses distribution within rock-like samples with offset open non-persistent joints under biaxial loading. The results of this study have explained the fracture mechanisms observed in tests on rock-like material with open non-persistent offset joints [1]. Finite element code SAP2000 was used to study the stresses distribution within the specimens. Four-nodded isoperimetric plain strain element with two degree of freedom per node, and the three-nodded constant strain triangular element with two degree of freedom per node were used in the present study.The results of the present study explained the formation of wing cracks at the tip of the joints for low confining stress as well as the formation of wing cracks at the middle of the joint for the higher confining stress. High shear stresses found in the numerical study at the tip of the joints explained the formation of secondary cracks at the tip of the joints in the experimental study. The study results coincide with the experimental observations which showed that for bridge inclination of 0o, the coalescence occurred due to shear failure and for bridge inclination of 90o the coalescence occurred due to tensile failure while for the other bridge inclinations coalescence occurred due to mixed tensile and shear failure.
Abstract: Many organisations are nowadays interested to adopt
lean manufacturing strategy that would enable them to compete in
this competitive globalisation market. In this respect, it is necessary
to assess the implementation of lean manufacturing in different
organisations so that the important best practices can be identified.
This paper describes the development of key areas which will be
used to assess the adoption and implementation of lean
manufacturing practices. There are some key areas developed to
evaluate and reduce the most optimal projects so as to enhance their
production efficiency and increase the purpose of the economic
benefits of the manufacturing unit.
Lean manufacturing is becoming lean enterprise by treating its
customers and suppliers as partners. This gives the extra edge in
today-s cost and time competitive markets. The organisation is
becoming strong in all the conventional competition points. They are
Price, Quality and Delivery. Lean enterprise owners can deliver high
quality products quickly, with low price.
Abstract: In this study, a low temperature sensor highly selective to CO in presence of methane is fabricated by using 4 nm SnO2 quantum dots (QDs) prepared by sonication assisted precipitation. SnCl4 aqueous solution was precipitated by ammonia under sonication, which continued for 2 h. A part of the sample was then dried and calcined at 400°C for 1.5 h and characterized by XRD and BET. The average particle size and the specific surface area of the SnO2 QDs as well as their sensing properties were compared with the SnO2 nano-particles which were prepared by conventional sol-gel method. The BET surface area of sonochemically as-prepared product and the one calcined at 400°C after 1.5 hr are 257 m2/gr and 212 m2/gr respectively while the specific surface area for SnO2 nanoparticles prepared by conventional sol-gel method is about 80m2/gr. XRD spectra revealed pure crystalline phase of SnO2 is formed for both as-prepared and calcined samples of SnO2 QDs. However, for the sample prepared by sol-gel method and calcined at 400°C SnO crystals are detected along with those of SnO2. Quantum dots of SnO2 show exceedingly high sensitivity to CO with different concentrations of 100, 300 and 1000 ppm in whole range of temperature (25- 350°C). At 50°C a sensitivity of 27 was obtained for 1000 ppm CO, which increases to a maximum of 147 when the temperature rises to 225°C and then drops off while the maximum sensitivity for the SnO2 sample prepared by the sol-gel method was obtained at 300°C with the amount of 47.2. At the same time no sensitivity to methane is observed in whole range of temperatures for SnO2 QDs. The response and recovery times of the sensor sharply decreases with temperature, while the high selectivity to CO does not deteriorate.
Abstract: In this paper we used data mining techniques to
identify outlier patients who are using large amount of drugs over a
long period of time. Any healthcare or health insurance system
should deal with the quantities of drugs utilized by chronic diseases
patients. In Kingdom of Bahrain, about 20% of health budget is spent
on medications. For the managers of healthcare systems, there is no
enough information about the ways of drug utilization by chronic
diseases patients, is there any misuse or is there outliers patients. In
this work, which has been done in cooperation with information
department in the Bahrain Defence Force hospital; we select the data
for Cardiac patients in the period starting from 1/1/2008 to
December 31/12/2008 to be the data for the model in this paper. We
used three techniques for finding the drug utilization for cardiac
patients. First we applied a clustering technique, followed by
measuring of clustering validity, and finally we applied a decision
tree as classification algorithm. The clustering results is divided into
three clusters according to the drug utilization, for 1603 patients, who
received 15,806 prescriptions during this period can be partitioned
into three groups, where 23 patients (2.59%) who received 1316
prescriptions (8.32%) are classified to be outliers. The classification
algorithm shows that the use of average drug utilization and the age,
and the gender of the patient can be considered to be the main
predictive factors in the induced model.
Abstract: This paper proposes a method for speckle reduction in
medical ultrasound imaging while preserving the edges with the
added advantages of adaptive noise filtering and speed. A nonlinear
image diffusion method that incorporates local image parameter,
namely, scatterer density in addition to gradient, to weight the
nonlinear diffusion process, is proposed. The method was tested for
the isotropic case with a contrast detail phantom and varieties of
clinical ultrasound images, and then compared to linear and some
other diffusion enhancement methods. Different diffusion parameters
were tested and tuned to best reduce speckle noise and preserve
edges. The method showed superior performance measured both
quantitatively and qualitatively when incorporating scatterer density
into the diffusivity function. The proposed filter can be used as a
preprocessing step for ultrasound image enhancement before
applying automatic segmentation, automatic volumetric calculations,
or 3D ultrasound volume rendering.
Abstract: The incidence of oral cancer in Taiwan increased year
by year. It replaced the nasopharyngeal as the top incurrence among
head and neck cancers since 1994. Early examination and earlier
identification for earlier treatment is the most effective medical
treatment for these cancers. Although the government fully subsidized
the expenses with tremendous promotion program for oral cancer
screening, the citizen-s participation remained low. Purpose of this
study is to understand the factors affecting the citizens- behavior
intensions of taking an oral cancer screening. Based on the Theory of
Planned Behavior, this study adopted four distinctive variables in
explaining the captioned behavior intentions.700 questionnaires were
dispatched with 500 valid responses or 71.4% returned by the citizens
with an age 30 or above from the eastern counties of Taiwan. Test
results has shown that attitude toward, subjective norms of, and
perceived behavioral control over the oral cancer screening varied
from some demographic factors to another. The study proofed that
attitude toward, subjective norms of, and perceived behavioral control
over the oral cancer screening had positive impacts on the
corresponding behavior intention. The test concluded that the theory
of planned behavior was appropriate as a theoretical framework in
explaining the influencing factors of intentions of taking oral cancer
screening. This study suggested the healthcare professional should
provide high accessibility of screening services other than just
delivering knowledge on oral cancer to promote the citizens-
intentions of taking the captioned screening. This research also
provided a practical implication to the healthcare professionals when
formulating and implementing promotion instruments for lifting the
screening rate of oral cancer.
Abstract: Information Retrieval has the objective of studying
models and the realization of systems allowing a user to find the
relevant documents adapted to his need of information. The
information search is a problem which remains difficult because the
difficulty in the representing and to treat the natural languages such
as polysemia. Intentional Structures promise to be a new paradigm to
extend the existing documents structures and to enhance the different
phases of documents process such as creation, editing, search and
retrieval. The intention recognition of the author-s of texts can reduce
the largeness of this problem. In this article, we present intentions
recognition system is based on a semi-automatic method of
extraction the intentional information starting from a corpus of text.
This system is also able to update the ontology of intentions for the
enrichment of the knowledge base containing all possible intentions
of a domain. This approach uses the construction of a semi-formal
ontology which considered as the conceptualization of the intentional
information contained in a text. An experiments on scientific
publications in the field of computer science was considered to
validate this approach.
Abstract: Cognitive Science appeared about 40 years ago,
subsequent to the challenge of the Artificial Intelligence, as common
territory for several scientific disciplines such as: IT, mathematics,
psychology, neurology, philosophy, sociology, and linguistics. The
new born science was justified by the complexity of the problems
related to the human knowledge on one hand, and on the other by the
fact that none of the above mentioned sciences could explain alone
the mental phenomena. Based on the data supplied by the
experimental sciences such as psychology or neurology, models of
the human mind operation are built in the cognition science. These
models are implemented in computer programs and/or electronic
circuits (specific to the artificial intelligence) – cognitive systems –
whose competences and performances are compared to the human
ones, leading to the psychology and neurology data reinterpretation,
respectively to the construction of new models. During these
processes if psychology provides the experimental basis, philosophy
and mathematics provides the abstraction level utterly necessary for
the intermission of the mentioned sciences.
The ongoing general problematic of the cognitive approach
provides two important types of approach: the computational one,
starting from the idea that the mental phenomenon can be reduced to
1 and 0 type calculus operations, and the connection one that
considers the thinking products as being a result of the interaction
between all the composing (included) systems. In the field of
psychology measurements in the computational register use classical
inquiries and psychometrical tests, generally based on calculus
methods. Deeming things from both sides that are representing the
cognitive science, we can notice a gap in psychological product
measurement possibilities, regarded from the connectionist
perspective, that requires the unitary understanding of the quality –
quantity whole. In such approach measurement by calculus proves to
be inefficient. Our researches, deployed for longer than 20 years,
lead to the conclusion that measuring by forms properly fits to the
connectionism laws and principles.
Abstract: The rapid pace of technological advancement and its
consequential widening digital divide has resulted in the
marginalization of the disabled especially the communication
challenged. The dearth of suitable technologies for the development
of assistive technologies has served to further marginalize the
communications challenged user population and widen this chasm
even further. Given the varying levels of disability there and its
associated requirement for customized solution based. This paper
explains the use of a Software Development Kits (SDK) for the
bridging of this communications divide through the use of industry
poplar communications SDKs towards identification of requirements
for communications challenged users as well as identification of
appropriate frameworks for future development initiatives.
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: In this research, effort was made to identify and
evaluate barriers to the development of entrepreneurship among
Iranian entrepreneur women who were graduated from universities.
In this study, perspectives of thirty-seven available entrepreneur
women were examined. In order to prepare questionnaires and
receive knowledge about barriers among these women, seven cases of
entrepreneur women took part in in-depth interviews. Then, to
evaluate the importance of barriers, the researchers made a
questionnaire with closed questions in which the barriers were
classified into the following categories: personal-familial barriers;
socio-cultural barriers; economic-financial-commercial barriers; and
structural barriers. Entrepreneur women were requested to rate the
importance of each item. The results indicated that there were
different obstacles among entrepreneur women. The order of the
important barriers was as fallow: economic-financial-commercial,
structural, socio-cultural, and personal-familial.
Abstract: Particle detection in very noisy and low contrast images
is an active field of research in image processing. In this article, a
method is proposed for the efficient detection and sizing of subsurface
spherical particles, which is used for the processing of softly fused
Au nanoparticles. Transmission Electron Microscopy is used for
imaging the nanoparticles, and the proposed algorithm has been
tested with the two-dimensional projected TEM images obtained.
Results are compared with the data obtained by transmission optical
spectroscopy, as well as with conventional circular object detection
algorithms.
Abstract: Accurate loss minimization is the critical component
for efficient electrical distribution power flow .The contribution of
this work presents loss minimization in power distribution system
through feeder restructuring, incorporating DG and placement of
capacitor. The study of this work was conducted on IEEE
distribution network and India Electricity Board benchmark
distribution system. The executed experimental result of Indian
system is recommended to board and implement practically for
regulated stable output.
Abstract: In this paper, we develop a Spatio-Temporal graph as
of a key component of our knowledge representation Scheme. We
design an integrated representation Scheme to depict not only present
and past but future in parallel with the spaces in an effective and
intuitive manner. The resulting multi-dimensional comprehensive
knowledge structure accommodates multi-layered virtual world
developing in the time to maximize the diversity of situations in the
historical context. This knowledge representation Scheme is to be used
as the basis for simulation of situations composing the virtual world
and for implementation of virtual agents' knowledge used to judge and
evaluate the situations in the virtual world. To provide natural contexts
for situated learning or simulation games, the virtual stage set by this
Spatio-Temporal graph is to be populated by agents and other objects
interrelated and changing which are abstracted in the ontology.
Abstract: This paper attempts to establish the fact that Multi
State Network Classification is essential for performance
enhancement of Transport protocols over Satellite based Networks. A
model to classify Multi State network condition taking into
consideration both congestion and channel error is evolved. In order
to arrive at such a model an analysis of the impact of congestion and
channel error on RTT values has been carried out using ns2. The
analysis results are also reported in the paper. The inference drawn
from this analysis is used to develop a novel statistical RTT based
model for multi state network classification.
An Adaptive Multi State Proactive Transport Protocol consisting
of Proactive Slow Start, State based Error Recovery, Timeout Action
and Proactive Reduction is proposed which uses the multi state
network state classification model. This paper also confirms through
detail simulation and analysis that a prior knowledge about the
overall characteristics of the network helps in enhancing the
performance of the protocol over satellite channel which is
significantly affected due to channel noise and congestion.
The necessary augmentation of ns2 simulator is done for
simulating the multi state network classification logic. This
simulation has been used in detail evaluation of the protocol under
varied levels of congestion and channel noise. The performance
enhancement of this protocol with reference to established protocols
namely TCP SACK and Vegas has been discussed. The results as
discussed in this paper clearly reveal that the proposed protocol
always outperforms its peers and show a significant improvement in
very high error conditions as envisaged in the design of the protocol.
Abstract: This work concerns the topological optimization
problem for determining the optimal petroleum refinery
configuration. We are interested in further investigating and
hopefully advancing the existing optimization approaches and
strategies employing logic propositions to conceptual process
synthesis problems. In particular, we seek to contribute to this
increasingly exciting area of chemical process modeling by
addressing the following potentially important issues: (a) how the
formulation of design specifications in a mixed-logical-and-integer
optimization model can be employed in a synthesis problem to enrich
the problem representation by incorporating past design experience,
engineering knowledge, and heuristics; and (b) how structural
specifications on the interconnectivity relationships by space (states)
and by function (tasks) in a superstructure should be properly
formulated within a mixed-integer linear programming (MILP)
model. The proposed modeling technique is illustrated on a case
study involving the alternative processing routes of naphtha, in which
significant improvement in the solution quality is obtained.
Abstract: Chess is one of the indoor games, which improves the
level of human confidence, concentration, planning skills and
knowledge. The main objective of this paper is to help the chess
players to improve their chess openings using data mining
techniques. Budding Chess Players usually do practices by analyzing
various existing openings. When they analyze and correlate
thousands of openings it becomes tedious and complex for them. The
work done in this paper is to analyze the best lines of Blackmar-
Diemer Gambit(BDG) which opens with White D4... using data
mining analysis. It is carried out on the collection of winning games
by applying association rules. The first step of this analysis is
assigning variables to each different sequence moves. In the second
step, the sequence association rules were generated to calculate
support and confidence factor which help us to find the best
subsequence chess moves that may lead to winning position.
Abstract: In order to optimize annual IT spending and to reduce
the complexity of an entire system architecture, SOA trials have been
started. It is common knowledge that to design an SOA system we
have to adopt the top-down approach, but in reality silo systems are
being made, so these companies cannot reuse newly designed services,
and cannot enjoy SOA-s economic benefits. To prevent this situation,
we designed a generic SOA development process referred to as the
architecture of “mass customization."
To define the generic detail development processes, we did a case
study on an imaginary company. Through the case study, we could
define the practical development processes and found this could vastly
reduce updating development costs.
Abstract: A virtual collaborative classroom was created at East Carolina University, using videoconference technology via regular internet to bring students from 18 different countries, 2 at a time, to the ECU classroom in real time to learn about each other-s culture. Students from two countries are partnered one on one, they meet for 4-5 weeks, and submit a joint paper. Then the same process is repeated for two other countries. Lectures and student discussions are managed with pre-determined topics and questions. Classes are conducted in English and reading assignments are placed on the website. Administratively all partners are independent, students pay fees and get credits at their home institution. Familiarity with technology, knowledge in cultural understanding and attitude change were assessed, only attitude changes are reported in this paper. After taking this course, all students stated their comfort level in working with, and their desire to interact with, culturally different others grew stronger and their xenophobia and isolationist attitudes decreased.