Abstract: In this era of technology, fueled by the pervasive usage of the internet, security is a prime concern. The number of new attacks by the so-called “bots", which are automated programs, is increasing at an alarming rate. They are most likely to attack online registration systems. Technology, called “CAPTCHA" (Completely Automated Public Turing test to tell Computers and Humans Apart) do exist, which can differentiate between automated programs and humans and prevent replay attacks. Traditionally CAPTCHA-s have been implemented with the challenge involved in recognizing textual images and reproducing the same. We propose an approach where the visual challenge has to be read out from which randomly selected keywords are used to verify the correctness of spoken text and in turn detect the presence of human. This is supplemented with a speaker recognition system which can identify the speaker also. Thus, this framework fulfills both the objectives – it can determine whether the user is a human or not and if it is a human, it can verify its identity.
Abstract: Nowaday-s, many organizations use systems that
support business process as a whole or partially. However, in some
application domains, like software development and health care
processes, a normative Process Aware System (PAS) is not suitable,
because a flexible support is needed to respond rapidly to new
process models. On the other hand, a flexible Process Aware System
may be vulnerable to undesirable and fraudulent executions, which
imposes a tradeoff between flexibility and security. In order to make
this tradeoff available, a genetic-based anomaly detection model for
logs of Process Aware Systems is presented in this paper. The
detection of an anomalous trace is based on discovering an
appropriate process model by using genetic process mining and
detecting traces that do not fit the appropriate model as anomalous
trace; therefore, when used in PAS, this model is an automated
solution that can support coexistence of flexibility and security.
Abstract: This article gives a short preview of the new software
created especially for palletizing process in automated production
systems. Each chapter of this article is about problem solving in
development of modules in Java programming language. First part
describes structure of the software, its modules and data flow
between them. Second part describes all deployment methods, which
are implemented in the software. Next chapter is about twodimensional
editor created for manipulation with objects in each
layer of the load and gives calculations for collision control. Module
of virtual reality used for three-dimensional preview and creation of
the load is described in the fifth chapter. The last part of this article
describes communication and data flow between control system of
the robot, vision system and software.
Abstract: Least Development Countries (LDC) like
Bangladesh, whose 25% revenue earning is achieved from Textile
export, requires producing less defective textile for minimizing
production cost and time. Inspection processes done on these
industries are mostly manual and time consuming. To reduce error
on identifying fabric defects requires more automotive and
accurate inspection process. Considering this lacking, this research
implements a Textile Defect Recognizer which uses computer
vision methodology with the combination of multi-layer neural
networks to identify four classifications of textile defects. The
recognizer, suitable for LDC countries, identifies the fabric defects
within economical cost and produces less error prone inspection
system in real time. In order to generate input set for the neural
network, primarily the recognizer captures digital fabric images by
image acquisition device and converts the RGB images into binary
images by restoration process and local threshold techniques.
Later, the output of the processed image, the area of the faulty
portion, the number of objects of the image and the sharp factor of
the image, are feed backed as an input layer to the neural network
which uses back propagation algorithm to compute the weighted
factors and generates the desired classifications of defects as an
output.
Abstract: Home Automation is a field that, among other
subjects, is concerned with the comfort, security and energy
requirements of private homes. The configuration of automatic
functions in this type of houses is not always simple to its inhabitants
requiring the initial setup and regular adjustments. In this work, the
ubiquitous computing system vision is used, where the users- action
patterns are captured, recorded and used to create the contextawareness
that allows the self-configuration of the home automation
system. The system will try to free the users from setup adjustments
as the home tries to adapt to its inhabitants- real habits. In this paper
it is described a completely automated process to determine the light
state and act on them, taking in account the users- daily habits.
Artificial Neural Network (ANN) is used as a pattern recognition
method, classifying for each moment the light state. The work
presented uses data from a real house where a family is actually
living.
Abstract: This research work proposed a study of fruit bruise detection by means of a biospeckle method, selecting the papaya fruit (Carica papaya) as testing body. Papaya is recognized as a fruit of outstanding nutritional qualities, showing high vitamin A content, calcium, carbohydrates, exhibiting high popularity all over the world, considering consumption and acceptability. The commercialization of papaya faces special problems which are associated to bruise generation during harvesting, packing and transportation. Papaya is classified as climacteric fruit, permitting to be harvested before the maturation is completed. However, by one side bruise generation is partially controlled once the fruit flesh exhibits high mechanical firmness. By the other side, mechanical loads can set a future bruise at that maturation stage, when it can not be detected yet by conventional methods. Mechanical damages of fruit skin leave an entrance door to microorganisms and pathogens, which will cause severe losses of quality attributes. Traditional techniques of fruit quality inspection include total soluble solids determination, mechanical firmness tests, visual inspections, which would hardly meet required conditions for a fully automated process. However, the pertinent literature reveals a new method named biospeckle which is based on the laser reflectance and interference phenomenon. The laser biospeckle or dynamic speckle is quantified by means of the Moment of Inertia, named after its mechanical counterpart due to similarity between the defining formulae. Biospeckle techniques are able to quantify biological activities of living tissues, which has been applied to seed viability analysis, vegetable senescence and similar topics. Since the biospeckle techniques can monitor tissue physiology, it could also detect changes in the fruit caused by mechanical damages. The proposed technique holds non invasive character, being able to generate numerical results consistent with an adequate automation. The experimental tests associated to this research work included the selection of papaya fruit at different maturation stages which were submitted to artificial mechanical bruising tests. Damages were visually compared with the frequency maps yielded by the biospeckle technique. Results were considered in close agreement.
Abstract: This paper investigates the problem of automated defect
detection for textile fabrics and proposes a new optimal filter design
method to solve this problem. Gabor Wavelet Network (GWN) is
chosen as the major technique to extract the texture features from
textile fabrics. Based on the features extracted, an optimal Gabor filter
can be designed. In view of this optimal filter, a new semi-supervised
defect detection scheme is proposed, which consists of one real-valued
Gabor filter and one smoothing filter. The performance of the scheme
is evaluated by using an offline test database with 78 homogeneous
textile images. The test results exhibit accurate defect detection with
low false alarm, thus showing the effectiveness and robustness of the
proposed scheme. To evaluate the detection scheme comprehensively,
a prototyped detection system is developed to conduct a real time test.
The experiment results obtained confirm the efficiency and
effectiveness of the proposed detection scheme.
Abstract: Policy management in organizations became rising issue in the last decade. It’s because of today’s regulatory requirements in the organizations. To manage policies in large organizations is an imperative work. However, major challenges facing organizations in the last decade is managing all the policies in the organization and making them an active documents rather than simple (inactive) documents stored in computer hard drive or on a shelf. Because of this challenge, organizations need policy management program. This policy management program can be either manual or automated. This paper presents suggestions towards managing policies in organizations. As well as possible policy management solution or program to be utilized, manual or automated. The research first examines the models and frameworks used for managing policies from various perspectives in the literature of the research area/domain. At the end of this paper, a policy management framework is proposed for managing enterprise policies effectively and in a simplified manner.
Abstract: The growing interest on national heritage
preservation has led to intensive efforts on digital documentation of
cultural heritage knowledge. Encapsulated within this effort is the
focus on ontology development that will help facilitate the
organization and retrieval of the knowledge. Ontologies surrounding
cultural heritage domain are related to archives, museum and library
information such as archaeology, artifacts, paintings, etc. The growth
in number and size of ontologies indicates the well acceptance of its
semantic enrichment in many emerging applications. Nowadays,
there are many heritage information systems available for access.
Among others is community-based e-museum designed to support the
digital cultural heritage preservation. This work extends previous
effort of developing the Traditional Malay Textile (TMT) Knowledge
Model where the model is designed with the intention of auxiliary
mapping with CIDOC CRM. Due to its internal constraints, the
model needs to be transformed in advance. This paper addresses the
issue by reviewing the previous harmonization works with CIDOC
CRM as exemplars in refining the facets in the model particularly
involving TMT-Artifact class. The result is an extensible model
which could lead to a common view for automated mapping with
CIDOC CRM. Hence, it promotes integration and exchange of
textile information especially batik-related between communities in
e-museum applications.
Abstract: For evaluating the severity of Chronic Obstructive Pulmonary Disease (COPD), one is interested in inspecting the airway wall thickening due to inflammation. Although airway segmentations have being well developed to reconstruct in high order, airway wall segmentation remains a challenge task. While tackling such problem as a multi-surface segmentation, the interrelation within surfaces needs to be considered. We propose a new method for three-dimensional airway wall segmentation using spring structural active contour model. The method incorporates the gravitational field of the image and repelling force field of the inner lumen as the soft constraint and the geometric spring structure of active contour as the hard constraint to approximate a three-dimensional coupled surface readily for thickness measurements. The results show the preservation of topology constraints of coupled surfaces. In conclusion, our springy, soft-tissue-like structure ensures the globally optimal solution and waives the shortness following by the inevitable improper inner surface constraint.
Abstract: The theory of Groebner Bases, which has recently been
honored with the ACM Paris Kanellakis Theory and Practice Award,
has become a crucial building block to computer algebra, and is
widely used in science, engineering, and computer science. It is wellknown
that Groebner bases computation is EXP-SPACE in a general
polynomial ring setting.
However, for many important applications in computer science
such as satisfiability and automated verification of hardware and
software, computations are performed in a Boolean ring. In this paper,
we give an algorithm to show that Groebner bases computation is PSPACE
in Boolean rings. We also show that with this discovery,
the Groebner bases method can theoretically be as efficient as
other methods for automated verification of hardware and software.
Additionally, many useful and interesting properties of Groebner
bases including the ability to efficiently convert the bases for different
orders of variables making Groebner bases a promising method in
automated verification.
Abstract: Currently is characterized production engineering
together with the integration of industrial automation and robotics
such very quick view of to manufacture the products. The production
range is continuously changing, expanding and producers have to be
flexible in this regard. It means that need to offer production
possibilities, which can respond to the quick change. Engineering
product development is focused on supporting CAD software, such
systems are mainly used for product design. That manufacturers are
competitive, it should be kept procured machines made available
capable of responding to output flexibility. In response to that
problem is the development of flexible manufacturing systems,
consisting of various automated systems. The integration of flexible
manufacturing systems and subunits together with product design and
of engineering is a possible solution for this issue. Integration is
possible through the implementation of CIM systems. Such a solution
and finding a hyphen between CAD and procurement system ICIM
3000 from Festo Co. is engaged in the research project and this
contribution. This can be designed the products in CAD systems and
watch the manufacturing process from order to shipping by the
development of methods and processes of integration, This can be
modeled in CAD systems products and watch the manufacturing
process from order to shipping to develop methods and processes of
integration, which will improve support for product design
parameters by monitoring of the production process, by creating of
programs for production using the CAD and therefore accelerates the
a total of process from design to implementation.
Abstract: This paper presents an overview of the Ocean wave kinetic energy harvesting system. Energy harvesting is a concept by which energy is captured, stored, and utilized using various sources by employing interfaces, storage devices, and other units. Ocean wave energy harvesting in which the kinetic and potential energy contained in the natural oscillations of Ocean waves are converted into electric power. The kinetic energy harvesting system could be used for a number of areas. The main applications that we have discussed in this paper are to how generate the energy from Ocean wave energy (kinetic energy) to electric energy that is to eliminate the requirement for continual battery replacement.
Abstract: Today, canines are still used effectively in acceleration detection situation. However, this method is becoming impractical in modern age and a new automated replacement to the canine is required. This paper reports the design of an innovative accelerant detector. Designing an accelerant detector is a long process as is any design process; therefore, a solution to the need for a mobile, effective accelerant detector is hereby presented. The device is simple and efficient to ensure that any accelerant detection can be conducted quickly and easily. The design utilizes Ultra Violet (UV) light to detect the accelerant. When the UV light shines on an accelerant, the hydrocarbons in the accelerant emit florescence. The advantages of using the UV light to detect accelerant are also outlined in this paper. The mobility of the device is achieved by using a Direct Current (DC) motor to run tank tracks. Tank tracks were chosen as to ensure that the device will be mobile in the rough terrain of a fire site. The materials selected for the various parts are also presented. A Solid Works Simulation was also conducted on the stresses in the shafts and the results are presented. This design is an innovative solution which offers a user friendly interface. The design is also environmentally friendly, ecologically sound and safe to use.
Abstract: In this paper, algorithms for the automatic localisation
of two anatomical soft tissue landmarks of the head the medial
canthus (inner corner of the eye) and the tragus (a small, pointed,
cartilaginous flap of the ear), in CT images are describet. These
landmarks are to be used as a basis for an automated image-to-patient
registration system we are developing. The landmarks are localised
on a surface model extracted from CT images, based on surface
curvature and a rule based system that incorporates prior knowledge
of the landmark characteristics. The approach was tested on a dataset
of near isotropic CT images of 95 patients. The position of the
automatically localised landmarks was compared to the position of
the manually localised landmarks. The average difference was 1.5
mm and 0.8 mm for the medial canthus and tragus, with a maximum
difference of 4.5 mm and 2.6 mm respectively.The medial canthus
and tragus can be automatically localised in CT images, with
performance comparable to manual localisation
Abstract: The number of intrusions and attacks against critical
infrastructures and other information networks is increasing rapidly.
While there is no identified evidence that terrorist organizations are
currently planning a coordinated attack against the vulnerabilities of
computer systems and network connected to critical infrastructure,
and origins of the indiscriminate cyber attacks that infect computers
on network remain largely unknown. The growing trend toward the
use of more automated and menacing attack tools has also
overwhelmed some of the current methodologies used for tracking
cyber attacks. There is an ample possibility that this kind of cyber
attacks can be transform to cyberterrorism caused by illegal purposes.
Cyberterrorism is a matter of vital importance to national welfare.
Therefore, each countries and organizations have to take a proper
measure to meet the situation and consider effective legislation about
cyberterrorism.
Abstract: Automated storage and retrieval systems (AS/RS)
become frequently used systems in warehouses. There has been a
transition from human based forklift applications to fast and safe
AS/RS applications in firm-s warehouse systems. In this study, basic
components and automation systems of the AS/RS are examined.
Proposed system's automation components and their tasks in the
system control algorithm were stated. According to this control
algorithm the control system structure was obtained.
Abstract: The evolution of current modeling specifications gives rise to the problem of generating automated test cases from a variety of application tools. Past endeavours on behavioural testing of UML statecharts have not systematically leveraged the potential of existing graph theory for testing of objects. Therefore there exists a need for a simple, tool-independent, and effective method for automatic test generation. An architecture, codenamed ACUTE-J (Automated stateChart Unit Testing Engine for Java), for automating the unit test generation process is presented. A sequential approach for converting UML statechart diagrams to JUnit test classes is described, with the application of existing graph theory. Research byproducts such as a universal XML Schema and API for statechart-driven testing are also proposed. The result from a Java implementation of ACUTE-J is discussed in brief. The Chinese Postman algorithm is utilised as an illustration for a run-through of the ACUTE-J architecture.
Abstract: Modern highly automated production systems faces
problems of reliability. Machine function reliability results in
changes of productivity rate and efficiency use of expensive
industrial facilities. Predicting of reliability has become an important
research and involves complex mathematical methods and
calculation. The reliability of high productivity technological
automatic machines that consists of complex mechanical, electrical
and electronic components is important. The failure of these units
results in major economic losses of production systems. The
reliability of transport and feeding systems for automatic
technological machines is also important, because failure of transport
leads to stops of technological machines. This paper presents
reliability engineering on the feeding system and its components for
transporting a complex shape parts to automatic machines. It also
discusses about the calculation of the reliability parameters of the
feeding unit by applying the probability theory. Equations produced
for calculating the limits of the geometrical sizes of feeders and the
probability of sticking the transported parts into the chute represents
the reliability of feeders as a function of its geometrical parameters.
Abstract: Segmenting the lungs in medical images is a
challenging and important task for many applications. In particular,
automatic segmentation of lung cavities from multiple magnetic
resonance (MR) images is very useful for oncological applications
such as radiotherapy treatment planning. However, distinguishing of
the lung areas is not trivial due to largely changing lung shapes, low
contrast and poorly defined boundaries. In this paper, we address
lung segmentation problem from pulmonary magnetic resonance
images and propose an automated method based on a robust regionaided
geometric snake with a modified diffused region force into the
standard geometric model definition. The extra region force gives the
snake a global complementary view of the lung boundary
information within the image which along with the local gradient
flow, helps detect fuzzy boundaries. The proposed method has been
successful in segmenting the lungs in every slice of 30 magnetic
resonance images with 80 consecutive slices in each image. We
present results by comparing our automatic method to manually
segmented lung cavities provided by an expert radiologist and with
those of previous works, showing encouraging results and high
robustness of our approach.