Abstract: For many industrial applications plate heat
exchangers are demonstrating a large superiority over the
other types of heat exchangers. The efficiency of such a
device depends on numerous factors the effect of which needs
to be analysed and accurately evaluated.
In this paper we present a theoretical analysis of a cocurrent
plate heat exchanger and the results of its numerical
simulation.
Knowing the hot and the cold fluid streams inlet temperatures,
the respective heat capacities mCp
and the value of the
overall heat transfer coefficient, a 1-D mathematical model
based on the steady flow energy balance for a differential
length of the device is developed resulting in a set of N first
order differential equations with boundary conditions where N
is the number of channels.For specific heat exchanger
geometry and operational parameters, the problem is
numerically solved using the shooting method.
The simulation allows the prediction of the temperature
map in the heat exchanger and hence, the evaluation of its
performances. A parametric analysis is performed to evaluate
the influence of the R-parameter on the e-NTU values. For
practical purposes effectiveness-NTU graphs are elaborated
for specific heat exchanger geometry and different operating
conditions.
Abstract: While the explosive increase in information published
on the Web, researchers have to filter information when searching for
conference related information. To make it easier for users to search
related information, this paper uses Topic Maps and social information
to implement ontology since ontology can provide the formalisms and
knowledge structuring for comprehensive and transportable machine
understanding that digital information requires. Besides enhancing
information in Topic Maps, this paper proposes a method of
constructing research Topic Maps considering social information.
First, extract conference data from the web. Then extract conference
topics and the relationships between them through the proposed
method. Finally visualize it for users to search and browse. This paper
uses ontology, containing abundant of knowledge hierarchy structure,
to facilitate researchers getting useful search results. However, most
previous ontology construction methods didn-t take “people" into
account. So this paper also analyzes the social information which helps
researchers find the possibilities of cooperation/combination as well as
associations between research topics, and tries to offer better results.
Abstract: Continuous measurements and multivariate methods are applied in researching the effects of energy consumption on indoor air quality (IAQ) in a Finnish one-family house. Measured data used in this study was collected continuously in a house in Kuopio, Eastern Finland, during fourteen months long period. Consumption parameters measured were the consumptions of district heat, electricity and water. Indoor parameters gathered were temperature, relative humidity (RH), the concentrations of carbon dioxide (CO2) and carbon monoxide (CO) and differential air pressure. In this study, self-organizing map (SOM) and Sammon's mapping were applied to resolve the effects of energy consumption on indoor air quality. Namely, the SOM was qualified as a suitable method having a property to summarize the multivariable dependencies into easily observable two-dimensional map. Accompanying that, the Sammon's mapping method was used to cluster pre-processed data to find similarities of the variables, expressing distances and groups in the data. The methods used were able to distinguish 7 different clusters characterizing indoor air quality and energy efficiency in the study house. The results indicate, that the cost implications in euros of heating and electricity energy vary according to the differential pressure, concentration of carbon dioxide, temperature and season.
Abstract: In this paper, the vessel inscribed trigonometry (VITM) for the vessel progression orientation (VPO) is proposed in the two-dimensional fundus image. The VPO is a major factor in the optic disc (OD) detection which is a basic process in the retina analysis. To measure the VPO, skeletons of vessel are used. First, the vessels are classified into three classes as vessel end, vessel branch and vessel stem. And the chain code maps of VS are generated. Next, two farthest neighborhoods of each point on VS are searched by the proposed angle restriction. Lastly, a gradient of the straight line between two farthest neighborhoods is estimated to measure the VPO. VITM is validated by comparing with manual results and 2D Gaussian templates. It is confirmed that VPO of the proposed mensuration is correct enough to detect OD from the results of experiment which applied VITM to detect OD in fundus images.
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: The Address Resolution Protocol (ARP) is used by
computers to map logical addresses (IP) to physical addresses
(MAC). However ARP is an all trusting protocol and is stateless
which makes it vulnerable to many ARP cache poisoning attacks
such as Man-in-the-Middle (MITM) and Denial of service (DoS)
attacks. These flaws result in security breaches thus weakening the
appeal of the computer for exchange of sensitive data. In this paper
we describe ARP, outline several possible ARP cache poisoning
attacks and give the detailed of some attack scenarios in network
having both wired and wireless hosts. We have analyzed each of
proposed solutions, identify their strengths and limitations. Finally
get that no solution offers a feasible solution. Hence, this paper
presents an efficient and secure version of ARP that is able to cope
up with all these types of attacks and is also a feasible solution. It is a
stateful protocol, by storing the information of the Request frame in
the ARP cache, to reduce the chances of various types of attacks in
ARP. It is more efficient and secure by broadcasting ARP Reply
frame in the network and storing related entries in the ARP cache
each time when communication take place.
Abstract: The performance of sensor-less controlled induction
motor drive depends on the accuracy of the estimated speed.
Conventional estimation techniques being mathematically complex
require more execution time resulting in poor dynamic response. The
nonlinear mapping capability and powerful learning algorithms of
neural network provides a promising alternative for on-line speed
estimation. The on-line speed estimator requires the NN model to be
accurate, simpler in design, structurally compact and computationally
less complex to ensure faster execution and effective control in real
time implementation. This in turn to a large extent depends on the
type of Neural Architecture. This paper investigates three types of
neural architectures for on-line speed estimation and their
performance is compared in terms of accuracy, structural
compactness, computational complexity and execution time. The
suitable neural architecture for on-line speed estimation is identified
and the promising results obtained are presented.
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: This paper presents an analytical method to solve
governing consolidation parabolic partial differential equation (PDE)
for inelastic porous Medium (soil) with consideration of variation of
equation coefficient under cyclic loading. Since under cyclic loads,
soil skeleton parameters change, this would introduce variable
coefficient of parabolic PDE. Classical theory would not rationalize
consolidation phenomenon in such condition. In this research, a
method based on time space mapping to a virtual time space along
with superimposing rule is employed to solve consolidation of
inelastic soils in cyclic condition. Changes of consolidation
coefficient applied in solution by modification of loading and
unloading duration by introducing virtual time. Mapping function is
calculated based on consolidation partial differential equation results.
Based on superimposing rule a set of continuous static loads in
specified times used instead of cyclic load. A set of laboratory
consolidation tests under cyclic load along with numerical
calculations were performed in order to verify the presented method.
Numerical solution and laboratory tests results showed accuracy of
presented method.
Abstract: A set of Artificial Neural Network (ANN) based methods
for the design of an effective system of speech recognition of
numerals of Assamese language captured under varied recording
conditions and moods is presented here. The work is related to
the formulation of several ANN models configured to use Linear
Predictive Code (LPC), Principal Component Analysis (PCA) and
other features to tackle mood and gender variations uttering numbers
as part of an Automatic Speech Recognition (ASR) system in
Assamese. The ANN models are designed using a combination of
Self Organizing Map (SOM) and Multi Layer Perceptron (MLP)
constituting a Learning Vector Quantization (LVQ) block trained in a
cooperative environment to handle male and female speech samples
of numerals of Assamese- a language spoken by a sizable population
in the North-Eastern part of India. The work provides a comparative
evaluation of several such combinations while subjected to handle
speech samples with gender based differences captured by a microphone
in four different conditions viz. noiseless, noise mixed, stressed
and stress-free.
Abstract: The paper describes a self supervised parallel self organizing neural network (PSONN) architecture for true color image segmentation. The proposed architecture is a parallel extension of the standard single self organizing neural network architecture (SONN) and comprises an input (source) layer of image information, three single self organizing neural network architectures for segmentation of the different primary color components in a color image scene and one final output (sink) layer for fusion of the segmented color component images. Responses to the different shades of color components are induced in each of the three single network architectures (meant for component level processing) by applying a multilevel version of the characteristic activation function, which maps the input color information into different shades of color components, thereby yielding a processed component color image segmented on the basis of the different shades of component colors. The number of target classes in the segmented image corresponds to the number of levels in the multilevel activation function. Since the multilevel version of the activation function exhibits several subnormal responses to the input color image scene information, the system errors of the three component network architectures are computed from some subnormal linear index of fuzziness of the component color image scenes at the individual level. Several multilevel activation functions are employed for segmentation of the input color image scene using the proposed network architecture. Results of the application of the multilevel activation functions to the PSONN architecture are reported on three real life true color images. The results are substantiated empirically with the correlation coefficients between the segmented images and the original images.
Abstract: As a result of the daily workflow in the design
development departments of companies, databases containing huge
numbers of 3D geometric models are generated. According to the
given problem engineers create CAD drawings based on their design
ideas and evaluate the performance of the resulting design, e.g. by
computational simulations. Usually, new geometries are built either
by utilizing and modifying sets of existing components or by adding
single newly designed parts to a more complex design.
The present paper addresses the two facets of acquiring
components from large design databases automatically and providing
a reasonable overview of the parts to the engineer. A unified
framework based on the topographic non-negative matrix
factorization (TNMF) is proposed which solves both aspects
simultaneously. First, on a given database meaningful components
are extracted into a parts-based representation in an unsupervised
manner. Second, the extracted components are organized and
visualized on square-lattice 2D maps. It is shown on the example of
turbine-like geometries that these maps efficiently provide a wellstructured
overview on the database content and, at the same time,
define a measure for spatial similarity allowing an easy access and
reuse of components in the process of design development.
Abstract: Monitored 3-Dimensional (3D) video experience can be utilized as “feedback information” to fine tune the service parameters for providing a better service to the demanding 3D service customers. The 3D video experience which includes both video quality and depth perception is influenced by several contextual and content related factors (e.g., ambient illumination condition, content characteristics, etc) due to the complex nature of the 3D video. Therefore, effective factors on this experience should be utilized while assessing it. In this paper, structural information of the depth map sequences of the 3D video is considered as content related factor effective on the depth perception assessment. Cartoon-like filter is utilized to abstract the significant depth levels in the depth map sequences to determine the structural information. Moreover, subjective experiments are conducted using 3D videos associated with cartoon-like depth map sequences to investigate the effectiveness of ambient illumination condition, which is a contextual factor, on depth perception. Using the knowledge gained through this study, 3D video experience metrics can be developed to deliver better service to the 3D video service users.
Abstract: This paper proposes fractal patterns for power quality
(PQ) detection using color relational analysis (CRA) based classifier.
Iterated function system (IFS) uses the non-linear interpolation in the
map and uses similarity maps to construct various fractal patterns of
power quality disturbances, including harmonics, voltage sag, voltage
swell, voltage sag involving harmonics, voltage swell involving
harmonics, and voltage interruption. The non-linear interpolation
functions (NIFs) with fractal dimension (FD) make fractal patterns
more distinguishing between normal and abnormal voltage signals.
The classifier based on CRA discriminates the disturbance events in a
power system. Compared with the wavelet neural networks, the test
results will show accurate discrimination, good robustness, and faster
processing time for detecting disturbing events.
Abstract: Development of levels of service in municipal context
is a flexible vehicle to assist in performing quality-cost trade-off
analysis for municipal services. This trade-off depends on the
willingness of a community to pay as well as on the condition of the
assets. Community perspective of the performance of an asset from
service point of view may be quite different from the municipality
perspective of the performance of the same asset from condition
point of view. This paper presents a three phased level of service
based methodology for water mains that consists of :1)development
of an Analytical Hierarchy model of level of service 2) development
of Fuzzy Weighted Sum model of water main condition index and 3)
deriving a Fuzzy logic based function that maps level of service to
asset condition index. This mapping will assist asset managers in
quantifying condition improvement requirement to meet service
goals and to make more informed decisions on interventions and
relayed priorities.
Abstract: This paper considers the (2+1)-dimensional breaking soliton equation in its bilinear form. Some exact solutions to this equation are explicitly derived by the idea of three-wave solution method with the assistance of Maple. We can see that the new idea is very simple and straightforward.
Abstract: This paper covers various aspects of film piracy over the Internet. In order to successfully deal with this matter, it is needed to recognize motivational factors related to film piracy. Thus, this study discusses group factors that could motivate individuals to engage in pirate activities. Furthermore, the paper discusses the theoretical effect on box office revenues and explains it on a proposed scheme of solutions for decreasing revenues. The article also maps the scheme of incentive motivational anti-piracy campaigns. Moreover, the paper proposes the preliminary scheme for system dynamic modeling of the Internet film piracy. Scheme is developed as a model of behaviors, influences and relations among the elements pertaining to the Internet film piracy.
Abstract: Robotic system is an important area in artificial intelligence that aims at developing the performance techniques of the robot and making it more efficient and more effective in choosing its correct behavior. In this paper the distributed learning classifier system is used for designing a simulated control system for robot to perform complex behaviors. A set of enhanced approaches that support default hierarchies formation is suggested and compared with each other in order to make the simulated robot more effective in mapping the input to the correct output behavior.
Abstract: Fuzzy Cognitive Maps (FCMs) is a causal graph, which shows the relations between essential components in complex systems. Experts who are familiar with the system components and their relations can generate a related FCM. There is a big gap when human experts cannot produce FCM or even there is no expert to produce the related FCM. Therefore, a new mechanism must be used to bridge this gap. In this paper, a novel learning method is proposed to construct causal graph based on historical data and by using metaheuristic such Tabu Search (TS). The efficiency of the proposed method is shown via comparison of its results of some numerical examples with those of some other methods.
Abstract: The principal purpose of this article is to present a new method based on Adaptive Neural Network Fuzzy Inference System (ANFIS) to generate additional artificial earthquake accelerograms from presented data, which are compatible with specified response spectra. The proposed method uses the learning abilities of ANFIS to develop the knowledge of the inverse mapping from response spectrum to earthquake records. In addition, wavelet packet transform is used to decompose specified earthquake records and then ANFISs are trained to relate the response spectrum of records to their wavelet packet coefficients. Finally, an interpretive example is presented which uses an ensemble of recorded accelerograms to demonstrate the effectiveness of the proposed method.