Abstract: Mathematical, graphical and intuitive models are often
constructed in the development process of computational systems.
The Unified Modeling Language (UML) is one of the most popular
modeling languages used by practicing software engineers. This
paper critically examines UML models and suggests an augmented
use case view with the addition of new constructs for modeling
software. It also shows how a use case diagram can be enhanced. The
improved modeling constructs are presented with examples for
clarifying important design and implementation issues.
Abstract: Mobile agent has motivated the creation of a new
methodology for parallel computing. We introduce a methodology
for the creation of parallel applications on the network. The proposed
Mobile-Agent parallel processing framework uses multiple Javamobile
Agents. Each mobile agent can travel to the specified
machine in the network to perform its tasks. We also introduce the
concept of master agent, which is Java object capable of
implementing a particular task of the target application. Master agent
is dynamically assigns the task to mobile agents. We have developed
and tested a prototype application: Mobile Agent Based Parallel
Computing. Boosted by the inherited benefits of using Java and
Mobile Agents, our proposed methodology breaks the barriers
between the environments, and could potentially exploit in a parallel
manner all the available computational resources on the network.
This paper elaborates performance issues of a mobile agent for
parallel computing.
Abstract: Due to the increasing and varying risks that economic units face with, derivative instruments gain substantial importance, and trading volumes of derivatives have reached very significant level. Parallel with these high trading volumes, researchers have developed many different models. Some are parametric, some are nonparametric. In this study, the aim is to analyse the success of artificial neural network in pricing of options with S&P 100 index options data. Generally, the previous studies cover the data of European type call options. This study includes not only European call option but also American call and put options and European put options. Three data sets are used to perform three different ANN models. One only includes data that are directly observed from the economic environment, i.e. strike price, spot price, interest rate, maturity, type of the contract. The others include an extra input that is not an observable data but a parameter, i.e. volatility. With these detail data, the performance of ANN in put/call dimension, American/European dimension, moneyness dimension is analyzed and whether the contribution of the volatility in neural network analysis make improvement in prediction performance or not is examined. The most striking results revealed by the study is that ANN shows better performance when pricing call options compared to put options; and the use of volatility parameter as an input does not improve the performance.
Abstract: Modeling of a heterogeneous industrial fixed bed
reactor for selective dehydrogenation of heavy paraffin with Pt-Sn-
Al2O3 catalyst has been the subject of current study. By applying
mass balance, momentum balance for appropriate element of reactor
and using pressure drop, rate and deactivation equations, a detailed
model of the reactor has been obtained. Mass balance equations have
been written for five different components. In order to estimate
reactor production by the passage of time, the reactor model which is
a set of partial differential equations, ordinary differential equations
and algebraic equations has been solved numerically.
Paraffins, olefins, dienes, aromatics and hydrogen mole percent as
a function of time and reactor radius have been found by numerical
solution of the model. Results of model have been compared with
industrial reactor data at different operation times. The comparison
successfully confirms validity of proposed model.
Abstract: Fats and oils are made of esterified hydrocarbons
(RCOOR-) and this work demonstrates the substitution of R by
multi-walled CNTs (MWNTs). The resultant materials are fluidic, oily,
electrically conducting and excellent lubricants. Esterified MWNTs
can also respond to magnetic field when tubules contain long segments
of Fe
Abstract: Information is increasing in volumes; companies are overloaded with information that they may lose track in getting the intended information. It is a time consuming task to scan through each of the lengthy document. A shorter version of the document which contains only the gist information is more favourable for most information seekers. Therefore, in this paper, we implement a text summarization system to produce a summary that contains gist information of oil and gas news articles. The summarization is intended to provide important information for oil and gas companies to monitor their competitor-s behaviour in enhancing them in formulating business strategies. The system integrated statistical approach with three underlying concepts: keyword occurrences, title of the news article and location of the sentence. The generated summaries were compared with human generated summaries from an oil and gas company. Precision and recall ratio are used to evaluate the accuracy of the generated summary. Based on the experimental results, the system is able to produce an effective summary with the average recall value of 83% at the compression rate of 25%.
Abstract: The Kinetics formation of labile Complex
Ag (I) tetra (p-carboxyphenyl) porphyrin, was investigated at 25oC
and I=0.1M (NaNO3). By spectrophotometric titration, the
composition ratio of the complex was established to be 2:1
(Ag : H2TCPP). The equilibrium constant, K, was found to be
log 10-6.53. Binding of the first Ag (I) was found to be rate
determining step with rate constant, k1= 4.67×102 . A plausible
mechanism is discussed. We discus theoretically why Ag(I)2TCPP is
unstable.
Abstract: Choosing the right metadata is a critical, as good
information (metadata) attached to an image will facilitate its
visibility from a pile of other images. The image-s value is enhanced
not only by the quality of attached metadata but also by the technique
of the search. This study proposes a technique that is simple but
efficient to predict a single human image from a website using the
basic image data and the embedded metadata of the image-s content
appearing on web pages. The result is very encouraging with the
prediction accuracy of 95%. This technique may become a great
assist to librarians, researchers and many others for automatically and
efficiently identifying a set of human images out of a greater set of
images.
Abstract: High speed networks provide realtime variable bit rate
service with diversified traffic flow characteristics and quality
requirements. The variable bit rate traffic has stringent delay and
packet loss requirements. The burstiness of the correlated traffic
makes dynamic buffer management highly desirable to satisfy the
Quality of Service (QoS) requirements. This paper presents an
algorithm for optimization of adaptive buffer allocation scheme for
traffic based on loss of consecutive packets in data-stream and buffer
occupancy level. Buffer is designed to allow the input traffic to be
partitioned into different priority classes and based on the input
traffic behavior it controls the threshold dynamically. This algorithm
allows input packets to enter into buffer if its occupancy level is less
than the threshold value for priority of that packet. The threshold is
dynamically varied in runtime based on packet loss behavior. The
simulation is run for two priority classes of the input traffic –
realtime and non-realtime classes. The simulation results show that
Adaptive Partial Buffer Sharing (ADPBS) has better performance
than Static Partial Buffer Sharing (SPBS) and First In First Out
(FIFO) queue under the same traffic conditions.
Abstract: The necessity of accurate and timely field data is
shared among organizations engaged in fundamentally different
activities, public services or commercial operations. Basically, there
are three major components in the process of the qualitative research:
data collection, interpretation and organization of data, and analytic
process. Representative technological advancements in terms of
innovation have been made in mobile devices (mobile phone, PDA-s,
tablets, laptops, etc). Resources that can be potentially applied on the
data collection activity for field researches in order to improve this
process.
This paper presents and discuss the main features of a mobile
phone based solution for field data collection, composed of basically
three modules: a survey editor, a server web application and a client
mobile application. The data gathering process begins with the
survey creation module, which enables the production of tailored
questionnaires. The field workforce receives the questionnaire(s) on
their mobile phones to collect the interviews responses and sending
them back to a server for immediate analysis.
Abstract: A model predictive controller based on recursive learning is proposed. In this SISO adaptive controller, a model is automatically updated using simple recursive equations. The identified models are then stored in the memory to be re-used in the future. The decision for model update is taken based on a new control performance index. The new controller allows the use of simple linear model predictive controllers in the control of nonlinear time varying processes.
Abstract: In this paper, a tooth shape optimization method for
cogging torque reduction in Permanent Magnet (PM) motors is
developed by using the Reduced Basis Technique (RBT) coupled by
Finite Element Analysis (FEA) and Design of Experiments (DOE)
methods. The primary objective of the method is to reduce the
enormous number of design variables required to define the tooth
shape. RBT is a weighted combination of several basis shapes. The
aim of the method is to find the best combination using the weights
for each tooth shape as the design variables. A multi-level design
process is developed to find suitable basis shapes or trial shapes at
each level that can be used in the reduced basis technique. Each level
is treated as a separated optimization problem until the required
objective – minimum cogging torque – is achieved. The process is
started with geometrically simple basis shapes that are defined by
their shape co-ordinates. The experimental design of Taguchi method
is used to build the approximation model and to perform
optimization. This method is demonstrated on the tooth shape
optimization of a 8-poles/12-slots PM motor.
Abstract: Increasing growth of information volume in the
internet causes an increasing need to develop new (semi)automatic
methods for retrieval of documents and ranking them according to
their relevance to the user query. In this paper, after a brief review
on ranking models, a new ontology based approach for ranking
HTML documents is proposed and evaluated in various
circumstances. Our approach is a combination of conceptual,
statistical and linguistic methods. This combination reserves the
precision of ranking without loosing the speed. Our approach
exploits natural language processing techniques to extract phrases
from documents and the query and doing stemming on words. Then
an ontology based conceptual method will be used to annotate
documents and expand the query. To expand a query the spread
activation algorithm is improved so that the expansion can be done
flexible and in various aspects. The annotated documents and the
expanded query will be processed to compute the relevance degree
exploiting statistical methods. The outstanding features of our
approach are (1) combining conceptual, statistical and linguistic
features of documents, (2) expanding the query with its related
concepts before comparing to documents, (3) extracting and using
both words and phrases to compute relevance degree, (4) improving
the spread activation algorithm to do the expansion based on
weighted combination of different conceptual relationships and (5)
allowing variable document vector dimensions. A ranking system
called ORank is developed to implement and test the proposed
model. The test results will be included at the end of the paper.
Abstract: The main goal of this paper is to show a possibility, how to solve numerically elliptic boundary value problems arising in 2D linear elasticity by using the fictitious domain method (FDM) and the Total-FETI domain decomposition method. We briefly mention the theoretical background of these methods and demonstrate their performance on a benchmark.
Abstract: Due to the ever growing amount of publications about
protein-protein interactions, information extraction from text is
increasingly recognized as one of crucial technologies in
bioinformatics. This paper presents a Protein Interaction Extraction
System using a Link Grammar Parser from biomedical abstracts
(PIELG). PIELG uses linkage given by the Link Grammar Parser to
start a case based analysis of contents of various syntactic roles as
well as their linguistically significant and meaningful combinations.
The system uses phrasal-prepositional verbs patterns to overcome
preposition combinations problems. The recall and precision are
74.4% and 62.65%, respectively. Experimental evaluations with two
other state-of-the-art extraction systems indicate that PIELG system
achieves better performance. For further evaluation, the system is
augmented with a graphical package (Cytoscape) for extracting
protein interaction information from sequence databases. The result
shows that the performance is remarkably promising.
Abstract: The overall penumbra is usually defined as the
distance, p20–80, separating the 20% and 80% of the dose on the beam axis at the depth of interest. This overall penumbra accounts
also for the fact that some photons emitted by the distal parts of the source are only partially attenuated by the collimator. Medulloblastoma is the most common type of childhood brain tumor
and often spreads to the spine. Current guidelines call for surgery to remove as much of the tumor as possible, followed by radiation of the brain and spinal cord, and finally treatment with chemotherapy.
The purpose of this paper was to present results on an Uniformity of dose distribution in radiation fields surrounding the spine using film
dosimetry and comparison with 3D treatment planning software.
Abstract: In most of the cases, natural disasters lead to the
necessity of evacuating people. The quality of evacuation
management is dramatically improved by the use of information
provided by decision support systems, which become indispensable
in case of large scale evacuation operations. This paper presents a
best practice case study. In November 2007, officers from the
Emergency Situations Inspectorate “Crisana" of Bihor County from
Romania participated to a cross-border evacuation exercise, when
700 people have been evacuated from Netherlands to Belgium. One
of the main objectives of the exercise was the test of four different
decision support systems. Afterwards, based on that experience,
software system called TEVAC (Trans Border Evacuation) has been
developed “in house" by the experts of this institution. This original
software system was successfully tested in September 2008, during
the deployment of the international exercise EU-HUROMEX 2008,
the scenario involving real evacuation of 200 persons from Hungary
to Romania. Based on the lessons learned and results, starting from
April 2009, the TEVAC software is used by all Emergency
Situations Inspectorates all over Romania.
Abstract: Although in sustainable development field, innovative
solutions have been sought worldwide by environmental groups,
academia, governments and companies for many years, recently,
citizens and communities have emerged as a new group and taken
more and more active role in this field. Many scholars call for more
research on the role of community and community innovation in
sustainable development. This paper is to respond to the calls. In
this paper, we first summarize a comprehensive set of innovation
principles. Then, we do a qualitative cross case study by comparing
three community innovation cases in three different areas of sustainable
development according to the innovation principles. Finally,
we summarize the case comparison and discuss the implications
to sustainable development. A unified role model and innovation
distribution map of community innovation are developed to better
understand community innovation in sustainable development..
Abstract: Artifact rejection plays a key role in many signal processing applications. The artifacts are disturbance that can occur during the signal acquisition and that can alter the analysis of the signals themselves. Our aim is to automatically remove the artifacts, in particular from the Electroencephalographic (EEG) recordings. A technique for the automatic artifact rejection, based on the Independent Component Analysis (ICA) for the artifact extraction and on some high order statistics such as kurtosis and Shannon-s entropy, was proposed some years ago in literature. In this paper we try to enhance this technique proposing a new method based on the Renyi-s entropy. The performance of our method was tested and compared to the performance of the method in literature and the former proved to outperform the latter.
Abstract: HSDPA is a new feature which is introduced in
Release-5 specifications of the 3GPP WCDMA/UTRA standard to
realize higher speed data rate together with lower round-trip times.
Moreover, the HSDPA concept offers outstanding improvement of
packet throughput and also significantly reduces the packet call
transfer delay as compared to Release -99 DSCH. Till now the
HSDPA system uses turbo coding which is the best coding technique
to achieve the Shannon limit. However, the main drawbacks of turbo
coding are high decoding complexity and high latency which makes
it unsuitable for some applications like satellite communications,
since the transmission distance itself introduces latency due to
limited speed of light. Hence in this paper it is proposed to use LDPC
coding in place of Turbo coding for HSDPA system which decreases
the latency and decoding complexity. But LDPC coding increases the
Encoding complexity. Though the complexity of transmitter
increases at NodeB, the End user is at an advantage in terms of
receiver complexity and Bit- error rate. In this paper LDPC Encoder
is implemented using “sparse parity check matrix" H to generate a
codeword at Encoder and “Belief Propagation algorithm "for LDPC
decoding .Simulation results shows that in LDPC coding the BER
suddenly drops as the number of iterations increase with a small
increase in Eb/No. Which is not possible in Turbo coding. Also same
BER was achieved using less number of iterations and hence the
latency and receiver complexity has decreased for LDPC coding.
HSDPA increases the downlink data rate within a cell to a theoretical
maximum of 14Mbps, with 2Mbps on the uplink. The changes that
HSDPA enables includes better quality, more reliable and more
robust data services. In other words, while realistic data rates are
only a few Mbps, the actual quality and number of users achieved
will improve significantly.