Abstract: The dramatic increasing of sea-freight container
transportations and the developing trends for using containers in the
multimodal handling systems through the sea, rail, road and land in
nowadays market cause general managers of container terminals to
face challenges such as increasing demand, competitive situation,
new investments and expansion of new activities and need to use new
methods to fulfil effective operations both along quayside and within
the yard. Among these issues, minimizing the turnaround time of
vessels is considered to be the first aim of every container port
system. Regarding the complex structure of container ports, this
paper presents a simulation model that calculates the number of
trucks needed in the Iranian Shahid Rajaee Container Port for
handling containers between the berth and the yard. In this research,
some important criteria such as vessel turnaround time, gantry crane
utilization and truck utilization have been considered. By analyzing
the results of the model, it has been shown that increasing the number
of trucks to 66 units has a significant effect on the performance
indices of the port and can increase the capacity of loading and
unloading up to 10.8%.
Abstract: In this paper, we propose an energy efficient cluster
based communication protocol for wireless sensor network. Our
protocol considers both the residual energy of sensor nodes and the
distance of each node from the BS when selecting cluster-head. This
protocol can successfully prolong the network-s lifetime by 1)
reducing the total energy dissipation on the network and 2) evenly
distributing energy consumption over all sensor nodes. In this
protocol, the nodes with more energy and less distance from the BS
are probable to be selected as cluster-head. Simulation results with
MATLAB show that proposed protocol could increase the lifetime of
network more than 94% for first node die (FND), and more than 6%
for the half of the nodes alive (HNA) factor as compared with
conventional protocols.
Abstract: The goal of this project is to design a system to
recognition voice commands. Most of voice recognition systems
contain two main modules as follow “feature extraction" and “feature
matching". In this project, MFCC algorithm is used to simulate
feature extraction module. Using this algorithm, the cepstral
coefficients are calculated on mel frequency scale. VQ (vector
quantization) method will be used for reduction of amount of data to
decrease computation time. In the feature matching stage Euclidean
distance is applied as similarity criterion. Because of high accuracy
of used algorithms, the accuracy of this voice command system is
high. Using these algorithms, by at least 5 times repetition for each
command, in a single training session, and then twice in each testing
session zero error rate in recognition of commands is achieved.
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: The advent of multi-million gate Field Programmable
Gate Arrays (FPGAs) with hardware support for multiplication opens
an opportunity to recreate a significant portion of the front end of a
human cochlea using this technology. In this paper we describe the
implementation of the cochlear filter and show that it is entirely
suited to a single device XC3S500 FPGA implementation .The filter
gave a good fit to real time data with efficiency of hardware usage.
Abstract: The paper reviews the relationship between spatial
and transportation planning in the Southern African Development
Community (SADC) region of Sub-Saharan Africa. It argues that
most urbanisation in the region has largely occurred subsequent to
the 1950s and, accordingly, urban development has been
profoundly and negatively affected by the (misguided) spatial and
institutional tenets of modernism. It demonstrates how a
considerable amount of the poor performance of these settlements
can be directly attributed to this. Two factors in particular about the
planning systems are emphasized: the way in which programmatic
land-use planning lies at the heart of both spatial and transportation
planning; and the way on which transportation and spatial planning
have been separated into independent processes. In the final
section, the paper identifies ways of improving the planning
system. Firstly, it identifies the performance qualities which
Southern African settlements should be seeking to achieve.
Secondly, it focuses on two necessary arenas of change: the need to
replace programmatic land-use planning practices with structuralspatial
approaches; and it makes a case for making urban corridors
a spatial focus of integrated planning, as a way of beginning the
restructuring and intensification of settlements which are currently
characterised by sprawl, fragmentation and separation
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: Nowadays, engineering ceramics have significant
applications in different industries such as; automotive, aerospace,
electrical, electronics and even martial industries due to their
attractive physical and mechanical properties like very high hardness
and strength at elevated temperatures, chemical stability, low friction
and high wear resistance. However, these interesting properties plus
low heat conductivity make their machining processes too hard,
costly and time consuming. Many attempts have been made in order
to make the grinding process of engineering ceramics easier and
many scientists have tried to find proper techniques to economize
ceramics' machining processes. This paper proposes a new diamond
plunge grinding technique using ultrasonic vibration for grinding
Alumina ceramic (Al2O3). For this purpose, a set of laboratory
equipments have been designed and simulated using Finite Element
Method (FEM) and constructed in order to be used in various
measurements. The results obtained have been compared with the
conventional plunge grinding process without ultrasonic vibration
and indicated that the surface roughness and fracture strength
improved and the grinding forces decreased.
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: In the present study, a heterogeneous and
homogeneous gas flow dispersion model for simulation and
optimisation of a large-scale catalytic slurry reactor for the direct
synthesis of dimethyl ether (DME) from syngas and CO2, using a
churn-turbulent regime was developed. In the heterogeneous gas flow
model the gas phase was distributed into two bubble phases: small
and large, however in the homogeneous one, the gas phase was
distributed into only one large bubble phase. The results indicated
that the heterogeneous gas flow model was in more agreement with
experimental pilot plant data than the homogeneous one.
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: Using neural network we try to model the unknown function f for given input-output data pairs. The connection strength of each neuron is updated through learning. Repeated simulations of crisp neural network produce different values of weight factors that are directly affected by the change of different parameters. We propose the idea that for each neuron in the network, we can obtain quasi-fuzzy weight sets (QFWS) using repeated simulation of the crisp neural network. Such type of fuzzy weight functions may be applied where we have multivariate crisp input that needs to be adjusted after iterative learning, like claim amount distribution analysis. As real data is subjected to noise and uncertainty, therefore, QFWS may be helpful in the simplification of such complex problems. Secondly, these QFWS provide good initial solution for training of fuzzy neural networks with reduced computational complexity.
Abstract: In this paper back-propagation artificial neural
network (BPANN) with Levenberg–Marquardt algorithm is
employed to predict the limiting drawing ratio (LDR) of the deep
drawing process. To prepare a training set for BPANN, some finite
element simulations were carried out. die and punch radius, die arc
radius, friction coefficient, thickness, yield strength of sheet and
strain hardening exponent were used as the input data and the LDR
as the specified output used in the training of neural network. As a
result of the specified parameters, the program will be able to
estimate the LDR for any new given condition. Comparing FEM and
BPANN results, an acceptable correlation was found.
Abstract: Whereas cellular wireless communication systems are
subject to short-and long-term fading. The effect of wireless channel
has largely been ignored in most of the teletraffic assessment
researches. In this paper, a mathematical teletraffic model is proposed
to estimate blocking and forced termination probabilities of cellular
wireless networks as a result of teletraffic behavior as well as the
outage of the propagation channel. To evaluate the proposed
teletraffic model, gamma inter-arrival and general service time
distributions have been considered based on wireless channel fading
effect. The performance is evaluated and compared with the classical
model. The proposed model is dedicated and investigated in different
operational conditions. These conditions will consider not only the
arrival rate process, but also, the different faded channels models.
Abstract: A new conceptual architecture for low-level neural
pattern recognition is presented. The key ideas are that the brain
implements support vector machines and that support vectors are
represented as memory patterns in competitive queuing memories. A
binary classifier is built from two competitive queuing memories
holding positive and negative valence training examples respectively.
The support vector machine classification function is calculated in
synchronized evaluation cycles. The kernel is computed by bisymmetric
feed-forward networks feed by sensory input and by
competitive queuing memories traversing the complete sequence of
support vectors. Temporary summation generates the output
classification. It is speculated that perception apparatus in the brain
reuses structures that have evolved for enabling fluent execution of
prepared action sequences so that pattern recognition is built on
internalized motor programmes.
Abstract: Prime Factorization based on Quantum approach in
two phases has been performed. The first phase has been achieved at
Quantum computer and the second phase has been achieved at the
classic computer (Post Processing). At the second phase the goal is to
estimate the period r of equation xrN ≡ 1 and to find the prime factors
of the composite integer N in classic computer. In this paper we
present a method based on Randomized Approach for estimation the
period r with a satisfactory probability and the composite integer N
will be factorized therefore with the Randomized Approach even the
gesture of the period is not exactly the real period at least we can find
one of the prime factors of composite N. Finally we present some
important points for designing an Emulator for Quantum Computer
Simulation.
Abstract: A 3D industrial computed tomography (CT)
manufactured based on a first generation CT systems, single-source
– single-detector, was evaluated. Operation accuracy assessment of
the manufactured system was achieved using simulation in
comparison with experimental tests. 137Cs and 60Co were used as a gamma source. Simulations were achieved using MCNP4C code.
Experimental tests of 137Cs were in good agreement with the simulations
Abstract: Finding the minimal logical functions has important applications in the design of logical circuits. This task is solved by many different methods but, frequently, they are not suitable for a computer implementation. We briefly summarise the well-known Quine-McCluskey method, which gives a unique procedure of computing and thus can be simply implemented, but, even for simple examples, does not guarantee an optimal solution. Since the Petrick extension of the Quine-McCluskey method does not give a generally usable method for finding an optimum for logical functions with a high number of values, we focus on interpretation of the result of the Quine-McCluskey method and show that it represents a set covering problem that, unfortunately, is an NP-hard combinatorial problem. Therefore it must be solved by heuristic or approximation methods. We propose an approach based on genetic algorithms and show suitable parameter settings.
Abstract: Diagnosis can be achieved by building a model of a
certain organ under surveillance and comparing it with the real time
physiological measurements taken from the patient. This paper deals
with the presentation of the benefits of using Data Mining techniques
in the computer-aided diagnosis (CAD), focusing on the cancer
detection, in order to help doctors to make optimal decisions quickly
and accurately. In the field of the noninvasive diagnosis techniques,
the endoscopic ultrasound elastography (EUSE) is a recent elasticity
imaging technique, allowing characterizing the difference between
malignant and benign tumors. Digitalizing and summarizing the main
EUSE sample movies features in a vector form concern with the use
of the exploratory data analysis (EDA). Neural networks are then
trained on the corresponding EUSE sample movies vector input in
such a way that these intelligent systems are able to offer a very
precise and objective diagnosis, discriminating between benign and
malignant tumors. A concrete application of these Data Mining
techniques illustrates the suitability and the reliability of this
methodology in CAD.
Abstract: The need in cognitive radio system for a simple, fast, and independent technique to sense the spectrum occupancy has led to the energy detection approach. Energy detector is known by its dependency on noise variation in the system which is one of its major drawbacks. In this paper, we are aiming to improve its performance by utilizing a weighted collaborative spectrum sensing, it is similar to the collaborative spectrum sensing methods introduced previously in the literature. These weighting methods give more improvement for collaborative spectrum sensing as compared to no weighting case. There is two method proposed in this paper: the first one depends on the channel status between each sensor and the primary user while the second depends on the value of the energy measured in each sensor.