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: Complexity, as a theoretical background has made it
easier to understand and explain the features and dynamic behavior
of various complex systems. As the common theoretical background
has confirmed, borrowing the terminology for design from the
natural sciences has helped to control and understand urban
complexity. Phenomena like self-organization, evolution and
adaptation are appropriate to describe the formerly inaccessible
characteristics of the complex environment in unpredictable bottomup
systems. Increased computing capacity has been a key element in
capturing the chaotic nature of these systems.
A paradigm shift in urban planning and architectural design has
forced us to give up the illusion of total control in urban
environment, and consequently to seek for novel methods for
steering the development. New methods using dynamic modeling
have offered a real option for more thorough understanding of
complexity and urban processes. At best new approaches may renew
the design processes so that we get a better grip on the complex
world via more flexible processes, support urban environmental
diversity and respond to our needs beyond basic welfare by liberating
ourselves from the standardized minimalism.
A complex system and its features are as such beyond human
ethics. Self-organization or evolution is either good or bad. Their
mechanisms are by nature devoid of reason. They are common in
urban dynamics in both natural processes and gas. They are features
of a complex system, and they cannot be prevented. Yet their
dynamics can be studied and supported.
The paradigm of complexity and new design approaches has been
criticized for a lack of humanity and morality, but the ethical
implications of scientific or computational design processes have not
been much discussed. It is important to distinguish the (unexciting)
ethics of the theory and tools from the ethics of computer aided
processes based on ethical decisions. Urban planning and architecture
cannot be based on the survival of the fittest; however, the natural
dynamics of the system cannot be impeded on grounds of being
“non-human".
In this paper the ethical challenges of using the dynamic models
are contemplated in light of a few examples of new architecture and
dynamic urban models and literature. It is suggested that ethical
challenges in computational design processes could be reframed
under the concepts of responsibility and transparency.
Abstract: Applicability of tuning the controller gains for Stewart manipulator using genetic algorithm as an efficient search technique is investigated. Kinematics and dynamics models were introduced in detail for simulation purpose. A PD task space control scheme was used. For demonstrating technique feasibility, a Stewart manipulator numerical-model was built. A genetic algorithm was then employed to search for optimal controller gains. The controller was tested onsite a generic circular mission. The simulation results show that the technique is highly convergent with superior performance operating for different payloads.
Abstract: Utilities use operating reserve for frequency regulation.To ensure that the operating frequency and system security are well maintained, the operating grid codes always specify that the reserve quantity and response rate should meet some prescribed levels. This paper proposes a methodology to evaluate system's contingency reserve for an isolated power network. With the presented algorithm to estimate system's frequency response characteristic, an online allocation of contingency reserve would be feasible to meet the grid codes for contingency operation. Test results from the simulated conditions, and from the actual operating data verify the merits of the proposed methodology to system's frequency control, and security.
Abstract: Multi-agent system approach has proven to be an effective and appropriate abstraction level to construct whole models of a diversity of biological problems, integrating aspects which can be found both in "micro" and "macro" approaches when modeling this type of phenomena. Taking into account these considerations, this paper presents the important computational characteristics to be gathered into a novel bioinformatics framework built upon a multiagent architecture. The version of the tool presented herein allows studying and exploring complex problems belonging principally to structural biology, such as protein folding. The bioinformatics framework is used as a virtual laboratory to explore a minimalist model of protein folding as a test case. In order to show the laboratory concept of the platform as well as its flexibility and adaptability, we studied the folding of two particular sequences, one of 45-mer and another of 64-mer, both described by an HP model (only hydrophobic and polar residues) and coarse grained 2D-square lattice. According to the discussion section of this piece of work, these two sequences were chosen as breaking points towards the platform, in order to determine the tools to be created or improved in such a way to overcome the needs of a particular computation and analysis of a given tough sequence. The backwards philosophy herein is that the continuous studying of sequences provides itself important points to be added into the platform, to any time improve its efficiency, as is demonstrated herein.
Abstract: The technical realization of data transmission using
glass fiber began after the development of diode laser in year 1962.
The erbium doped fiber amplifiers (EDFA's) in high speed networks
allow information to be transmitted over longer distances without
using of signal amplification repeaters. These kinds of fibers are
doped with erbium atoms which have energy levels in its atomic
structure for amplifying light at 1550nm. When a carried signal wave
at 1550nm enters the erbium fiber, the light stimulates the excited
erbium atoms which pumped with laser beam at 980nm as additional
light. The wavelength and intensity of the semiconductor lasers
depend on the temperature of active zone and the injection current.
The present paper shows the effect of the diode lasers temperature
and injection current on the optical amplification. From the results of
in- and output power one may calculate the max. optical gain by
erbium doped fiber amplifier.
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: This study aims to demonstrate the quantification of
peptides based on isotope dilution surface enhanced Raman
scattering (IDSERS). SERS spectra of phenylalanine (Phe), leucine
(Leu) and two peptide sequences TGQIFK (T13) and
YSFLQNPQTSLCFSESIPTPSNR (T6) as part of the 22-kDa
human growth hormone (hGH) were obtained on Ag-nanoparticle
covered substrates. On the basis of the dominant Phe and Leu
vibrational modes, precise partial least squares (PLS) prediction
models were built enabling the determination of unknown T13 and
T6 concentrations. Detection of hGH in its physiological
concentration in order to investigate the possibility of protein
quantification has been achieved.
Abstract: The necessity of updating the numerical models inputs, because of geometrical and resistive variations in rivers subject to solid transport phenomena, requires detailed control and monitoring activities. The human employment and financial resources of these activities moves the research towards the development of expeditive methodologies, able to evaluate the outflows through the measurement of more easily acquirable sizes. Recent studies highlighted the dependence of the entropic parameter on the kinematical and geometrical flow conditions. They showed a meaningful variability according to the section shape, dimension and slope. Such dependences, even if not yet well defined, could reduce the difficulties during the field activities, and also the data elaboration time. On the basis of such evidences, the relationships between the entropic parameter and the geometrical and resistive sizes, obtained through a large and detailed laboratory experience on steady free surface flows in conditions of macro and intermediate homogeneous roughness, are analyzed and discussed.
Abstract: The aim of this paper is to present a methodology in
three steps to forecast supply chain demand. In first step, various data
mining techniques are applied in order to prepare data for entering
into forecasting models. In second step, the modeling step, an
artificial neural network and support vector machine is presented
after defining Mean Absolute Percentage Error index for measuring
error. The structure of artificial neural network is selected based on
previous researchers' results and in this article the accuracy of
network is increased by using sensitivity analysis. The best forecast
for classical forecasting methods (Moving Average, Exponential
Smoothing, and Exponential Smoothing with Trend) is resulted based
on prepared data and this forecast is compared with result of support
vector machine and proposed artificial neural network. The results
show that artificial neural network can forecast more precisely in
comparison with other methods. Finally, forecasting methods'
stability is analyzed by using raw data and even the effectiveness of
clustering analysis is measured.
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: Wireless sensor networks (WSN) are currently
receiving significant attention due to their unlimited potential. These
networks are used for various applications, such as habitat
monitoring, automation, agriculture, and security. The efficient nodeenergy
utilization is one of important performance factors in wireless
sensor networks because sensor nodes operate with limited battery
power. In this paper, we proposed the MiSense hierarchical cluster
based routing algorithm (MiCRA) to extend the lifetime of sensor
networks and to maintain a balanced energy consumption of nodes.
MiCRA is an extension of the HEED algorithm with two levels of
cluster heads. The performance of the proposed protocol has been
examined and evaluated through a simulation study. The simulation
results clearly show that MiCRA has a better performance in terms of
lifetime than HEED. Indeed, MiCRA our proposed protocol can
effectively extend the network lifetime without other critical
overheads and performance degradation. It has been noted that there
is about 35% of energy saving for MiCRA during the clustering
process and 65% energy savings during the routing process compared
to the HEED algorithm.
Abstract: Synthesis gas manufacturing by steam reforming of hydrocarbons is an important industrial process. High endothermic nature of the process makes it one of the most cost and heat intensive processes. In the present work, composite effect of different inert gases on synthesis gas yield, feed gas conversion and temperature distribution along the reactor length has been studied using a heterogeneous model. Mathematical model was developed as a first stage and validated against the existing process models. With the addition of inert gases, a higher yield of synthesis gas is observed. Simultaneously the rector outlet temperature drops to as low as 810 K. It was found that Xenon gives the highest yield and conversion while Helium gives the lowest temperature. Using Xenon inert gas 20 percent reduction in outlet temperature was observed compared to traditional case.
Abstract: This paper presents two simplified models to
determine nodal voltages in power distribution networks. These
models allow estimating the impact of the installation of reactive
power compensations equipments like fixed or switched capacitor
banks. The procedure used to develop the models is similar to the
procedure used to develop linear power flow models of transmission
lines, which have been widely used in optimization problems of
operation planning and system expansion. The steady state non-linear
load flow equations are approximated by linear equations relating the
voltage amplitude and currents. The approximations of the linear
equations are based on the high relationship between line resistance
and line reactance (ratio R/X), which is valid for power distribution
networks. The performance and accuracy of the models are evaluated
through comparisons with the exact results obtained from the
solution of the load flow using two test networks: a hypothetical
network with 23 nodes and a real network with 217 nodes.
Abstract: The dynamics of User Datagram Protocol (UDP) traffic
over Ethernet between two computers are analyzed using nonlinear
dynamics which shows that there are two clear regimes in the data
flow: free flow and saturated. The two most important variables
affecting this are the packet size and packet flow rate. However,
this transition is due to a transcritical bifurcation rather than phase
transition in models such as in vehicle traffic or theorized large-scale
computer network congestion. It is hoped this model will help lay
the groundwork for further research on the dynamics of networks,
especially computer networks.
Abstract: This study applied Theory of Planned Behaviour
(TPB) to explain the knowledge sharing behaviour among academic
staff at a Public Higher Education Institution (HEI) in Malaysia. The
main objectives of this study are; to identify the components that
influence knowledge sharing behaviour and to determine the levels of
knowledge sharing behaviour among academic staff. A total of 200
respondents were participated in answering questionnaires. The
findings of this study revealed that level of perceiving and
implementing knowledge sharing behaviour among academic staff at
a Public HEI in Malaysia exist but not openly or strongly practiced.
The findings were discussed and recommendations for the future
research were also addressed.
Abstract: The increased number of automobiles in recent years
has resulted in great demand for fossil fuel. This has led to the
development of automobile by using alternative fuels which include
gaseous fuels, biofuels and vegetables oils as fuel. Energy from
biomass and more specific bio-diesel is one of the opportunities that
could cover the future demand of fossil fuel shortage. Biomass in the
form of cashew nut shell represents a new energy source and
abundant source of energy in India. The bio-fuel is derived from
cashew nut shell oil and its blend with diesel are promising
alternative fuel for diesel engine. In this work the pyrolysis Cashew
Nut Shell Liquid (CNSL)-Diesel Blends (CDB) was used to run the
Direct Injection (DI) diesel engine. The experiments were conducted
with various blends of CNSL and Diesel namely B20, B40, B60, B80
and B100. The results are compared with neat diesel operation. The
brake thermal efficiency was decreased for blends of CNSL and
Diesel except the lower blends of B20. The brake thermal efficiency
of B20 is nearly closer to that of diesel fuel. Also the emission level
of the all CNSL and Diesel blends was increased compared to neat
diesel. The higher viscosity and lower volatility of CNSL leads to
poor mixture formation and hence lower brake thermal efficiency and
higher emission levels. The higher emission level can be reduced by
adding suitable additives and oxygenates with CNSL and Diesel
blends.
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: 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 bit error rate (BER) performance for ultra-wide
band (UWB) indoor communication with impact of metallic furniture
is investigated. The impulse responses of different indoor
environments for any transmitter and receiver location are computed
by shooting and bouncing ray/image and inverse Fourier transform
techniques. By using the impulse responses of these multipath
channels, the BER performance for binary pulse amplitude
modulation (BPAM) impulse radio UWB communication system are
calculated. Numerical results have shown that the multi-path effect
by the metallic cabinets is an important factor for BER performance.
Also the outage probability for the UWB multipath environment with
metallic cabinets is more serious (about 18%) than with wooden
cabinets. Finally, it is worth noting that in these cases the present
work provides not only comparative information but also quantitative
information on the performance reduction.