Abstract: Multi-loop (De-centralized) Proportional-Integral-
Derivative (PID) controllers have been used extensively in process
industries due to their simple structure for control of multivariable
processes. The objective of this work is to design multiple-model
adaptive multi-loop PID strategy (Multiple Model Adaptive-PID)
and neural network based multi-loop PID strategy (Neural Net
Adaptive-PID) for the control of multivariable system. The first
method combines the output of multiple linear PID controllers,
each describing process dynamics at a specific level of operation.
The global output is an interpolation of the individual multi-loop
PID controller outputs weighted based on the current value of the
measured process variable. In the second method, neural network
is used to calculate the PID controller parameters based on the
scheduling variable that corresponds to major shift in the process
dynamics. The proposed control schemes are simple in structure with
less computational complexity. The effectiveness of the proposed
control schemes have been demonstrated on the CSTR process,
which exhibits dynamic non-linearity.
Abstract: Designing modern machine tools is a complex task. A
simulation tool to aid the design work, a virtual machine, has
therefore been developed in earlier work. The virtual machine
considers the interaction between the mechanics of the machine
(including structural flexibility) and the control system. This paper
exemplifies the usefulness of the virtual machine as a tool for product
development. An optimisation study is conducted aiming at
improving the existing design of a machine tool regarding weight and
manufacturing accuracy at maintained manufacturing speed. The
problem can be categorised as constrained multidisciplinary multiobjective
multivariable optimisation. Parameters of the control and
geometric quantities of the machine are used as design variables. This
results in a mix of continuous and discrete variables and an
optimisation approach using a genetic algorithm is therefore
deployed. The accuracy objective is evaluated according to
international standards. The complete systems model shows nondeterministic
behaviour. A strategy to handle this based on statistical
analysis is suggested. The weight of the main moving parts is reduced
by more than 30 per cent and the manufacturing accuracy is
improvement by more than 60 per cent compared to the original
design, with no reduction in manufacturing speed. It is also shown
that interaction effects exist between the mechanics and the control,
i.e. this improvement would most likely not been possible with a
conventional sequential design approach within the same time, cost
and general resource frame. This indicates the potential of the virtual
machine concept for contributing to improved efficiency of both
complex products and the development process for such products.
Companies incorporating such advanced simulation tools in their
product development could thus improve its own competitiveness as
well as contribute to improved resource efficiency of society at large.
Abstract: Nowadays Multilevel inverters are widely using in various applications. Modulation strategy at fundamental switching frequency like, SHEPWM is prominent technique to eliminate lower order of harmonics with less switching losses and better harmonic profile. The equations which are formed by SHE are highly nonlinear transcendental in nature, there may exist single, multiple or even no solutions for a particular MI. However, some loads such as electrical drives, it is required to operate in whole range of MI. In order to solve SHE equations for whole range of MI, intelligent techniques are well suited to solve equations so as to produce lest %THDV. Hence, this paper uses Continuous genetic algorithm for minimising harmonics. This paper also presents wavelet based analysis of harmonics. The developed algorithm is simulated and %THD from FFT analysis and Wavelet analysis are compared. MATLAB programming environment and SIMULINK models are used whenever necessary.
Abstract: Mobile banking services present a unique growth
opportunity for mobile operators in emerging markets, and have
already made good progress in bringing financial services to the
previously unbanked populations of many developing countries. The
potential is amazing, but what about the risks? In the complex
process of establishing a mobile banking business model, many kinds
of risks and factors need to be monitored and well-managed. Risk
identification is the first stage of risk management. Correct risk
identification ensures risk management effectiveness. Keeping the
risks low makes it possible to use the full potential of mobile banking
and carry out the planned business strategy. The focus should be on
adoption of consumers which is the main risk factor of mobile
banking services.
Abstract: This paper is a simple and systematic approaches to the design and analysis a pulse width modulation (PWM) based sliding mode controller for buck DC-DC Converters. Various aspects of the design, including the practical problems and the proposed solutions, are detailed. However, these control strategies can't compensate for large load current and input voltage variations. In this paper, a new control strategy by compromising both schemes advantages and avoiding their drawbacks is proposed, analyzed and simulated.
Abstract: In this paper, we present a technical and an economic
assessment of several sources of renewable energy in Saudi Arabia;
mainly solar, wind, hydro and biomass. We analyze the
environmental and climatic conditions in relation to these sources
and give an overview of some of the existing clean energy
technologies. Using standardized cost and efficiency data, we carry
out a cost benefit analysis to understand the economic factors
influencing the sustainability of energy production from renewable
sources in light of the energy cost and demand in the Saudi market.
Finally, we take a look at the Saudi petroleum industry and the
existing sources of conventional energy and assess the potential of
building a successful market for renewable energy under the
constraints imposed by the flow of subsidized cheap oil. We show
that while some renewable energy resources are well suited for
distributed or grid connected generation in the kingdom, their
viability is greatly undercut by the well developed and well
capitalized oil industry.
Abstract: This paper discusses the design characteristics management accounting systems should have to be useful for strategic planning and control and provides brief introductions to strategic variance analysis, profit-linked performance measurement models and balanced scorecard. It shows two multi-period, multiproduct models are specified, can be related to Porter's strategy framework and cost and revenue drivers, and can be used to support strategic planning, control and cost management.
Abstract: Almost all Libyan industries (both private and public) have struggled with many difficulties during the past three decades due to many problems. These problems have created a strongly negative impact on the productivity and utilization of many companies within Libya. This paper studies the current awareness and implementation levels of Just-In-Time (JIT) within the Libyan Textile private industry. A survey has been applied in this study using an intensive detailed questionnaire. Based on the analysis of the survey responses, the results show that the management body within the surveyed companies has a modest strategy towards most of the areas that are considered as being very crucial in any successful implementation of JIT. The results also show a variation within the implementation levels of the JIT elements as these varies between Low and Acceptable levels. The paper has also identified limitations within the investigated areas within this industry, and has pointed to areas where senior managers within the Libyan textile industry should take immediate actions in order to achieve effective implementation of JIT within their companies.
Abstract: Workload and resource management are two essential functions provided at the service level of the grid software infrastructure. To improve the global throughput of these software environments, workloads have to be evenly scheduled among the available resources. To realize this goal several load balancing strategies and algorithms have been proposed. Most strategies were developed in mind, assuming homogeneous set of sites linked with homogeneous and fast networks. However for computational grids we must address main new issues, namely: heterogeneity, scalability and adaptability. In this paper, we propose a layered algorithm which achieve dynamic load balancing in grid computing. Based on a tree model, our algorithm presents the following main features: (i) it is layered; (ii) it supports heterogeneity and scalability; and, (iii) it is totally independent from any physical architecture of a grid.
Abstract: The analysis of Acoustic Emission (AE) signal
generated from metal cutting processes has often approached
statistically. This is due to the stochastic nature of the emission
signal as a result of factors effecting the signal from its generation
through transmission and sensing. Different techniques are applied in
this manner, each of which is suitable for certain processes. In metal
cutting where the emission generated by the deformation process is
rather continuous, an appropriate method for analysing the AE signal
based on the root mean square (RMS) of the signal is often used and
is suitable for use with the conventional signal processing systems.
The aim of this paper is to set a strategy in tool failure detection in
turning processes via the statistic analysis of the AE generated from
the cutting zone. The strategy is based on the investigation of the
distribution moments of the AE signal at predetermined sampling.
The skews and kurtosis of these distributions are the key elements in
the detection. A normal (Gaussian) distribution has first been
suggested then this was eliminated due to insufficiency. The so
called Beta distribution was then considered, this has been used with
an assumed β density function and has given promising results with
regard to chipping and tool breakage detection.
Abstract: When choosing marketing strategies for international markets, one of the factors that should be considered is the cultural differences that exist among consumers in different countries. If the branding strategy has to be contextual and in tune with the culture, then the brand positioning variables has to interact, adapt and respond to the cultural variables in which the brand is operating. This study provides an overview of the relevance of culture in the development of an effective branding strategy in the international business environment. Hence, the main objective of this study is to provide a managerial framework for developing strategies for cross cultural brand management. The framework is useful because it incorporates the variables that are important in the competitiveness of fast food enterprises irrespective of their size. It provides practical, proactive and result oriented analysis that will help fast food firms augment their strategies in the international fast food markets. The proposed framework will enable managers understand the intricacies involved in branding in the global fast food industry and decrease the use of 'trial and error' when entering into unfamiliar markets.
Abstract: In this study, a reformer model simulation to use
refinery (Farashband refinery, Iran) waste natural gas. In the
petroleum and allied sectors where natural gas is being encountered
(in form of associated gas) without prior preparation for its positive
use, its combustion (which takes place in flares, an equipment through
which they are being disposed) has become a great problem because
of its associated environmental problems in form of gaseous emission.
The proposed model is used to product syngas from waste natural gas.
A detailed steady model described by a set of ordinary differential and
algebraic equations was developed to predict the behavior of the
overall process. The proposed steady reactor model was validated
against process data of a reformer synthesis plant recorded and a good
agreement was achieved. H2/CO ratio has important effect on Fischer-
Tropsch synthesis reactor product and we try to achieve this parameter
with best designing reformer reactor. We study different kind of
reformer reactors and then select auto thermal reforming process of
natural gas in a fixed bed reformer that adjustment H2/CO ratio with
CO2 and H2O injection. Finally a strategy was proposed for prevention
of extra natural gas to atmosphere.
Abstract: Perishable goods constitute a large portion of retailer inventory and lose value with time due to deterioration and/or obsolescence. Retailers dealing with such goods required considering the factors of short shelf life and the dependency of sales on inventory displayed in determining optimal procurement policy. Many retailers follow the practice of using two bins - primary bin sales fresh items at a list price and secondary bin sales unsold items at a discount price transferred from primary bin on attaining certain age. In this paper, mathematical models are developed for primary bin and for secondary bin that maximizes profit with decision variables of order quantities, optimal review period and optimal selling price at secondary bin. The demand rates in two bins are assumed to be deterministic and dependent on displayed inventory level, price and age but independent of each other. The validity of the model is shown by solving an example and the sensitivity analysis of the model is also reported.
Abstract: A self tuning PID control strategy using reinforcement
learning is proposed in this paper to deal with the control of wind
energy conversion systems (WECS). Actor-Critic learning is used to
tune PID parameters in an adaptive way by taking advantage of the
model-free and on-line learning properties of reinforcement learning
effectively. In order to reduce the demand of storage space and to
improve the learning efficiency, a single RBF neural network is used
to approximate the policy function of Actor and the value function of
Critic simultaneously. The inputs of RBF network are the system
error, as well as the first and the second-order differences of error.
The Actor can realize the mapping from the system state to PID
parameters, while the Critic evaluates the outputs of the Actor and
produces TD error. Based on TD error performance index and
gradient descent method, the updating rules of RBF kernel function
and network weights were given. Simulation results show that the
proposed controller is efficient for WECS and it is perfectly
adaptable and strongly robust, which is better than that of a
conventional PID controller.
Abstract: This paper presents recent work on the improvement
of the robotics vision based control strategy for underwater pipeline
tracking system. The study focuses on developing image processing
algorithms and a fuzzy inference system for the analysis of the
terrain. The main goal is to implement the supervisory fuzzy learning
control technique to reduce the errors on navigation decision due to
the pipeline occlusion problem. The system developed is capable of
interpreting underwater images containing occluded pipeline, seabed
and other unwanted noise. The algorithm proposed in previous work
does not explore the cooperation between fuzzy controllers,
knowledge and learnt data to improve the outputs for underwater
pipeline tracking. Computer simulations and prototype simulations
demonstrate the effectiveness of this approach. The system accuracy
level has also been discussed.
Abstract: Within the healthcare system, training and continued professional development although essential, can be effected by cost and logistical restraints due to the nature of healthcare provision e.g employee shift patterns, access to expertise, cost factors in releasing staff to attend training etc. The use of multimedia technology for the development of e-learning applications is also a major cost consideration for healthcare management staff, and this type of media whether optical or on line requires careful planning in order to remain inclusive of all staff with potentially varied access to multimedia computing. This paper discusses a project in which the use of DVD authoring technology has been successfully implemented to meet the needs of distance learning and user considerations, and is based on film production techniques and reduced product turnaround deadlines.
Abstract: Electronic Government is one of the special concepts
which has been performed successfully within recent decades.
Electronic government is a digital, wall-free government with a
virtual organization for presenting of online governmental services
and further cooperation in different political/social activities. In order
to have a successful implementation of electronic government
strategy and benefiting from its complete potential and benefits and
generally for establishment and applying of electronic government, it
is necessary to have different infrastructures as the basics of
electronic government with lack of which it is impossible to benefit
from mentioned services. For this purpose, in this paper we have
managed to recognize relevant obstacles for establishment of
electronic government in Iran. All required data for recognition of
obstacles were collected from statistical society of involved
specialists of Ministry of Communications & Information
Technology of Iran and Information Technology Organization of
Tehran Municipality through questionnaire. Then by considering of
five-point Likert scope and μ =3 as the index of relevant factors of
proposed model, we could specify current obstacles against
electronic government in Iran along with some guidelines and
proposal in this regard. According to the results, mentioned obstacles
for applying of electronic government in Iran are as follows:
Technical & technological problems, Legal, judicial & safety
problems, Economic problems and Humanistic Problems.
Abstract: While the form of crises may change, their essence
remains the same (such as a cycle of abundant liquidity, rapid credit
growth, and a low-inflation environment followed by an asset-price
bubble). The current market turbulence began in mid-2000s when the
US economy shifted to imbalanced both internal and external
macroeconomic positions. We see two key causes of these problems
– loose US monetary policy in early 2000s and US government
guarantees issued on the securities by government-sponsored
enterprises what was further fueled by financial innovations such as
structured credit products. We have discovered both negative and
positive lessons deriving from this crisis and divided the negative
lessons into three groups: financial products and valuation, processes
and business models, and strategic issues. Moreover, we address key
risk management lessons and exit strategies derived from the current
crisis and recommend policies that should help diminish the negative
impact of future potential crises.
Abstract: Data mining uses a variety of techniques each of which is useful for some particular task. It is important to have a deep understanding of each technique and be able to perform sophisticated analysis. In this article we describe a tool built to simulate a variation of the Kohonen network to perform unsupervised clustering and support the entire data mining process up to results visualization. A graphical representation helps the user to find out a strategy to optmize classification by adding, moving or delete a neuron in order to change the number of classes. The tool is also able to automatically suggest a strategy for number of classes optimization.The tool is used to classify macroeconomic data that report the most developed countries? import and export. It is possible to classify the countries based on their economic behaviour and use an ad hoc tool to characterize the commercial behaviour of a country in a selected class from the analysis of positive and negative features that contribute to classes formation.
Abstract: Heat-inducible gene expression vectors are useful for hyperthermia-induced cancer gene therapy, because the combination
of hyperthermia and gene therapy can considerably improve the therapeutic effects. In the present study, we developed an enhanced
heat-inducible transgene expression system in which a heat-shock
protein (HSP) promoter and tetracycline-responsive transactivator
were combined. When the transactivator plasmid containing the
tetracycline-responsive transactivator gene was co-transfected with
the reporter gene expression plasmid, a high level of heat-induced gene expression was observed compared with that using the HSP
promoter without the transactivator. In vitro evaluation of the
therapeutic effect using HeLa cells showed that heat-induced therapeutic gene expression caused cell death in a high percentage of
these cells, indicating that this strategy is promising for cancer gene therapy.