Abstract: Model Predictive Control (MPC) is an established control
technique in a wide range of process industries. The reason for
this success is its ability to handle multivariable systems and systems
having input, output or state constraints. Neverthless comparing to
PID controller, the implementation of the MPC in miniaturized
devices like Field Programmable Gate Arrays (FPGA) and microcontrollers
has historically been very small scale due to its complexity in
implementation and its computation time requirement. At the same
time, such embedded technologies have become an enabler for future
manufacturing enterprisers as well as a transformer of organizations
and markets. In this work, we take advantage of these recent advances
in this area in the deployment of one of the most studied and applied
control technique in the industrial engineering. In this paper, we
propose an efficient firmware for the implementation of constrained
MPC in the performed STM32 microcontroller using interior point
method. Indeed, performances study shows good execution speed
and low computational burden. These results encourage to develop
predictive control algorithms to be programmed in industrial standard
processes. The PID anti windup controller was also implemented in
the STM32 in order to make a performance comparison with the
MPC. The main features of the proposed constrained MPC framework
are illustrated through two examples.
Abstract: Managing the emergency situations at the Emergency
Staff requires a high co-operation between its members and their fast
decision making. For these purpose it is necessary to prepare Emergency Staff members adequately. The aim of this paper is to
describe the development of information support that focuses to
emergency staff processes and effective decisions. The information
support is based on the principles of process management, and
Process Framework for Emergency Management was used during the
development. The output is the information system that allows users
to simulate an emergency situation, including effective decision making. The system also evaluates the progress of the emergency
processes solving by quantitative and qualitative indicators. By using
the simulator, a higher quality education of specialists can be achieved. Therefore, negative impacts resulting from arising emergency situations can be directly reduced.
Abstract: Early breast cancer detection is an emerging field of
research as it can save the women infected by malignant tumors.
Microwave breast imaging is based on the electrical property contrast
between healthy and malignant tumor. This contrast can be detected
by use of microwave energy with an array of antennas that illuminate
the breast through coupling medium and by measuring the scattered
fields. In this paper, author has been presented the design and
simulation results of the bowtie antenna. This bowtie antenna is
designed for the detection of breast cancer detection.
Abstract: Basel III (or the Third Basel Accord) is a global
regulatory standard on bank capital adequacy, stress testing and
market liquidity risk agreed upon by the members of the Basel
Committee on Banking Supervision in 2010-2011, and scheduled to
be introduced from 2013 until 2018. Basel III is a comprehensive set
of reform measures. These measures aim to; (1) improve the banking
sector-s ability to absorb shocks arising from financial and economic
stress, whatever the source, (2) improve risk management and
governance, (3) strengthen banks- transparency and disclosures.
Similarly the reform target; (1) bank level or micro-prudential,
regulation, which will help raise the resilience of individual banking
institutions to periods of stress. (2) Macro-prudential regulations,
system wide risk that can build up across the banking sector as well
as the pro-cyclical implication of these risks over time. These two
approaches to supervision are complementary as greater resilience at
the individual bank level reduces the risk system wide shocks.
Macroeconomic impact of Basel III; OECD estimates that the
medium-term impact of Basel III implementation on GDP growth is
in the range -0,05 percent to -0,15 percent per year. On the other hand
economic output is mainly affected by an increase in bank lending
spreads as banks pass a rise in banking funding costs, due to higher
capital requirements, to their customers. Consequently the estimated
effects on GDP growth assume no active response from monetary
policy. Basel III impact on economic output could be offset by a
reduction (or delayed increase) in monetary policy rates by about 30
to 80 basis points. The aim of this paper is to create a framework
based on the recent regulations in order to prevent financial crises.
Thus the need to overcome the global financial crisis will contribute
to financial crises that may occur in the future periods. In the first
part of the paper, the effects of the global crisis on the banking
system examine the concept of financial regulations. In the second
part; especially in the financial regulations and Basel III are analyzed.
The last section in this paper explored the possible consequences of
the macroeconomic impacts of Basel III.
Abstract: In this paper, the two-dimensional stagger grid
interface pressure (SGIP) model has been generalized and presented
into three-dimensional form. For this purpose, various models of
surface tension force for interfacial flows have been investigated and
compared with each other. The VOF method has been used for
tracking the interface. To show the ability of the SGIP model for
three-dimensional flows in comparison with other models, pressure
contours, maximum spurious velocities, norm spurious flow
velocities and pressure jump error for motionless drop of liquid and
bubble of gas are calculated using different models. It has been
pointed out that SGIP model in comparison with the CSF, CSS and
PCIL models produces the least maximum and norm spurious
velocities. Additionally, the new model produces more accurate
results in calculating the pressure jumps across the interface for
motionless drop of liquid and bubble of gas which is generated in
surface tension force.
Abstract: India is currently the second most populous nation in
the world with over 1.2 billion people, growing annually at the rate of
1.5%. It is experiencing a surge in energy demands, expected to grow
more than three to four times in 25 years. Most of the energy
requirements are currently satisfied by the import of fossil fuels –
coal, petroleum-based products and natural gas. Biofuels can satisfy
these energy needs in an environmentally benign and cost effective
manner while reducing dependence on import of fossil fuels, thus
providing National Energy Security. Among various forms of
bioenergy, bioethanol is one of the major options for India because of
availability of feed stock crops.
This paper presents an overview on bioethanol production and
technology, steps taken by the Indian government to facilitate and
bring about optimal development and utilization of indigenous
biomass feedstocks for production of this biofuel.
Abstract: Tacit knowledge has been one of the most discussed
and contradictory concepts in the field of knowledge management
since the mid 1990s. The concept is used relatively vaguely to refer
to any type of information that is difficult to articulate, which has led
to discussions about the original meaning of the concept (adopted
from Polanyi-s philosophy) and the nature of tacit knowing. It is
proposed that the subject should be approached from the perspective
of cognitive science in order to connect tacit knowledge to
empirically studied cognitive phenomena. Some of the most
important examples of tacit knowing presented by Polanyi are
analyzed in order to trace the cognitive mechanisms of tacit knowing
and to promote better understanding of the nature of tacit knowledge.
The cognitive approach to Polanyi-s theory reveals that the
tacit/explicit typology of knowledge often presented in the
knowledge management literature is not only artificial but totally
opposite approach compared to Polanyi-s thinking.
Abstract: Rapid process of urbanism development has increased
the demand for some infrastructures such as supplying potable water,
electricity network and transportation facilities and etc. Nonefficiency
of the existing system with parallel managements of urban
traffic management has increased the gap between supply and
demand of traffic facilities. A sustainable transport system requires
some activities more important than air pollution control, traffic or
fuel consumption reduction and the studies show that there is no
unique solution for solving complicated transportation problems and
solving such a problem needs a comprehensive, dynamic and reliable
mechanism. Sustainable transport management considers the effects
of transportation development on economic efficiency, environmental
issues, resources consumption, land use and social justice and helps
reduction of environmental effects, increase of transportation system
efficiency as well as improvement of social life and aims to enhance
efficiency, goods transportation, provide services with minimum
access problems that cannot be realized without reorganization of
strategies, policies and plans.
Abstract: This paper presents the use of a newly created network
structure known as a Self-Delaying Dynamic Network (SDN) to
create a high resolution image from a set of time stepped input
frames. These SDNs are non-recurrent temporal neural networks
which can process time sampled data. SDNs can store input data
for a lifecycle and feature dynamic logic based connections between
layers. Several low resolution images and one high resolution image
of a scene were presented to the SDN during training by a Genetic
Algorithm. The SDN was trained to process the input frames in order
to recreate the high resolution image. The trained SDN was then used
to enhance a number of unseen noisy image sets. The quality of high
resolution images produced by the SDN is compared to that of high
resolution images generated using Bi-Cubic interpolation. The SDN
produced images are superior in several ways to the images produced
using Bi-Cubic interpolation.
Abstract: Money laundering has been described by many as the lifeblood of crime and is a major threat to the economic and social well-being of societies. It has been recognized that the banking system has long been the central element of money laundering. This is in part due to the complexity and confidentiality of the banking system itself. It is generally accepted that effective anti-money laundering (AML) measures adopted by banks will make it tougher for criminals to get their "dirty money" into the financial system. In fact, for law enforcement agencies, banks are considered to be an important source of valuable information for the detection of money laundering. However, from the banks- perspective, the main reason for their existence is to make as much profits as possible. Hence their cultural and commercial interests are totally distinct from that of the law enforcement authorities. Undoubtedly, AML laws create a major dilemma for banks as they produce a significant shift in the way banks interact with their customers. Furthermore, the implementation of the laws not only creates significant compliance problems for banks, but also has the potential to adversely affect the operations of banks. As such, it is legitimate to ask whether these laws are effective in preventing money launderers from using banks, or whether they simply put an unreasonable burden on banks and their customers. This paper attempts to address these issues and analyze them against the background of the Malaysian AML laws. It must be said that effective coordination between AML regulator and the banking industry is vital to minimize problems faced by the banks and thereby to ensure effective implementation of the laws in combating money laundering.
Abstract: Comparison of two approaches for the simulation of
the dynamic behaviour of a permanent magnet linear actuator is
presented. These are full coupled model, where the electromagnetic
field, electric circuit and mechanical motion problems are solved
simultaneously, and decoupled model, where first a set of static
magnetic filed analysis is carried out and then the electric circuit and
mechanical motion equations are solved employing bi-cubic spline
approximations of the field analysis results. The results show that the
proposed decoupled model is of satisfactory accuracy and gives more
flexibility when the actuator response is required to be estimated for
different external conditions, e.g. external circuit parameters or
mechanical loads.
Abstract: Multi-energy systems will enhance the system
reliability and power quality. This paper presents an integrated
approach for the design and operation of distributed energy resources
(DER) systems, based on energy hub modeling. A multi-objective
optimization model is developed by considering an integrated view of
electricity and natural gas network to analyze the optimal design and
operating condition of DER systems, by considering two conflicting
objectives, namely, minimization of total cost and the minimization
of environmental impact which is assessed in terms of CO2
emissions. The mathematical model considers energy demands of the
site, local climate data, and utility tariff structure, as well as technical
and financial characteristics of the candidate DER technologies. To
provide energy demands, energy systems including photovoltaic, and
co-generation systems, boiler, central power grid are considered. As
an illustrative example, a hotel in Iran demonstrates potential
applications of the proposed method. The results prove that
increasing the satisfaction degree of environmental objective leads to
increased total cost.
Abstract: A series of microarray experiments produces observations
of differential expression for thousands of genes across multiple
conditions.
Principal component analysis(PCA) has been widely used in
multivariate data analysis to reduce the dimensionality of the data in
order to simplify subsequent analysis and allow for summarization of
the data in a parsimonious manner. PCA, which can be implemented
via a singular value decomposition(SVD), is useful for analysis of
microarray data.
For application of PCA using SVD we use the DNA microarray
data for the small round blue cell tumors(SRBCT) of childhood
by Khan et al.(2001). To decide the number of components which
account for sufficient amount of information we draw scree plot.
Biplot, a graphic display associated with PCA, reveals important
features that exhibit relationship between variables and also the
relationship of variables with observations.
Abstract: The crystalline quality of the AlGaN/GaN high electron mobility transistor (HEMT) structure grown on a 200 mm silicon substrate has been investigated using UV-visible micro- Raman scattering and photoluminescence (PL). The visible Raman scattering probes the whole nitride stack with the Si substrate and shows the presence of a small component of residual in-plane stress in the thick GaN buffer resulting from a wafer bowing, while the UV micro-Raman indicates a tensile interfacial stress induced at the top GaN/AlGaN/AlN layers. PL shows a good crystal quality GaN channel where the yellow band intensity is very low compared to that of the near-band-edge transition. The uniformity of this sample is shown by measurements from several points across the epiwafer.
Abstract: Embedded systems need to respect stringent real
time constraints. Various hardware components included in such
systems such as cache memories exhibit variability and therefore
affect execution time. Indeed, a cache memory access from an
embedded microprocessor might result in a cache hit where the
data is available or a cache miss and the data need to be fetched
with an additional delay from an external memory. It is therefore
highly desirable to predict future memory accesses during
execution in order to appropriately prefetch data without incurring
delays. In this paper, we evaluate the potential of several artificial
neural networks for the prediction of instruction memory
addresses. Neural network have the potential to tackle the nonlinear
behavior observed in memory accesses during program
execution and their demonstrated numerous hardware
implementation emphasize this choice over traditional forecasting
techniques for their inclusion in embedded systems. However,
embedded applications execute millions of instructions and
therefore millions of addresses to be predicted. This very
challenging problem of neural network based prediction of large
time series is approached in this paper by evaluating various neural
network architectures based on the recurrent neural network
paradigm with pre-processing based on the Self Organizing Map
(SOM) classification technique.
Abstract: Requirements are critical to system validation as they guide all subsequent stages of systems development. Inadequately specified requirements generate systems that require major revisions or cause system failure entirely. Use Cases have become the main vehicle for requirements capture in many current Object Oriented (OO) development methodologies, and a means for developers to communicate with different stakeholders. In this paper we present the results of a laboratory experiment that explored whether different types of use case format are equally effective in facilitating high knowledge user-s understanding. Results showed that the provision of diagrams along with the textual use case descriptions significantly improved user comprehension of system requirements in both familiar and unfamiliar application domains. However, when comparing groups that received models of textual description accompanied with diagrams of different level of details (simple and detailed) we found no significant difference in performance.
Abstract: Echocardiography imaging is one of the most common diagnostic tests that are widely used for assessing the abnormalities of the regional heart ventricle function. The main goal of the image enhancement task in 2D-echocardiography (2DE) is to solve two major anatomical structure problems; speckle noise and low quality. Therefore, speckle noise reduction is one of the important steps that used as a pre-processing to reduce the distortion effects in 2DE image segmentation. In this paper, we present the common filters that based on some form of low-pass spatial smoothing filters such as Mean, Gaussian, and Median. The Laplacian filter was used as a high-pass sharpening filter. A comparative analysis was presented to test the effectiveness of these filters after being applied to original 2DE images of 4-chamber and 2-chamber views. Three statistical quantity measures: root mean square error (RMSE), peak signal-to-ratio (PSNR) and signal-tonoise ratio (SNR) are used to evaluate the filter performance quantitatively on the output enhanced image.
Abstract: In this note, we investigate the blind source separability of linear FIR-MIMO systems. The concept of semi-reversibility of a system is presented. It is shown that for a semi-reversible system, if the input signals belong to a binary alphabet, then the source data can be blindly separated. One sufficient condition for a system to be semi-reversible is obtained. It is also shown that the proposed criteria is weaker than that in the literature which requires that the channel matrix is irreducible/invertible or reversible.
Abstract: The purpose of this paper is to improve electromagnetic characteristics on grounding grid by applying the conductive concrete. The conductive concrete in this study is under an extra high voltage (EHV, 345kV) system located in a high-tech industrial park or science park. Instead of surrounding soil of grounding grid, the application of conductive concrete can reduce equipment damage and body damage caused by switching surges. The focus of the two cases on the EHV distribution system in a high-tech industrial park is presented to analyze four soil material styles. By comparing several soil material styles, the study results have shown that the conductive concrete can effectively reduce the negative damages caused by electromagnetic transient. The adoption of the style of grounding grid located 1.0 (m) underground and conductive concrete located from the ground surface to 1.25 (m) underground can obviously improve the electromagnetic characteristics so as to advance protective efficiency.
Abstract: Falling has been one of the major concerns and threats
to the independence of the elderly in their daily lives. With the
worldwide significant growth of the aging population, it is essential
to have a promising solution of fall detection which is able to operate
at high accuracy in real-time and supports large scale implementation
using multiple cameras. Field Programmable Gate Array (FPGA) is a
highly promising tool to be used as a hardware accelerator in many
emerging embedded vision based system. Thus, it is the main
objective of this paper to present an FPGA-based solution of visual
based fall detection to meet stringent real-time requirements with
high accuracy. The hardware architecture of visual based fall
detection which utilizes the pixel locality to reduce memory accesses
is proposed. By exploiting the parallel and pipeline architecture of
FPGA, our hardware implementation of visual based fall detection
using FGPA is able to achieve a performance of 60fps for a series of
video analytical functions at VGA resolutions (640x480). The results
of this work show that FPGA has great potentials and impacts in
enabling large scale vision system in the future healthcare industry
due to its flexibility and scalability.