Abstract: The objective of this work is to present a expertise on
flooding hazard analysis and how to reduce the risk. The analysis
concerns the disaster induced by the flood on November 10/11, 2001
in the Bab El Oued district of the city of Algiers.The study begins by
an expertise of damages in related with the urban environment and
the history of the urban growth of the site. After this phase, the work
is focalized on the identification of the existing correlations between
the development of the town and its vulnerability. The final step
consists to elaborate the interpretations on the interactions between
the urban growth, the sewerage network and the vulnerability of the
urban system.In conclusion, several recommendations are formulated
permitting the mitigation of the risk in the future. The principal
recommendations concern the new urban operations and the existing
urbanized sites.
Abstract: A method of dynamic mesh based airfoil optimization is proposed according to the drawbacks of surrogate model based airfoil optimization. Programs are designed to achieve the dynamic mesh. Boundary condition is add by integrating commercial software Pointwise, meanwhile the CFD calculation is carried out by commercial software Fluent. The data exchange and communication between the software and programs referred above have been accomplished, and the whole optimization process is performed in iSIGHT platform. A simplified airfoil optimization study case is brought out to show that aerodynamic performances of airfoil have been significantly improved, even save massive repeat operations and increase the robustness and credibility of the optimization result. The case above proclaims that dynamic mesh based airfoil optimization is an effective and high efficient method.
Abstract: Pattern recognition is the research area of Artificial Intelligence that studies the operation and design of systems that recognize patterns in the data. Important application areas are image analysis, character recognition, fingerprint classification, speech analysis, DNA sequence identification, man and machine diagnostics, person identification and industrial inspection. The interest in improving the classification systems of data analysis is independent from the context of applications. In fact, in many studies it is often the case to have to recognize and to distinguish groups of various objects, which requires the need for valid instruments capable to perform this task. The objective of this article is to show several methodologies of Artificial Intelligence for data classification applied to biomedical patterns. In particular, this work deals with the realization of a Computer-Aided Detection system (CADe) that is able to assist the radiologist in identifying types of mammary tumor lesions. As an additional biomedical application of the classification systems, we present a study conducted on blood samples which shows how these methods may help to distinguish between carriers of Thalassemia (or Mediterranean Anaemia) and healthy subjects.
Abstract: In the visual servoing systems, the data obtained by
Visionary is used for controlling robots. In this project, at first the
simulator which was proposed for simulating the performance of a
6R robot before, was examined in terms of software and test, and in
the proposed simulator, existing defects were obviated. In the first
version of simulation, the robot was directed toward the target object only in a Position-based method using two cameras in the
environment. In the new version of the software, three cameras were used simultaneously. The camera which is installed as eye-inhand on the end-effector of the robot is used for visual servoing in a
Feature-based method. The target object is recognized according to
its characteristics and the robot is directed toward the object in compliance with an algorithm similar to the function of human-s
eyes. Then, the function and accuracy of the operation of the robot are examined through Position-based visual servoing method using
two cameras installed as eye-to-hand in the environment. Finally, the obtained results are tested under ANSI-RIA R15.05-2 standard.
Abstract: The purpose of this research is to reduce the amount of incomplete coating of stainless steel washers in the electrodeposition painting process by using an experimental design technique. The surface preparation was found to be a major cause of painted surface quality. The influence of pretreating and painting process parameters, which are cleaning time, chemical concentration and shape of hanger were studied. A 23 factorial design with two replications was performed. The analysis of variance for the designed experiment showed the great influence of cleaning time and shape of hanger. From this study, optimized cleaning time was determined and a newly designed electrical conductive hanger was proved to be superior to the original one. The experimental verification results showed that the amount of incomplete coating defects decreased from 4% to 1.02% and operation cost decreased by 10.5%.
Abstract: Image processing for capsule endoscopy requires large
memory and it takes hours for diagnosis since operation time is
normally more than 8 hours. A real-time analysis algorithm of capsule
images can be clinically very useful. It can differentiate abnormal
tissue from health structure and provide with correlation information
among the images. Bleeding is our interest in this regard and we
propose a method of detecting frames with potential bleeding in
real-time. Our detection algorithm is based on statistical analysis and
the shapes of bleeding spots. We tested our algorithm with 30 cases of
capsule endoscopy in the digestive track. Results were excellent where
a sensitivity of 99% and a specificity of 97% were achieved in
detecting the image frames with bleeding spots.
Abstract: An improved topology of a voltage-fed quasi-resonant
soft switching LCrCdc series-parallel half bridge inverter with a constant-frequency for electronic ballast applications is proposed in this paper. This new topology introduces a low-cost solution to
reduce switching losses and circuit rating to achieve high-efficiency
ballast. Switching losses effect on ballast efficiency is discussed
through experimental point of view. In this discussion, an improved
topology in which accomplishes soft switching operation over a wide
power regulation range is proposed. The proposed structure uses reverse recovery diode to provide better operation for the ballast system. A symmetrical pulse wide modulation (PWM) control scheme is implemented to regulate a wide range of out-put power.
Simulation results are kindly verified with the experimental
measurements obtained by ballast-lamp laboratory prototype. Different load conditions are provided in order to clarify the
performance of the proposed converter.
Abstract: A theory for optimal filtering of infinite sets of random
signals is presented. There are several new distinctive features of the
proposed approach. First, a single optimal filter for processing any
signal from a given infinite signal set is provided. Second, the filter is
presented in the special form of a sum with p terms where each term
is represented as a combination of three operations. Each operation
is a special stage of the filtering aimed at facilitating the associated
numerical work. Third, an iterative scheme is implemented into the
filter structure to provide an improvement in the filter performance at
each step of the scheme. The final step of the scheme concerns signal
compression and decompression. This step is based on the solution of
a new rank-constrained matrix approximation problem. The solution
to the matrix problem is described in this paper. A rigorous error
analysis is given for the new filter.
Abstract: Modern manufacturing facilities are large scale,
highly complex, and operate with large number of variables under
closed loop control. Early and accurate fault detection and diagnosis
for these plants can minimise down time, increase the safety of plant
operations, and reduce manufacturing costs. Fault detection and
isolation is more complex particularly in the case of the faulty analog
control systems. Analog control systems are not equipped with
monitoring function where the process parameters are continually
visualised. In this situation, It is very difficult to find the relationship
between the fault importance and its consequences on the product
failure. We consider in this paper an approach to fault detection and
analysis of its effect on the production quality using an adaptive
centring and scaling in the pickling process in cold rolling. The fault
appeared on one of the power unit driving a rotary machine, this
machine can not track a reference speed given by another machine.
The length of metal loop is then in continuous oscillation, this affects
the product quality. Using a computerised data acquisition system,
the main machine parameters have been monitored. The fault has
been detected and isolated on basis of analysis of monitored data.
Normal and faulty situation have been obtained by an artificial neural
network (ANN) model which is implemented to simulate the normal
and faulty status of rotary machine. Correlation between the product
quality defined by an index and the residual is used to quality
classification.
Abstract: This paper deals with a novel approach of power
transformers diagnostics. This approach identifies the exact location
and the range of a fault in the transformer and helps to reduce
operation costs related to handling of the faulty transformer, its
disassembly and repair. The advantage of the approach is a
possibility to simulate healthy transformer and also all faults, which
can occur in transformer during its operation without its
disassembling, which is very expensive in practice. The approach is
based on creating frequency dependent impedance of the transformer
by sweep frequency response analysis measurements and by 3D FE
parametrical modeling of the fault in the transformer. The parameters
of the 3D FE model are the position and the range of the axial short
circuit. Then, by comparing the frequency dependent impedances of
the parametrical models with the measured ones, the location and the
range of the fault is identified. The approach was tested on a real
transformer and showed high coincidence between the real fault and
the simulated one.
Abstract: Most, if not all, public hospitals in Thailand have encountered a common problem regarding the increasing demand for medical services. The increasing number of patients causes so much strain on the hospital-s services, over-crowded, overloaded working hours, staff fatigue, medical error and long waiting time. This research studied the characteristics of operational processes of the medical care services at the medicine department in a large public university hospital. The research focuses on details regarding methods, procedures, processes, resources, and time management in overall processes. The simulation model is used as a tool to analyze the impact of various improvement strategies.
Abstract: Cybercrime is now becoming a big challenge in Nigeria apart from the traditional crime. Inability to identify perpetrators is one of the reasons for the growing menace. This paper proposes a design for monitoring internet users’ activities in order to curbing cybercrime. It requires redefining the operations of Internet Service Providers (ISPs) which will now mandate users to be authenticated before accessing the internet. In implementing this work which can be adapted to a larger scale, a virtual router application is developed and configured to mimic a real router device. A sign-up portal is developed to allow users to register with the ISP. The portal asks for identification information which will include bio-data and government issued identification data like National Identity Card number, et cetera. A unique username and password are chosen by the user to enable access to the internet which will be used to reference him to an Internet Protocol Address (IP Address) of any system he uses on the internet and thereby associating him to any criminal act related to that IP address at that particular time. Questions such as “What happen when another user knows the password and uses it to commit crime?” and other pertinent issues are addressed.
Abstract: Electron multiplying charge coupled devices (EMCCDs) have revolutionized the world of low light imaging by introducing on-chip multiplication gain based on the impact ionization effect in the silicon. They combine the sub-electron readout noise with high frame rates. Signal-to-noise Ratio (SNR) is an important performance parameter for low-light-level imaging systems. This work investigates the SNR performance of an EMCCD operated in Non-inverted Mode (NIMO) and Inverted Mode (IMO). The theory of noise characteristics and operation modes is presented. The results show that the SNR of is determined by dark current and clock induced charge at high gain level. The optimum SNR performance is provided by an EMCCD operated in NIMO in short exposure and strong cooling applications. In contrast, an IMO EMCCD is preferable.
Abstract: Morgan-s refinement calculus (MRC) is one of the
well-known methods allowing the formality presented in the program
specification to be continued all the way to code. On the other hand,
Object-Z (OZ) is an extension of Z adding support for classes and
objects. There are a number of methods for obtaining code from OZ
specifications that can be categorized into refinement and animation
methods. As far as we know, only one refinement method exists
which refines OZ specifications into code. However, this method
does not have fine-grained refinement rules and thus cannot be
automated. On the other hand, existing animation methods do not
present mapping rules formally and do not support the mapping of
several important constructs of OZ, such as all cases of operation
expressions and most of constructs in global paragraph. In this paper,
with the aim of providing an automatic path from OZ specifications
to code, we propose an approach to map OZ specifications into their
counterparts in MRC in order to use fine-grained refinement rules of
MRC. In this way, having counterparts of our specifications in MRC,
we can refine them into code automatically using MRC tools such as
RED. Other advantages of our work pertain to proposing mapping
rules formally, supporting the mapping of all important constructs of
Object-Z, and considering dynamic instantiation of objects while OZ
itself does not cover this facility.
Abstract: A color image edge detection algorithm is proposed in
this paper using Pseudo-complement and matrix rotation operations.
First, pseudo-complement method is applied on the image for each
channel. Then, matrix operations are applied on the output image of
the first stage. Dominant pixels are obtained by image differencing
between the pseudo-complement image and the matrix operated
image. Median filtering is carried out to smoothen the image thereby
removing the isolated pixels. Finally, the dominant or core pixels
occurring in at least two channels are selected. On plotting the
selected edge pixels, the final edge map of the given color image is
obtained. The algorithm is also tested in HSV and YCbCr color
spaces. Experimental results on both synthetic and real world images
show that the accuracy of the proposed method is comparable to
other color edge detectors. All the proposed procedures can be
applied to any image domain and runs in polynomial time.
Abstract: The paper provides a literature review of the STEPNC
compliant research around the world. The first part of this paper
focuses on projects based on STEP compliance followed by research
and development in this area based on machining operations. Review
the literature relating to relevant STEP standards and application in
the area of turning centers. This research will review the various
research work, carried out from the evolution of STEP-NC of the
CNC manufacturing activities. The paper concludes with discussion
of the applications in this particular area.
Abstract: This paper presents an approach for daily optimal operation of distribution networks considering Distributed Generators (DGs). Due to private ownership of DGs, a cost based compensation method is used to encourage DGs in active and reactive power generation. The objective function is summation of electrical energy generated by DGs and substation bus (main bus) in the next day. A genetic algorithm is used to solve the optimal operation problem. The approach is tested on an IEEE34 buses distribution feeder.
Abstract: In this paper, low end Digital Signal Processors (DSPs)
are applied to accelerate integer neural networks. The use of DSPs
to accelerate neural networks has been a topic of study for some
time, and has demonstrated significant performance improvements.
Recently, work has been done on integer only neural networks, which
greatly reduces hardware requirements, and thus allows for cheaper
hardware implementation. DSPs with Arithmetic Logic Units (ALUs)
that support floating or fixed point arithmetic are generally more
expensive than their integer only counterparts due to increased circuit
complexity. However if the need for floating or fixed point math
operation can be removed, then simpler, lower cost DSPs can be
used. To achieve this, an integer only neural network is created in
this paper, which is then accelerated by using DSP instructions to
improve performance.
Abstract: The goal of this research is discovering the
determinants of the success or failure of external cooperation in small
and medium enterprises (SMEs). For this, a survey was given to 190
SMEs that experienced external cooperation within the last 3 years. A
logistic regression model was used to derive organizational or strategic
characteristics that significantly influence whether external
collaboration of domestic SMEs is successful or not. Results suggest
that research and development (R&D) features in general
characteristics (both idea creation and discovering market
opportunities) that focused on and emphasized indirected-market
stakeholders (such as complementary companies and affiliates) and
strategies in innovative strategic characteristics raise the probability of
successful external cooperation. This can be used meaningfully to
build a policy or strategy for inducing successful external cooperation
or to understand the innovation of SMEs.
Abstract: An economic operation scheduling problem of a
hydro-thermal power generation system has been properly solved by
the proposed multipath adaptive tabu search algorithm (MATS). Four
reservoirs with their own hydro plants and another one thermal plant
are integrated to be a studied system used to formulate the objective
function under complicated constraints, eg water managements,
power balance and thermal generator limits. MATS with four subsearch
units (ATSs) and two stages of discarding mechanism (DM),
has been setting and trying to solve the problem through 25 trials
under function evaluation criterion. It is shown that MATS can
provide superior results with respect to single ATS and other
previous methods, genetic algorithms (GA) and differential evolution
(DE).