Abstract: This study presents an active vibration control
technique to reduce the earthquake responses of a retained structural
system. The proposed technique is a synthesis of the adaptive input
estimation method (AIEM) and linear quadratic Gaussian (LQG)
controller. The AIEM can estimate an unknown system input online.
The LQG controller offers optimal control forces to suppress
wall-structural system vibration. The numerical results show robust
performance in the active vibration control technique.
Abstract: Due to heightened concerns over environmental and economic issues the growing important of air pollution, and the importance of conserving fossil fuel resources in the world, the automotive industry is now forced to produce more fuel efficient, low emission vehicles and new drive system technologies. One of the most promising technologies to receive attention is the hybrid electric vehicle (HEV), which consists of two or more energy sources that supply energy to electric traction motors that in turn drive the wheels. This paper presents the various structures of HEV systems, the basic theoretical knowledge for describing their operation and the general behaviour of the HEV in acceleration, cruise and deceleration phases. The conventional design and sizing of a series HEV is studied. A conventional bus and its series configuration are defined and evaluated using the ADVISOR. In this section the simulation of a standard driving cycle and prediction of its fuel consumption and emissions of the HEV are discussed. Finally the bus performance is investigated to establish whether it can satisfy the performance, fuel consumption and emissions requested. The validity of the simulation has been established by the close conformity between the fuel consumption of the conventional bus reported by the manufacturer to what has achieved from the simulation.
Abstract: Documents retrieval in Information Retrieval
Systems (IRS) is generally about understanding of
information in the documents concern. The more the system
able to understand the contents of documents the more
effective will be the retrieval outcomes. But understanding of the
contents is a very complex task. Conventional IRS apply algorithms
that can only approximate the meaning of document contents through
keywords approach using vector space model. Keywords may be
unstemmed or stemmed. When keywords are stemmed and conflated
in retrieving process, we are a step forwards in applying semantic
technology in IRS. Word stemming is a process in morphological
analysis under natural language processing, before syntactic and
semantic analysis. We have developed algorithms for Malay and
Arabic and incorporated stemming in our experimental systems in
order to measure retrieval effectiveness. The results have shown that
the retrieval effectiveness has increased when stemming is used in
the systems.
Abstract: Many real-world optimization problems involve multiple conflicting objectives and the use of evolutionary algorithms to solve the problems has attracted much attention recently. This paper investigates the application of multi-objective optimization technique for the design of a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the performance of a power system. The design objective is to improve both rotor angle stability and system voltage profile. A Genetic Algorithm (GA) based solution technique is applied to generate a Pareto set of global optimal solutions to the given multi-objective optimisation problem. Further, a fuzzy-based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto solution set. Simulation results are presented to show the effectiveness and robustness of the proposed approach.
Abstract: This paper presents and evaluates a new classification
method that aims to improve classifiers performances and speed up
their training process. The proposed approach, called labeled
classification, seeks to improve convergence of the BP (Back
propagation) algorithm through the addition of an extra feature
(labels) to all training examples. To classify every new example, tests
will be carried out each label. The simplicity of implementation is the
main advantage of this approach because no modifications are
required in the training algorithms. Therefore, it can be used with
others techniques of acceleration and stabilization. In this work, two
models of the labeled classification are proposed: the LMLP
(Labeled Multi Layered Perceptron) and the LNFC (Labeled Neuro
Fuzzy Classifier). These models are tested using Iris, wine, texture
and human thigh databases to evaluate their performances.
Abstract: Although automotive industry has brought different beneficiaries to human life, it is being pointed out as one of the major cause of global air pollution which resulted in climate change, smog, green house gases (GHGs), and human diseases by many reasons. Since auto industry is one of the largest consumers of fossil fuels, the realization of green innovations is becoming a crucial choice to meet the challenges towards sustainable development. Recently, many auto manufacturers have embarked on green technology initiatives to gain a competitive advantage in the global market; however, innovative manufacturing systems and technologies can enhance operational performance only if the human resource management is in place to elicit the motivation of the employees and develop their organizational expertise. No organization can perform at peak levels unless each employee is committed to the company goals and works as an effective team member. Strategic human resource practices are the primary means by which firms can shape the skills, attitudes, and behavior of individuals to align with the business strategic objectives. This study investigates on the comprehensive approach of multiple advanced technology innovations and human resource management at Toyota Motor Corporation as the market leader of full hybrid technology in the automotive industry. Then, HRM framework of the company is described and three sets of human resource practices that support the innovation-oriented HR system, presented. Finally, a conceptual framework for innovativeness in green technology in automotive industry by applying a deliberate strategic HR management system and knowledge management with the intervening factors of organizational culture, knowledge application and knowledge sharing is proposed.
Abstract: A two dimensional numerical simulation has been
performed for incompressible and compressible fluid flow through
microchannels in slip flow regime. The Navier-Stokes equations have
been solved in conjunction with Maxwell slip conditions for
modeling flow field associated with slip flow regime. The wall
roughness is simulated with triangular microelements distributed on
wall surfaces to study the effects of roughness on fluid flow. Various
Mach and Knudsen numbers are used to investigate the effects of
rarefaction as well as compressibility. It is found that rarefaction has
more significant effect on flow field in microchannels with higher
relative roughness. It is also found that compressibility has more
significant effects on Poiseuille number when relative roughness
increases. In addition, similar to incompressible models the increase
in average fRe is more significant at low Knudsen number flows but
the increase of Poiseuille number duo to relative roughness is sharper
for compressible models. The numerical results have also validated
with some available theoretical and experimental relations and good
agreements have been seen.
Abstract: Multicarrier transmission system such as Orthogonal
Frequency Division Multiplexing (OFDM) is a promising technique
for high bit rate transmission in wireless communication system.
OFDM is a spectrally efficient modulation technique that can achieve
high speed data transmission over multipath fading channels without
the need for powerful equalization techniques. However the price
paid for this high spectral efficiency and less intensive equalization
is low power efficiency. OFDM signals are very sensitive to nonlinear
effects due to the high Peak-to-Average Power Ratio (PAPR),
which leads to the power inefficiency in the RF section of the
transmitter. This paper investigates the effect of PAPR reduction on
the performance parameter of multicarrier communication system.
Performance parameters considered are power consumption of Power
Amplifier (PA) and Digital-to-Analog Converter (DAC), power amplifier
efficiency, SNR of DAC and BER performance of the system.
From our analysis it is found that irrespective of PAPR reduction
technique being employed, the power consumption of PA and DAC
reduces and power amplifier efficiency increases due to reduction in
PAPR. Moreover, it has been shown that for a given BER performance
the requirement of Input-Backoff (IBO) reduces with reduction in
PAPR.
Abstract: In this paper, the construction of a detailed spine
model is presented using the LifeMOD Biomechanics Modeler. The
detailed spine model is obtained by refining spine segments in
cervical, thoracic and lumbar regions into individual vertebra
segments, using bushing elements representing the intervertebral
discs, and building various ligamentous soft tissues between
vertebrae. In the sagittal plane of the spine, constant force will be
applied from the posterior to anterior during simulation to determine
dynamic characteristics of the spine. The force magnitude is
gradually increased in subsequent simulations. Based on these
recorded dynamic properties, graphs of displacement-force
relationships will be established in terms of polynomial functions by
using the least-squares method and imported into a haptic integrated
graphic environment. A thoracolumbar spine model with complex
geometry of vertebrae, which is digitized from a resin spine
prototype, will be utilized in this environment. By using the haptic
technique, surgeons can touch as well as apply forces to the spine
model through haptic devices to observe the locomotion of the spine
which is computed from the displacement-force relationship graphs.
This current study provides a preliminary picture of our ongoing
work towards building and simulating bio-fidelity scoliotic spine
models in a haptic integrated graphic environment whose dynamic
properties are obtained from LifeMOD. These models can be helpful
for surgeons to examine kinematic behaviors of scoliotic spines and
to propose possible surgical plans before spine correction operations.
Abstract: This paper presents a procedure of forming the
mathematical model of radial electric power systems for simulation
of both transient and steady-state conditions. The research idea has
been based on nodal voltages technique and on differentiation of
Kirchhoff's current law (KCL) applied to each non-reference node of
the radial system, the result of which the nodal voltages has been
calculated by solving a system of algebraic equations. Currents of the
electric power system components have been determined by solving
their respective differential equations. Transforming the three-phase
coordinate system into Cartesian coordinate system in the model
decreased the overall number of equations by one third. The use of
Cartesian coordinate system does not ignore the DC component
during transient conditions, but restricts the model's implementation
for symmetrical modes of operation only. An example of the input
data for a four-bus radial electric power system has been calculated.
Abstract: Maximal Ratio Combining (MRC) is considered the most complex combining technique as it requires channel coefficients estimation. It results in the lowest bit error rate (BER) compared to all other combining techniques. However the BER starts to deteriorate as errors are introduced in the channel coefficients estimation. A novel combining technique, termed Generalized Maximal Ratio Combining (GMRC) with a polynomial kernel, yields an identical BER as MRC with perfect channel estimation and a lower BER in the presence of channel estimation errors. We show that GMRC outperforms the optimal MRC scheme in general and we hereinafter introduce it to the scientific community as a new “supraoptimal" algorithm. Since diversity combining is especially effective in small femto- and pico-cells, internet-associated wireless peripheral systems are to benefit most from GMRC. As a result, many spinoff applications can be made to IP-based 4th generation networks.
Abstract: this paper aims to provide an approach to predict the
performance of the product produced after multi-stages of
manufacturing processes, as well as the assembly. Such approach
aims to control and subsequently identify the relationship between
the process inputs and outputs so that a process engineer can more
accurately predict how the process output shall perform based on the
system inputs. The approach is guided by a six-sigma methodology to
obtain improved performance.
In this paper a case study of the manufacture of a hermetic
reciprocating compressor is presented. The application of artificial
neural networks (ANNs) technique is introduced to improve
performance prediction within this manufacturing environment. The
results demonstrate that the approach predicts accurately and
effectively.
Abstract: The study of proteomics reached unexpected levels of
interest, as a direct consequence of its discovered influence over some
complex biological phenomena, such as problematic diseases like
cancer. This paper presents the latest authors- achievements regarding
the analysis of the networks of proteins (interactome networks), by
computing more efficiently the betweenness centrality measure. The
paper introduces the concept of betweenness centrality, and then
describes how betweenness computation can help the interactome net-
work analysis. Current sequential implementations for the between-
ness computation do not perform satisfactory in terms of execution
times. The paper-s main contribution is centered towards introducing
a speedup technique for the betweenness computation, based on
modified shortest path algorithms for sparse graphs. Three optimized
generic algorithms for betweenness computation are described and
implemented, and their performance tested against real biological
data, which is part of the IntAct dataset.
Abstract: In this study, effects of EGR on CO and HC emissions
of a dual fuel HCCI-DI engine are investigated. Tests were
conducted on a single-cylinder variable compression ratio (VCR)
diesel engine with compression ratio of 17.5. Premixed gasoline is
provided by a carburetor connected to intake manifold and equipped
with a screw to adjust premixed air-fuel ratio, and diesel fuel is
injected directly into the cylinder through an injector at pressure of
250 bars. A heater placed at inlet manifold is used to control the
intake charge temperature. Optimal intake charge temperature was
110-115ºC due to better formation of a homogeneous mixture
causing HCCI combustion. Timing of diesel fuel injection has a great
effect on stratification of in-cylinder charge in HCCI combustion.
Experiments indicated 35 BTDC as the optimum injection timing.
Coolant temperature was maintained 50ºC during the tests. Results
show that increasing engine speed at a constant EGR rate leads to
increase in CO and UHC emissions due to the incomplete
combustion caused by shorter combustion duration and less
homogeneous mixture. Results also show that increasing EGR
reduces the amount of oxygen and leads to incomplete combustion
and therefore increases CO emission due to lower combustion
temperature. HC emission also increases as a result of lower
combustion temperatures.
Abstract: Universities have an important role in social education in many aspects. In terms of creating awareness and convincing public about social issues, universities take a leading position for public. The best way to provide public support for social education is to develop public communication campaigns. The aim of this study is to present a public communication model which will be guided in social education practices. The study titled “Importance of public communication campaigns and art activities in Social Education “is based on the following topics: Effects of public communication campaigns on social education, Public relations techniques for education, communication strategies, Steps of public relations campaigns in social education, making persuasive messages for public communication campaigns, developing artistic messages and organizing art activities in social education. In addition to these topics, media planning for social education, forming a team as campaign managers, dialogues with opinion leaders in education and preparing creative communication models for social education will be taken into consideration. This study also aims to criticize social education Case studies in Turkey. At the same time, some communicative methods and principles will be given in the light of communication campaigns within the context of this notice.
Abstract: In metal cutting industries, mathematical/statistical
models are typically used to predict tool replacement time. These
off-line methods usually result in less than optimum replacement
time thereby either wasting resources or causing quality problems.
The few online real-time methods proposed use indirect measurement
techniques and are prone to similar errors. Our idea is based on
identifying the optimal replacement time using an electronic nose to
detect the airborne compounds released when the tool wear reaches
to a chemical substrate doped into tool material during the
fabrication. The study investigates the feasibility of the idea, possible
doping materials and methods along with data stream mining
techniques for detection and monitoring different phases of tool
wear.
Abstract: This paper describes part of a project about Learningby-
Modeling (LbM). Studying complex systems is increasingly
important in teaching and learning many science domains. Many
features of complex systems make it difficult for students to develop
deep understanding. Previous research indicates that involvement
with modeling scientific phenomena and complex systems can play a
powerful role in science learning. Some researchers argue with this
view indicating that models and modeling do not contribute to
understanding complexity concepts, since these increases the
cognitive load on students. This study will investigate the effect of
different modes of involvement in exploring scientific phenomena
using computer simulation tools, on students- mental model from the
perspective of structure, behavior and function. Quantitative and
qualitative methods are used to report about 121 freshmen students
that engaged in participatory simulations about complex phenomena,
showing emergent, self-organized and decentralized patterns. Results
show that LbM plays a major role in students' concept formation
about complexity concepts.
Abstract: The primary objective of this paper was to construct a
“kinematic parameter-independent modeling of three-axis machine
tools for geometric error measurement" technique. Improving the
accuracy of the geometric error for three-axis machine tools is one of
the machine tools- core techniques. This paper first applied the
traditional method of HTM to deduce the geometric error model for
three-axis machine tools. This geometric error model was related to the
three-axis kinematic parameters where the overall errors was relative
to the machine reference coordinate system. Given that the
measurement of the linear axis in this model should be on the ideal
motion axis, there were practical difficulties. Through a measurement
method consolidating translational errors and rotational errors in the
geometric error model, we simplified the three-axis geometric error
model to a kinematic parameter-independent model. Finally, based on
the new measurement method corresponding to this error model, we
established a truly practical and more accurate error measuring
technique for three-axis machine tools.
Abstract: Shadows add great amount of realism to a scene and
many algorithms exists to generate shadows. Recently, Shadow
volumes (SVs) have made great achievements to place a valuable
position in the gaming industries. Looking at this, we concentrate on
simple but valuable initial partial steps for further optimization in SV
generation, i.e.; model simplification and silhouette edge detection
and tracking. Shadow volumes (SVs) usually takes time in generating
boundary silhouettes of the object and if the object is complex then
the generation of edges become much harder and slower in process.
The challenge gets stiffer when real time shadow generation and
rendering is demanded. We investigated a way to use the real time
silhouette edge detection method, which takes the advantage of
spatial and temporal coherence, and exploit the level-of-details
(LOD) technique for reducing silhouette edges of the model to use
the simplified version of the model for shadow generation speeding
up the running time. These steps highly reduce the execution time of
shadow volume generations in real-time and are easily flexible to any
of the recently proposed SV techniques. Our main focus is to exploit
the LOD and silhouette edge detection technique, adopting them to
further enhance the shadow volume generations for real time
rendering.
Abstract: The main goal of the study is to analyze all relevant properties of the electro hydraulic systems and based on that to make a proper choice of the neural network control strategy that may be used for the control of the mechatronic system. A combination of electronic and hydraulic systems is widely used since it combines the advantages of both. Hydraulic systems are widely spread because of their properties as accuracy, flexibility, high horsepower-to-weight ratio, fast starting, stopping and reversal with smoothness and precision, and simplicity of operations. On the other hand, the modern control of hydraulic systems is based on control of the circuit fed to the inductive solenoid that controls the position of the hydraulic valve. Since this circuit may be easily handled by PWM (Pulse Width Modulation) signal with a proper frequency, the combination of electrical and hydraulic systems became very fruitful and usable in specific areas as airplane and military industry. The study shows and discusses the experimental results obtained by the control strategy of neural network control using MATLAB and SIMULINK [1]. Finally, the special attention was paid to the possibility of neuro-controller design and its application to control of electro-hydraulic systems and to make comparative with other kinds of control.