Abstract: In this paper two different Antilock braking system (ABS) are simulated and compared. One is the ordinary hydraulic ABS system which we call it ABS and the other is Electromagnetic Antilock braking system which is called (EMABS) the basis of performance of an EMABS is based upon Electromagnetic force. In this system there is no need to use servo hydraulic booster which are used in ABS system. In EMABS to generate the desired force we have use a magnetic relay which works with an input voltage through an air gap (g). The generated force will be amplified by the relay arm, and is applied to the brake shoes and thus the braking torque is generated. The braking torque is proportional to the applied electrical voltage E. to adjust the braking torque it is only necessary to regulate the electrical voltage E which is very faster and has a much smaller time constant T than the ABS system. The simulations of these two different ABS systems are done with MATLAB/SIMULINK software and the superiority of the EMABS has been shown.
Abstract: In this study we present the effect of elevated
temperatures from 300K to 400K on the electrical properties of
copper Phthalocyanine (CuPc) based organic field effect transistors
(OFET). Thin films of organic semiconductor CuPc (40nm) and
semitransparent Al (20nm) were deposited in sequence, by vacuum
evaporation on a glass substrate with previously deposited Ag source
and drain electrodes with a gap of 40 μm. Under resistive mode of
operation, where gate was suspended it was observed that drain
current of this organic field effect transistor (OFET) show an
increase with temperature. While in grounded gate condition metal
(aluminum) – semiconductor (Copper Phthalocyanine) Schottky
junction dominated the output characteristics and device showed
switching effect from low to high conduction states like Zener diode
at higher bias voltages. This threshold voltage for switching effect
has been found to be inversely proportional to temperature and shows
an abrupt decrease after knee temperature of 360K. Change in
dynamic resistance (Rd = dV/dI) with respect to temperature was
observed to be -1%/K.
Abstract: The paper presents an on-line recognition machine
(RM) for continuous/isolated, dynamic and static gestures that arise
in Flight Deck Officer (FDO) training. RM is based on generic pattern
recognition framework. Gestures are represented as templates using
summary statistics. The proposed recognition algorithm exploits temporal
and spatial characteristics of gestures via dynamic programming
and Markovian process. The algorithm predicts corresponding index
of incremental input data in the templates in an on-line mode.
Accumulated consistency in the sequence of prediction provides a
similarity measurement (Score) between input data and the templates.
The algorithm provides an intuitive mechanism for automatic detection
of start/end frames of continuous gestures. In the present paper,
we consider isolated gestures. The performance of RM is evaluated
using four datasets - artificial (W TTest), hand motion (Yang) and
FDO (tracker, vision-based ). RM achieves comparable results which
are in agreement with other on-line and off-line algorithms such as
hidden Markov model (HMM) and dynamic time warping (DTW).
The proposed algorithm has the additional advantage of providing
timely feedback for training purposes.
Abstract: The presence of a vertical edge-crack within a web
plate subjected to pure bending induces local compressive stresses
about the crack which may cause tension buckling. Approximate
theoretical expressions were derived for the critical far-field tensile
stress and bending moment capacity of an edge-cracked web plate
associated with tension buckling. These expressions were validated
with finite element analyses and used to investigate the possibility of
tension buckling in web-cracked trial girders. It was found that
tension buckling is an unlikely occurrence unless the web is relatively
thin or the crack is very long.
Abstract: A novel application of neural network approach to
fault classification and fault location of Medium voltage cables is
demonstrated in this paper. Different faults on a protected cable
should be classified and located correctly. This paper presents the use
of neural networks as a pattern classifier algorithm to perform these
tasks. The proposed scheme is insensitive to variation of different
parameters such as fault type, fault resistance, and fault inception
angle. Studies show that the proposed technique is able to offer high
accuracy in both of the fault classification and fault location tasks.
Abstract: The radius-of-curvature (ROC) defines the degree of
curvature along the centerline of a roadway whereby a travelling
vehicle must follow. Roadway designs must encompass ROC in
mitigating the cost of earthwork associated with construction while
also allowing vehicles to travel at maximum allowable design speeds.
Thus, a road will tend to follow natural topography where possible,
but curvature must also be optimized to permit fast, but safe vehicle
speeds. The more severe the curvature of the road, the slower the
permissible vehicle speed. For route planning, whether for urban
settings, emergency operations, or even parcel delivery, ROC is a
necessary attribute of road arcs for computing travel time.
It is extremely rare for a geo-spatial database to contain ROC. This
paper will present a procedure and mathematical algorithm to
calculate and assign ROC to a segment pair and/or polyline.
Abstract: In this paper, an magnetorheological (MR) mount with
fuzzy sliding mode controller (FSMC) is studied for vibration
suppression when the system is subject to base excitations. In recent
years, magnetorheological fluids are becoming a popular material in
the field of the semi-active control. However, the dynamic equation of
an MR mount is highly nonlinear and it is difficult to identify. FSMC
provides a simple method to achieve vibration attenuation of the
nonlinear system with uncertain disturbances. This method is capable
of handling the chattering problem of sliding mode control effectively
and the fuzzy control rules are obtained by using the Lyapunov
stability theory. The numerical simulations using one-dimension and
two-dimension FSMC show effectiveness of the proposed controller
for vibration suppression. Further, the well-known skyhook control
scheme and an adaptive sliding mode controller are also included in
the simulation for comparison with the proposed FSMC.
Abstract: The Beshar River is one of the most important aquatic ecosystems in the upstream of the Karun watershed in south of Iran which is affected by point and non point pollutant sources . This study was done in order to evaluate the effects of pollutants activities on the water quality of the Beshar river and its aquatic ecosystems. This river is approximately 190 km in length and situated at the geographical positions of 51° 20´ to 51° 48´ E and 30° 18´ to 30° 52´ N it is one of the most important aquatic ecosystems of Kohkiloye and Boyerahmad province in south-west Iran. In this research project, five study stations were selected to examine water pollution in the Beshar River systems. Human activity is now one of the most important factors affecting on hydrology and water quality of the Beshar river. Humans use large amounts of resources to sustain various standards of living, although measures of sustainability are highly variable depending on how sustainability is defined. The Beshar river ecosystems are particularly sensitive and vulnerable to human activities. Therefore, to determine the impact of human activities on the Beshar River, the most important water quality parameters such as pH, dissolve oxygen (DO), Biological Oxygen Demand (BOD5), Total Dissolve Solids (TDS), Nitrates (NO3-N) and Phosphates (PO4) were estimated at the five stations. As the results show, the most important pollution index parameters such as BOD5, NO3 and PO4 increase and DO and pH decrease according to human activities (P
Abstract: Prediction of sinusoidal signals with time-varying
frequencies has been an important research topic in power electronics
systems. To solve this problem, we propose a new fuzzy
predictive filtering scheme, which is based on a Finite Impulse
Response (FIR) filter bank. Fuzzy logic is introduced here to provide
appropriate interpolation of individual filter outputs. Therefore,
instead of regular 'hard' switching, our method has the advantageous
'soft' switching among different filters. Simulation
comparisons between the fuzzy predictive filtering and conventional
filter bank-based approach are made to demonstrate that the
new scheme can achieve an enhanced prediction performance for
slowly changing sinusoidal input signals.
Abstract: Studies in economics domain tried to reveal the correlation between stock markets. Since the globalization era, interdependence between stock markets becomes more obvious. The Dynamic Interaction Network (DIN) algorithm, which was inspired by a Gene Regulatory Network (GRN) extraction method in the bioinformatics field, is applied to reveal important and complex dynamic relationship between stock markets. We use the data of the stock market indices from eight countries around the world in this study. Our results conclude that DIN is able to reveal and model patterns of dynamic interaction from the observed variables (i.e. stock market indices). Furthermore, it is also found that the extracted network models can be utilized to predict movement of the stock market indices with a considerably good accuracy.
Abstract: This research was undertaken to study enzymatic activity in the shoots, roots, and rhizosphere of alfalfa (Medicago sativa L.) grown in quartz sand that was uncontaminated and
contaminated with phenanthrene at concentrations of 10 and 100 mg kg-1. The higher concentration of phehanthrene had a distinct
phytotoxic effect on alfalfa, inhibiting seed germination energy, plant survival, and biomass accumulation. The plant stress response to the
environmental pollution was an increase in peroxidase activity. Peroxidases were the predominant enzymes in the alfalfa shoots and
roots. The peroxidase profile in the shoots differed from that in the roots and had different isoenzyme numbers. 2,2'-Azinobis-(3-ethylbenzo-thiazoline-6-sulphonate) (ABTS) peroxidase was
predominant in the shoots, and 2,7-diaminofluorene (2,2-DAF)
peroxidase was predominant in the roots. Under the influence of
phenanthrene, the activity of 2,7-DAF peroxidase increased in the
shoots, and the activity of ABTS peroxidase increased in the roots.
Alfalfa root peroxidases were the prevalent enzyme systems in the
rhizosphere sand. Examination of the activity of alfalfa root
peroxidase toward phenanthrene revealed the possibility of
involvement of the plant enzyme in rhizosphere degradation of the
PAH.
Abstract: The research was designed to examine the relationship
between the development of muscle fatigue and the effect it has on
sport performance, specifically during maximal voluntary
contraction. This kind of this investigation using simultaneous
electrophysiological and mechanical recordings, based on advanced
mathematical processing, allows us to get parameters, and indexes in
a short time, and finally, the mapping to use for the thorough
investigation of the muscle contraction force, respectively the
phenomenon of local muscle fatigue, both for athletes and other
subjects.
Abstract: The ongoing effort to develop an in-house
compressible solver with multi-disciplinary physics is presented in
this paper. Basic compressible solver combined with IBM technique
provides us an effective numerical tool able to tackle the physics
phenomena and especially physic phenomena involved in Solid
Rocket Motors (SRMs). Main principles are introduced step by step
describing its implementation. This paper sheds light on the whole
potentiality of our proposed numerical model and we strongly believe
a way to introduce multi-physics mechanisms strongly coupled is
opened to ablation in nozzle, fluid/structure interaction and burning
propellant surface with time.
Abstract: Rotor Flux based Model Reference Adaptive System
(RF-MRAS) is the most popularly used conventional speed
estimation scheme for sensor-less IM drives. In this scheme, the
voltage model equations are used for the reference model. This
encounters major drawbacks at low frequencies/speed which leads to
the poor performance of RF-MRAS. Replacing the reference model
using Neural Network (NN) based flux estimator provides an
alternate solution and addresses such drawbacks. This paper
identifies an NN based flux estimator using Single Neuron Cascaded
(SNC) Architecture. The proposed SNC-NN model replaces the
conventional voltage model in RF-MRAS to form a novel MRAS
scheme named as SNC-NN-MRAS. Through simulation the proposed
SNC-NN-MRAS is shown to be promising in terms of all major
issues and robustness to parameter variation. The suitability of the
proposed SNC-NN-MRAS based speed estimator and its advantages
over RF-MRAS for sensor-less induction motor drives is
comprehensively presented through extensive simulations.
Abstract: Descriptive statistics was performed with the aim to achieve research objective of to investigate lecturers- usage of the mobile technology for teaching. A representative sample of 20 lecturers from the Faculty of Industrial Art & Design Technology of Universiti Industri Selangor (UNISEL), Malaysia was selected as the respondents. The result attested that lecturers fully accept the concept of mobility in learning and game play is appealing concept to support classroom learning. Subsequently, analogous experience on small size of keypad, screen resolution, and navigation could be the major problematic factors to students and affect their mobile learning process. Recommendation for future research is also presented.
Abstract: This work presents a theoretical investigation of the
simultaneous absorption of CO2 and H2S into aqueous solutions of
MDEA and DEA. In this process the acid components react
with the basic alkanolamine solution via an exothermic,
reversible reaction in a gas/liquid absorber. The use of amine
solvents for gas sweetening has been investigated using
process simulation programs called HYSYS and ASPEN. We
use Electrolyte NRTL and Amine Package and Amines
(experimental) equation of state. The effects of temperature and
circulation rate and amine concentration and packed column and
murphree efficiency on the rate of absorption were studied.
When lean amine flow and concentration increase, CO2 and H2S
absorption increase too. With the improvement of inlet amine
temperature in absorber, CO2 and H2S penetrate to upper stages of
absorber and absorption of acid gases in absorber decreases. The CO2
concentration in the clean gas can be greatly influenced by the
packing height, whereas for the H2S concentration in the clean gas the
packing height plays a minor role. HYSYS software can not
estimate murphree efficiency correctly and it applies the same
contributions in all diagrams for HYSYS software. By
improvement in murphree efficiency, maximum temperature
of absorber decrease and the location of reaction transfer to the
stages of bottoms absorber and the absorption of acid gases
increase.
Abstract: This paper proposes the use of metrics in design space exploration that highlight where in the structure of the model and at what point in the behaviour, prevention is needed against transient faults. Previous approaches to tackle transient faults focused on recovery after detection. Almost no research has been directed towards preventive measures. But in real-time systems, hard deadlines are performance requirements that absolutely must be met and a missed deadline constitutes an erroneous action and a possible system failure. This paper proposes the use of metrics to assess the system design to flag where transient faults may have significant impact. These tools then allow the design to be changed to minimize that impact, and they also flag where particular design techniques – such as coding of communications or memories – need to be applied in later stages of design.
Abstract: Building condition assessment is a critical activity in Malaysia-s Comprehensive Asset Management Model. It is closely related to building performance that impact user-s life and decision making. This study focuses on public primary school, one of the most valuable assets for the country. The assessment was carried out based on CSP1 Matrix in Kuching Division of Sarawak, Malaysia. Based on the matrix used, three main criteria of the buildings has successfully evaluate: the number of defects; schools rating; and total schools rating. The analysis carried out on 24 schools found that the overall 4, 725 defects has been identified. Meanwhile, the overall score obtained was 45, 868 and the overall rating is 9.71, which is at the fair condition. This result has been associated with building age to evaluate its impacts on school buildings condition. The findings proved that building condition is closely related to building age and its support the theory that 'the ageing building has more defect than the new one'.
Abstract: In pattern recognition applications the low level segmentation and the high level object recognition are generally considered as two separate steps. The paper presents a method that bridges the gap between the low and the high level object recognition. It is based on a Bayesian network representation and network propagation algorithm. At the low level it uses hierarchical structure of quadratic spline wavelet image bases. The method is demonstrated for a simple circuit diagram component identification problem.
Abstract: This paper presents an optimal and unsupervised satellite image segmentation approach based on Pearson system and k-Means Clustering Algorithm Initialization. Such method could be considered as original by the fact that it utilised K-Means clustering algorithm for an optimal initialisation of image class number on one hand and it exploited Pearson system for an optimal statistical distributions- affectation of each considered class on the other hand. Satellite image exploitation requires the use of different approaches, especially those founded on the unsupervised statistical segmentation principle. Such approaches necessitate definition of several parameters like image class number, class variables- estimation and generalised mixture distributions. Use of statistical images- attributes assured convincing and promoting results under the condition of having an optimal initialisation step with appropriated statistical distributions- affectation. Pearson system associated with a k-means clustering algorithm and Stochastic Expectation-Maximization 'SEM' algorithm could be adapted to such problem. For each image-s class, Pearson system attributes one distribution type according to different parameters and especially the Skewness 'β1' and the kurtosis 'β2'. The different adapted algorithms, K-Means clustering algorithm, SEM algorithm and Pearson system algorithm, are then applied to satellite image segmentation problem. Efficiency of those combined algorithms was firstly validated with the Mean Quadratic Error 'MQE' evaluation, and secondly with visual inspection along several comparisons of these unsupervised images- segmentation.