Abstract: In the present paper, Fatigue life assessment of an
anti-roll bar component of a passenger vehicle, is investigated by
ANSYS 11 software. A stress analysis is also carried out by the
finite element technique for the determination of highly stressed
regions on the bar. Anti-roll bar is a suspension element used at the
front, rear, or at both ends of a car that reduces body roll by resisting
any unequal vertical motion between the pair of wheels to which it is
connected. As a first stage, fatigue damage models proposed by some
well-known references and the corresponding assumptions are
discussed and some enhancements are proposed. Then, fracture
analysis of an anti-roll bar of an automobile is carried out. The
analysed type of the anti-roll bar is especially important as many
cases are reported about the fracture after a 100,000 km of travel
fatigue and fracture conditions. This paper demonstrates fatigue life
of an anti-roll bar and then evaluated by experimental analytically
results from other researcher.
Abstract: In this paper an efficient implementation of Ripemd-
160 hash function is presented. Hash functions are a special family
of cryptographic algorithms, which is used in technological
applications with requirements for security, confidentiality and
validity. Applications like PKI, IPSec, DSA, MAC-s incorporate
hash functions and are used widely today. The Ripemd-160 is
emanated from the necessity for existence of very strong algorithms
in cryptanalysis. The proposed hardware implementation can be
synthesized easily for a variety of FPGA and ASIC technologies.
Simulation results, using commercial tools, verified the efficiency of
the implementation in terms of performance and throughput. Special
care has been taken so that the proposed implementation doesn-t
introduce extra design complexity; while in parallel functionality was
kept to the required levels.
Abstract: In order to evaluate the Effects of dual inoculation of
Azotobacter and Mycorrhiza with Nitrogen and Phosphorus levels on
yield and yield components of spring safflower, this study was
carried out in field of Farahan university in Markazi province in
2007. A factorial in a randomized complete block design with three
replications was used inoculation of Azotobacter (with inoculation
and without inoculation) and Mycorrhiza (with inoculation and
without inoculation ) with Nitrogen and Phosphorus levels [F0= N0+
P0 (kg.ha-1), F1= N50+ P25(kg.ha-1), F2= N100+ P50(kg.ha-1) and
F3= N150+ P75 (kg.ha-1)] on spring safflower (cultivar IL-111). In
this study characteristics such as: Harvest index, Hectolitre weight,
Root dry weight, Seed yield, Mycorrhizal Colonization Root,
Number of days to maturity were assessed. Results indicated that
treatment (A0M1F3) with grain yield (1556 kg.ha-1) and treatment
(A0M1F0) with grain yield (918 kg.ha-1) were significantly superior
to the other treatments and according to calculated, inoculation seeds
in plantig date with Azotobacter and Mycorrhiza to cause increase
grain yield about 5/38 percentage. we can by inoculation safflower
seeds with Azotobacter and Mycorrhiza too easily at the time sowing
date. The purpose of this research, study and evaluation the role of
biological fixation N and P, to provide for feeds plants.
Abstract: Grid environments consist of the volatile integration
of discrete heterogeneous resources. The notion of the Grid is to
unite different users and organisations and pool their resources into
one large computing platform where they can harness, inter-operate,
collaborate and interact. If the Grid Community is to achieve this
objective, then participants (Users and Organisations) need to be
willing to donate or share their resources and permit other
participants to use their resources. Resources do not have to be
shared at all times, since it may result in users not having access to
their own resource. The idea of reward-based computing was
developed to address the sharing problem in a pragmatic manner.
Participants are offered a reward to donate their resources to the
Grid. A reward may include monetary recompense or a pro rata share
of available resources when constrained. This latter point may imply
a quality of service, which in turn may require some globally agreed
reservation mechanism. This paper presents a platform for economybased
computing using the WebCom Grid middleware. Using this
middleware, participants can configure their resources at times and
priority levels to suit their local usage policy. The WebCom system
accounts for processing done on individual participants- resources
and rewards them accordingly.
Abstract: When considering the development of constitutive
equations describing the behavior of materials under cyclic plastic
strains, different kinds of formulations can be adopted. The primary
intention of this study is to develop computer programming of
plasticity models to accurately predict the life of engineering
components. For this purpose, the energy or cyclic strain is computed
in multi-surface plasticity models in non-proportional loading and to
present their procedures and codes results.
Abstract: Temperature, humidity and precipitation in an area,
are parameters proved influential in the climate of that area, and one
should recognize them so that he can determine the climate of that
area. Climate changes are of primary importance in climatology, and
in recent years, have been of great concern to researchers and even
politicians and organizations, for they can play an important role in
social, political and economic activities. Even though the real cause
of climate changes or their stability is not yet fully recognized, they
are a matter of concern to researchers and their importance for
countries has prompted them to investigate climate changes in
different levels, especially in regional, national and continental level.
This issue has less been investigated in our country. However, in
recent years, there have been some researches and conferences on
climate changes. This study is also in line with such researches and
tries to investigate and analyze the trends of climate changes
(temperature and precipitation) in Sefid-roud (the name of a river)
basin. Three parameters of mean annual precipitation, temperature,
and maximum and minimum temperatures in 36 synoptic and
climatology stations in a statistical period of 49 years (1956-2005) in
the stations of Sefid-roud basin were analyzed by Mann-Kendall test.
The results obtained by data analysis show that climate changes are
short term and have a trend. The analysis of mean temperature
revealed that changes have a significantly rising trend, besides the
precipitation has a significantly falling trend.
Abstract: A new Feed-Forward/Feedback Generalized
Minimum Variance Pole-placement Controller to incorporate the
robustness of classical pole-placement into the flexibility of
generalized minimum variance self-tuning controller for Single-Input
Single-Output (SISO) has been proposed in this paper. The design,
which provides the user with an adaptive mechanism, which ensures
that the closed loop poles are, located at their pre-specified positions.
In addition, the controller design which has a feed-forward/feedback
structure overcomes the certain limitations existing in similar poleplacement
control designs whilst retaining the simplicity of
adaptation mechanisms used in other designs. It tracks set-point
changes with the desired speed of response, penalizes excessive
control action, and can be applied to non-minimum phase systems.
Besides, at steady state, the controller has the ability to regulate the
constant load disturbance to zero. Example simulation results using
both simulated and real plant models demonstrate the effectiveness of
the proposed controller.
Abstract: In this paper, free vibration analysis of carbon nanotube (CNT) reinforced laminated composite panels is presented. Three types of panels such as flat, concave and convex are considered for study. Numerical simulation is carried out using commercially available finite element analysis software ANSYS. Numerical homogenization is employed to calculate the effective elastic properties of randomly distributed carbon nanotube reinforced composites. To verify the accuracy of the finite element method, comparisons are made with existing results available in the literature for conventional laminated composite panels and good agreements are obtained. The results of the CNT reinforced composite materials are compared with conventional composite materials under different boundary conditions.
Abstract: Bus Rapid Transit (BRT) has emerged as a cost-effective transport system for urban mobility. However its ability to stimulate land development remains largely unexplored. The study makes use of qualitative (interview method) and quantitative analysis (questionnaire survey and longitudinal analysis of property data) to investigate land development impact resulting from BRT in Beijing, China. The empirical analysis suggests that BRT has a positive impact on the residential and commercial property attractiveness along the busway corridor. The statistical analysis suggests that accessibility advantage conferred by BRT is capitalized into higher property price. The average price of apartments adjacent to a BRT station has gained a relatively faster increase than those not served by the BRT system. The capitalization effect mostly occurs after the full operation of BRT, and is more evident over time and particularly observed in areas which previously lack alternative mobility opportunity.
Abstract: In Geographic Information System, one of the sources
of obtaining needed geographic data is digitizing analog maps and
evaluation of aerial and satellite photos. In this study, a method will
be discussed which can be used to extract vectorial features and
creating vectorized drawing files for aerial photos. At the same time
a software developed for these purpose. Converting from raster to
vector is also known as vectorization and it is the most important step
when creating vectorized drawing files. In the developed algorithm,
first of all preprocessing on the aerial photo is done. These are;
converting to grayscale if necessary, reducing noise, applying some
filters and determining the edge of the objects etc. After these steps,
every pixel which constitutes the photo are followed from upper left
to right bottom by examining its neighborhood relationship and one
pixel wide lines or polylines obtained. The obtained lines have to be
erased for preventing confusion while continuing vectorization
because if not erased they can be perceived as new line, but if erased
it can cause discontinuity in vector drawing so the image converted
from 2 bit to 8 bit and the detected pixels are expressed as a different
bit. In conclusion, the aerial photo can be converted to vector form
which includes lines and polylines and can be opened in any CAD
application.
Abstract: Fault-proneness of a software module is the
probability that the module contains faults. A correlation exists
between the fault-proneness of the software and the measurable
attributes of the code (i.e. the static metrics) and of the testing (i.e.
the dynamic metrics). Early detection of fault-prone software
components enables verification experts to concentrate their time and
resources on the problem areas of the software system under
development. This paper introduces Genetic Algorithm based
software fault prediction models with Object-Oriented metrics. The
contribution of this paper is that it has used Metric values of JEdit
open source software for generation of the rules for the classification
of software modules in the categories of Faulty and non faulty
modules and thereafter empirically validation is performed. The
results shows that Genetic algorithm approach can be used for
finding the fault proneness in object oriented software components.
Abstract: In this paper, we demonstrate the adaptive
least-mean-square (LMS) filter modeling using SystemC. SystemC is
a modeling language that allows designer to model both hardware and
software component and makes it possible to design from high level
system of abstraction to low level system of abstraction. We produced
five adaptive least-mean-square filter models that are classed as five
abstraction levels using SystemC proceeding from the abstract model
to the more concrete model.
Abstract: A numerical study of flow in a horizontally channel
partially filled with a porous screen with non-uniform inlet has been
performed by lattice Boltzmann method (LBM). The flow in porous
layer has been simulated by the Brinkman-Forchheimer model.
Numerical solutions have been obtained for variable porosity models
and the effects of Darcy number and porosity have been studied in
detail. It is found that the flow stabilization is reliant on the Darcy
number. Also the results show that the stabilization of flow field and
heat transfer is depended to Darcy number. Distribution of stream
field becomes more stable by decreasing Darcy number. Results
illustrate that the effect of variable porosity is significant just in the
region of the solid boundary. In addition, difference between constant
and variable porosity models is decreased by decreasing the Darcy
number.
Abstract: This study investigated morphology of the Spanner Barb (Puntius lateristriga Valenciennes, 1842) and water quality at Thepchana waterfall. This study was conducted at Thepchana Waterfall, Khao Nan National Park from March to May 2007. There were 40 Spanner Barb collected with 20 males and 20 females. Males had an average of 5.57 cm in standard length, 6.62 cm in total length and 5.18 g in total body weight. Females had an average of 7.25 cm in standard length, 8.24 cm in total length and 10.96 g in total body weight. The length (L) – weight (W) relationships for combining sexes, males and females were LogW = -2.137 + 3.355logL, log W = -0.068 + 3.297logL, and log W = -2.068 + 3.297logL, respectively. The Spanner Barb were smaller size fish with a compressed form; terminal mouth; villiform teeth; ctenoid scale; concave tail; general body color yellowish olive, with slight reddish tint to fins; vertical band beginning below dorsal and horizontal stripe from base of tail almost to vertical band. They also had a vertical band midway between the eye and first vertical band. There was a black spot above anal fin. The bladder looked like J-shape. Inside of the bladder was found small insects and insect lava. The body length and the bowels length was 1:1 ratio. The water temperature ranged from 25.00 – 27.00 °C which was appropriate for their habitat characteristics. Acid - alkalinity ranged from 6.65 – 6.90 mg/l. Dissolved oxygen ranged from 4.55 – 4.70 mg/l. Water hardness ranged from 31.00 – 48.00 mg/l. The amount of ammonia was about 0.25 mg/l.
Abstract: Until recently, researchers have developed various
tools and methodologies for effective clinical decision-making.
Among those decisions, chest pain diseases have been one of
important diagnostic issues especially in an emergency department. To
improve the ability of physicians in diagnosis, many researchers have
developed diagnosis intelligence by using machine learning and data
mining. However, most of the conventional methodologies have been
generally based on a single classifier for disease classification and
prediction, which shows moderate performance. This study utilizes an
ensemble strategy to combine multiple different classifiers to help
physicians diagnose chest pain diseases more accurately than ever.
Specifically the ensemble strategy is applied by using the integration
of decision trees, neural networks, and support vector machines. The
ensemble models are applied to real-world emergency data. This study
shows that the performance of the ensemble models is superior to each
of single classifiers.
Abstract: This paper investigates the problem of tracking spa¬tiotemporal changes of a satellite image through the use of Knowledge Discovery in Database (KDD). The purpose of this study is to help a given user effectively discover interesting knowledge and then build prediction and decision models. Unfortunately, the KDD process for spatiotemporal data is always marked by several types of imperfections. In our paper, we take these imperfections into consideration in order to provide more accurate decisions. To achieve this objective, different KDD methods are used to discover knowledge in satellite image databases. Each method presents a different point of view of spatiotemporal evolution of a query model (which represents an extracted object from a satellite image). In order to combine these methods, we use the evidence fusion theory which considerably improves the spatiotemporal knowledge discovery process and increases our belief in the spatiotemporal model change. Experimental results of satellite images representing the region of Auckland in New Zealand depict the improvement in the overall change detection as compared to using classical methods.
Abstract: Parametric models have been quite popular for
studying human growth, particularly in relation to biological
parameters such as peak size velocity and age at peak size velocity.
Longitudinal data are generally considered to be vital for fittinga
parametric model to individual-specific data, and for studying the
distribution of these biological parameters in a human population.
However, cross-sectional data are easier to obtain than longitudinal
data. In this paper, we present a method of combining longitudinal
and cross-sectional data for the purpose of estimating the distribution
of the biological parameters. We demonstrate, through simulations in
the special case ofthePreece Baines model, how estimates based on
longitudinal data can be improved upon by harnessing the
information contained in cross-sectional data.We study the extent of
improvement for different mixes of the two types of data, and finally
illustrate the use of the method through data collected by the Indian
Statistical Institute.
Abstract: The dynamics of the Autonomous Underwater
Vehicles (AUVs) are highly nonlinear and time varying and the hydrodynamic coefficients of vehicles are difficult to estimate
accurately because of the variations of these coefficients with
different navigation conditions and external disturbances. This study presents the on-line system identification of AUV dynamics to obtain
the coupled nonlinear dynamic model of AUV as a black box. This black box has an input-output relationship based upon on-line
adaptive fuzzy model and adaptive neural fuzzy network (ANFN)
model techniques to overcome the uncertain external disturbance and
the difficulties of modelling the hydrodynamic forces of the AUVs instead of using the mathematical model with hydrodynamic parameters estimation. The models- parameters are adapted according
to the back propagation algorithm based upon the error between the
identified model and the actual output of the plant. The proposed
ANFN model adopts a functional link neural network (FLNN) as the
consequent part of the fuzzy rules. Thus, the consequent part of the
ANFN model is a nonlinear combination of input variables. Fuzzy
control system is applied to guide and control the AUV using both
adaptive models and mathematical model. Simulation results show
the superiority of the proposed adaptive neural fuzzy network
(ANFN) model in tracking of the behavior of the AUV accurately
even in the presence of noise and disturbance.
Abstract: Financial forecasting using machine learning techniques has received great efforts in the last decide . In this ongoing work, we show how machine learning of graphical models will be able to infer a visualized causal interactions between different banks in the Saudi equities market. One important discovery from such learned causal graphs is how companies influence each other and to what extend. In this work, a set of graphical models named Gaussian graphical models with developed ensemble penalized feature selection methods that combine ; filtering method, wrapper method and a regularizer will be shown. A comparison between these different developed ensemble combinations will also be shown. The best ensemble method will be used to infer the causal relationships between banks in Saudi equities market.
Abstract: An experimental study of Reinforced Concrete, RC, columns strengthened using a steel jacketing technique was conducted. The jacketing technique consisted of four steel vertical angles installed at the corners of the column joined by horizontal steel straps confining the column externally. The effectiveness of the technique was evaluated by testing the RC column specimens under eccentric monotonic loading until failure occurred. Strain gauges were installed to monitor the strains in the internal reinforcement as well as the external jacketing system. The effectiveness of the jacketing technique was demonstrated, and the parameters affecting the technique were studied.