Abstract: Clearance in the joints of multibody mechanical
systems such as linkage mechanisms and robots is a main source of
vibration, and noise of the whole system, and wear of the joints
themselves. This clearance is an inevitable matter and cannot be
eliminated, since it allows the relative motion between joint
components and make them assemblage. This paper presents an
experimental verification of the obtained simulation results of a slider
– crank mechanism of one clearance revolute joint. The simulation
results are obtained with the aid of CAD and dynamic simulation
softwares, which is an effective method of simulation multibody
systems with clearance joints and have many advantages. The
comparison between both simulation and experimental results shows
that the simulation results are so close to the experimental ones which
proves the accuracy and efficiency of this method of modeling and
simulation of mechanical systems with clearance joints.
Abstract: Theoptimal extraction condition of dried Phaseolus
vulgaris powderwas studied. The three independent variables are raw
material concentration, shaking and centrifugaltime. The dependent
variables are both yield percentage of crude extract and alphaamylase
enzyme inhibition activity. The experimental design was
based on box-behnkendesign. Highest yield percentage of crude
extract could get from extraction condition at concentration of 1, 0,1,
concentration of 0.15 M ,extraction time for 2hour, and
separationtime for60 min. Moreover, the crude extract with highest
alpha-amylase enzyme inhibition activityoccurred by extraction
condition at concentration of 0.10 M, extraction time for 2 min, and
separation time for 45 min
Abstract: Least Development Countries (LDC) like
Bangladesh, whose 25% revenue earning is achieved from Textile
export, requires producing less defective textile for minimizing
production cost and time. Inspection processes done on these
industries are mostly manual and time consuming. To reduce error
on identifying fabric defects requires more automotive and
accurate inspection process. Considering this lacking, this research
implements a Textile Defect Recognizer which uses computer
vision methodology with the combination of multi-layer neural
networks to identify four classifications of textile defects. The
recognizer, suitable for LDC countries, identifies the fabric defects
within economical cost and produces less error prone inspection
system in real time. In order to generate input set for the neural
network, primarily the recognizer captures digital fabric images by
image acquisition device and converts the RGB images into binary
images by restoration process and local threshold techniques.
Later, the output of the processed image, the area of the faulty
portion, the number of objects of the image and the sharp factor of
the image, are feed backed as an input layer to the neural network
which uses back propagation algorithm to compute the weighted
factors and generates the desired classifications of defects as an
output.
Abstract: The vehicle fleet of public transportation companies is often equipped with intelligent on-board passenger information systems. A frequently used but time and labor-intensive way for keeping the on-board controllers up-to-date is the manual update using different memory cards (e.g. flash cards) or portable computers. This paper describes a compression algorithm that enables data transmission using low bandwidth wireless radio networks (e.g. GPRS) by minimizing the amount of data traffic. In typical cases it reaches a compression rate of an order of magnitude better than that of the general purpose compressors. Compressed data can be easily expanded by the low-performance controllers, too.
Abstract: It has been recognized that due to the autonomy and
heterogeneity, of Web services and the Web itself, new approaches
should be developed to describe and advertise Web services. The
most notable approaches rely on the description of Web services
using semantics. This new breed of Web services, termed semantic
Web services, will enable the automatic annotation, advertisement,
discovery, selection, composition, and execution of interorganization
business logic, making the Internet become a common
global platform where organizations and individuals communicate
with each other to carry out various commercial activities and to
provide value-added services. This paper deals with two of the
hottest R&D and technology areas currently associated with the Web
– Web services and the semantic Web. It describes how semantic
Web services extend Web services as the semantic Web improves the
current Web, and presents three different conceptual approaches to
deploying semantic Web services, namely, WSDL-S, OWL-S, and
WSMO.
Abstract: Metal matrix composites have been increasingly used
as materials for components in automotive and aerospace industries
because of their improved properties compared with non-reinforced
alloys. During machining the selection of appropriate machining
parameters to produce job for desired surface roughness is of great
concern considering the economy of manufacturing process. In this
study, a surface roughness prediction model using fuzzy logic is
developed for end milling of Al-SiCp metal matrix composite
component using carbide end mill cutter. The surface roughness is
modeled as a function of spindle speed (N), feed rate (f), depth of cut
(d) and the SiCp percentage (S). The predicted values surface
roughness is compared with experimental result. The model predicts
average percentage error as 4.56% and mean square error as 0.0729.
It is observed that surface roughness is most influenced by feed rate,
spindle speed and SiC percentage. Depth of cut has least influence.
Abstract: Studying alternative raw materials for biodiesel production is of major importance. The use of mixtures with incorporation of wastes is an environmental friendly alternative and might reduce biodiesel production costs. The objective of the present work was: (i) to study biodiesel production using waste frying oil mixed with pork lard and (ii) to understand how mixture composition influences biodiesel quality. Biodiesel was produced by transesterification and quality was evaluated through determination of several parameters according to EN 14214. The weight fraction of lard in the mixture varied from 0 to 1 in 0.2 intervals. Biodiesel production yields varied from 81.7 to 88.0 (wt%), the lowest yields being the ones obtained using waste frying oil and lard alone as raw materials. The obtained products fulfilled most of the determined quality specifications according to European biodiesel quality standard EN 14214. Minimum purity (96.5 wt%) was closely obtained when waste frying oil was used alone and when 0.2% of lard was incorporated in the raw material (96.3 wt%); however, it ranged from 93.9 to 96.3 (wt%) being always close to the limit. From the evaluation of the influence of mixture composition in biodiesel quality, it was possible to establish a model to be used for predicting some parameters of biodiesel resulting from mixtures of waste frying oil with lard when different lard contents are used.
Abstract: Home Automation is a field that, among other
subjects, is concerned with the comfort, security and energy
requirements of private homes. The configuration of automatic
functions in this type of houses is not always simple to its inhabitants
requiring the initial setup and regular adjustments. In this work, the
ubiquitous computing system vision is used, where the users- action
patterns are captured, recorded and used to create the contextawareness
that allows the self-configuration of the home automation
system. The system will try to free the users from setup adjustments
as the home tries to adapt to its inhabitants- real habits. In this paper
it is described a completely automated process to determine the light
state and act on them, taking in account the users- daily habits.
Artificial Neural Network (ANN) is used as a pattern recognition
method, classifying for each moment the light state. The work
presented uses data from a real house where a family is actually
living.
Abstract: Aim of this study is to evaluate a new three-equation turbulence model applied to flow and heat transfer through a pipe. Uncertainty is approximated by comparing with published direct numerical simulation results for fully-developed flow. Error in the mean axial velocity, temperature, friction, and heat transfer is found to be negligible.
Abstract: A numerical method for solving nonlinear Fredholm integral equations of second kind is proposed. The Fredholm type equations which have many applications in mathematical physics are then considered. The method is based on hybrid function approximations. The properties of hybrid of block-pulse functions and Chebyshev polynomials are presented and are utilized to reduce the computation of nonlinear Fredholm integral equations to a system of nonlinear. Some numerical examples are selected to illustrate the effectiveness and simplicity of the method.
Abstract: Given a large sparse signal, great wishes are to
reconstruct the signal precisely and accurately from lease number of
measurements as possible as it could. Although this seems possible
by theory, the difficulty is in built an algorithm to perform the
accuracy and efficiency of reconstructing. This paper proposes a new
proved method to reconstruct sparse signal depend on using new
method called Least Support Matching Pursuit (LS-OMP) merge it
with the theory of Partial Knowing Support (PSK) given new method
called Partially Knowing of Least Support Orthogonal Matching
Pursuit (PKLS-OMP).
The new methods depend on the greedy algorithm to compute the
support which depends on the number of iterations. So to make it
faster, the PKLS-OMP adds the idea of partial knowing support of its
algorithm. It shows the efficiency, simplicity, and accuracy to get
back the original signal if the sampling matrix satisfies the Restricted
Isometry Property (RIP).
Simulation results also show that it outperforms many algorithms
especially for compressible signals.
Abstract: In this paper, the vessel inscribed trigonometry (VITM) for the vessel progression orientation (VPO) is proposed in the two-dimensional fundus image. The VPO is a major factor in the optic disc (OD) detection which is a basic process in the retina analysis. To measure the VPO, skeletons of vessel are used. First, the vessels are classified into three classes as vessel end, vessel branch and vessel stem. And the chain code maps of VS are generated. Next, two farthest neighborhoods of each point on VS are searched by the proposed angle restriction. Lastly, a gradient of the straight line between two farthest neighborhoods is estimated to measure the VPO. VITM is validated by comparing with manual results and 2D Gaussian templates. It is confirmed that VPO of the proposed mensuration is correct enough to detect OD from the results of experiment which applied VITM to detect OD in fundus images.
Abstract: The aim of this paper is to experimentally discover the workability coefficient of the Inconel 718 material by using a slide turning machining. Two different types of cutting inserts, one made of carbide and the other one made of ceramic, are being used. The purpose is to compare measured results and recommend the appropriate materials and cutting parameters for a machining of the Inconel 718. Furthermore, the durability of inserts with the chosen wear criterion is being compared for different cutting speeds. Machinability of these materials is a crucial characteristic as it allows us to shorten the technological cycle time and increase the machining productivity. And this is of great importance from an economic point of view.
Abstract: Knowledge is a key asset for any organisation to
sustain competitive advantages, but it is difficult to identify and
represent knowledge which is needed to perform activities in
business processes. The effective knowledge management and
support for relevant business activities definitely gives a huge impact
to the performance of the organisation as a whole. This is because
that knowledge have the functions of directing, coordinating and
controlling actions within business processes. The study has
introduced organisational morphology, a norm-based approach by
applying semiotic theories which emphasise on the representation of
knowledge in norms. This approach is concerned with the
identification of activities into three categories: substantive,
communication and control activities. All activities are directed by
norms; hence three types of norms exist; each is associated to a
category of activities. The paper describes the approach briefly and
illustrates the application of this approach through a case study of
academic activities in higher education institutions. The result of the
study shows that the approach provides an effective way to profile
business knowledge and the profile enables the understanding and
specification of business requirements of an organisation.
Abstract: Climate change has profound consequences for the agriculture of south-eastern Australia and its climate-induced water shortage in the Murray-Darling Basin. Post Keynesian Economics (PKE) macro-dynamics, along with Kaleckian investment and growth theory, are used to develop an ecological-economic system dynamics model of this complex nonlinear river basin system. The Murray- Darling Basin Simulation Model (MDB-SM) uses the principles of PKE to incorporate the fundamental uncertainty of economic behaviors of farmers regarding the investments they make and the climate change they face, particularly as regards water ecosystem services. MDB-SM provides a framework for macroeconomic policies, especially for long-term fiscal policy and for policy directed at the sustainability of agricultural water, as measured by socio-economic well-being considerations, which include sustainable consumption and investment in the river basin. The model can also reproduce other ecological and economic aspects and, for certain parameters and initial values, exhibit endogenous business cycles and ecological sustainability with realistic characteristics. Most importantly, MDBSM provides a platform for the analysis of alternative economic policy scenarios. These results reveal the importance of understanding water ecosystem adaptation under climate change by integrating a PKE macroeconomic analytical framework with the system dynamics modelling approach. Once parameterised and supplied with historical initial values, MDB-SM should prove to be a practical tool to provide alternative long-term policy simulations of agricultural water and socio-economic well-being.
Abstract: This paper proposes an algorithm which automatically aligns and stitches the component medical images (fluoroscopic) with varying degrees of overlap into a single composite image. The alignment method is based on similarity measure between the component images. As applied here the technique is intensity based rather than feature based. It works well in domains where feature based methods have difficulty, yet more robust than traditional correlation. Component images are stitched together using the new triangular averaging based blending algorithm. The quality of the resultant image is tested for photometric inconsistencies and geometric misalignments. This method cannot correct rotational, scale and perspective artifacts.
Abstract: The daily increase of organic waste materials resulting
from different activities in the country is one of the main factors for
the pollution of environment. Today, with regard to the low level of
the output of using traditional methods, the high cost of disposal
waste materials and environmental pollutions, the use of modern
methods such as anaerobic digestion for the production of biogas has
been prevailing. The collected biogas from the process of anaerobic
digestion, as a renewable energy source similar to natural gas but
with a less methane and heating value is usable. Today, with the help
of technologies of filtration and proper preparation, access to biogas
with features fully similar to natural gas has become possible. At
present biogas is one of the main sources of supplying electrical and
thermal energy and also an appropriate option to be used in four
stroke engine, diesel engine, sterling engine, gas turbine, gas micro
turbine and fuel cell to produce electricity. The use of biogas for
different reasons which returns to socio-economic and environmental
advantages has been noticed in CHP for the production of energy in
the world. The production of biogas from the technology of anaerobic
digestion and its application in CHP power plants in Iran can not only
supply part of the energy demands in the country, but it can
materialize moving in line with the sustainable development. In this
article, the necessity of the development of CHP plants with biogas
fuels in the country will be dealt based on studies performed from the
economic, environmental and social aspects. Also to prove the
importance of the establishment of these kinds of power plants from
the economic point of view, necessary calculations has been done as
a case study for a CHP power plant with a biogas fuel.
Abstract: The concept of order reduction by least-squares moment matching and generalised least-squares methods has been extended about a general point ?a?, to obtain the reduced order models for linear, time-invariant dynamic systems. Some heuristic criteria have been employed for selecting the linear shift point ?a?, based upon the means (arithmetic, harmonic and geometric) of real parts of the poles of high order system. It is shown that the resultant model depends critically on the choice of linear shift point ?a?. The validity of the criteria is illustrated by solving a numerical example and the results are compared with the other existing techniques.
Abstract: This research work proposed a study of fruit bruise detection by means of a biospeckle method, selecting the papaya fruit (Carica papaya) as testing body. Papaya is recognized as a fruit of outstanding nutritional qualities, showing high vitamin A content, calcium, carbohydrates, exhibiting high popularity all over the world, considering consumption and acceptability. The commercialization of papaya faces special problems which are associated to bruise generation during harvesting, packing and transportation. Papaya is classified as climacteric fruit, permitting to be harvested before the maturation is completed. However, by one side bruise generation is partially controlled once the fruit flesh exhibits high mechanical firmness. By the other side, mechanical loads can set a future bruise at that maturation stage, when it can not be detected yet by conventional methods. Mechanical damages of fruit skin leave an entrance door to microorganisms and pathogens, which will cause severe losses of quality attributes. Traditional techniques of fruit quality inspection include total soluble solids determination, mechanical firmness tests, visual inspections, which would hardly meet required conditions for a fully automated process. However, the pertinent literature reveals a new method named biospeckle which is based on the laser reflectance and interference phenomenon. The laser biospeckle or dynamic speckle is quantified by means of the Moment of Inertia, named after its mechanical counterpart due to similarity between the defining formulae. Biospeckle techniques are able to quantify biological activities of living tissues, which has been applied to seed viability analysis, vegetable senescence and similar topics. Since the biospeckle techniques can monitor tissue physiology, it could also detect changes in the fruit caused by mechanical damages. The proposed technique holds non invasive character, being able to generate numerical results consistent with an adequate automation. The experimental tests associated to this research work included the selection of papaya fruit at different maturation stages which were submitted to artificial mechanical bruising tests. Damages were visually compared with the frequency maps yielded by the biospeckle technique. Results were considered in close agreement.
Abstract: In this paper, we propose improved versions of DVHop
algorithm as QDV-Hop algorithm and UDV-Hop algorithm for
better localization without the need for additional range measurement
hardware. The proposed algorithm focuses on third step of DV-Hop,
first error terms from estimated distances between unknown node and
anchor nodes is separated and then minimized. In the QDV-Hop
algorithm, quadratic programming is used to minimize the error to
obtain better localization. However, quadratic programming requires
a special optimization tool box that increases computational
complexity. On the other hand, UDV-Hop algorithm achieves
localization accuracy similar to that of QDV-Hop by solving
unconstrained optimization problem that results in solving a system
of linear equations without much increase in computational
complexity. Simulation results show that the performance of our
proposed schemes (QDV-Hop and UDV-Hop) is superior to DV-Hop
and DV-Hop based algorithms in all considered scenarios.