Abstract: Machining is an important manufacturing process used to produce a wide variety of metallic parts. Among various machining processes, turning is one of the most important one which is employed to shape cylindrical parts. In turning, the quality of finished product is measured in terms of surface roughness. In turn, surface quality is determined by machining parameters and tool geometry specifications. The main objective of this study is to simultaneously model and optimize machining parameters and tool geometry in order to improve the surface roughness for AISI1045 steel. Several levels of machining parameters and tool geometry specifications are considered as input parameters. The surface roughness is selected as process output measure of performance. A Taguchi approach is employed to gather experimental data. Then, based on signal-to-noise (S/N) ratio, the best sets of cutting parameters and tool geometry specifications have been determined. Using these parameters values, the surface roughness of AISI1045 steel parts may be minimized. Experimental results are provided to illustrate the effectiveness of the proposed approach.
Abstract: The development of biomimetic micro-aerial-vehicles
(MAVs) with flapping wings is the future trend in military/domestic
field. The successful flight of MAVs is strongly related to the
understanding of unsteady aerodynamic performance of low Reynolds
number airfoils under dynamic flapping motion. This study explored
the effects of flapping frequency, stroke amplitude, and the inclined
angle of stroke plane on lift force and thrust force of a bio-inspiration
corrugated airfoil with 33 full factorial design of experiment and
ANOVA analysis. Unsteady vorticity flows over a corrugated thin
airfoil executing flapping motion are computed with time-dependent
two-dimensional laminar incompressible Reynolds-averaged
Navier-Stokes equations with the conformal hybrid mesh. The tested
freestream Reynolds number based on the chord length of airfoil as
characteristic length is fixed of 103. The dynamic mesh technique is
applied to model the flapping motion of a corrugated airfoil. Instant
vorticity contours over a complete flapping cycle clearly reveals the
flow mechanisms for lift force generation are dynamic stall, rotational
circulation, and wake capture. The thrust force is produced as the
leading edge vortex shedding from the trailing edge of airfoil to form a
reverse von Karman vortex. Results also indicated that the inclined
angle is the most significant factor on both the lift force and thrust
force. There are strong interactions between tested factors which mean
an optimization study on parameters should be conducted in further
runs.
Abstract: The aim of this study was to demonstrate the possible
effect of some variables such as age, gender, blood sugar level, and
duration of diabetes on the serum level of zinc in diabetic individuals
from Murzuk area. Serum zinc (Zn), Fasting blood sugar (FBS),
hemoglobin HbA1c (HbA1c) were evaluated in 46 type I diabetic
subjects (group 1), 48 type II diabetic subjects (group 2) and 43
healthy individuals (control) of both genders aged (30-81) years. Data
showed that both diabetic groups have significantly higher (P0.05) differences in serum Zn levels were observed
between Males and Females. Serum Zn levels were non-significantly
decreased with increasing age. In type II diabetic subjects, serum Zn
levels were non-significantly decreased with increasing duration of
disease whereas those in type I were non-significantly increased.
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: The aim for this research is to deliberately discuss
how and why the contexts of culture are the main significant factors
which need to be considered when conducting the international
business oversea. As a consequence of understanding these various
factors, the researcher would be able to infer some suggestions to the
international organizations. With this in mind, the results of the
understanding in a national culture environment can support the
organizations to settle its international strategies which may be useful
to develop the national export and import effectiveness. This data
collecting methods will be concentrated upon 5-10 interviews from
the senior members and business officers in the international
company in Thailand by e-mail interview and analyses the individual
manager’s viewpoint. As well as, focus on the questionnaires which
the respondents were selected randomly around 100 samples from
UK and Thailand, together with providing a functional sample size
and comparable to data. The results of the study question the role of
national culture, which contributed to in international business
effectiveness and emphasize the positive and negative aspects, as
well as suggestions to business investors are informed.
Abstract: This paper addresses the problem of source separation
in images. We propose a FastICA algorithm employing a modified
Gaussian contrast function for the Blind Source Separation.
Experimental result shows that the proposed Modified Gaussian
FastICA is effectively used for Blind Source Separation to obtain
better quality images. In this paper, a comparative study has been
made with other popular existing algorithms. The peak signal to
noise ratio (PSNR) and improved signal to noise ratio (ISNR) are
used as metrics for evaluating the quality of images. The ICA metric
Amari error is also used to measure the quality of separation.
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: Due to the limited energy resources, energy efficient operation of sensor node is a key issue in wireless sensor networks. Clustering is an effective method to prolong the lifetime of energy constrained wireless sensor network. However, clustering in wireless sensor network faces several challenges such as selection of an optimal group of sensor nodes as cluster, optimum selection of cluster head, energy balanced optimal strategy for rotating the role of cluster head in a cluster, maintaining intra and inter cluster connectivity and optimal data routing in the network. In this paper, we propose a protocol supporting an energy efficient clustering, cluster head selection/rotation and data routing method to prolong the lifetime of sensor network. Simulation results demonstrate that the proposed protocol prolongs network lifetime due to the use of efficient clustering, cluster head selection/rotation and data routing.
Abstract: The article deals with experimental and numerical
investigation of axi-symmetric subsonic air to air ejector with
diffuser adapted for boundary layer suction. The diffuser, which is
placed behind the mixing chamber of the ejector, has high divergence
angle and therefore low efficiency. To increase the efficiency, the
diffuser is equipped with slot enabling boundary layer suction. The
effect of boundary layer suction on flow in ejector, static pressure
distribution on the mixing chamber wall and characteristic were
measured and studied numerically. Both diffuser and ejector
efficiency were evaluated. The diffuser efficiency was increased,
however, the efficiency of ejector itself remained low.
Abstract: K-Means (KM) is considered one of the major
algorithms widely used in clustering. However, it still has some
problems, and one of them is in its initialization step where it is
normally done randomly. Another problem for KM is that it
converges to local minima. Genetic algorithms are one of the
evolutionary algorithms inspired from nature and utilized in the field
of clustering. In this paper, we propose two algorithms to solve the
initialization problem, Genetic Algorithm Initializes KM (GAIK) and
KM Initializes Genetic Algorithm (KIGA). To show the effectiveness
and efficiency of our algorithms, a comparative study was done
among GAIK, KIGA, Genetic-based Clustering Algorithm (GCA),
and FCM [19].
Abstract: We report in this paper the procedure of a system of
automatic speech recognition based on techniques of the dynamic
programming. The technique of temporal retiming is a technique
used to synchronize between two forms to compare. We will see how
this technique is adapted to the field of the automatic speech
recognition. We will expose, in a first place, the theory of the
function of retiming which is used to compare and to adjust an
unknown form with a whole of forms of reference constituting the
vocabulary of the application. Then we will give, in the second place,
the various algorithms necessary to their implementation on machine.
The algorithms which we will present were tested on part of the
corpus of words in Arab language Arabdic-10 [4] and gave whole
satisfaction. These algorithms are effective insofar as we apply them
to the small ones or average vocabularies.
Abstract: Locating the critical slip surface with the minimum factor of safety for a rock slope is a difficult problem. In recent years, some modern global optimization methods have been developed with success in treating various types of problems, but very few of such methods have been applied to rock mechanical problems. In this paper, use of hybrid model based on artificial immune system and cellular learning automata is proposed. The results show that the algorithm is an effective and efficient optimization method with a high level of confidence rate.
Abstract: Image interpolation is a common problem in imaging applications. However, most interpolation algorithms in existence suffer visually to some extent the effects of blurred edges and jagged artifacts in the image. This paper presents an adaptive feature preserving bidirectional flow process, where an inverse diffusion is performed to enhance edges along the normal directions to the isophote lines (edges), while a normal diffusion is done to remove artifacts (''jaggies'') along the tangent directions. In order to preserve image features such as edges, angles and textures, the nonlinear diffusion coefficients are locally adjusted according to the first and second order directional derivatives of the image. Experimental results on synthetic images and nature images demonstrate that our interpolation algorithm substantially improves the subjective quality of the interpolated images over conventional interpolations.
Abstract: The performance of sensor-less controlled induction
motor drive depends on the accuracy of the estimated speed.
Conventional estimation techniques being mathematically complex
require more execution time resulting in poor dynamic response. The
nonlinear mapping capability and powerful learning algorithms of
neural network provides a promising alternative for on-line speed
estimation. The on-line speed estimator requires the NN model to be
accurate, simpler in design, structurally compact and computationally
less complex to ensure faster execution and effective control in real
time implementation. This in turn to a large extent depends on the
type of Neural Architecture. This paper investigates three types of
neural architectures for on-line speed estimation and their
performance is compared in terms of accuracy, structural
compactness, computational complexity and execution time. The
suitable neural architecture for on-line speed estimation is identified
and the promising results obtained are presented.
Abstract: This study was aimed to determine seasonal variations
of leaf nutrient concentrations to define nutrient needs related to
growing period and to compare irrigation programs in terms of
nutrient uptake. In this study,'Starkrimson Delicious' variety grafted
onto seedling rootstock was used during 2009-2010 growing seasons.
The study was conducted at E─ƒirdir Fruit Growing Research Station.
Leaf samples were taken in five different sample seasons (May, June,
July, August and September). Four different pan coefficients (0.50,
0.75, 1.0, 1.25) were applied during drip irrigation treatments in 7
days irrigation interval. Leaf K, Mg, Ca, P, Fe, Zn, Mn and Cu
concentrations were determined.
The results showed that among the seasonal changes, the highest
concentrations of K, Mg, P and Mn in leaves were recorded in May,
followed by a decrease in the other months, while in contrast Ca and
Fe showed the lowest concentration in May.
Results of the study demonstrate that among irrigation programs K
and Cu concentration in plants was significantly influenced. Cu
concentrations decreased with seasonal variations and different
irrigation programs. Thus, nutrient needs of 'Starkrimson Delicious'apple trees at different growth stages should be taken into
consideration before making effective fertilization program.
Abstract: Imitation learning is considered to be an effective way of teaching humanoid robots and action recognition is the key step to imitation learning. In this paper an online algorithm to recognize
parametric actions with object context is presented. Objects are key instruments in understanding an action when there is uncertainty.
Ambiguities arising in similar actions can be resolved with objectn context. We classify actions according to the changes they make to
the object space. Actions that produce the same state change in the object movement space are classified to belong to the same class. This allow us to define several classes of actions where members of
each class are connected with a semantic interpretation.
Abstract: Materials added to the matrix help improving operating properties of a composite. This experimental study has targeted to investigate this aim where Silicon Oxide particles were added to glass fibre and epoxy resin at an amount of 15% to the main material to obtain a sort of new composite material. Erosive wear behavior of epoxy-resin dipped composite materials reinforced with glass fibre and Silicon Oxide under three different impingement angles (30°, 60° and 90°), three different impact velocities (23, 34 and 53 m/s), two different angular Aluminum abrasive particle sizes (approximately 200 and 400 μm) and the fibre orientation of 45° (45/-45) were investigated. In the test results, erosion rates were obtained as functions of impingement angles, impact velocities, particle sizes and fibre orientation. Moreover, materials with addition of Silicon Oxide filler material exhibited lower wear as compared to neat materials with no added filler material. In addition, SEM views showing worn out surfaces of the test specimens were scrutinized.
Abstract: In order to study the effect of phosphate solubilization
microorganisms (PSM) and plant growth promoting rhizobacteria
(PGPR) on yield and yield components of corn Zea mays (L. cv.
SC604) an experiment was conducted at research farm of Sari
Agricultural Sciences and Natural Resources University, Iran during
2007. Experiment laid out as split plot based on randomized
complete block design with three replications. Three levels of
manures (consisted of 20 Mg.ha-1 farmyard manure, 15 Mg.ha-1 green
manure and check or without any manures) as main plots and eight
levels of biofertilizers (consisted of 1-NPK or conventional fertilizer
application; 2-NPK+PSM+PGPR; 3 NP50%K+PSM+PGPR; 4-
N50%PK+PSM +PGPR; 5-N50%P50%K+PSM+ PGPR; 6-PK+PGPR; 7-
NK+PSM and 8-PSM+PGPR) as sub plots were treatments. Results
showed that farmyard manure application increased row number, ear
weight, grain number per ear, grain yield, biological yield and
harvest index compared to check. Furthermore, using of PSM and
PGPR in addition to conventional fertilizer applications (NPK) could
improve ear weight, row number and grain number per row and
ultimately increased grain yield in green manure and check plots.
According to results in all fertilizer treatments application of PSM
and PGPR together could reduce P application by 50% without any
significant reduction of grain yield. However, this treatment could
not compensate 50% reduction of N application.
Abstract: A three-dimensional finite element modeling for austenitic stainless steel AISI 304 annealed condition sheets of 1.0 mm thickness are developed using ABAQUS® software. This includes spot welded and weld bonded joints models. Both models undergo thermal heat caused by spot welding process and then are subjected to axial load up to the failure point. The properties of elastic and plastic regions, modulus of elasticity, fracture limit, nugget and heat affected zones are determined. Complete loaddisplacement curve for each joining model is obtained and compared with the experiment data and with the finite element models without including the effect of thermal process. In general, the results obtained for both spot welded and weld-bonded joints affected by thermal process showed an excellent agreement with the experimental data.
Abstract: The main objective of this paper is to investigate the
enhancement of power system stability via coordinated tuning of
Power System Stabilizers (PSSs) in a multi-machine power system.
The design problem of the proposed controllers is formulated as an
optimization problem. Chaotic catfish particle swarm optimization
(C-Catfish PSO) algorithm is used to minimize the ITAE objective
function. The proposed algorithm is evaluated on a two-area, 4-
machines system. The robustness of the proposed algorithm is
verified on this system under different operating conditions and
applying a three-phase fault. The nonlinear time-domain simulation
results and some performance indices show the effectiveness of the
proposed controller in damping power system oscillations and this
novel optimization algorithm is compared with particle swarm
optimization (PSO).