Abstract: Despite the internet, which is one of the mass media
that has become quite common in recent years, the relationship of
Advertisement with Television and Cinema, which have always
drawn attention of researchers as basic media and where visual use is
in the foreground, have also become the subject of various studies.
Based on the assumption that the known fundamental effects of
advertisements on consumers are closely related to the creative
process of advertisements as well as the nature and characteristics of
the medium where they are used, these basic mass media (Television
and Cinema) and the consumer motivations of the advertisements
they broadcast have become a focus of study.
Given that the viewers of the mass media in question have shifted
from a passive position to a more active one especially in recent years
and approach contents of advertisements, as they do all contents, in a
more critical and “pitiless" manner, it is possible to say that
individuals make more use of advertisements than in the past and
combine their individual goals with the goals of the advertisements.
This study, which aims at finding out what the goals of these new
individual advertisement use are, how they are shaped by the distinct
characteristics of Television and Cinema, where visuality takes
precedence as basic mass media, and what kind of places they occupy
in the minds of consumers, has determined consumers- motivations
as: “Entertainment", “Escapism", “Play", “Monitoring/Discovery",
“Opposite Sex" and “Aspirations and Role Models".
This study intends to reveal the differences or similarities among
the needs and hence the gratifications of viewers who consume
advertisements on Television or at the Cinema, which are two basic
media where visuality is prioritized.
Abstract: The performance of a type of fuzzy sliding mode control is researched by considering the nonlinear characteristic of a missile-target interception problem to obtain a robust interception process. The variable boundary layer by using fuzzy logic is proposed to reduce the chattering around the switching surface then is applied to the interception model which was derived. The performances of the sliding mode control with constant and fuzzy boundary layer are compared at the end of the study and the results are evaluated.
Abstract: The present work is motivated by the idea that the
layer deformation in anisotropic elasticity can be estimated from the
theory of interfacial dislocations. In effect, this work which is an
extension of a previous approach given by one of the authors
determines the anisotropic displacement fields and the critical
thickness due to a complex biperiodic network of MDs lying just
below the free surface in view of the arrangement of dislocations.
The elastic fields of such arrangements observed along interfaces
play a crucial part in the improvement of the physical properties of
epitaxial systems. New results are proposed in anisotropic elasticity
for hexagonal networks of MDs which contain intrinsic and extrinsic
stacking faults. We developed, using a previous approach based on
the relative interfacial displacement and a Fourier series formulation
of the displacement fields, the expressions of elastic fields when
there is a possible dissociation of MDs. The numerical investigations
in the case of the observed system Si/(111)Si with low twist angles
show clearly the effect of the anisotropy and thickness when the
misfit networks are dissociated.
Abstract: The present experimental investigation brings about
a comparative study of lactic acid production by pure strains of
Lactobacilli (1) L. delbreuckii (NCIM2025), (2) L. pentosus (NCIM
2912), (3) Lactobacillus sp.(NCIM 2734, (4) Lactobacillus sp.
(NCIM2084) and coculture of strain-1 and Stain-2 in solid bed of
wheat bran, under the influence of different nitrogen sources such as
baker-s yeast, meat extract and proteose peptone. Among the pure
cultures, strain-3 attained lowest pH value of 3.44, hence highest acid
formation 46.41 g/L, while the coculture attained an overall
maximum value 47.56 g/L lactic acid (pH 3.38) at 15 g/L and 20 g/L
level of baker-s yeast, respectively.
Abstract: The current methods of predictive controllers are
utilized for those processes in which the rate of output variations is
not high. For such processes, therefore, stability can be achieved by
implementing the constrained predictive controller or applying
infinite prediction horizon. When the rate of the output growth is
high (e.g. for unstable nonminimum phase process) the stabilization
seems to be problematic. In order to avoid this, it is suggested to
change the method in the way that: first, the prediction error growth
should be decreased at the early stage of the prediction horizon, and
second, the rate of the error variation should be penalized. The
growth of the error is decreased through adjusting its weighting
coefficients in the cost function. Reduction in the error variation is
possible by adding the first order derivate of the error into the cost
function. By studying different examples it is shown that using these
two remedies together, the closed-loop stability of unstable
nonminimum phase process can be achieved.
Abstract: New methodologies for XOR-XNOR circuits are
proposed to improve the speed and power as these circuits are basic
building blocks of many arithmetic circuits. This paper evaluates and
compares the performance of various XOR-XNOR circuits. The
performance of the XOR-XNOR circuits based on TSMC 0.18μm
process models at all range of the supply voltage starting from 0.6V
to 3.3V is evaluated by the comparison of the simulation results
obtained from HSPICE. Simulation results reveal that the proposed
circuit exhibit lower PDP and EDP, more power efficient and faster
when compared with best available XOR-XNOR circuits in the
literature.
Abstract: This paper proposes a novel architecture for developing decision support systems. Unlike conventional decision support systems, the proposed architecture endeavors to reveal the decision-making process such that humans' subjectivity can be incorporated into a computerized system and, at the same time, to preserve the capability of the computerized system in processing information objectively. A number of techniques used in developing the decision support system are elaborated to make the decisionmarking process transparent. These include procedures for high dimensional data visualization, pattern classification, prediction, and evolutionary computational search. An artificial data set is first employed to compare the proposed approach with other methods. A simulated handwritten data set and a real data set on liver disease diagnosis are then employed to evaluate the efficacy of the proposed approach. The results are analyzed and discussed. The potentials of the proposed architecture as a useful decision support system are demonstrated.
Abstract: In most rule-induction algorithms, the only operator used against nominal attributes is the equality operator =. In this paper, we first propose the use of the inequality operator, ≠, in addition to the equality operator, to increase the expressiveness of induced rules. Then, we present a new method, Binary Coding, which can be used along with an arbitrary rule-induction algorithm to make use of the inequality operator without any need to change the algorithm. Experimental results suggest that the Binary Coding method is promising enough for further investigation, especially in cases where the minimum number of rules is desirable.
Abstract: For controlling urban transportations, traffic lights
show similar behavior for different kinds of vehicles at intersections.
Emergency vehicles need special behavior at intersections, so traffic
lights should behave in different manner when emergency vehicles
approach them. At the present time, intelligent traffic lights control
urban transportations intelligently. In this paper the ethical aspect of
this topic is considered. A model is proposed for adding special
component to emergency vehicles and traffic lights for controlling
traffic in ethical manner. The proposed model is simulated by JADE.
Abstract: Keystroke authentication is a new access control system
to identify legitimate users via their typing behavior. In this paper,
machine learning techniques are adapted for keystroke authentication.
Seven learning methods are used to build models to differentiate user
keystroke patterns. The selected classification methods are Decision
Tree, Naive Bayesian, Instance Based Learning, Decision Table, One
Rule, Random Tree and K-star. Among these methods, three of them
are studied in more details. The results show that machine learning
is a feasible alternative for keystroke authentication. Compared to
the conventional Nearest Neighbour method in the recent research,
learning methods especially Decision Tree can be more accurate. In
addition, the experiment results reveal that 3-Grams is more accurate
than 2-Grams and 4-Grams for feature extraction. Also, combination
of attributes tend to result higher accuracy.
Abstract: In this paper, the effect of bolt clamping force on the fatigue behavior of bolted single lap joints of aluminum alloy 2024- T3 have been studied using numerical finite element method. To do so, a three dimensional model according to the bolted single lap joint has been created and numerical analysis has been carried out using finite element based package. Then the stress distribution and also the slip amplitudes have been calculated in the critical regions and the outcome have been compared with the available experimental fatigue tests results. The numerical results show that in low applied clamping force, the fatigue failure of the specimens occur around the stress concentration location (the bolted hole edge) due to the tensile stresses and thus fatigue crack propagation, but with increase of the clamping force, the fatigue life increases and the cracks nucleate and propagate far from the hole edge because of fretting fatigue. In other words, with the further increase of clamping force value of the joint, the fatigue life reduces due to occurrence of the fretting fatigue in the critical location where the slip amplitude is within its critical occurs earlier.
Abstract: Topology Optimization is a defined as the method of
determining optimal distribution of material for the assumed design
space with functionality, loads and boundary conditions [1].
Topology optimization can be used to optimize shape for the
purposes of weight reduction, minimizing material requirements or
selecting cost effective materials [2]. Topology optimization has been
implemented through the use of finite element methods for the
analysis, and optimization techniques based on the method of moving
asymptotes, genetic algorithms, optimality criteria method, level sets
and topological derivatives. Case study of Typical “Fuselage design"
is considered for this paper to explain the benefits of Topology
Optimization in the design cycle. A cylindrical shell is assumed as
the design space and aerospace standard pay loads were applied on
the fuselage with wing attachments as constraints. Then topological
optimization is done using Finite Element (FE) based software. This
optimization results in the structural concept design which satisfies
all the design constraints using minimum material.
Abstract: This paper explores the extent of the gap in poverty rates between immigrant and native households in Spanish regions and assess to what extent regional differences in individual and contextual characteristics can explain the divergences in such a gap. By using multilevel techniques and European Union Survey on Income and Living Conditions, we estimate immigrant households experiments an increase of 76 per cent in the odds of being poor compared with a native one when we control by individual variables. In relation to regional differences in the risk of poverty, regionallevel variables have higher effect in the reduction of these differences than individual variables.
Abstract: One of the most important applications of
wireless sensor networks is data collection. This paper
proposes as efficient approach for data collection in wireless
sensor networks by introducing Member Forward List. This list
includes the nodes with highest priority for forwarding the data.
When a node fails or dies, this list is used to select the next node
with higher priority. The benefit of this node is that it prevents
the algorithm from repeating when a node fails or dies. The
results show that Member Forward List decreases power
consumption and latency in wireless sensor networks.
Abstract: This paper presents the design and implementation of CASTE, a Cloud-based automatic software test environment. We first present the architecture of CASTE, then the main packages and classes of it are described in detail. CASTE is built upon a private Infrastructure as a Service platform. Through concentrated resource management of virtualized testing environment and automatic execution control of test scripts, we get a better solution to the testing resource utilization and test automation problem. Experiments on CASTE give very appealing results.
Abstract: Real-time hand tracking is a challenging task in many
computer vision applications such as gesture recognition. This paper
proposes a robust method for hand tracking in a complex environment
using Mean-shift analysis and Kalman filter in conjunction with 3D
depth map. The depth information solve the overlapping problem
between hands and face, which is obtained by passive stereo measuring
based on cross correlation and the known calibration data of
the cameras. Mean-shift analysis uses the gradient of Bhattacharyya
coefficient as a similarity function to derive the candidate of the hand
that is most similar to a given hand target model. And then, Kalman
filter is used to estimate the position of the hand target. The results
of hand tracking, tested on various video sequences, are robust to
changes in shape as well as partial occlusion.
Abstract: Cavitation in pumps is known as the formation of
vapor bubbles due to pressure drop and collapsing these bubbles. In
some conditions, it has been observed that the formation of bubbles
occurs at the pressure side of centrifugal pump blades. In this study,
the formation of bubbles at the pressure side of blades has been
investigated. Water is used in this study as the fluid and performance
curves were depicted for different flow rates in an approximately
constant speed. The results show that when a centrifugal pump works
in low flow rates, a secondary flow namely recirculation starts to
begin. In this condition, separation of flow increases which causes
vortex formation and local pressure drop and eventually the
formation of vapor bubbles starts.
Abstract: Sequential pattern mining is a challenging task in data mining area with large applications. One among those applications is mining patterns from weblog. Recent times, weblog is highly dynamic and some of them may become absolute over time. In addition, users may frequently change the threshold value during the data mining process until acquiring required output or mining interesting rules. Some of the recently proposed algorithms for mining weblog, build the tree with two scans and always consume large time and space. In this paper, we build Revised PLWAP with Non-frequent Items (RePLNI-tree) with single scan for all items. While mining sequential patterns, the links related to the nonfrequent items are not considered. Hence, it is not required to delete or maintain the information of nodes while revising the tree for mining updated transactions. The algorithm supports both incremental and interactive mining. It is not required to re-compute the patterns each time, while weblog is updated or minimum support changed. The performance of the proposed tree is better, even the size of incremental database is more than 50% of existing one. For evaluation purpose, we have used the benchmark weblog dataset and found that the performance of proposed tree is encouraging compared to some of the recently proposed approaches.
Abstract: Sequences of execution of algorithms in an interactive
manner using multimedia tools are employed in this paper. It helps to
realize the concept of fundamentals of algorithms such as searching
and sorting method in a simple manner. Visualization gains more
attention than theoretical study and it is an easy way of learning
process. We propose methods for finding runtime sequence of each
algorithm in an interactive way and aims to overcome the drawbacks
of the existing character systems. System illustrates each and every
step clearly using text and animation. Comparisons of its time
complexity have been carried out and results show that our approach
provides better perceptive of algorithms.
Abstract: Exploring an autistic child in Elementary school is a
difficult task that must be fully thought out and the teachers should
be aware of the many challenges they face raising their child
especially the behavioral problems of autistic children. Hence there
arises a need for developing Artificial intelligence (AI)
Contemporary Techniques to help diagnosis to discover autistic
people.
In this research, we suggest designing architecture of expert
system that combine Cognitive Maps (CM) with Case Based
Reasoning technique (CBR) in order to reduce time and costs of
traditional diagnosis process for the early detection to discover
autistic children. The teacher is supposed to enter child's information
for analyzing by CM module. Then, the reasoning processor would
translate the output into a case to be solved a current problem by
CBR module. We will implement a prototype for the model as a
proof of concept using java and MYSQL.
This will be provided a new hybrid approach that will achieve new
synergies and improve problem solving capabilities in AI. And we
will predict that will reduce time, costs, the number of human errors
and make expertise available to more people who want who want to
serve autistic children and their families.