Abstract: Efficient utilization of existing water is a pressing
need for Pakistan. Due to rising population, reduction in present
storage capacity and poor delivery efficiency of 30 to 40% from
canal. A study to evaluate an irrigation system in the cotton-wheat
zone of Pakistan, after the watercourse lining was conducted. The
study is made on the basis of cropping pattern and salinity to evaluate
the system. This study employed an index-based approach of using
Geographic information system with field data. The satellite images
of different years were use to examine the effective area. Several
combinations of the ratio of signals received in different spectral
bands were used for development of this index. Near Infrared and
Thermal IR spectral bands proved to be most effective as this
combination helped easy detection of salt affected area and cropping
pattern of the study area. Result showed that 9.97% area under
salinity in 1992, 9.17% in 2000 and it left 2.29% in year 2005.
Similarly in 1992, 45% area is under vegetation it improves to 56%
and 65% in 2000 and 2005 respectively. On the basis of these results
evaluation is done 30% performance is increase after the watercourse
improvement.
Abstract: The problem of updating damped gyroscopic systems using measured modal data can be mathematically formulated as following two problems. Problem I: Given Ma ∈ Rn×n, Λ = diag{λ1, ··· , λp} ∈ Cp×p, X = [x1, ··· , xp] ∈ Cn×p, where p
Abstract: Context awareness is a capability whereby mobile
computing devices can sense their physical environment and adapt
their behavior accordingly. The term context-awareness, in
ubiquitous computing, was introduced by Schilit in 1994 and has
become one of the most exciting concepts in early 21st-century
computing, fueled by recent developments in pervasive computing
(i.e. mobile and ubiquitous computing). These include computing
devices worn by users, embedded devices, smart appliances, sensors
surrounding users and a variety of wireless networking technologies.
Context-aware applications use context information to adapt
interfaces, tailor the set of application-relevant data, increase the
precision of information retrieval, discover services, make the user
interaction implicit, or build smart environments. For example: A
context aware mobile phone will know that the user is currently in a
meeting room, and reject any unimportant calls. One of the major
challenges in providing users with context-aware services lies in
continuously monitoring their contexts based on numerous sensors
connected to the context aware system through wireless
communication. A number of context aware frameworks based on
sensors have been proposed, but many of them have neglected the
fact that monitoring with sensors imposes heavy workloads on
ubiquitous devices with limited computing power and battery. In this
paper, we present CALEEF, a lightweight and energy efficient
context aware framework for resource limited ubiquitous devices.
Abstract: Knowledge discovery from text and ontology learning
are relatively new fields. However their usage is extended in many
fields like Information Retrieval (IR) and its related domains. Human
Plausible Reasoning based (HPR) IR systems for example need a
knowledge base as their underlying system which is currently made
by hand. In this paper we propose an architecture based on ontology
learning methods to automatically generate the needed HPR
knowledge base.
Abstract: A thin coating of hexamethyldisiloxane and subsequent O2-plasma treatment was performed on mirror-polished titanium in order to regulate the wide range of wettability including 106 and almost 0 degrees of contact angles. The adsorption behavior of
fibronectin and albumin in both individual and competitive mode,
and initial attachment of fibroblasts and osteoblasts were investigated.
Individually, fibronectin adsorption showed a biphasic inclination, whereas albumin showed greater adsorption to hydrophobic surfaces.
In competitive mode, in solution containing both fibronectin and albumin, fibronectin showed greater adsorption on hydrophilic
surfaces, whereas Alb predominantly adsorbed on hydrophobic
surfaces. Initial attachment of both cells increased with increase in
surface wettability, in particular, on super-hydrophilic surface, which
correlated well with fibronectin adsorption in competitive mode.
These results suggest that a cold plasma-surface modification enabled
to regulate the surface wettability, and fibronectin adsorption may be
responsible for increasing cell adhesion on hydrophilic surfaces in a
body fluid
Abstract: In this paper the General Game problem is described.
In this problem the competition or cooperation dilemma occurs as the
two basic types of strategies. The strategy possibilities have been
analyzed for finding winning strategy in uncertain situations (no
information about the number of players and their strategy types).
The winning strategy is missing, but a good solution can be found by
simulation by varying the ratio of the two types of strategies. This
new method has been used in a real contest with human players,
where the created strategies by simulation have reached very good
ranks. This construction can be applied in other real social games as
well.
Abstract: Finger spelling is an art of communicating by signs
made with fingers, and has been introduced into sign language to serve
as a bridge between the sign language and the verbal language.
Previous approaches to finger spelling recognition are classified into
two categories: glove-based and vision-based approaches. The
glove-based approach is simpler and more accurate recognizing work
of hand posture than vision-based, yet the interfaces require the user to
wear a cumbersome and carry a load of cables that connected the
device to a computer. In contrast, the vision-based approaches provide
an attractive alternative to the cumbersome interface, and promise
more natural and unobtrusive human-computer interaction. The
vision-based approaches generally consist of two steps: hand
extraction and recognition, and two steps are processed independently.
This paper proposes real-time vision-based Korean finger spelling
recognition system by integrating hand extraction into recognition.
First, we tentatively detect a hand region using CAMShift algorithm.
Then fill factor and aspect ratio estimated by width and height
estimated by CAMShift are used to choose candidate from database,
which can reduce the number of matching in recognition step. To
recognize the finger spelling, we use DTW(dynamic time warping)
based on modified chain codes, to be robust to scale and orientation
variations. In this procedure, since accurate hand regions, without
holes and noises, should be extracted to improve the precision, we use
graph cuts algorithm that globally minimize the energy function
elegantly expressed by Markov random fields (MRFs). In the
experiments, the computational times are less than 130ms, and the
times are not related to the number of templates of finger spellings in
database, as candidate templates are selected in extraction step.
Abstract: Dielectric sheet perturbation to the dominant TE111
mode resonant frequency of a circular cavity is studied and presented
in this paper. The dielectric sheet, placed at the middle of the airfilled
cavity, introduces discontinuities and disturbs the configuration
of electromagnetic fields in the cavity. For fixed dimensions of cavity
and fixed thickness of the loading dielectric, the dominant resonant
frequency varies quite linearly with the permittivity of the dielectric.
This quasi-linear relationship is plotted using Maple software and
verified using 3D electromagnetic simulations. Two probes are used
in the simulation for wave excitation into and from the cavity. The
best length of probe is found to be 3 mm, giving the closest resonant
frequency to the one calculated using Maple. A total of fourteen
different dielectrics of permittivity ranging from 1 to 12.9 are tested
one by one in the simulation. The works show very close agreement
between the results from Maple and the simulation. A constant
difference of 0.04 GHz is found between the resonant frequencies
collected during simulation and the ones from Maple. The success of
this project may lead to the possibility of using the middle loaded
cavity at TE111 mode as a microwave non-destructive testing of solid
materials.
Abstract: Localization is one of the critical issues in the field of
robot navigation. With an accurate estimate of the robot pose, robots will be capable of navigating in the environment autonomously and efficiently. In this paper, a hybrid Distributed Vision System (DVS)
for robot localization is presented. The presented approach integrates
odometry data from robot and images captured from overhead cameras
installed in the environment to help reduce possibilities of fail
localization due to effects of illumination, encoder accumulated errors,
and low quality range data. An odometry-based motion model is applied to predict robot poses, and robot images captured by overhead
cameras are then used to update pose estimates with HSV histogram-based measurement model. Experiment results show the
presented approach could localize robots in a global world coordinate system with localization errors within 100mm.
Abstract: Social bookmarking is an environment in which
the user gradually changes interests over time so that the tag
data associated with the current temporal period is usually more
important than tag data temporally far from the current period.
This implies that in the social tagging system, the newly tagged
items by the user are more relevant than older items. This study
proposes a novel recommender system that considers the users-
recent tag preferences. The proposed system includes the
following stages: grouping similar users into clusters using an
E-M clustering algorithm, finding similar resources based on
the user-s bookmarks, and recommending the top-N items to
the target user. The study examines the system-s information
retrieval performance using a dataset from del.icio.us, which is
a famous social bookmarking web site. Experimental results
show that the proposed system is better and more effective than
traditional approaches.
Abstract: The control of sprayer boom undesired vibrations pose a great challenge to investigators due to various disturbances and conditions. Sprayer boom movements lead to reduce of spread efficiency and crop yield. This paper describes the design of a novel control method for an active suspension system applying proportional-integral-derivative (PID) controller with an active force control (AFC) scheme integration of an iterative learning algorithm employed to a sprayer boom. The iterative learning as an intelligent method is principally used as a method to calculate the best value of the estimated inertia of the sprayer boom needed for the AFC loop. Results show that the proposed AFC-based scheme performs much better than the standard PID control technique. Also, this shows that the system is more robust and accurate.
Abstract: In the paper we submit the non-local modification of
kinetic Smoluchowski equation for binary aggregation applying to
dispersed media having memory. Our supposition consists in that that
intensity of evolution of clusters is supposed to be a function of the
product of concentrations of the lowest orders clusters at different
moments. The new form of kinetic equation for aggregation is
derived on the base of the transfer kernels approach. This approach
allows considering the influence of relaxation times hierarchy on
kinetics of aggregation process in media with memory.
Abstract: Transportation is of great importance in the current
life of human beings. The transportation system plays many roles,
from economical development to after-catastrophe aids such as
rescue operation in the first hours and days after an earthquake. In
after earthquakes response phase, transportation system acts as a
basis for ground operations including rescue and relief operation,
food providing for victims and etc. It is obvious that partial or
complete obstruction of this system results in the stop of these
operations. Bridges are one of the most important elements of
transportation network. Failure of a bridge, in the most optimistic
case, cuts the relation between two regions and in more developed
countries, cuts the relation of numerous regions. In this paper, to
evaluate the vulnerability and estimate the damage level of Tehran
bridges, HAZUS method, developed by Federal Emergency
Management Agency (FEMA) with the aid of National Institute of
Building Science (NIBS), is used for the first time in Iran. In this
method, to evaluate the collapse probability, fragility curves are
used. Iran is located on seismic belt and thus, it is vulnerable to
earthquakes. Thus, the study of the probability of bridge collapses, as
an important part of transportation system, during earthquakes is of
great importance. The purpose of this study is to provide fragility
curves for Gisha Bridge, one of the longest steel bridges in Tehran,
as an important lifeline element. Besides, the damage probability for
this bridge during a specific earthquake, introduced as scenario
earthquakes, is calculated. The fragility curves show that for the
considered scenario, the probability of occurrence of complete
collapse for the bridge is 8.6%.
Abstract: The modified Arcan fixture was used in order to
investigate the mixed mode fracture properties of high strength steel
butt weld through experimental and numerical analysis. The fixture
consisted of a central section with "butterfly-shaped" specimen that
had central crack. The specimens were under pure mode I (opening),
pure mode II (shearing) and all in plane mixed mode loading angles
starting from 0 to 90 degrees. The geometric calibration factors were
calculated with the aid of finite element analysis for various loading
mode and different crack length (0.45≤ a/w ≤0.55) and the critical
fracture loads obtained experimentally. The critical fracture
toughness (KIC & KIIC) estimated with experimental and numerical
analysis under mixed mode loading conditions.
Abstract: In this study, participants with adjustment disorder with depressed mood (aged 18-54 years) with mild depression (N=18), severe depression (N=12) were compared with healthy controls (N=20) on the Multidimensional Aptitude Battery (MAB) a cognitive performance test. Using One Way Analysis of Variance and Matched Sample t-test. The results of the analysis shows that severely depressed participants performed poorly on the cognitive performance test relative to controls, however there were no significant differences on the cognitive performance test scores between the severely depressed and the mildly depressed. In addition, performance on the non-verbal performance subtest was poorer than that of the verbal subtest, suggesting that depression affects the executive functions of the person.
Abstract: Many measures have been proposed for machine
translation evaluation (MTE) while little research has been done on
the performance of MTE methods. This paper is an effort for MTE
performance analysis. A general frame is proposed for the description
of the MTE measure and the test suite, including whether the
automatic measure is consistent with human evaluation, whether
different results from various measures or test suites are consistent,
whether the content of the test suite is suitable for performance
evaluation, the degree of difficulty of the test suite and its influence
on the MTE, the relationship of MTE result significance and the size
of the test suite, etc. For a better clarification of the frame, several
experiment results are analyzed relating human evaluation, BLEU
evaluation, and typological MTE. A visualization method is
introduced for better presentation of the results. The study aims for
aid in construction of test suite and method selection in MTE
practice.
Abstract: This paper focuses on a technique for identifying the geological boundary of the ground strata in front of a tunnel excavation site using the first order adjoint method based on the optimal control theory. The geological boundary is defined as the boundary which is different layers of elastic modulus. At tunnel excavations, it is important to presume the ground situation ahead of the cutting face beforehand. Excavating into weak strata or fault fracture zones may cause extension of the construction work and human suffering. A theory for determining the geological boundary of the ground in a numerical manner is investigated, employing excavating blasts and its vibration waves as the observation references. According to the optimal control theory, the performance function described by the square sum of the residuals between computed and observed velocities is minimized. The boundary layer is determined by minimizing the performance function. The elastic analysis governed by the Navier equation is carried out, assuming the ground as an elastic body with linear viscous damping. To identify the boundary, the gradient of the performance function with respect to the geological boundary can be calculated using the adjoint equation. The weighed gradient method is effectively applied to the minimization algorithm. To solve the governing and adjoint equations, the Galerkin finite element method and the average acceleration method are employed for the spatial and temporal discretizations, respectively. Based on the method presented in this paper, the different boundary of three strata can be identified. For the numerical studies, the Suemune tunnel excavation site is employed. At first, the blasting force is identified in order to perform the accuracy improvement of analysis. We identify the geological boundary after the estimation of blasting force. With this identification procedure, the numerical analysis results which almost correspond with the observation data were provided.
Abstract: This paper considers a multi criteria cell formation
problem in Cellular Manufacturing System (CMS). Minimizing the
number of voids and exceptional elements in cells simultaneously are
two proposed objective functions. This problem is an Np-hard
problem according to the literature, and therefore, we can-t find the
optimal solution by an exact method. In this paper we developed two
ant algorithms, Ant Colony Optimization (ACO) and Max-Min Ant
System (MMAS), based on Data Envelopment Analysis (DEA). Both
of them try to find the efficient solutions based on efficiency concept
in DEA. Each artificial ant is considered as a Decision Making Unit
(DMU). For each DMU we considered two inputs, the values of
objective functions, and one output, the value of one for all of them.
In order to evaluate performance of proposed methods we provided
an experimental design with some empirical problem in three
different sizes, small, medium and large. We defined three different
criteria that show which algorithm has the best performance.
Abstract: With the extensive inclusion of document, especially
text, in the business systems, data mining does not cover the full
scope of Business Intelligence. Data mining cannot deliver its impact
on extracting useful details from the large collection of unstructured
and semi-structured written materials based on natural languages.
The most pressing issue is to draw the potential business intelligence
from text. In order to gain competitive advantages for the business, it
is necessary to develop the new powerful tool, text mining, to expand
the scope of business intelligence.
In this paper, we will work out the strong points of text mining in
extracting business intelligence from huge amount of textual
information sources within business systems. We will apply text
mining to each stage of Business Intelligence systems to prove that
text mining is the powerful tool to expand the scope of BI. After
reviewing basic definitions and some related technologies, we will
discuss the relationship and the benefits of these to text mining. Some
examples and applications of text mining will also be given. The
motivation behind is to develop new approach to effective and
efficient textual information analysis. Thus we can expand the scope
of Business Intelligence using the powerful tool, text mining.
Abstract: In this paper, we propose an improved 3D star skeleton
technique, which is a suitable skeletonization for human posture representation
and reflects the 3D information of human posture.
Moreover, the proposed technique is simple and then can be performed
in real-time. The existing skeleton construction techniques, such as
distance transformation, Voronoi diagram, and thinning, focus on the
precision of skeleton information. Therefore, those techniques are not
applicable to real-time posture recognition since they are computationally
expensive and highly susceptible to noise of boundary. Although
a 2D star skeleton was proposed to complement these problems,
it also has some limitations to describe the 3D information of the
posture. To represent human posture effectively, the constructed skeleton
should consider the 3D information of posture. The proposed 3D
star skeleton contains 3D data of human, and focuses on human action
and posture recognition. Our 3D star skeleton uses the 8 projection
maps which have 2D silhouette information and depth data of human
surface. And the extremal points can be extracted as the features of 3D
star skeleton, without searching whole boundary of object. Therefore,
on execution time, our 3D star skeleton is faster than the “greedy" 3D
star skeleton using the whole boundary points on the surface. Moreover,
our method can offer more accurate skeleton of posture than the
existing star skeleton since the 3D data for the object is concerned.
Additionally, we make a codebook, a collection of representative 3D
star skeletons about 7 postures, to recognize what posture of constructed
skeleton is.