Abstract: This paper presents a solution for a robotic
manipulation problem. We formulate the problem as combining
target identification, tracking and interception. The task in our
solution is sensing a target on a conveyor belt and then intercepting
robot-s end-effector at a convenient rendezvous point. We used
an object recognition method which identifies the target and finds
its position from visualized scene picture, then the robot system
generates a solution for rendezvous problem using the target-s initial
position and belt velocity . The interception of the target and the
end-effector is executed at a convenient rendezvous point along the
target-s calculated trajectory. Experimental results are obtained using
a real platform with an industrial robot and a vision system over it.
Abstract: In the past, there were many bridge-s collapses due to
lack of bridge structural capacity information. Most of concrete
bridge health was relied on information from visual inspection, which
sometime was inadequate. This study was conducted in order to
investigate relationship between bridge structural condition and
bridge visual condition. This study was a part of a big project
conducted at Department of Highways of Thailand. In this study, 31
bridges including slab-type bridges, plank-girder bridges, prestressed
box-beam bridges, prestressed I-girder bridges and prestressed multibeam
bridges were selected for visual inspection and load test. It was
found a positive correlation between bridge appearance and bridge-s
load carrying capacity. However, statistical characteristic revealed
low correlation between them.
Abstract: The concerns of education and practice of architecture
do not necessarily overlap. Indeed the gap between them could be
seen increasingly and less frequently bridged. We suggest that
changing in architecture education and clarifying the relationship
between these two can help to find and address the opportunities and
unique positions to bridge this gulf.
Abstract: A novel feature selection strategy to improve the recognition accuracy on the faces that are affected due to nonuniform illumination, partial occlusions and varying expressions is proposed in this paper. This technique is applicable especially in scenarios where the possibility of obtaining a reliable intra-class probability distribution is minimal due to fewer numbers of training samples. Phase congruency features in an image are defined as the points where the Fourier components of that image are maximally inphase. These features are invariant to brightness and contrast of the image under consideration. This property allows to achieve the goal of lighting invariant face recognition. Phase congruency maps of the training samples are generated and a novel modular feature selection strategy is implemented. Smaller sub regions from a predefined neighborhood within the phase congruency images of the training samples are merged to obtain a large set of features. These features are arranged in the order of increasing distance between the sub regions involved in merging. The assumption behind the proposed implementation of the region merging and arrangement strategy is that, local dependencies among the pixels are more important than global dependencies. The obtained feature sets are then arranged in the decreasing order of discriminating capability using a criterion function, which is the ratio of the between class variance to the within class variance of the sample set, in the PCA domain. The results indicate high improvement in the classification performance compared to baseline algorithms.
Abstract: In Blind Source Separation (BSS) processing, taking
advantage of scaling factor indetermination and based on the floatingpoint
representation, we propose a scaling technique applied to the
separation matrix, to avoid the saturation or the weakness in the
recovered source signals. This technique performs an Automatic Gain
Control (AGC) in an on-line BSS environment. We demonstrate
the effectiveness of this technique by using the implementation of
a division free BSS algorithm with two input, two output. This
technique is computationally cheaper and efficient for a hardware
implementation.
Abstract: We describe an effective method for image encryption
which employs magnitude and phase manipulation using carrier
images. Although it involves traditional methods like magnitude and
phase encryptions, the novelty of this work lies in deploying the
concept of carrier images for encryption purpose. To this end, a
carrier image is randomly chosen from a set of stored images. One
dimensional (1-D) discrete Fourier transform (DFT) is then carried
out on the original image to be encrypted along with the carrier
image. Row wise spectral addition and scaling is performed between
the magnitude spectra of the original and carrier images by randomly
selecting the rows. Similarly, row wise phase addition and scaling is
performed between the original and carrier images phase spectra by
randomly selecting the rows. The encrypted image obtained by these
two operations is further subjected to one more level of magnitude
and phase manipulation using another randomly chosen carrier image
by 1-D DFT along the columns. The resulting encrypted image is
found to be fully distorted, resulting in increasing the robustness
of the proposed work. Further, applying the reverse process at the
receiver, the decrypted image is found to be distortionless.
Abstract: Supply network management adopts a systematic
and integrative approach to managing the operations and
relationships of various parties in a supply network. The objective
of the manufactures in their supply network is to reduce inventory
costs and increase customer satisfaction levels. One way of doing
that is to synchronize delivery performance. A supply network can
be described by nodes representing the companies and the links
(relationships) between these nodes. Uncertainty in delivery time
depends on type of network relationship between suppliers. The
problem is to understand how the individual uncertainties influence
the total uncertainty of the network and identify those parts of the
network, which has the highest potential for improving the total
delivery time uncertainty.
Abstract: Bio-electrical responses obtained from freshwater
sediments by employing microbial fuel cell (MFC) technology were
investigated in this experimental study. During the electricity
generation, organic matter in the sediment was microbially oxidized
under anaerobic conditions with an electrode serving as a terminal
electron acceptor. It was found that the sediment organic matter
(SOM) associated with electrochemically-active electrodes became
more humified, aromatic, and polydispersed, and had a higher average
molecular weight, together with the decrease in the quantity of SOM.
The alteration of characteristics of the SOM was analogous to that
commonly observed in the early stage of SOM diagenetic process (i.e.,
humification). These findings including an elevation of the sediment
redox potential present a possibility of the MFC technology as a new
soil/sediment remediation technique based on its potential benefits:
non-destructive electricity generation and bioremediation.
Abstract: Iris-based biometric authentication is gaining importance
in recent times. Iris biometric processing however, is a complex
process and computationally very expensive. In the overall processing
of iris biometric in an iris-based biometric authentication system,
feature processing is an important task. In feature processing, we extract
iris features, which are ultimately used in matching. Since there
is a large number of iris features and computational time increases
as the number of features increases, it is therefore a challenge to
develop an iris processing system with as few as possible number of
features and at the same time without compromising the correctness.
In this paper, we address this issue and present an approach to feature
extraction and feature matching process. We apply Daubechies D4
wavelet with 4 levels to extract features from iris images. These
features are encoded with 2 bits by quantizing into 4 quantization
levels. With our proposed approach it is possible to represent an
iris template with only 304 bits, whereas existing approaches require
as many as 1024 bits. In addition, we assign different weights to
different iris region to compare two iris templates which significantly
increases the accuracy. Further, we match the iris template based on
a weighted similarity measure. Experimental results on several iris
databases substantiate the efficacy of our approach.
Abstract: Skin color can provide a useful and robust cue
for human-related image analysis, such as face detection,
pornographic image filtering, hand detection and tracking,
people retrieval in databases and Internet, etc. The major
problem of such kinds of skin color detection algorithms is
that it is time consuming and hence cannot be applied to a real
time system. To overcome this problem, we introduce a new
fast technique for skin detection which can be applied in a real
time system. In this technique, instead of testing each image
pixel to label it as skin or non-skin (as in classic techniques),
we skip a set of pixels. The reason of the skipping process is
the high probability that neighbors of the skin color pixels are
also skin pixels, especially in adult images and vise versa. The
proposed method can rapidly detect skin and non-skin color
pixels, which in turn dramatically reduce the CPU time
required for the protection process. Since many fast detection
techniques are based on image resizing, we apply our
proposed pixel skipping technique with image resizing to
obtain better results. The performance evaluation of the
proposed skipping and hybrid techniques in terms of the
measured CPU time is presented. Experimental results
demonstrate that the proposed methods achieve better result
than the relevant classic method.
Abstract: The purpose of this work is to present the potential of
solar energy in Zarqa region. The solar radiation along year 2009 was
obtained from Pyranometer which measures the global radiation over
horizontal surfaces. Solar data in several different forms, over period
of 5 minutes, hour-by-hour, daily and monthly data radiation have
been presented. Briefly, the yearly global solar radiation in Zarqa is
7297.5 MJ/m2 (2027 kWh/m²) and the average annual solar radiation
per day is 20 MJ/m2 (5.5 Kwh/m2). More specifically, the average
annual solar radiation per day is 12.9 MJ/m2 (3.57 Kwh/m2) in winter
and 25 MJ/m2 (7 Kwh/m2) in summer.
Abstract: Although the field of parametric Pattern Recognition (PR) has been thoroughly studied for over five decades, the use of the Order Statistics (OS) of the distributions to achieve this has not been reported. The pioneering work on using OS for classification was presented in [1] for the Uniform distribution, where it was shown that optimal PR can be achieved in a counter-intuitive manner, diametrically opposed to the Bayesian paradigm, i.e., by comparing the testing sample to a few samples distant from the mean. This must be contrasted with the Bayesian paradigm in which, if we are allowed to compare the testing sample with only a single point in the feature space from each class, the optimal strategy would be to achieve this based on the (Mahalanobis) distance from the corresponding central points, for example, the means. In [2], we showed that the results could be extended for a few symmetric distributions within the exponential family. In this paper, we attempt to extend these results significantly by considering asymmetric distributions within the exponential family, for some of which even the closed form expressions of the cumulative distribution functions are not available. These distributions include the Rayleigh, Gamma and certain Beta distributions. As in [1] and [2], the new scheme, referred to as Classification by Moments of Order Statistics (CMOS), attains an accuracy very close to the optimal Bayes’ bound, as has been shown both theoretically and by rigorous experimental testing.
Abstract: The present study was carried out to evaluate the
nutritional value of sorghum flour during processing of injera
(unleavened thick bread). The proximate composition of sorghum
flour before and after fermentation and that of injera was determined.
Compared to the raw flour and fermented one, injera had low protein
(11.55%), ash (1.57%) and fat (2.40%) contents but high in fiber
content. Moreover, injera was found to have significantly (P ≤ 0.05)
higher energy (389.08 Kcal/100g) compared to raw and fermented
sorghum flour. Injera contained lower levels of anti-nutritional
factors (polyphenols, phytate and tannins) compared to raw and
fermented sorghum. Also it was found to be rich in Ca
(4.75mg/100g), Fe (3.95 mg/100g), and Cu (0.7 mg/100g) compared
to that of raw and fermented flour. Moreover, both the extractable
minerals and protein digestibility were high for injera due to low
amount of anti-nutrients. Injera was found to contain an appreciable
amount of amino acids except arginine and tyrosine.
Abstract: Synchronization between 0.1 Hz oscillations in heart rate and blood pressure is studied and its change during vertical tilt is evaluated in 37 myocardial infarction patients. Two groups of patients are identified with decreased and increased, respectively, synchronization of the studied oscillations as a response to a tilt test. It is shown that assessment of synchronization of 0.1 Hz oscillations as a response to vertical tilt can be used as a guideline for selecting optimal dose of beta-blocker treatment in post-myocardial infarction patients.
Abstract: The information on the Web increases tremendously.
A number of search engines have been developed for searching Web
information and retrieving relevant documents that satisfy the
inquirers needs. Search engines provide inquirers irrelevant
documents among search results, since the search is text-based rather
than semantic-based. Information retrieval research area has
presented a number of approaches and methodologies such as
profiling, feedback, query modification, human-computer interaction,
etc for improving search results. Moreover, information retrieval has
employed artificial intelligence techniques and strategies such as
machine learning heuristics, tuning mechanisms, user and system
vocabularies, logical theory, etc for capturing user's preferences and
using them for guiding the search based on the semantic analysis
rather than syntactic analysis. Although a valuable improvement has
been recorded on search results, the survey has shown that still
search engines users are not really satisfied with their search results.
Using ontologies for semantic-based searching is likely the key
solution. Adopting profiling approach and using ontology base
characteristics, this work proposes a strategy for finding the exact
meaning of the query terms in order to retrieve relevant information
according to user needs. The evaluation of conducted experiments
has shown the effectiveness of the suggested methodology and
conclusion is presented.
Abstract: The aim of this paper is to propose a dynamic integrated approach, based on modularity concept and on the business ecosystem approach, that exploit different eBusiness services for SMEs under an open business network platform. The adoption of this approach enables firms to collaborate locally for delivering the best product/service to the customers as well as globally by accessing international markets, interrelate directly with the customers, create relationships and collaborate with worldwide actors. The paper will be structured as following: We will start by offering an overview of the state of the art of eBusiness platforms among SME of food and tourism firms and then we discuss the main drawbacks that characterize them. The digital business ecosystem approach and the modularity concept will be described as the theoretical ground in which our proposed integrated model is rooted. Finally, the proposed model along with a discussion of the main value creation potentialities it might create for SMEs will be presented.
Abstract: The very nonlinear nature of the generator and system
behaviour following a severe disturbance precludes the use of
classical linear control technique. In this paper, a new approach of
nonlinear control is proposed for transient and steady state stability
analysis of a synchronous generator. The control law of the generator
excitation is derived from the basis of Lyapunov stability criterion.
The overall stability of the system is shown using Lyapunov
technique. The application of the proposed controller to simulated
generator excitation control under a large sudden fault and wide
range of operating conditions demonstrates that the new control
strategy is superior to conventional automatic voltage regulator
(AVR), and show very promising results.
Abstract: In this paper, the Fuzzy Autocatalytic Set (FACS) is
composed into Omega Algebra by embedding the membership value
of fuzzy edge connectivity using the property of transitive affinity.
Then, the Omega Algebra of FACS is a transformation semigroup
which is a special class of semigroup is shown.
Abstract: Several researchers have proposed methods about
combination of Genetic Algorithm (GA) and Fuzzy Logic (the use of
GA to obtain fuzzy rules and application of fuzzy logic in
optimization of GA). In this paper, we suggest a new method in
which fuzzy decision making is used to improve the performance of
genetic algorithm. In the suggested method, we determine the alleles
that enhance the fitness of chromosomes and try to insert them to the
next generation.
In this algorithm we try to present an innovative vaccination in the
process of reproduction in genetic algorithm, with considering the
trade off between exploration and exploitation.
Abstract: The Constraints imposed by non-thermal
leptogenesis on the survival of the neutrino mass models describing
the presently available neutrino mass patterns, are studied
numerically. We consider the Majorana CP violating phases coming
from right-handed Majorana mass matrices to estimate the baryon
asymmetry of the universe, for different neutrino mass models
namely quasi-degenerate, inverted hierarchical and normal
hierarchical models, with tribimaximal mixings. Considering two
possible diagonal forms of Dirac neutrino mass matrix as either
charged lepton or up-quark mass matrix, the heavy right-handed
mass matrices are constructed from the light neutrino mass matrix.
Only the normal hierarchical model leads to the best predictions of
baryon asymmetry of the universe, consistent with observations in
non-thermal leptogenesis scenario.