Abstract: The paper describes a knowledge based system for
analysis of microscopic wear particles. Wear particles contained in
lubricating oil carry important information concerning machine
condition, in particular the state of wear. Experts (Tribologists) in the
field extract this information to monitor the operation of the machine
and ensure safety, efficiency, quality, productivity, and economy of
operation. This procedure is not always objective and it can also be
expensive. The aim is to classify these particles according to their
morphological attributes of size, shape, edge detail, thickness ratio,
color, and texture, and by using this classification thereby predict
wear failure modes in engines and other machinery. The attribute
knowledge links human expertise to the devised Knowledge Based
Wear Particle Analysis System (KBWPAS). The system provides an
automated and systematic approach to wear particle identification
which is linked directly to wear processes and modes that occur in
machinery. This brings consistency in wear judgment prediction
which leads to standardization and also less dependence on
Tribologists.
Abstract: This paper presents the novel Rao-Blackwellised
particle filter (RBPF) for mobile robot simultaneous localization and
mapping (SLAM) using monocular vision. The particle filter is
combined with unscented Kalman filter (UKF) to extending the path
posterior by sampling new poses that integrate the current observation
which drastically reduces the uncertainty about the robot pose. The
landmark position estimation and update is also implemented through
UKF. Furthermore, the number of resampling steps is determined
adaptively, which seriously reduces the particle depletion problem,
and introducing the evolution strategies (ES) for avoiding particle
impoverishment. The 3D natural point landmarks are structured with
matching Scale Invariant Feature Transform (SIFT) feature pairs. The
matching for multi-dimension SIFT features is implemented with a
KD-Tree in the time cost of O(log2
N). Experiment results on real robot
in our indoor environment show the advantages of our methods over
previous approaches.
Abstract: Deep Brain Stimulation or DBS is a surgical treatment for Parkinson-s Disease with three stimulation parameters: frequency, pulse width, and voltage. The parameters should be selected appropriately to achieve effective treatment. This selection now, performs clinically. The aim of this research is to study chaotic behavior of recorded tremor of patients under DBS in order to present a computational method to recognize stimulation optimum voltage. We obtained some chaotic features of tremor signal, and discovered embedding space of it has an attractor, and its largest Lyapunov exponent is positive, which show tremor signal has chaotic behavior, also we found out, in optimal voltage, entropy and embedding space variance of tremor signal have minimum values in comparison with other voltages. These differences can help neurologists recognize optimal voltage numerically, which leads to reduce patients' role and discomfort in optimizing stimulation parameters and to do treatment with high accuracy.
Abstract: Social ideology, cultural values and principles shaping environment are inferred by environment and structural characteristics of construction site. In other words, this inference manifestation also indicates ideology and culture of its foundation and also applies its principles and values and somehow plays an important role in Cultural Revolution. All human behaviors and artifacts are affected and being influenced by culture. Culture is not abstract concept, it is a spiritual domain that an individual and society grow and develop in it. Social behaviors are affected by environmental comprehension, so the architecture work influences on its audience and it is the environment that fosters social behaviors. Indeed, sustainable architecture should be considered as background of culture for establishing optimal sustainable culture. Since unidentified architecture roots in cultural non identity and abnormalities, so the society possesses identity characteristics and life and as a consequence, the society and architecture are changed by transformation of life style. This article aims to investigate the interaction of architecture, society, environment and sustainable architecture formation in its cultural basis and analyzes the results approaching behavior and sustainable culture in recent era.
Abstract: In neural networks, when new patterns are learned by a network, the new information radically interferes with previously stored patterns. This drawback is called catastrophic forgetting or catastrophic interference. In this paper, we propose a biologically inspired neural network model which overcomes this problem. The proposed model consists of two distinct networks: one is a Hopfield type of chaotic associative memory and the other is a multilayer neural network. We consider that these networks correspond to the hippocampus and the neocortex of the brain, respectively. Information given is firstly stored in the hippocampal network with fast learning algorithm. Then the stored information is recalled by chaotic behavior of each neuron in the hippocampal network. Finally, it is consolidated in the neocortical network by using pseudopatterns. Computer simulation results show that the proposed model has much better ability to avoid catastrophic forgetting in comparison with conventional models.
Abstract: A lot of research has been done in the past decade in the field of audio content analysis for extracting various information from audio signal. One such significant information is the "perceived mood" or the "emotions" related to a music or audio clip. This information is extremely useful in applications like creating or adapting the play-list based on the mood of the listener. This information could also be helpful in better classification of the music database. In this paper we have presented a method to classify music not just based on the meta-data of the audio clip but also include the "mood" factor to help improve the music classification. We propose an automated and efficient way of classifying music samples based on the mood detection from the audio data. We in particular try to classify the music based on mood for Indian bollywood music. The proposed method tries to address the following problem statement: Genre information (usually part of the audio meta-data) alone does not help in better music classification. For example the acoustic version of the song "nothing else matters by Metallica" can be classified as melody music and thereby a person in relaxing or chill out mood might want to listen to this track. But more often than not this track is associated with metal / heavy rock genre and if a listener classified his play-list based on the genre information alone for his current mood, the user shall miss out on listening to this track. Currently methods exist to detect mood in western or similar kind of music. Our paper tries to solve the issue for Indian bollywood music from an Indian cultural context
Abstract: Estimating the reliability of a computer network has been a subject of great interest. It is a well known fact that this problem is NP-hard. In this paper we present a very efficient combinatorial approach for Monte Carlo reliability estimation of a network with unreliable nodes and unreliable edges. Its core is the computation of some network combinatorial invariants. These invariants, once computed, directly provide pure and simple framework for computation of network reliability. As a specific case of this approach we obtain tight lower and upper bounds for distributed network reliability (the so called residual connectedness reliability). We also present some simulation results.
Abstract: In this paper we propose a segmentation system for unconstrained Arabic online handwriting. An essential problem addressed by analytical-based word recognition system. The system is composed of two-stages the first is a newly special designed hidden Markov model (HMM) and the second is a rules based stage. In our system, handwritten words are broken up into characters by simultaneous segmentation-recognition using HMMs of unique design trained using online features most of which are novel. The HMM output characters boundaries represent the proposed segmentation points (PSP) which are then validated by rules-based post stage without any contextual information help to solve different segmentation errors. The HMM has been designed and tested using a self collected dataset (OHASD) [1]. Most errors cases are cured and remarkable segmentation enhancement is achieved. Very promising word and character segmentation rates are obtained regarding the unconstrained Arabic handwriting difficulty and not using context help.
Abstract: Exposure to ambient air pollution has been linked to a
number of health outcomes, starting from modest transient changes in
the respiratory tract and impaired pulmonary function, continuing to
restrict activity/reduce performance and to the increase emergency
rooms visits, hospital admissions or mortality. The increase of
allergenic symptoms has been associated with air contaminants such
as ozone, particulate matter, fungal spores and pollen.
Considering the potential relevance of crossed effects of nonbiological
pollutants and airborne pollens and fungal spores on
allergy worsening, the aim of this work was to evaluate the influence
of non-biological pollutants (O3 and PM10) and meteorological
parameters on the concentrations of pollen and fungal spores using
multiple linear regressions.
The data considered in this study were collected in Oporto which
is the second largest Portuguese city, located in the North. Daily
mean of O3, PM10, pollen and fungal spore concentrations,
temperature, relative humidity, precipitation, wind velocity, pollen
and fungal spore concentrations, for 2003, 2004 and 2005 were
considered. Results showed that the 90th percentile of the adjusted
coefficient of determination, P90 (R2aj), of the multiple regressions
varied from 0.613 to 0.916 for pollen and from 0.275 to 0.512 for
fungal spores. O3 and PM10 showed to have some influence on the
biological pollutants. Among the meteorological parameters
analysed, temperature was the one that most influenced the pollen
and fungal spores airborne concentrations. Relative humidity also
showed to have some influence on the fungal spore dispersion.
Nevertheless, the models for each pollen and fungal spore were
different depending on the analysed period, which means that the
correlations identified as statistically significant can not be, even so,
consistent enough.
Abstract: We compare three categorical data clustering
algorithms with respect to the problem of classifying cultural data
related to the aesthetic judgment of comics artists. Such a
classification is very important in Comics Art theory since the
determination of any classes of similarities in such kind of data will
provide to art-historians very fruitful information of Comics Art-s
evolution. To establish this, we use a categorical data set and we
study it by employing three categorical data clustering algorithms.
The performances of these algorithms are compared each other,
while interpretations of the clustering results are also given.
Abstract: In analyzing large scale nonlinear dynamical systems,
it is often desirable to treat the overall system as a collection of
interconnected subsystems. Solutions properties of the large scale
system are then deduced from the solution properties of the
individual subsystems and the nature of the interconnections. In this
paper a new approach is proposed for the stability analysis of large
scale systems, which is based upon the concept of vector Lyapunov
functions and the decomposition methods. The present results make
use of graph theoretic decomposition techniques in which the overall
system is partitioned into a hierarchy of strongly connected
components. We show then, that under very reasonable assumptions,
the overall system is stable once the strongly connected subsystems
are stables. Finally an example is given to illustrate the constructive
methodology proposed.
Abstract: In this paper, we proposed an invention of an
accessory into a communication device that will help humans to be
connected universally. Generally, this device will be made up of
crystal and will combine many technologies that will enable the user
to run various applications and software anywhere and everywhere.
Bringing up the concept of from being user friendly, we had used the
crystal as the main material of the device that will trap the
surrounding lights to produce projection of its screen. This leads to a
lesser energy consumption and allows smaller sized battery to be
used, making the device less bulky. Additionally, we proposed the
usage of micro batteries as our energy source. Thus, researches
regarding crystal were made along with explanations in details of
specification and function of the technology used in the device.
Finally, we had also drawn several views of the invention from
different sides to be visualized.
Abstract: Accurate modeling of high speed RLC interconnects
has become a necessity to address signal integrity issues in current
VLSI design. To accurately model a dispersive system of interconnects
at higher frequencies; a full-wave analysis is required.
However, conventional circuit simulation of interconnects with full
wave models is extremely CPU expensive. We present an algorithm
for reducing large VLSI circuits to much smaller ones with similar
input-output behavior. A key feature of our method, called Frequency
Shift Technique, is that it is capable of reducing linear time-varying
systems. This enables it to capture frequency-translation and sampling
behavior, important in communication subsystems such as mixers,
RF components and switched-capacitor filters. Reduction is obtained
by projecting the original system described by linear differential
equations into a lower dimension. Experiments have been carried out
using Cadence Design Simulator cwhich indicates that the proposed
technique achieves more % reduction with less CPU time than the
other model order reduction techniques existing in literature. We
also present applications to RF circuit subsystems, obtaining size
reductions and evaluation speedups of orders of magnitude with
insignificant loss of accuracy.
Abstract: This study is concerned with pH solution detection
using 2 × 4 flexible sensor array based on a plastic polyethylene
terephthalate (PET) substrate that is coated a conductive layer and a
ruthenium dioxide (RuO2) sensitive membrane with the technologies
of screen-printing and RF sputtering. For data analysis, we also
prepared a dynamic measurement system for acquiring the response
voltage and analyzing the characteristics of the working electrodes
(WEs), such as sensitivity and linearity. In this condition, an array
measurement system was designed to acquire the original signal from
sensor array, and it is based on the method of digital signal processing
(DSP). The DSP modifies the unstable acquisition data to a direct
current (DC) output using the technique of digital filter. Hence, this
sensor array can obtain a satisfactory yield, 62.5%, through the design
measurement and analysis system in our laboratory.
Abstract: How to maintain the service speeds for the business
to make the biggest profit is a problem worthy of study, which is
discussed in this paper with the use of queuing theory. An M/M/1/N
queuing model with variable input rates, variable service rates and
impatient customers is established, and the following conclusions
are drawn: the stationary distribution of the model, the relationship
between the stationary distribution and the probability that there are n
customers left in the system when a customer leaves (not including
the customer who leaves himself), the busy period of the system,
the average operating cycle, the loss probability for the customers
not entering the system while they arriving at the system, the mean
of the customers who leaves the system being for impatient, the
loss probability for the customers not joining the queue due to the
limited capacity of the system and many other indicators. This paper
also indicates that the following conclusion is not correct: the more
customers the business serve, the more profit they will get. At last,
this paper points out the appropriate service speeds the business
should keep to make the biggest profit.
Abstract: Let A and B be two linear algebras. A linear map ϕ : A → B is called an n-homomorphism if ϕ(a1...an) = ϕ(a1)...ϕ(an) for all a1, ..., an ∈ A. In this note we have a verification on the behavior of almost n-multiplicative linear maps with n > 2 in the fuzzy normed spaces
Abstract: Multiple-input multiple-output (MIMO) systems are
widely in use to improve quality, reliability of wireless transmission
and increase the spectral efficiency. However in MIMO systems,
multiple copies of data are received after experiencing various
channel effects. The limitations on account of complexity due to
number of antennas in case of conventional decoding techniques have
been looked into. Accordingly we propose a modified sphere decoder
(MSD-1) algorithm with lower complexity and give rise to system
with high spectral efficiency. With the aim to increase signal
diversity we apply rotated quadrature amplitude modulation (QAM)
constellation in multi dimensional space. Finally, we propose a new
architecture involving space time trellis code (STTC) concatenated
with space time block code (STBC) using MSD-1 at the receiver for
improving system performance. The system gains have been verified
with channel state information (CSI) errors.
Abstract: Supplement use is common in athletes. Besides their cost, they may have side effects on health and performance. 250 questionnaires were distributed among female athletes (mean age 27.08 years). The questionnaire aimed to explore the frequency, type, believes, attitudes and knowledge regarding dietary supplements. Knowledge was good in 30.3%, fair in 60.2%, and poor in 9.1% of respondents. 65.3% of athletes did not use supplements regularly. The most widely used supplements were vitamins (48.4%), minerals (42.9%), energy supplements (21.3%), and herbals (20.9%). 68.9% of athletes believed in their efficacy. 34.4% experienced performance enhancement and 6.8% of reported side effects. 68.2% reported little knowledge and 60.9% were eager to learn more. In conclusion, many of the female athletes believe in the efficacy of supplements and think they are an unavoidable part of competitive sports. However, their information is not sufficient. We have to stress on education, consulting sessions, and rational prescription.
Abstract: This paper describes a new method of unequal error
protection (UEP) for region of interest (ROI) with embedded zerotree
wavelet algorithm (EZW). ROI technique is important in applications
with different parts of importance. In ROI coding, a chosen ROI is
encoded with higher quality than the background (BG). Unequal
error protection of image is provided by different coding techniques.
In our proposed method, image is divided into two parts (ROI, BG)
that consist of more important bytes (MIB) and less important bytes
(LIB). The experimental results verify effectiveness of the design.
The results of our method demonstrate the comparison of the unequal
error protection (UEP) of image transmission with defined ROI and
the equal error protection (EEP) over multiple noisy channels.
Abstract: The study of cytokine expression in mice under the
influence of inactivated poliovirus and Imovaks polio vaccine in
combination with derivatives of chitosan shows various kinds of
processes. There is a significant increase in IL-12 in the serum of
immunized animals, which should stimulate the production of IFN-γ
NK-cells and T-cells and polarize the immune response to Th1 type.
Thus, the derivatives of chitosan can promote cell component of the
immune response, providing a full antiviral immunity.