Abstract: The new concept of two–dimensional (2D) image
processing implementation for auto-guiding system is shown in this
paper. It is dedicated to astrophotography and operates with
astronomy CCD guide cameras or with self-guided dual-detector
CCD cameras and ST4 compatible equatorial mounts. This idea was
verified by MATLAB model, which was used to test all procedures
and data conversions. Next the circuit prototype was implemented at
Altera MAX II CPLD device and tested for real astronomical object
images. The digital processing speed of CPLD prototype board was
sufficient for correct equatorial mount guiding in real-time system.
Abstract: None of the processing models in the software
development has explained the software systems performance
evaluation and modeling; likewise, there exist uncertainty in the
information systems because of the natural essence of requirements,
and this may cause other challenges in the processing of software
development. By definition an extended version of UML (Fuzzy-
UML), the functional requirements of the software defined
uncertainly would be supported. In this study, the behavioral
description of uncertain information systems by the aid of fuzzy-state
diagram is crucial; moreover, the introduction of behavioral diagrams
role in F-UML is investigated in software performance modeling
process. To get the aim, a fuzzy sub-profile is used.
Abstract: The ITE Project is a project that has 1800 km length
and across the Turkey's land through east to west. The project of
pipeline enters geographically from Iran to Doğubayazit (Turkey) in
the east, exits to Greece from Ipsala province of Turkey in the west.
This project is the one of the international projects in such scale that
provides the natural gas of Iran and Caspian Sea through the
European continent. In this investigation, some information will be
given about the methods used to verify the direction of the pipeline
and the technical properties of the results obtained. The cost of
project itself entirely depends on the direction of the pipeline which
would be as short as possible and the specifications of the land cover.
Production standards of 1/2000 scaled digital orthophoto and vectoral
maps as a results of the use of map production materials and methods
(such as high resolution satellite images, and digital aerial images
captured from digital aerial cameras), will also be given in this report.
According to Turkish national map production standards, TM
((Transversal Mercator, 3 degree) projection is used for large scale
map and UTM (Universal Transversal Mercator, 6 degree) is used for
small scale map production standards. Some information is also given
about the projection used in the ITE natural gas pipeline project.
Abstract: Human identification at a distance has recently gained
growing interest from computer vision researchers. Gait recognition
aims essentially to address this problem by identifying people based
on the way they walk [1]. Gait recognition has 3 steps. The first step
is preprocessing, the second step is feature extraction and the third
one is classification. This paper focuses on the classification step that
is essential to increase the CCR (Correct Classification Rate).
Multilayer Perceptron (MLP) is used in this work. Neural Networks
imitate the human brain to perform intelligent tasks [3].They can
represent complicated relationships between input and output and
acquire knowledge about these relationships directly from the data
[2]. In this paper we apply MLP NN for 11 views in our database and
compare the CCR values for these views. Experiments are performed
with the NLPR databases, and the effectiveness of the proposed
method for gait recognition is demonstrated.
Abstract: The paper deals with the estimation of amplitude and phase of an analogue multi-harmonic band-limited signal from irregularly spaced sampling values. To this end, assuming the signal fundamental frequency is known in advance (i.e., estimated at an independent stage), a complexity-reduced algorithm for signal reconstruction in time domain is proposed. The reduction in complexity is achieved owing to completely new analytical and summarized expressions that enable a quick estimation at a low numerical error. The proposed algorithm for the calculation of the unknown parameters requires O((2M+1)2) flops, while the straightforward solution of the obtained equations takes O((2M+1)3) flops (M is the number of the harmonic components). It is applied in signal reconstruction, spectral estimation, system identification, as well as in other important signal processing problems. The proposed method of processing can be used for precise RMS measurements (for power and energy) of a periodic signal based on the presented signal reconstruction. The paper investigates the errors related to the signal parameter estimation, and there is a computer simulation that demonstrates the accuracy of these algorithms.
Abstract: We have previously introduced an ultrasonic imaging
approach that combines harmonic-sensitive pulse sequences with a
post-beamforming quadratic kernel derived from a second-order
Volterra filter (SOVF). This approach is designed to produce images
with high sensitivity to nonlinear oscillations from microbubble
ultrasound contrast agents (UCA) while maintaining high levels of
noise rejection. In this paper, a two-step algorithm for computing the
coefficients of the quadratic kernel leading to reduction of tissue
component introduced by motion, maximizing the noise rejection and
increases the specificity while optimizing the sensitivity to the UCA
is presented. In the first step, quadratic kernels from individual
singular modes of the PI data matrix are compared in terms of their
ability of maximize the contrast to tissue ratio (CTR). In the second
step, quadratic kernels resulting in the highest CTR values are
convolved. The imaging results indicate that a signal processing
approach to this clinical challenge is feasible.
Abstract: This paper discusses the designing of knowledge
integration of clinical information extracted from distributed medical
ontologies in order to ameliorate a machine learning-based multilabel
coding assignment system. The proposed approach is
implemented using a decision tree technique of the machine learning
on the university hospital data for patients with Coronary Heart
Disease (CHD). The preliminary results obtained show a satisfactory
finding that the use of medical ontologies improves the overall
system performance.
Abstract: Information sharing and exchange, rather than
information processing, is what characterizes information
technology in the 21st century. Ontologies, as shared common
understanding, gain increasing attention, as they appear as the
most promising solution to enable information sharing both at
a semantic level and in a machine-processable way. Domain
Ontology-based modeling has been exploited to provide
shareability and information exchange among diversified,
heterogeneous applications of enterprises.
Contextual ontologies are “an explicit specification of
contextual conceptualization". That is: ontology is
characterized by concepts that have multiple representations
and they may exist in several contexts. Hence, contextual
ontologies are a set of concepts and relationships, which are
seen from different perspectives. Contextualization is to allow
for ontologies to be partitioned according to their contexts.
The need for contextual ontologies in enterprise modeling
has become crucial due to the nature of today's competitive
market. Information resources in enterprise is distributed and
diversified and is in need to be shared and communicated
locally through the intranet and globally though the internet.
This paper discusses the roles that ontologies play in an
enterprise modeling, and how ontologies assist in building a
conceptual model in order to provide communicative and
interoperable information systems. The issue of enterprise
modeling based on contextual domain ontology is also
investigated, and a framework is proposed for an enterprise
model that consists of various applications.
Abstract: The proposed system identifies the species of the wood
using the textural features present in its barks. Each species of a wood
has its own unique patterns in its bark, which enabled the proposed
system to identify it accurately. Automatic wood recognition system
has not yet been well established mainly due to lack of research in this
area and the difficulty in obtaining the wood database. In our work, a
wood recognition system has been designed based on pre-processing
techniques, feature extraction and by correlating the features of those
wood species for their classification. Texture classification is a problem
that has been studied and tested using different methods due to its
valuable usage in various pattern recognition problems, such as wood
recognition, rock classification. The most popular technique used
for the textural classification is Gray-level Co-occurrence Matrices
(GLCM). The features from the enhanced images are thus extracted
using the GLCM is correlated, which determines the classification
between the various wood species. The result thus obtained shows a
high rate of recognition accuracy proving that the techniques used in
suitable to be implemented for commercial purposes.
Abstract: There have been different approaches to compute the
analytic instantaneous frequency with a variety of background reasoning
and applicability in practice, as well as restrictions. This paper presents an adaptive Fourier decomposition and (α-counting) based
instantaneous frequency computation approach. The adaptive Fourier
decomposition is a recently proposed new signal decomposition
approach. The instantaneous frequency can be computed through the so called mono-components decomposed by it. Due to the fast energy
convergency, the highest frequency of the signal will be discarded by the adaptive Fourier decomposition, which represents the noise of
the signal in most of the situation. A new instantaneous frequency
definition for a large class of so-called simple waves is also proposed
in this paper. Simple wave contains a wide range of signals for which
the concept instantaneous frequency has a perfect physical sense.
The α-counting instantaneous frequency can be used to compute the highest frequency for a signal. Combination of these two approaches one can obtain the IFs of the whole signal. An experiment is demonstrated the computation procedure with promising results.
Abstract: This paper describes how the correct endian mode of
the TMS320C6713 DSK board can be identified. It also explains how
the TMS320C6713 DSK board can be used in the little endian and in
the big endian modes for assembly language programming in
particular and for signal processing in general. Similarly, it discusses
how crucially important it is for a user of the TMS320C6713 DSK
board to identify the mode of operation and then use it correctly
during the development stages of the assembly language
programming; otherwise, it will cause unnecessary confusion and
erroneous results as far as storing data into the memory and loading
data from the memory is concerned. Furthermore, it highlights and
strongly recommends to the users of the TMS320C6713 DSK board
to be aware of the availability and importance of various display
options in the Code Composer Studio (CCS) for correctly
interpreting and displaying the desired data in the memory. The
information presented in this paper will be of great importance and
interest to those practitioners and developers who wants to use the
TMS320C6713 DSK board for assembly language programming as
well as input-output signal processing manipulations. Finally,
examples that clearly illustrate the concept are presented.
Abstract: In this paper, we proposed an efficient data
compression strategy exploiting the multi-resolution characteristic of
the wavelet transform. We have developed a sensor node called
“Smart Sensor Node; SSN". The main goals of the SSN design are
lightweight, minimal power consumption, modular design and robust
circuitry. The SSN is made up of four basic components which are a
sensing unit, a processing unit, a transceiver unit and a power unit.
FiOStd evaluation board is chosen as the main controller of the SSN
for its low costs and high performance. The software coding of the
implementation was done using Simulink model and MATLAB
programming language. The experimental results show that the
proposed data compression technique yields recover signal with good
quality. This technique can be applied to compress the collected data
to reduce the data communication as well as the energy consumption
of the sensor and so the lifetime of sensor node can be extended.
Abstract: Electromyography (EMG) signal processing has been investigated remarkably regarding various applications such as in rehabilitation systems. Specifically, wavelet transform has served as a powerful technique to scrutinize EMG signals since wavelet transform is consistent with the nature of EMG as a non-stationary signal. In this paper, the efficiency of wavelet transform in surface EMG feature extraction is investigated from four levels of wavelet decomposition and a comparative study between different mother wavelets had been done. To recognize the best function and level of wavelet analysis, two evaluation criteria, scatter plot and RES index are recruited. Hereupon, four wavelet families, namely, Daubechies, Coiflets, Symlets and Biorthogonal are studied in wavelet decomposition stage. Consequently, the results show that only features from first and second level of wavelet decomposition yields good performance and some functions of various wavelet families can lead to an improvement in separability class of different hand movements.
Abstract: Personal name matching system is the core of
essential task in national citizen database, text and web mining,
information retrieval, online library system, e-commerce and record
linkage system. It has necessitated to the all embracing research in
the vicinity of name matching. Traditional name matching methods
are suitable for English and other Latin based language. Asian
languages which have no word boundary such as Myanmar language
still requires sounds alike matching system in Unicode based
application. Hence we proposed matching algorithm to get analogous
sounds alike (phonetic) pattern that is convenient for Myanmar
character spelling. According to the nature of Myanmar character, we
consider for word boundary fragmentation, collation of character.
Thus we use pattern conversion algorithm which fabricates words in
pattern with fragmented and collated. We create the Myanmar sounds
alike phonetic group to help in the phonetic matching. The
experimental results show that fragmentation accuracy in 99.32% and
processing time in 1.72 ms.
Abstract: System is using multiple processors for computing and information processing, is increasing rapidly speed operation of these systems compared with single processor systems, very significant impact on system performance is increased .important differences to yield a single multi-processor cpu, the scheduling policies, to reduce the implementation time of all processes. Notwithstanding the famous algorithms such as SPT, LPT, LSPT and RLPT for scheduling and there, but none led to the answer are not optimal.In this paper scheduling using genetic algorithms and innovative way to finish the whole process faster that we do and the result compared with three algorithms we mentioned.
Abstract: By taking advantage of computer-s processing power, an unlimited number of variations and parameters in both spatial and environmental can be provided while following the same set of rules and constraints. This paper focuses on using the tools of parametric urbanism towards a more responsive environmental and sustainable urban morphology. It presents an understanding to Parametric Urban Comfort Envelope (PUCE) as an interactive computational assessment urban model. In addition, it investigates the applicability potentials of this model to generate an optimized urban form to Borg El Arab city (a new Egyptian Community) concerning the human comfort values specially wind and solar envelopes. Finally, this paper utilizes its application outcomes -both visual and numerical- to extend the designer-s limitations by decrease the concern of controlling and manipulation of geometry, and increase the designer-s awareness about the various potentials of using the parametric tools to create relationships that generate multiple geometric alternatives.
Abstract: The intermittent connectivity modifies the “always
on" network assumption made by all the distributed query processing
systems. In modern- day systems, the absence of network
connectivity is considered as a fault. Since the last upload, it might
not be feasible to transmit all the data accumulated right away over
the available connection. It is possible that vital information may be
delayed excessively when the less important information takes place
of the vital information. Owing to the restricted and uneven
bandwidth, it is vital that the mobile nodes make the most
advantageous use of the connectivity when it arrives. Hence, in order
to select the data that needs to be transmitted first, some sort of data
prioritization is essential. A continuous query processing system for
intermittently connected mobile networks that comprises of a delaytolerant
continuous query processor distributed across the mobile
hosts has been proposed in this paper. In addition, a mechanism for
prioritizing query results has been designed that guarantees enhanced
accuracy and reduced delay. It is illustrated that our architecture
reduces the client power consumption, increases query efficiency by
the extensive simulation results.
Abstract: Quality evaluation of an image is an important task in image processing applications. In case of image compression, quality of decompressed image is also the criterion for evaluation of given coding scheme. In the process of compression -decompression various artifacts such as blocking artifacts, blur artifact, ringing or edge artifact are observed. However quantification of these artifacts is a difficult task. We propose here novel method to quantify blur and ringing artifact in an image.
Abstract: Array signal processing involves signal enumeration and source localization. Array signal processing is centered on the ability to fuse temporal and spatial information captured via sampling signals emitted from a number of sources at the sensors of an array in order to carry out a specific estimation task: source characteristics (mainly localization of the sources) and/or array characteristics (mainly array geometry) estimation. Array signal processing is a part of signal processing that uses sensors organized in patterns or arrays, to detect signals and to determine information about them. Beamforming is a general signal processing technique used to control the directionality of the reception or transmission of a signal. Using Beamforming we can direct the majority of signal energy we receive from a group of array. Multiple signal classification (MUSIC) is a highly popular eigenstructure-based estimation method of direction of arrival (DOA) with high resolution. This Paper enumerates the effect of missing sensors in DOA estimation. The accuracy of the MUSIC-based DOA estimation is degraded significantly both by the effects of the missing sensors among the receiving array elements and the unequal channel gain and phase errors of the receiver.
Abstract: In this study, the ability of Aspergillus niger and
Penicillium simplicissimum to extract heavy metals from a spent
refinery catalyst was investigated. For the first step, a spent
processing catalyst from one of the oil refineries in Iran was
physically and chemically characterized. Aspergillus niger and
Penicillium simplicissimum were used to mobilize Al/Co/Mo/Ni from
hazardous spent catalysts. The fungi were adapted to the mixture of
metals at 100-800 mg L-1 with increments in concentration of 100 mg
L-1. Bioleaching experiments were carried out in batch cultures. To
investigate the production of organic acids in sucrose medium,
analyses of the culture medium by HPLC were performed at specific
time intervals after inoculation. The results obtained from Inductive
coupled plasma-optical emission spectrometry (ICP-OES) showed
that after the one-step bioleaching process using Aspergillus niger,
maximum removal efficiencies of 27%, 66%, 62% and 38% were
achieved for Al, Co, Mo and Ni, respectively. However, the highest
removal efficiencies using Penicillium simplicissimum were of 32%,
67%, 65% and 38% for Al, Co, Mo and Ni, respectively