Abstract: A Ground Control System (GCS), which controls Unmanned Aerial Vehicles (UAVs) and monitors their missionrelated data, is one of the major components of UAVs. In fact, some traditional GCSs were built on an expensive, complicated hardware infrastructure with workstations and PCs. In contrast, a GCS on a portable device – such as an Android phone or tablet – takes advantage of its light-weight hardware and the rich User Interface supported by the Android Operating System. We implemented that kind of GCS and called it Ground System Software (GSS) in this paper. In operation, our GSS communicates with UAVs or other GSS via TCP/IP connection to get mission-related data, visualizes it on the device-s screen, and saves the data in its own database. Our study showed that this kind of system will become a potential instrument in UAV-related systems and this kind of topic will appear in many research studies in the near future.
Abstract: The radio frequency identification (RFID) is a
technology for automatic identification of items, particularly in
supply chain, but it is becoming increasingly important for industrial
applications. Unlike barcode technology that detects the optical
signals reflected from barcode labels, RFID uses radio waves to
transmit the information from an RFID tag affixed to the physical
object. In contrast to today most often use of this technology in
warehouse inventory and supply chain, the focus of this paper is an
overview of the structure of RFID systems used by RFID technology
and it also presents a solution based on the application of RFID for
brand authentication, traceability and tracking, by implementing a
production management system and extending its use to traders.
Abstract: This paper presents a vocoder to obtain high quality synthetic speech at 600 bps. To reduce the bit rate, the algorithm is based on a sinusoidally excited linear prediction model which extracts few coding parameters, and three consecutive frames are grouped into a superframe and jointly vector quantization is used to obtain high coding efficiency. The inter-frame redundancy is exploited with distinct quantization schemes for different unvoiced/voiced frame combinations in the superframe. Experimental results show that the quality of the proposed coder is better than that of 2.4kbps LPC10e and achieves approximately the same as that of 2.4kbps MELP and with high robustness.
Abstract: The batch nature limits the standard kernel principal component analysis (KPCA) methods in numerous applications, especially for dynamic or large-scale data. In this paper, an efficient adaptive approach is presented for online extraction of the kernel principal components (KPC). The contribution of this paper may be divided into two parts. First, kernel covariance matrix is correctly updated to adapt to the changing characteristics of data. Second, KPC are recursively formulated to overcome the batch nature of standard KPCA.This formulation is derived from the recursive eigen-decomposition of kernel covariance matrix and indicates the KPC variation caused by the new data. The proposed method not only alleviates sub-optimality of the KPCA method for non-stationary data, but also maintains constant update speed and memory usage as the data-size increases. Experiments for simulation data and real applications demonstrate that our approach yields improvements in terms of both computational speed and approximation accuracy.
Abstract: This research examines possible effects of climatic
change focusing on global warming and its impacts on world
agricultural product markets, by using a world food model developed
to consider climate changes. GDP and population for each scenario
were constructed by IPCC and climate data for each scenario was
reported by the Hadley Center and are used in this research to consider
results in different contexts. Production and consumption of primary
agriculture crops of the world for each socio-economic scenario are
obtained and investigated by using the modified world food model.
Simulation results show that crop production in some countries or
regions will have different trends depending on the context. These
alternative contexts depend on the rate of GDP growth, population,
temperature, and rainfall. Results suggest that the development of
environment friendly technologies lead to more consumption of food
in many developing countries. Relationships among environmental
policy, clean energy development, and poverty elimination warrant
further investigation.
Abstract: PCMs have always been viewed as a suitable
candidate for off peak thermal storage, particularly for refrigeration
systems, due to the high latent energy densities of these materials.
However, due to the need to have them encapsulated within a
container this density is reduced. Furthermore, PCMs have a low
thermal conductivity which reduces the useful amount of energy
which can be stored. To consider these factors, the true energy
storage density of a PCM system was proposed and optimised for
PCMs encapsulated in slabs. Using a validated numerical model of
the system, a parametric study was undertaken to investigate the
impact of the slab thickness, gap between slabs and the mass flow
rate. The study showed that, when optimised, a PCM system can
deliver a true energy storage density between 53% and 83% of the
latent energy density of the PCM.
Abstract: This paper presents a formant-tracking linear prediction
(FTLP) model for speech processing in noise. The main focus of this
work is the detection of formant trajectory based on Hidden Markov
Models (HMM), for improved formant estimation in noise. The
approach proposed in this paper provides a systematic framework for
modelling and utilization of a time- sequence of peaks which satisfies
continuity constraints on parameter; the within peaks are modelled
by the LP parameters. The formant tracking LP model estimation
is composed of three stages: (1) a pre-cleaning multi-band spectral
subtraction stage to reduce the effect of residue noise on formants
(2) estimation stage where an initial estimate of the LP model of
speech for each frame is obtained (3) a formant classification using
probability models of formants and Viterbi-decoders. The evaluation
results for the estimation of the formant tracking LP model tested
in Gaussian white noise background, demonstrate that the proposed
combination of the initial noise reduction stage with formant tracking
and LPC variable order analysis, results in a significant reduction in
errors and distortions. The performance was evaluated with noisy
natual vowels extracted from international french and English vocabulary
speech signals at SNR value of 10dB. In each case, the
estimated formants are compared to reference formants.
Abstract: The speech signal conveys information about the
identity of the speaker. The area of speaker identification is
concerned with extracting the identity of the person speaking the
utterance. As speech interaction with computers becomes more
pervasive in activities such as the telephone, financial transactions
and information retrieval from speech databases, the utility of
automatically identifying a speaker is based solely on vocal
characteristic. This paper emphasizes on text dependent speaker
identification, which deals with detecting a particular speaker from a
known population. The system prompts the user to provide speech
utterance. System identifies the user by comparing the codebook of
speech utterance with those of the stored in the database and lists,
which contain the most likely speakers, could have given that speech
utterance. The speech signal is recorded for N speakers further the
features are extracted. Feature extraction is done by means of LPC
coefficients, calculating AMDF, and DFT. The neural network is
trained by applying these features as input parameters. The features
are stored in templates for further comparison. The features for the
speaker who has to be identified are extracted and compared with the
stored templates using Back Propogation Algorithm. Here, the
trained network corresponds to the output; the input is the extracted
features of the speaker to be identified. The network does the weight
adjustment and the best match is found to identify the speaker. The
number of epochs required to get the target decides the network
performance.
Abstract: In some real applications of Statistical Process Control
it is necessary to design a control chart to not detect small process
shifts, but keeping a good performance to detect moderate and large
shifts in the quality. In this work we develop a new quality control
chart, the synthetic T2 control chart, that can be designed to cope with
this objective. A multi-objective optimization is carried out employing
Genetic Algorithms, finding the Pareto-optimal front of
non-dominated solutions for this optimization problem.
Abstract: A model predictive controller based on recursive learning is proposed. In this SISO adaptive controller, a model is automatically updated using simple recursive equations. The identified models are then stored in the memory to be re-used in the future. The decision for model update is taken based on a new control performance index. The new controller allows the use of simple linear model predictive controllers in the control of nonlinear time varying processes.
Abstract: HSDPA is a new feature which is introduced in
Release-5 specifications of the 3GPP WCDMA/UTRA standard to
realize higher speed data rate together with lower round-trip times.
Moreover, the HSDPA concept offers outstanding improvement of
packet throughput and also significantly reduces the packet call
transfer delay as compared to Release -99 DSCH. Till now the
HSDPA system uses turbo coding which is the best coding technique
to achieve the Shannon limit. However, the main drawbacks of turbo
coding are high decoding complexity and high latency which makes
it unsuitable for some applications like satellite communications,
since the transmission distance itself introduces latency due to
limited speed of light. Hence in this paper it is proposed to use LDPC
coding in place of Turbo coding for HSDPA system which decreases
the latency and decoding complexity. But LDPC coding increases the
Encoding complexity. Though the complexity of transmitter
increases at NodeB, the End user is at an advantage in terms of
receiver complexity and Bit- error rate. In this paper LDPC Encoder
is implemented using “sparse parity check matrix" H to generate a
codeword at Encoder and “Belief Propagation algorithm "for LDPC
decoding .Simulation results shows that in LDPC coding the BER
suddenly drops as the number of iterations increase with a small
increase in Eb/No. Which is not possible in Turbo coding. Also same
BER was achieved using less number of iterations and hence the
latency and receiver complexity has decreased for LDPC coding.
HSDPA increases the downlink data rate within a cell to a theoretical
maximum of 14Mbps, with 2Mbps on the uplink. The changes that
HSDPA enables includes better quality, more reliable and more
robust data services. In other words, while realistic data rates are
only a few Mbps, the actual quality and number of users achieved
will improve significantly.
Abstract: This paper mainly about the study on one of the
widely used error correcting codes that is Low parity check Codes
(LDPC). In this paper, the Regular LDPC code has been discussed
The LDPC codes explained in this paper is about the Regular Binary
LDPC codes or the Gallager.
Abstract: With Power system movement toward restructuring along with factors such as life environment pollution, problems of transmission expansion and with advancement in construction technology of small generation units, it is expected that small units like wind turbines, fuel cells, photovoltaic, ... that most of the time connect to the distribution networks play a very essential role in electric power industry. With increase in developing usage of small generation units, management of distribution networks should be reviewed. The target of this paper is to present a new method for optimal management of active and reactive power in distribution networks with regard to costs pertaining to various types of dispersed generations, capacitors and cost of electric energy achieved from network. In other words, in this method it-s endeavored to select optimal sources of active and reactive power generation and controlling equipments such as dispersed generations, capacitors, under load tapchanger transformers and substations in a way that firstly costs in relation to them are minimized and secondly technical and physical constraints are regarded. Because the optimal management of distribution networks is an optimization problem with continuous and discrete variables, the new evolutionary method based on Ant Colony Algorithm has been applied. The simulation results of the method tested on two cases containing 23 and 34 buses exist and will be shown at later sections.
Abstract: This research deals with a flexible flowshop
scheduling problem with arrival and delivery of jobs in groups and
processing them individually. Due to the special characteristics of
each job, only a subset of machines in each stage is eligible to
process that job. The objective function deals with minimization of
sum of the completion time of groups on one hand and minimization
of sum of the differences between completion time of jobs and
delivery time of the group containing that job (waiting period) on the
other hand. The problem can be stated as FFc / rj , Mj / irreg which
has many applications in production and service industries. A
mathematical model is proposed, the problem is proved to be NPcomplete,
and an effective heuristic method is presented to schedule
the jobs efficiently. This algorithm can then be used within the body
of any metaheuristic algorithm for solving the problem.
Abstract: The quest of providing more secure identification
system has led to a rise in developing biometric systems. Dorsal
hand vein pattern is an emerging biometric which has attracted the
attention of many researchers, of late. Different approaches have
been used to extract the vein pattern and match them. In this work,
Principle Component Analysis (PCA) which is a method that has
been successfully applied on human faces and hand geometry is
applied on the dorsal hand vein pattern. PCA has been used to obtain
eigenveins which is a low dimensional representation of vein pattern
features. Low cost CCD cameras were used to obtain the vein
images. The extraction of the vein pattern was obtained by applying
morphology. We have applied noise reduction filters to enhance the
vein patterns. The system has been successfully tested on a database
of 200 images using a threshold value of 0.9. The results obtained are
encouraging.
Abstract: This paper proposed a nonlinear model predictive
control (MPC) method for the control of gantry crane. One of the main
motivations to apply MPC to control gantry crane is based on its
ability to handle control constraints for multivariable systems. A
pre-compensator is constructed to compensate the input nonlinearity
(nonsymmetric dead zone with saturation) by using its inverse
function. By well tuning the weighting function matrices, the control
system can properly compromise the control between crane position
and swing angle. The proposed control algorithm was implemented for
the control of gantry crane system in System Control Lab of University
of Technology, Sydney (UTS), and achieved desired experimental
results.
Abstract: The study and development of an innovative material
for building insulation is really important for a sustainable society in order to improve comfort and reducing energy consumption. The aim of this work is the development of insulating panels for
sustainable buildings based on an innovative material made by
cardboard and Phase Change Materials (PCMs).
The research has consisted in laboratory tests whose purpose has been the obtaining of the required properties for insulation panels: lightweight, porous structures and mechanical resistance. PCMs have been used for many years in the building industry as
smart insulation technology because of their properties of storage and release high quantity of latent heat at useful specific temperatures [1]- [2].
The integration of PCMs into cellulose matrix during the waste paper recycling process has been developed in order to obtain a
composite material.
Experiments on the productive process for the realization of insulating panels were done in order to make the new material
suitable for building application. The addition of rising agents
demonstrated the possibility to obtain a lighter structure with better
insulation properties.
Several tests were conducted to verify the new panel properties. The results obtained have shown the possibility to realize an
innovative and sustainable material suitable to replace insulating panels currently used.
Abstract: A geothermal power plant multiple simulator for
operators training is presented. The simulator is designed to be
installed in a wireless local area network and has a capacity to train
one to six operators simultaneously, each one with an independent
simulation session. The sessions must be supervised only by one
instructor. The main parts of this multiple simulator are: instructor
and operator-s stations. On the instructor station, the instructor
controls the simulation sessions, establishes training exercises and
supervises each power plant operator in individual way. This station
is hosted in a Main Personal Computer (NS) and its main functions
are: to set initial conditions, snapshots, malfunctions or faults,
monitoring trends, and process and soft-panel diagrams. On the other
hand the operators carry out their actions over the power plant
simulated on the operator-s stations; each one is also hosted in a PC.
The main software of instructor and operator-s stations are executed
on the same NS and displayed in PCs through graphical Interactive
Process Diagrams (IDP). The geothermal multiple simulator has been
installed in the Geothermal Simulation Training Center (GSTC) of
the Comisi├│n Federal de Electricidad, (Federal Commission of
Electricity, CFE), Mexico, and is being utilized as a part of the
training courses for geothermal power plant operators.
Abstract: Recently, a growing interest has emerged on the
development of new and efficient energy sources, due to the inevitable extinction of the nonrenewable energy reserves. One of
these alternative sources which has a great potential and sustainability to meet up the energy demand is biomass energy. This
significant energy source can be utilized with various energy
conversion technologies, one of which is biomass gasification in
supercritical water.
Water, being the most important solvent in nature, has very important characteristics as a reaction solvent under supercritical
circumstances. At temperatures above its critical point (374.8oC and
22.1 MPa), water becomes more acidic and its diffusivity increases.
Working with water at high temperatures increases the thermal
reaction rate, which in consequence leads to a better dissolving of the
organic matters and a fast reaction with oxygen. Hence, supercritical water offers a control mechanism depending on solubility, excellent
transport properties based on its high diffusion ability and new reaction possibilities for hydrolysis or oxidation.
In this study the gasification of a real biomass, namely olive mill
wastewater (OMW), in supercritical water is investigated with the
use of Pt/Al2O3 and Ni/Al2O3 catalysts. OMW is a by-product
obtained during olive oil production, which has a complex nature
characterized by a high content of organic compounds and
polyphenols. These properties impose OMW a significant pollution
potential, but at the same time, the high content of organics makes
OMW a desirable biomass candidate for energy production.
All of the catalytic gasification experiments were made with five
different reaction temperatures (400, 450, 500, 550 and 600°C),
under a constant pressure of 25 MPa. For the experiments conducted
with Ni/Al2O3 catalyst, the effect of five reaction times (30, 60, 90,
120 and 150 s) was investigated. However, procuring that similar
gasification efficiencies could be obtained at shorter times, the experiments were made by using different reaction times (10, 15, 20,
25 and 30 s) for the case of Pt/Al2O3 catalyst. Through these experiments, the effects of temperature, time and catalyst type on the
gasification yields and treatment efficiencies were investigated.
Abstract: A. niger XP isolated from Vietnam produces very low amount of acidic phytase with optimal pH at 2.5 and 5.5. The phytase production of this strain was successfully improved through gene cloning and expression. A 1.4 - kb DNA fragment containing the coding region of the phyA gene was amplified by PCR and inserted into the expression vector pPICZαA with a signal peptide α- factor, under the control of AOX1 promoter. The recombined plasmid was transformed into the host strain P. pastoris KM71H and X33 by electroporation. Both host strains could efficiently express and secret phytase. The multicopy strains were screened for over expression of phytase. All the selected multicopy strains of P. pastoris X33 were examined for phytase activity, the maximum phytase yield of 1329 IU/ml was obtained after 4 days of incubation in medium BMM. The recombinant protein with MW of 97.4 KW showed to be the only one protein secreted in the culture broth. Multicopy transformant P. pastoris X33 supposed to be potential candidate for producing the commercial preparation of phytase.