Abstract: Changes in stem diameter of orchid plants were
investigated in a control growing climate. Previous studies have
focused on stem diameter in relation to plant water on terrestrial
plants in order to schedule the irrigation. The objective of this work
was to evaluate the ability of the strain gauges to capture changes in
the epiphytes plant stem. Experiments were carried out by using the
sympodial orchid, Dendrobium Sonia in a stressed condition. From
the findings, the sensor can detect changes in the plant stem and the
result can easily be used as a reference for further studies for the
development of a proper watering system.
Abstract: In this paper, the application of multiple Elman neural networks to time series data regression problems is studied. An ensemble of Elman networks is formed by boosting to enhance the performance of the individual networks. A modified version of the AdaBoost algorithm is employed to integrate the predictions from multiple networks. Two benchmark time series data sets, i.e., the Sunspot and Box-Jenkins gas furnace problems, are used to assess the effectiveness of the proposed system. The simulation results reveal that an ensemble of boosted Elman networks can achieve a higher degree of generalization as well as performance than that of the individual networks. The results are compared with those from other learning systems, and implications of the performance are discussed.
Abstract: Optimal load shedding (LS) design as an emergency plan is one of the main control challenges posed by emerging new uncertainties and numerous distributed generators including renewable energy sources in a modern power system. This paper presents an overview of the key issues and new challenges on optimal LS synthesis concerning the integration of wind turbine units into the power systems. Following a brief survey on the existing LS methods, the impact of power fluctuation produced by wind powers on system frequency and voltage performance is presented. The most LS schemas proposed so far used voltage or frequency parameter via under-frequency or under-voltage LS schemes. Here, the necessity of considering both voltage and frequency indices to achieve a more effective and comprehensive LS strategy is emphasized. Then it is clarified that this problem will be more dominated in the presence of wind turbines.
Abstract: Multi-user interference (MUI) is the main reason of system deterioration in the Spectral Amplitude Coding Optical Code Division Multiple Access (SAC-OCDMA) system. MUI increases with the number of simultaneous users, resulting into higher probability bit rate and limits the maximum number of simultaneous users. On the other hand, Phase induced intensity noise (PIIN) problem which is originated from spontaneous emission of broad band source from MUI severely limits the system performance should be addressed as well. Since the MUI is caused by the interference of simultaneous users, reducing the MUI value as small as possible is desirable. In this paper, an extensive study for the system performance specified by MUI and PIIN reducing is examined. Vectors Combinatorial (VC) codes families are adopted as a signature sequence for the performance analysis and a comparison with reported codes is performed. The results show that, when the received power increases, the PIIN noise for all the codes increases linearly. The results also show that the effect of PIIN can be minimized by increasing the code weight leads to preserve adequate signal to noise ratio over bit error probability. A comparison study between the proposed code and the existing codes such as Modified frequency hopping (MFH), Modified Quadratic- Congruence (MQC) has been carried out.
Abstract: This article describes Uruk, the virtual museum of
Iraq that we developed for visual exploration and retrieval of image
collections. The system largely exploits the loosely-structured
hierarchy of XML documents that provides a useful representation
method to store semi-structured or unstructured data, which does not
easily fit into existing database. The system offers users the
capability to mine and manage the XML-based image collections
through a web-based Graphical User Interface (GUI). Typically, at an
interactive session with the system, the user can browse a visual
structural summary of the XML database in order to select interesting
elements. Using this intermediate result, queries combining structure
and textual references can be composed and presented to the system.
After query evaluation, the full set of answers is presented in a visual
and structured way.
Abstract: The condition of lightning surge causes the traveling waves and the temporary increase in voltage in the transmission line system. Lightning is the most harmful for destroying the transmission line and setting devices so it is necessary to study and analyze the temporary increase in voltage for designing and setting the surge arrester. This analysis describes the figure of the lightning wave in transmission line with 115 kV voltage level in Thailand by using ATP/EMTP program to create the model of the transmission line and lightning surge. Because of the limit of this program, it must be calculated for the geometry of the transmission line and surge parameter and calculation in the manual book for the closest value of the parameter. On the other hand, for the effects on surge protector when the lightning comes, the surge arrester model must be right and standardized as metropolitan electrical authority's standard. The candidate compared the real information to the result from calculation, also. The results of the analysis show that the temporary increase in voltage value will be rise to 326.59 kV at the line which is done by lightning when the surge arrester is not set in the system. On the other hand, the temporary increase in voltage value will be 182.83 kV at the line which is done by lightning when the surge arrester is set in the system and the period of the traveling wave is reduced, also. The distance for setting the surge arrester must be as near to the transformer as possible. Moreover, it is necessary to know the right distance for setting the surge arrester and the size of the surge arrester for preventing the temporary increase in voltage, effectively.
Abstract: PARIS (Personal Archiving and Retrieving Image
System) is an experiment personal photograph library, which includes
more than 80,000 of consumer photographs accumulated within a
duration of approximately five years, metadata based on our proposed
MPEG-7 annotation architecture, Dozen Dimensional Digital Content
(DDDC), and a relational database structure. The DDDC architecture
is specially designed for facilitating the managing, browsing and
retrieving of personal digital photograph collections. In annotating
process, we also utilize a proposed Spatial and Temporal Ontology
(STO) designed based on the general characteristic of personal
photograph collections. This paper explains PRAIS system.
Abstract: IMCS is Integrated Monitoring and Control System for
thermal power plant. This system consists of mainly two parts; controllers and OIS (Operator Interface System). These two parts are
connected by Ethernet-based communication. The controller side of communication is managed by CNet module and OIS side is managed
by data server of OIS. CNet module sends the data of controller to data
server and receives commend data from data server. To minimizes or
balance the load of data server, this module buffers data created by controller at every cycle and send buffered data to data server on request of data server. For multiple data server, this module manages
the connection line with each data server and response for each request
from multiple data server. CNet module is included in each controller
of redundant system. When controller fail-over happens on redundant system, this module can provide data of controller to data sever
without loss. This paper presents three main features – separation of get task, usage of ring buffer and monitoring communication status –of CNet module to carry out these functions.
Abstract: Neighborhood Rough Sets (NRS) has been proven to
be an efficient tool for heterogeneous attribute reduction. However,
most of researches are focused on dealing with complete and noiseless
data. Factually, most of the information systems are noisy, namely,
filled with incomplete data and inconsistent data. In this paper, we
introduce a generalized neighborhood rough sets model, called
VPTNRS, to deal with the problem of heterogeneous attribute
reduction in noisy system. We generalize classical NRS model with
tolerance neighborhood relation and the probabilistic theory.
Furthermore, we use the neighborhood dependency to evaluate the
significance of a subset of heterogeneous attributes and construct a
forward greedy algorithm for attribute reduction based on it.
Experimental results show that the model is efficient to deal with noisy
data.
Abstract: Lighting upgrades involve relatively lower costs which
allow the benefits to be spread more widely than is possible with any
other energy efficiency measure. In order to popularize the adoption of
CFL in Taiwan, the authority proposes to implement a new energy efficient lamp comparative label system. The current study was
accordingly undertaken to investigate the factors affecting the performance and the deviation of actual and labeled performance of
commercially available integrated CFLs. In this paper, standard test
methods to determine the electrical and photometric performances of
CFL were developed based on CIE 84-1989 and CIE 60901-1987,
then 55 selected CFLs from market were tested. The results show that
with higher color temperature of CFLs lower efficacy are achieved. It
was noticed that the most packaging of CFL often lack the information of Color Rendering Index. Also, there was no correlation between
price and performance of the CFLs was indicated in this work. The results of this paper might help consumers to make more informed
CFL-purchasing decisions.
Abstract: Image synthesis is an important area in image processing.
To synthesize images various systems are proposed in
the literature. In this paper, we propose a bio-inspired system to
synthesize image and to study the generating power of the system, we
define the class of languages generated by our system. We call image
as array in this paper. We use a primitive called iso-array to synthesize
image/array. The operation is double splicing on iso-arrays. The
double splicing operation is used in DNA computing and we use
this to synthesize image. A comparison of the family of languages
generated by the proposed self restricted double splicing systems on
iso-arrays with the existing family of local iso-picture languages is
made. Certain closure properties such as union, concatenation and
rotation are studied for the family of languages generated by the
proposed model.
Abstract: In this paper, an improved technique for contingency
ranking using artificial neural network (ANN) is presented. The
proposed approach is based on multi-layer perceptrons trained by
backpropagation to contingency analysis. Severity indices in dynamic
stability assessment are presented. These indices are based on the
concept of coherency and three dot products of the system variables.
It is well known that some indices work better than others for a
particular power system. This paper along with test results using
several different systems, demonstrates that combination of indices
with ANN provides better ranking than a single index. The presented
results are obtained through the use of power system simulation
(PSS/E) and MATLAB 6.5 software.
Abstract: Throughput is an important measure of performance of production system. Analyzing and modeling of production throughput is complex in today-s dynamic production systems due to uncertainties of production system. The main reasons are that uncertainties are materialized when the production line faces changes in setup time, machinery break down, lead time of manufacturing, and scraps. Besides, demand changes are fluctuating from time to time for each product type. These uncertainties affect the production performance. This paper proposes Bayesian inference for throughput modeling under five production uncertainties. Bayesian model utilized prior distributions related to previous information about the uncertainties where likelihood distributions are associated to the observed data. Gibbs sampling algorithm as the robust procedure of Monte Carlo Markov chain was employed for sampling unknown parameters and estimating the posterior mean of uncertainties. The Bayesian model was validated with respect to convergence and efficiency of its outputs. The results presented that the proposed Bayesian models were capable to predict the production throughput with accuracy of 98.3%.
Abstract: This paper investigates the application of large scale (LS-PV) two-axis tracking photovoltaic power plant in Al-Jagbob, Libya. A 50MW PV-grid connected (two-axis tracking) power plant design in Al-Jagbob, Libya has been carried out presently. A hetero-junction with intrinsic thin layer (HIT) type PV module has been selected and modeled. A Microsoft Excel-VBA program has been constructed to compute slope radiation, dew-point, sky temperature, and then cell temperature, maximum power output and module efficiency for this system, for tracking system. The results for energy production show that the total energy output is 128.5 GWh/year. The average module efficiency is 16.6%. The electricity generation capacity factor (CF) and solar capacity factor (SCF) were found to be 29.3% and 70.4% respectively. A 50MW two axis tracking power plant with a total energy output of 128.5 GWh/year would reduce CO2 pollution by 85,581 tonnes of each year. The payback time for the proposed LS-PV photovoltaic power plant was found to be 4 years.
Abstract: This paper proposes a new parameter identification
method based on Linear Fractional Transformation (LFT). It is
assumed that the target linear system includes unknown parameters.
The parameter deviations are separated from a nominal system via
LFT, and identified by organizing I/O signals around the separated
deviations of the real system. The purpose of this paper is to apply LFT
to simultaneously identify the parameter deviations in systems with
fewer outputs than unknown parameters. As a fundamental example,
this method is implemented to one degree of freedom vibratory system.
Via LFT, all physical parameters were simultaneously identified in this
system. Then, numerical simulations were conducted for this system to
verify the results. This study shows that all the physical parameters of a
system with fewer outputs than unknown parameters can be effectively
identified simultaneously using LFT.
Abstract: Power flow (PF) study, which is performed to
determine the power system static states (voltage magnitudes and
voltage angles) at each bus to find the steady state operating
condition of a system, is very important and is the most frequently
carried out study by power utilities for power system planning,
operation and control. In this paper, a counterpropagation neural
network (CPNN) is proposed to solve power flow problem under
different loading/contingency conditions for computing bus voltage
magnitudes and angles of the power system. The counterpropagation
network uses a different mapping strategy namely
counterpropagation and provides a practical approach for
implementing a pattern mapping task, since learning is fast in this
network. The composition of the input variables for the proposed
neural network has been selected to emulate the solution process of a
conventional power flow program. The effectiveness of the proposed
CPNN based approach for solving power flow is demonstrated by
computation of bus voltage magnitudes and voltage angles for
different loading conditions and single line-outage contingencies in
IEEE 14-bus system.
Abstract: Human activity is a major concern in a wide variety of
applications, such as video surveillance, human computer interface
and face image database management. Detecting and recognizing
faces is a crucial step in these applications. Furthermore, major
advancements and initiatives in security applications in the past years
have propelled face recognition technology into the spotlight. The
performance of existing face recognition systems declines significantly
if the resolution of the face image falls below a certain level.
This is especially critical in surveillance imagery where often, due to
many reasons, only low-resolution video of faces is available. If these
low-resolution images are passed to a face recognition system, the
performance is usually unacceptable. Hence, resolution plays a key
role in face recognition systems. In this paper we introduce a new
low resolution face recognition system based on mixture of expert
neural networks. In order to produce the low resolution input images
we down-sampled the 48 × 48 ORL images to 12 × 12 ones using
the nearest neighbor interpolation method and after that applying
the bicubic interpolation method yields enhanced images which is
given to the Principal Component Analysis feature extractor system.
Comparison with some of the most related methods indicates that
the proposed novel model yields excellent recognition rate in low
resolution face recognition that is the recognition rate of 100% for
the training set and 96.5% for the test set.
Abstract: In this paper, we propose a new model of English-
Vietnamese bilingual Information Retrieval system. Although there
are so many CLIR systems had been researched and built, the accuracy of searching results in different languages that the CLIR
system supports still need to improve, especially in finding bilingual documents. The problems identified in this paper are the limitation of
machine translation-s result and the extra large collections of document to be found. So we try to establish a different model to overcome these problems.
Abstract: In the urban traffic network, the intersections are the
“bottleneck point" of road network capacity. And the arterials are the
main body in road network and the key factor which guarantees the
normal operation of the city-s social and economic activities. The
rapid increase in vehicles leads to seriously traffic jam and cause the
increment of vehicles- delay. Most cities of our country are
traditional single control system, which cannot meet the need for the
city traffic any longer. In this paper, Synchro6.0 as a platform to
minimize the intersection delay, optimizesingle signal cycle and split
for Zhonghua Street in Handan City. Meanwhile, linear control
system uses to optimize the phase for the t arterial road in this
system. Comparing before and after use the control, capacities and
service levels of this road and the adjacent road have improved
significantly.
Abstract: Long Term Evolution (LTE) is a 4G wireless
broadband technology developed by the Third Generation
Partnership Project (3GPP) release 8, and it's represent the
competitiveness of Universal Mobile Telecommunications System
(UMTS) for the next 10 years and beyond. The concepts for LTE
systems have been introduced in 3GPP release 8, with objective of
high-data-rate, low-latency and packet-optimized radio access
technology. In this paper, performance of different TCP variants
during LTE network investigated. The performance of TCP over
LTE is affected mostly by the links of the wired network and total
bandwidth available at the serving base station. This paper describes
an NS-2 based simulation analysis of TCP-Vegas, TCP-Tahoe, TCPReno,
TCP-Newreno, TCP-SACK, and TCP-FACK, with full
modeling of all traffics of LTE system. The Evaluation of the
network performance with all TCP variants is mainly based on
throughput, average delay and lost packet. The analysis of TCP
performance over LTE ensures that all TCP's have a similar
throughput and the best performance return to TCP-Vegas than other
variants.