Abstract: Over the years, there is a growing trend towards
quality-based specifications in highway construction. In many
Quality Control/Quality Assurance (QC/QA) specifications, the
contractor is primarily responsible for quality control of the process,
whereas the highway agency is responsible for testing the acceptance
of the product. A cooperative investigation was conducted in Illinois
over several years to develop a prototype End-Result Specification
(ERS) for asphalt pavement construction. The final characteristics of
the product are stipulated in the ERS and the contractor is given
considerable freedom in achieving those characteristics. The risk for
the contractor or agency depends on how the acceptance limits and
processes are specified. Stochastic simulation models are very useful
in estimating and analyzing payment risk in ERS systems and these
form an integral part of the Illinois-s prototype ERS system. This
paper describes the development of an innovative methodology to
estimate the variability components in in-situ density, air voids and
asphalt content data from ERS projects. The information gained from
this would be crucial in simulating these ERS projects for estimation
and analysis of payment risks associated with asphalt pavement
construction. However, these methods require at least two parties to
conduct tests on all the split samples obtained according to the
sampling scheme prescribed in present ERS implemented in Illinois.
Abstract: Deoxyribonucleic Acid or DNA computing has
emerged as an interdisciplinary field that draws together chemistry,
molecular biology, computer science and mathematics. Thus, in this
paper, the possibility of DNA-based computing to solve an absolute
1-center problem by molecular manipulations is presented. This is
truly the first attempt to solve such a problem by DNA-based
computing approach. Since, part of the procedures involve with
shortest path computation, research works on DNA computing for
shortest path Traveling Salesman Problem, in short, TSP are reviewed.
These approaches are studied and only the appropriate one is adapted
in designing the computation procedures. This DNA-based
computation is designed in such a way that every path is encoded by
oligonucleotides and the path-s length is directly proportional to the
length of oligonucleotides. Using these properties, gel electrophoresis
is performed in order to separate the respective DNA molecules
according to their length. One expectation arise from this paper is that
it is possible to verify the instance absolute 1-center problem using
DNA computing by laboratory experiments.
Abstract: This paper describes the development of a fully
automated measurement software for antenna radiation pattern
measurements in a Compact Antenna Test Range (CATR). The
CATR has a frequency range from 2-40 GHz and the measurement
hardware includes a Network Analyzer for transmitting and
Receiving the microwave signal and a Positioner controller to control
the motion of the Styrofoam column. The measurement process
includes Calibration of CATR with a Standard Gain Horn (SGH)
antenna followed by Gain versus angle measurement of the Antenna
under test (AUT). The software is designed to control a variety of
microwave transmitter / receiver and two axis Positioner controllers
through the standard General Purpose interface bus (GPIB) interface.
Addition of new Network Analyzers is supported through a slight
modification of hardware control module. Time-domain gating is
implemented to remove the unwanted signals and get the isolated
response of AUT. The gated response of the AUT is compared with
the calibration data in the frequency domain to obtain the desired
results. The data acquisition and processing is implemented in
Agilent VEE and Matlab. A variety of experimental measurements
with SGH antennas were performed to validate the accuracy of
software. A comparison of results with existing commercial
softwares is presented and the measured results are found to be
within .2 dBm.
Abstract: This paper presents a new Hybrid Fuzzy (HF) PID type controller based on Genetic Algorithms (GA-s) for solution of the Automatic generation Control (AGC) problem in a deregulated electricity environment. In order for a fuzzy rule based control system to perform well, the fuzzy sets must be carefully designed. A major problem plaguing the effective use of this method is the difficulty of accurately constructing the membership functions, because it is a computationally expensive combinatorial optimization problem. On the other hand, GAs is a technique that emulates biological evolutionary theories to solve complex optimization problems by using directed random searches to derive a set of optimal solutions. For this reason, the membership functions are tuned automatically using a modified GA-s based on the hill climbing method. The motivation for using the modified GA-s is to reduce fuzzy system effort and take large parametric uncertainties into account. The global optimum value is guaranteed using the proposed method and the speed of the algorithm-s convergence is extremely improved, too. This newly developed control strategy combines the advantage of GA-s and fuzzy system control techniques and leads to a flexible controller with simple stricture that is easy to implement. The proposed GA based HF (GAHF) controller is tested on a threearea deregulated power system under different operating conditions and contract variations. The results of the proposed GAHF controller are compared with those of Multi Stage Fuzzy (MSF) controller, robust mixed H2/H∞ and classical PID controllers through some performance indices to illustrate its robust performance for a wide range of system parameters and load changes.
Abstract: In this work we present a solution for DAGC (Digital
Automatic Gain Control) in WLAN receivers compatible to IEEE 802.11a/g standard. Those standards define communication in 5/2.4
GHz band using Orthogonal Frequency Division Multiplexing OFDM modulation scheme. WLAN Transceiver that we have used
enables gain control over Low Noise Amplifier (LNA) and a
Variable Gain Amplifier (VGA). The control over those signals is
performed in our digital baseband processor using dedicated hardware block DAGC. DAGC in this process is used to automatically control the VGA and LNA in order to achieve better
signal-to-noise ratio, decrease FER (Frame Error Rate) and hold the
average power of the baseband signal close to the desired set point.
DAGC function in baseband processor is done in few steps: measuring power levels of baseband samples of an RF signal,accumulating the differences between the measured power level and
actual gain setting, adjusting a gain factor of the accumulation, and
applying the adjusted gain factor the baseband values. Based on the measurement results of RSSI signal dependence to input power we have concluded that this digital AGC can be implemented applying
the simple linearization of the RSSI. This solution is very simple but also effective and reduces complexity and power consumption of the
DAGC. This DAGC is implemented and tested both in FPGA and in ASIC as a part of our WLAN baseband processor. Finally, we have integrated this circuit in a compact WLAN PCMCIA board based on MAC and baseband ASIC chips designed from us.
Abstract: This study aims to investigate empirically the valuerelevance
of accounting information to domestic investors in Tehran
stock exchange from 1999 to 2006. During the present research
impacts of two factors, including positive vs. negative earnings and
the firm size are considered as well. The authors used earnings per
share and annual change of earnings per share as the income
statement indices, and book value of equity per share as the balance
sheet index. Return and Price models through regression analysis are
deployed in order to test the research hypothesis. Results depicted
that accounting information is value-relevance to domestic investors
in Tehran Stock Exchange according to both studied models.
However, income statement information has more value-relevance
than the balance sheet information. Furthermore, positive vs. negative
earnings and firm size seems to have significant impact on valuerelevance
of accounting information.
Abstract: Bioinformatics methods for predicting the T cell
coreceptor usage from the array of membrane protein of HIV-1 are
investigated. In this study, we aim to propose an effective prediction
method for dealing with the three-class classification problem of
CXCR4 (X4), CCR5 (R5) and CCR5/CXCR4 (R5X4). We made
efforts in investigating the coreceptor prediction problem as follows: 1)
proposing a feature set of informative physicochemical properties
which is cooperated with SVM to achieve high prediction test
accuracy of 81.48%, compared with the existing method with
accuracy of 70.00%; 2) establishing a large up-to-date data set by
increasing the size from 159 to 1225 sequences to verify the proposed
prediction method where the mean test accuracy is 88.59%, and 3)
analyzing the set of 14 informative physicochemical properties to
further understand the characteristics of HIV-1coreceptors.
Abstract: This research was aimed to develop and determine the
quality of online learning activities kit as well as to examine the
learning achievement of students and their satisfaction towards the kit
through authentic assessment. The tools in this research contained
online learning activities kit on plant in Thai literature in compliance
with the School Botanical Garden of Plant Genetic Conservation
Project under the Royal Initiative of Her Royal Highness Princess
Maha Chakri Sirindhorn, the assessment form, the learning
achievement test, the satisfaction form and the authentic assessment
form. The population consisted of 40 students in the second range of
primary years (Prathomsuksa 4 to 6) at Ban Khao Rak School,
Suratthani Province, Thailand. The research results showed that the
content quality of the developed online learning activities kit as
assessed by the experts was 4.70 on average or at very high level.
The pre-test and post-test comparison was made to examine the
learning achievement and it revealed that the post-test score was
higher than the pre-test score with statistical significance at the .01
level. The satisfaction of the sampling group towards the online
learning activities kit was 4.74 or at the highest level. The authentic
assessment showed an average of 1.69 or at good level. Therefore,
the online learning activities kit on plant in Thai literature in
compliance with the School Botanical Garden of Plant Genetic
Conservation Project under the Royal Initiative of Her Royal
Highness Princess Maha Chakri Sirindhorn could be used in real
classroom situations.
Abstract: Speech enhancement is the process of eliminating
noise and increasing the quality of a speech signal, which is
contaminated with other kinds of distortions. This paper is on
developing an optimum cascaded system for speech enhancement.
This aim is attained without diminishing any relevant speech
information and without much computational and time complexity.
LMS algorithm, Spectral Subtraction and Kalman filter have been
deployed as the main de-noising algorithms in this work. Since these
algorithms suffer from respective shortcomings, this work has been
undertaken to design cascaded systems in different combinations and
the evaluation of such cascades by qualitative (listening) and
quantitative (SNR) tests.
Abstract: An image compression method has been developed
using fuzzy edge image utilizing the basic Block Truncation Coding
(BTC) algorithm. The fuzzy edge image has been validated with
classical edge detectors on the basis of the results of the well-known
Canny edge detector prior to applying to the proposed method. The
bit plane generated by the conventional BTC method is replaced with
the fuzzy bit plane generated by the logical OR operation between
the fuzzy edge image and the corresponding conventional BTC bit
plane. The input image is encoded with the block mean and standard
deviation and the fuzzy bit plane. The proposed method has been
tested with test images of 8 bits/pixel and size 512×512 and found to
be superior with better Peak Signal to Noise Ratio (PSNR) when
compared to the conventional BTC, and adaptive bit plane selection
BTC (ABTC) methods. The raggedness and jagged appearance, and
the ringing artifacts at sharp edges are greatly reduced in
reconstructed images by the proposed method with the fuzzy bit
plane.
Abstract: Recognition of Indian languages scripts is challenging problems. In Optical Character Recognition [OCR], a character or symbol to be recognized can be machine printed or handwritten characters/numerals. There are several approaches that deal with problem of recognition of numerals/character depending on the type of feature extracted and different way of extracting them. This paper proposes a recognition scheme for handwritten Hindi (devnagiri) numerals; most admired one in Indian subcontinent. Our work focused on a technique in feature extraction i.e. global based approach using end-points information, which is extracted from images of isolated numerals. These feature vectors are fed to neuro-memetic model [18] that has been trained to recognize a Hindi numeral. The archetype of system has been tested on varieties of image of numerals. . In proposed scheme data sets are fed to neuro-memetic algorithm, which identifies the rule with highest fitness value of nearly 100 % & template associates with this rule is nothing but identified numerals. Experimentation result shows that recognition rate is 92-97 % compared to other models.
Abstract: Due to the tremendous amount of information provided
by the World Wide Web (WWW) developing methods for mining
the structure of web-based documents is of considerable interest. In
this paper we present a similarity measure for graphs representing
web-based hypertext structures. Our similarity measure is mainly
based on a novel representation of a graph as linear integer strings,
whose components represent structural properties of the graph. The
similarity of two graphs is then defined as the optimal alignment of
the underlying property strings. In this paper we apply the well known
technique of sequence alignments for solving a novel and challenging
problem: Measuring the structural similarity of generalized trees.
In other words: We first transform our graphs considered as high
dimensional objects in linear structures. Then we derive similarity
values from the alignments of the property strings in order to
measure the structural similarity of generalized trees. Hence, we
transform a graph similarity problem to a string similarity problem for
developing a efficient graph similarity measure. We demonstrate that
our similarity measure captures important structural information by
applying it to two different test sets consisting of graphs representing
web-based document structures.
Abstract: In today scenario, to meet enhanced demand imposed
by domestic, commercial and industrial consumers, various
operational & control activities of Radial Distribution Network
(RDN) requires a focused attention. Irrespective of sub-domains
research aspects of RDN like network reconfiguration, reactive
power compensation and economic load scheduling etc, network
performance parameters are usually estimated by an iterative process
and is commonly known as load (power) flow algorithm. In this
paper, a simple mechanism is presented to implement the load flow
analysis (LFA) algorithm. The reported algorithm utilizes graph
theory principles and is tested on a 69- bus RDN.
Abstract: The importance of supply chain and logistics
management has been widely recognised. Effective management of
the supply chain can reduce costs and lead times and improve
responsiveness to changing customer demands. This paper proposes a
multi-matrix real-coded Generic Algorithm (MRGA) based
optimisation tool that minimises total costs associated within supply
chain logistics. According to finite capacity constraints of all parties
within the chain, Genetic Algorithm (GA) often produces infeasible
chromosomes during initialisation and evolution processes. In the
proposed algorithm, chromosome initialisation procedure, crossover
and mutation operations that always guarantee feasible solutions
were embedded. The proposed algorithm was tested using three sizes
of benchmarking dataset of logistic chain network, which are typical
of those faced by most global manufacturing companies. A half
fractional factorial design was carried out to investigate the influence
of alternative crossover and mutation operators by varying GA
parameters. The analysis of experimental results suggested that the
quality of solutions obtained is sensitive to the ways in which the
genetic parameters and operators are set.
Abstract: This paper deals with tracking and estimating time delay between two signals. The simulation of this algorithm accomplished by using Mathcad package is carried out. The algorithm we will present adaptively controls and tracking the delay, so as to minimize the mean square of this error. Thus the algorithm in this case has task not only of seeking the minimum point of error but also of tracking the change of position, leading to a significant improving of performance. The flowchart of the algorithm is presented as well as several tests of different cases are carried out.
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: In this paper is being described a possible use of
virtualization technology in teaching computer networks. The
virtualization can be used as a suitable tool for creating virtual
network laboratories, supplementing the real laboratories and
network simulation software in teaching networking concepts. It will
be given a short description of characteristic projects in the area of
virtualization technology usage in network simulation, network
experiments and engineering education. A method for implementing
laboratory has also been explained, together with possible laboratory
usage and design of laboratory exercises. At the end, the laboratory
test results of virtual laboratory are presented as well.
Abstract: We proposed a new class of asymmetric turbo encoder for 3G systems that performs well in both “water fall" and “error floor" regions in [7]. In this paper, a modified (optimal) power allocation scheme for the different bits of new class of asymmetric turbo encoder has been investigated to enhance the performance. The simulation results and performance bound for proposed asymmetric turbo code with modified Unequal Power Allocation (UPA) scheme for the frame length, N=400, code rate, r=1/3 with Log-MAP decoder over Additive White Gaussian Noise (AWGN) channel are obtained and compared with the system with typical UPA and without UPA. The performance tests are extended over AWGN channel for different frame size to verify the possibility of implementation of the modified UPA scheme for the proposed asymmetric turbo code. From the performance results, it is observed that the proposed asymmetric turbo code with modified UPA performs better than the system without UPA and with typical UPA and it provides a coding gain of 0.4 to 0.52dB.
Abstract: In this paper we present a GP-based method for automatically evolve projections, so that data can be more easily classified in the projected spaces. At the same time, our approach can reduce dimensionality by constructing more relevant attributes. Fitness of each projection measures how easy is to classify the dataset after applying the projection. This is quickly computed by a Simple Linear Perceptron. We have tested our approach in three domains. The experiments show that it obtains good results, compared to other Machine Learning approaches, while reducing dimensionality in many cases.
Abstract: Since Software testing becomes an important part of
Software development in order to improve the quality of software,
many automation tools are created to help testing functionality of
software. There are a few issues about usability of these tools, one is
that the result log which is generated from tools contains useless
information that the tester cannot use result log to communicate
efficiently, or the result log needs to use a specific application to open.
This paper introduces a new method, SBTAR that improves usability
of automated test tools in a part of a result log. The practice will use
the capability of tools named as IBM Rational Robot to create a
customized function, the function would generate new format of a
result log which contains useful information faster and easier to
understand than using the original result log which was generated
from the tools. This result log also increases flexibility by Microsoft
Word or WordPad to make them readable.