Abstract: This paper explores an application of an adaptive learning mechanism for robots based on the natural immune system. Most of the research carried out so far are based either on the innate or adaptive characteristics of the immune system, we present a combination of these to achieve behavior arbitration wherein a robot learns to detect vulnerable areas of a track and adapts to the required speed over such portions. The test bed comprises of two Lego robots deployed simultaneously on two predefined near concentric tracks with the outer robot capable of helping the inner one when it misaligns. The helper robot works in a damage-control mode by realigning itself to guide the other robot back onto its track. The panic-stricken robot records the conditions under which it was misaligned and learns to detect and adapt under similar conditions thereby making the overall system immune to such failures.
Abstract: In this paper, the effect of transmission codes on the
performance of coherent square M-ary quadrature amplitude
modulation (CSMQAM) under hybrid selection/maximal-ratio
combining (H-S/MRC) diversity is analysed. The fading channels are
modeled as frequency non-selective slow independent and identically
distributed Rayleigh fading channels corrupted by additive white
Gaussian noise (AWGN). The results for coded MQAM are
computed numerically for the case of (24,12) extended Golay code
and compared with uncoded MQAM under H-S/MRC diversity by
plotting error probabilities versus average signal to noise ratio (SNR)
for various values L and N in order to examine the improvement in
the performance of the digital communications system as the number
of selected diversity branches is increased. The results for no
diversity, conventional SC and Lth order MRC schemes are also
plotted for comparison. Closed form analytical results derived in this
paper are sufficiently simple and therefore can be computed
numerically without any approximations. The analytical results
presented in this paper are expected to provide useful information
needed for design and analysis of digital communication systems
over wireless fading channels.
Abstract: Previous studies on political budget cycles (PBCs)
implicitly assume the executive has full discretion power over fiscal
policy, neglecting the role of checks and balances of the legislature.
This paper goes beyond traditional PBCs models and sheds light on
the case study of Japan, South Korea, and Taiwan over the 1988-2007
periods. Based on the results, we find no evidence of electoral impacts
on the public expenditures in South Korean and Taiwan's
congressional elections. We also noted that PBCs are found on
Taiwan-s government expenditures during our sample periods.
Furthermore, the results also show that Japan-s legislature has a
significant checks and balances on government-s expenditures.
However, empirical results show that the legislature veto player in
Taiwan neither has effect on the reduction of public expenditures, nor
has the moderating effect over Taiwan-s political budget cycles, albeit
that they are statistically insignificant.We suggest that the existence of
PBCs in Taiwan is due to a weaker systemof checks and balances. Our
conjecture is that Taiwan either has no legislative veto player or has
observed low compliance to the law during the time period examined
in our study.
Abstract: The proper design of RF pulses in magnetic resonance imaging (MRI) has a direct impact on the quality of acquired images, and is needed for many applications. Several techniques have been proposed to obtain the RF pulse envelope given the desired slice profile. Unfortunately, these techniques do not take into account the limitations of practical implementation such as limited amplitude resolution. Moreover, implementing constraints for special RF pulses on most techniques is not possible. In this work, we propose to develop an approach for designing optimal RF pulses under theoretically any constraints. The new technique will pose the RF pulse design problem as a combinatorial optimization problem and uses efficient techniques from this area such as genetic algorithms (GA) to solve this problem. In particular, an objective function will be proposed as the norm of the difference between the desired profile and the one obtained from solving the Bloch equations for the current RF pulse design values. The proposed approach will be verified using analytical solution based RF simulations and compared to previous methods such as Shinnar-Le Roux (SLR) method, and analysis, selected, and tested the options and parameters that control the Genetic Algorithm (GA) can significantly affect its performance to get the best improved results and compared to previous works in this field. The results show a significant improvement over conventional design techniques, select the best options and parameters for GA to get most improvement over the previous works, and suggest the practicality of using of the new technique for most important applications as slice selection for large flip angles, in the area of unconventional spatial encoding, and another clinical use.
Abstract: The rotation of starting pitchers is a strategic issue
which has a significant impact on the performance of a professional
team. Choosing an optimal starting pitcher from among many
alternatives is a multi-criteria decision-making (MCDM) problem. In
this study, a model using the Analytic Hierarchy Process (AHP) and
Technique for Order Performance by Similarity to the Ideal Solution
(TOPSIS) is proposed with which to arrange the starting pitcher
rotation for teams of the Chinese Professional Baseball League. The
AHP is used to analyze the structure of the starting pitcher selection
problem and to determine the weights of the criteria, while the
TOPSIS method is used to make the final ranking. An empirical
analysis is conducted to illustrate the utilization of the model for the
starting pitcher rotation problem. The results demonstrate the
effectiveness and feasibility of the proposed model.
Abstract: The aim of this paper is to present current and future
procedures in castings procurement. Differences in procurement are
highlighted. The supplier selection criteria used in practice is
compared to literature findings. Different trends related to supply
chains are presented and it is described how they are reflected in
reality to castings procurement. To fulfil the aim, interviews were
conducted in nine companies using castings. It was found that largest
casting users have the most subcontractor foundries and it is more
typical that they have multiple suppliers for the same parts. Currently
only two companies out of nine purchase castings outside Europe,
but the others are also progressing in the same direction. The main
reason is the need to lower purchasing costs. Another trend is that all
companies want to buy cast components or sub-assemblies instead of
raw castings from foundries. It was found that price is a main
supplier selection criterion. All companies use competitive bidding in
supplier selection.
Abstract: Dynamic location referencing method is an important technology to shield map differences. These method references objects of the road network by utilizing condensed selection of its real-world geographic properties stored in a digital map database, which overcomes the defections existing in pre-coded location referencing methods. The high attributes completeness requirements and complicated reference point selection algorithm are the main problems of recent researches. Therefore, a dynamic location referencing algorithm combining intersection points selected at the extremities compulsively and road link points selected according to link partition principle was proposed. An experimental system based on this theory was implemented. The tests using Beijing digital map database showed satisfied results and thus verified the feasibility and practicability of this method.
Abstract: Mostly the real life signals are time varying in nature. For proper characterization of such signals, time-frequency representation is required. The STFT (short-time Fourier transform) is a classical tool used for this purpose. The limitation of the STFT is its fixed time-frequency resolution. Thus, an enhanced version of the STFT, which is based on the cross-level sampling, is devised. It can adapt the sampling frequency and the window function length by following the input signal local variations. Therefore, it provides an adaptive resolution time-frequency representation of the input. The computational complexity of the proposed STFT is deduced and compared to the classical one. The results show a significant gain of the computational efficiency and hence of the processing power. The processing error of the proposed technique is also discussed.
Abstract: Three similar negative differential resistance (NDR)
profiles with both high peak to valley current density ratio (PVCDR)
value and high peak current density (PCD) value in unity resonant
tunneling electronic circuit (RTEC) element is developed in this paper.
The PCD values and valley current density (VCD) values of the three
NDR curves are all about 3.5 A and 0.8 A, respectively. All PV values
of NDR curves are 0.40 V, 0.82 V, and 1.35 V, respectively. The VV
values are 0.61 V, 1.07 V, and 1.69 V, respectively. All PVCDR
values reach about 4.4 in three NDR curves. The PCD value of 3.5 A
in triple PVCDR RTEC element is better than other resonant
tunneling devices (RTD) elements. The high PVCDR value is
concluded the lower VCD value about 0.8 A. The low VCD value is
achieved by suitable selection of resistors in triple PVCDR RTEC
element. The low PV value less than 1.35 V possesses low power
dispersion in triple PVCDR RTEC element. The designed multiple
value logical level (MVLL) system using triple PVCDR RTEC
element provides equidistant logical level. The logical levels of
MVLL system are about 0.2 V, 0.8 V, 1.5 V, and 2.2 V from low
voltage to high voltage and then 2.2 V, 1.3 V, 0.8 V, and 0.2 V from
high voltage back to low voltage in half cycle of sinusoid wave. The
output level of four levels MVLL system is represented in 0.3 V, 1.1 V,
1.7 V, and 2.6 V, which satisfies the NMP condition of traditional
two-bit system. The remarkable logical characteristic of improved
MVLL system with paralleled capacitor are with four significant
stable logical levels about 220 mV, 223 mV, 228 mV, and 230 mV.
The stability and articulation of logical levels of improved MVLL
system are outstanding. The average holding time of improved MVLL
system is approximately 0.14 μs. The holding time of improved
MVLL system is fourfold than of basic MVLL system. The function of
additional capacitor in the improved MVLL system is successfully
discovered.
Abstract: This paper presents a new approach for the protection
of Thyristor-Controlled Series Compensator (TCSC) line using
Support Vector Machine (SVM). One SVM is trained for fault
classification and another for section identification. This method use
three phase current measurement that results in better speed and
accuracy than other SVM based methods which used single phase
current measurement. This makes it suitable for real-time protection.
The method was tested on 10,000 data instances with a very wide
variation in system conditions such as compensation level, source
impedance, location of fault, fault inception angle, load angle at
source bus and fault resistance. The proposed method requires only
local current measurement.
Abstract: Regression testing is a maintenance activity applied to
modified software to provide confidence that the changed parts are
correct and that the unchanged parts have not been adversely affected
by the modifications. Regression test selection techniques reduce the
cost of regression testing, by selecting a subset of an existing test
suite to use in retesting modified programs. This paper presents the
first general regression-test-selection technique, which based on code
and allows selecting test cases for any programs written in any
programming language. Then it handles incomplete program. We
also describe RTSDiff, a regression-test-selection system that
implements the proposed technique. The results of the empirical
studied that performed in four programming languages java, C#, Cµ
and Visual basic show that the efficiency and effective in reducing
the size of test suit.
Abstract: This paper compares the recent transformerless ACDC
power converter architectures and provides an assessment of
each. A prototype of one of the transformerless AC-DC converter
architecture is also presented depicting the feasibility of a small form
factor, power supply design. In this paper component selection
guidelines to achieve high efficiency AC-DC power conversion are
also discussed.
Abstract: A Decision Support System/Expert System for stock
portfolio selection presented where at first step, both technical and
fundamental data used to estimate technical and fundamental return
and risk (1st phase); Then, the estimated values are aggregated with
the investor preferences (2nd phase) to produce convenient stock
portfolio.
In the 1st phase, there are two expert systems, each of which is
responsible for technical or fundamental estimation. In the technical
expert system, for each stock, twenty seven candidates are identified
and with using rough sets-based clustering method (RC) the effective
variables have been selected. Next, for each stock two fuzzy rulebases
are developed with fuzzy C-Mean method and Takai-Sugeno-
Kang (TSK) approach; one for return estimation and the other for
risk. Thereafter, the parameters of the rule-bases are tuned with backpropagation
method. In parallel, for fundamental expert systems,
fuzzy rule-bases have been identified in the form of “IF-THEN" rules
through brainstorming with the stock market experts and the input
data have been derived from financial statements; as a result two
fuzzy rule-bases have been generated for all the stocks, one for return
and the other for risk.
In the 2nd phase, user preferences represented by four criteria and
are obtained by questionnaire. Using an expert system, four estimated
values of return and risk have been aggregated with the respective
values of user preference. At last, a fuzzy rule base having four rules,
treats these values and produce a ranking score for each stock which
will lead to a satisfactory portfolio for the user.
The stocks of six manufacturing companies and the period of
2003-2006 selected for data gathering.
Abstract: As a popular rank-reduced vector space approach,
Latent Semantic Indexing (LSI) has been used in information
retrieval and other applications. In this paper, an LSI-based content
vector model for text classification is presented, which constructs
multiple augmented category LSI spaces and classifies text by their
content. The model integrates the class discriminative information
from the training data and is equipped with several pertinent feature
selection and text classification algorithms. The proposed classifier
has been applied to email classification and its experiments on a
benchmark spam testing corpus (PU1) have shown that the approach
represents a competitive alternative to other email classifiers based
on the well-known SVM and naïve Bayes algorithms.
Abstract: Selecting the routes and the assignment of link flow in a computer communication networks are extremely complex combinatorial optimization problems. Metaheuristics, such as genetic or simulated annealing algorithms, are widely applicable heuristic optimization strategies that have shown encouraging results for a large number of difficult combinatorial optimization problems. This paper considers the route selection and hence the flow assignment problem. A genetic algorithm and simulated annealing algorithm are used to solve this problem. A new hybrid algorithm combining the genetic with the simulated annealing algorithm is introduced. A modification of the genetic algorithm is also introduced. Computational experiments with sample networks are reported. The results show that the proposed modified genetic algorithm is efficient in finding good solutions of the flow assignment problem compared with other techniques.
Abstract: The recognition of human faces, especially those with
different orientations is a challenging and important problem in image
analysis and classification. This paper proposes an effective scheme
for rotation invariant face recognition using Log-Polar Transform and
Discrete Cosine Transform combined features. The rotation invariant
feature extraction for a given face image involves applying the logpolar
transform to eliminate the rotation effect and to produce a row
shifted log-polar image. The discrete cosine transform is then applied
to eliminate the row shift effect and to generate the low-dimensional
feature vector. A PSO-based feature selection algorithm is utilized to
search the feature vector space for the optimal feature subset.
Evolution is driven by a fitness function defined in terms of
maximizing the between-class separation (scatter index).
Experimental results, based on the ORL face database using testing
data sets for images with different orientations; show that the
proposed system outperforms other face recognition methods. The
overall recognition rate for the rotated test images being 97%,
demonstrating that the extracted feature vector is an effective rotation
invariant feature set with minimal set of selected features.
Abstract: This paper presents a solution for the behavioural animation of autonomous virtual agent navigation in virtual environments. We focus on using Dempster-Shafer-s Theory of Evidence in developing visual sensor for virtual agent. The role of the visual sensor is to capture the information about the virtual environment or identifie which part of an obstacle can be seen from the position of the virtual agent. This information is require for vitual agent to coordinate navigation in virtual environment. The virual agent uses fuzzy controller as a navigation system and Fuzzy α - level for the action selection method. The result clearly demonstrates the path produced is reasonably smooth even though there is some sharp turn and also still not diverted too far from the potential shortest path. This had indicated the benefit of our method, where more reliable and accurate paths produced during navigation task.
Abstract: wind catchers have been served as a cooling system, used to provide acceptable ventilation by means of renewable energy of wind. In the present study, the city of Yazd in arid climate is selected as case study. From the architecture point of view, learning about wind catchers in this study is done by means of field surveys. Research method for selection of the case is based on random form, and analytical method. Wind catcher typology and knowledge of relationship governing the wind catcher's architecture were those measures that are taken for the first time. 53 wind catchers were analyzed. The typology of the wind-catchers is done by the physical analyzing, patterns and common concepts as incorporated in them. How the architecture of wind catcher can influence their operations by analyzing thermal behavior are the archetypes of selected wind catchers. Calculating fluids dynamics science, fluent software and numerical analysis are used in this study as the most accurate analytical approach. The results obtained from these analyses show the formal specifications of wind catchers with optimum operation in Yazd. The knowledge obtained from the optimum model could be used for design and construction of wind catchers with more improved operation
Abstract: Tumor classification is a key area of research in the
field of bioinformatics. Microarray technology is commonly used in
the study of disease diagnosis using gene expression levels. The
main drawback of gene expression data is that it contains thousands
of genes and a very few samples. Feature selection methods are used
to select the informative genes from the microarray. These methods
considerably improve the classification accuracy. In the proposed
method, Genetic Algorithm (GA) is used for effective feature
selection. Informative genes are identified based on the T-Statistics,
Signal-to-Noise Ratio (SNR) and F-Test values. The initial candidate
solutions of GA are obtained from top-m informative genes. The
classification accuracy of k-Nearest Neighbor (kNN) method is used
as the fitness function for GA. In this work, kNN and Support Vector
Machine (SVM) are used as the classifiers. The experimental results
show that the proposed work is suitable for effective feature
selection. With the help of the selected genes, GA-kNN method
achieves 100% accuracy in 4 datasets and GA-SVM method
achieves in 5 out of 10 datasets. The GA with kNN and SVM
methods are demonstrated to be an accurate method for microarray
based tumor classification.
Abstract: Today, advantage of biotechnology especially in environmental issues compared to other technologies is irrefragable. Kimia Gharb Gostar Industries Company, as a largest producer of citric acid in Middle East, applies biotechnology for this goal. Citrogypsum is a by–product of citric acid production and it considered as a valid residuum of this company. At this paper summary of acid citric production and condition of Citrogypsum production in company were introduced in addition to defmition of Citrogypsum production and its applications in world. According to these information and evaluation of present conditions about Iran needing to Citrogypsum, the best priority was introduced and emphasized on strategy selection and proper programming for self-sufficiency. The Delphi technique was used to elicit expert opinions about criteria for evaluating the usages. The criteria identified by the experts were profitability, capacity of production, the degree of investment, marketable, production ease and time production. The Analytical Hierarchy Process (ARP) and Expert Choice software were used to compare the alternatives on the criteria derived from the Delphi process.