Abstract: The conjugate gradient optimization algorithm
usually used for nonlinear least squares is presented and is
combined with the modified back propagation algorithm yielding
a new fast training multilayer perceptron (MLP) algorithm
(CGFR/AG). The approaches presented in the paper consist of
three steps: (1) Modification on standard back propagation
algorithm by introducing gain variation term of the activation
function, (2) Calculating the gradient descent on error with
respect to the weights and gains values and (3) the determination
of the new search direction by exploiting the information
calculated by gradient descent in step (2) as well as the previous
search direction. The proposed method improved the training
efficiency of back propagation algorithm by adaptively modifying
the initial search direction. Performance of the proposed method
is demonstrated by comparing to the conjugate gradient algorithm
from neural network toolbox for the chosen benchmark. The
results show that the number of iterations required by the
proposed method to converge is less than 20% of what is required
by the standard conjugate gradient and neural network toolbox
algorithm.
Abstract: This article discusses the customs and traditions in
Turkestan in the late XIXth and early XXth centuries. Having a long
history, Turkestan is well-known as the birthplace of many nations
and nationalities. The name of Turkestan is also given to it for a
reason - the land of the Turkic peoples who inhabited Central Asia
and united under together. Currently, nations and nationalities of the
Turkestan region formed their own sovereign states, and every year
they prove their country names in the world community. Political,
economic importance of Turkestan, which became the gold wire
between Asia and Europe was always very high. So systematically
various aggressive actions were made by several great powers. As a
result of expansionary policy of colonization of the Russian Empire -
the Turkestan has appeared.
Abstract: This paper begins with formal defining of human rights and freedoms, and the basic document regarding the said subject is undoubtedly French Declaration of the Rights of Man and of the Citizen from 789. This paper furthermore parses legal sources relevant for the workers' rights in legal system of the Republic of Croatia, international contracts and the Labour Act, which is also a master bill regarding workers' rights The authors are also dealing with issues of Constitutional Court of the Republic of Croatia and its' position in judicial system of the Republic of Croatia, as well as with the specifics of Constitutional Complaint, and the crucial part of the paper is based on the research conducted with an aim to determine implementation of rights and liberties guaranteed by the articles 54. and 55. of the Constitution of the Republic of Croatia by means of Constitutional Complaint.
Abstract: Computations with higher than the IEEE 754 standard double-precision (about 16 significant digits) are required recently. Although there are available software routines in Fortran and C for high-precision computation, users are required to implement such routines in their own computers with detailed knowledges about them. We have constructed an user-friendly online system for octupleprecision computation. In our Web system users with no knowledges about high-precision computation can easily perform octupleprecision computations, by choosing mathematical functions with argument(s) inputted, by writing simple mathematical expression(s) or by uploading C program(s). In this paper we enhance the Web system above by adding the facility of uploading Fortran programs, which have been widely used in scientific computing. To this end we construct converter routines in two stages.
Abstract: In this paper we present a method for gene ranking
from DNA microarray data. More precisely, we calculate the correlation
networks, which are unweighted and undirected graphs, from
microarray data of cervical cancer whereas each network represents
a tissue of a certain tumor stage and each node in the network
represents a gene. From these networks we extract one tree for
each gene by a local decomposition of the correlation network. The
interpretation of a tree is that it represents the n-nearest neighbor
genes on the n-th level of a tree, measured by the Dijkstra distance,
and, hence, gives the local embedding of a gene within the correlation
network. For the obtained trees we measure the pairwise similarity
between trees rooted by the same gene from normal to cancerous
tissues. This evaluates the modification of the tree topology due to
progression of the tumor. Finally, we rank the obtained similarity
values from all tissue comparisons and select the top ranked genes.
For these genes the local neighborhood in the correlation networks
changes most between normal and cancerous tissues. As a result
we find that the top ranked genes are candidates suspected to be
involved in tumor growth and, hence, indicates that our method
captures essential information from the underlying DNA microarray
data of cervical cancer.
Abstract: It is known that if harmonic spectra are decreased, then
acoustic noise also decreased. Hence, this paper deals with a new
random switching strategy using DSP TMS320F2812 to decrease the
harmonics spectra of single phase switched reluctance motor. The
proposed method which combines random turn-on, turn-off angle
technique and random pulse width modulation technique is shown. A
harmonic spread factor (HSF) is used to evaluate the random
modulation scheme. In order to confirm the effectiveness of the new
method, the experimental results show that the harmonic intensity of
output voltage for the proposed method is better than that for
conventional methods.
Abstract: Environmental factors affect agriculture production
productivity and efficiency resulted in changing of profit efficiency.
This paper attempts to estimate the impacts of environmental factors
to profitability of rice farmers in the Red River Delta of Vietnam. The
dataset was extracted from 349 rice farmers using personal
interviews. Both OLS and MLE trans-log profit functions were used
in this study. Five production inputs and four environmental factors
were included in these functions. The estimation of the stochastic
profit frontier with a two-stage approach was used to measure
profitability. The results showed that the profit efficiency was about
75% on the average and environmental factors change profit
efficiency significantly beside farm specific characteristics. Plant
disease, soil fertility, irrigation apply and water pollution were the
four environmental factors cause profit loss in rice production. The
result indicated that farmers should reduce household size, farm
plots, apply row seeding technique and improve environmental
factors to obtain high profit efficiency with special consideration is
given for irrigation water quality improvement.
Abstract: A mobile agent is a software which performs an
action autonomously and independently as a person or an
organizations assistance. Mobile agents are used for searching
information, retrieval information, filtering, intruder recognition in
networks, and so on. One of the important issues of mobile agent is
their security. It must consider different security issues in effective
and secured usage of mobile agent. One of those issues is the
integrity-s protection of mobile agents.
In this paper, the advantages and disadvantages of each method,
after reviewing the existing methods, is examined. Regarding to this
matter that each method has its own advantage or disadvantage, it
seems that by combining these methods, one can reach to a better
method for protecting the integrity of mobile agents. Therefore, this
method is provided in this paper and then is evaluated in terms of
existing method. Finally, this method is simulated and its results are
the sign of improving the possibility of integrity-s protection of
mobile agents.
Abstract: Studies in neuroscience suggest that both global and
local feature information are crucial for perception and recognition of
faces. It is widely believed that local feature is less sensitive to
variations caused by illumination, expression and illumination. In
this paper, we target at designing and learning local features for face
recognition. We designed three types of local features. They are
semi-global feature, local patch feature and tangent shape feature.
The designing of semi-global feature aims at taking advantage of
global-like feature and meanwhile avoiding suppressing AdaBoost
algorithm in boosting weak classifies established from small local
patches. The designing of local patch feature targets at automatically
selecting discriminative features, and is thus different with traditional
ways, in which local patches are usually selected manually to cover
the salient facial components. Also, shape feature is considered in
this paper for frontal view face recognition. These features are
selected and combined under the framework of boosting algorithm
and cascade structure. The experimental results demonstrate that the
proposed approach outperforms the standard eigenface method and
Bayesian method. Moreover, the selected local features and
observations in the experiments are enlightening to researches in
local feature design in face recognition.
Abstract: Based on the feature of model disturbances and uncertainty being compensated dynamically in auto – disturbances-rejection-controller (ADRC), a new method using ADRC is proposed for the decoupling control of dispenser longitudinal movement in big flight envelope. Developed from nonlinear model directly, ADRC is especially suitable for dynamic model that has big disturbances. Furthermore, without changing the structure and parameters of the controller in big flight envelope, this scheme can simplify the design of flight control system. The simulation results in big flight envelope show that the system achieves high dynamic performance, steady state performance and the controller has strong robustness.
Abstract: Fuel and oxidant gas delivery plate, or fuel cell
plate, is a key component of a Proton Exchange Membrane (PEM)
fuel cell. To manufacture low-cost and high performance fuel cell
plates, advanced computer modeling and finite element structure
analysis are used as virtual prototyping tools for the optimization
of the plates at the early design stage. The present study examines
thermal stress analysis of the fuel cell plates that are produced
using a patented, low-cost fuel cell plate production technique
based on screen-printing. Design optimization is applied to
minimize the maximum stress within the plate, subject to strain
constraint with both geometry and material parameters as design
variables. The study reveals the characteristics of the printed
plates, and provides guidelines for the structure and material design
of the fuel cell plate.
Abstract: Let k ≥ 1 and t ≥ 0 be two integers and let d = k2 + k be a positive non-square integer. In this paper, we consider the integer solutions of Pell equation x2 - dy2 = 2t. Further we derive a recurrence relation on the solutions of this equation.
Abstract: This paper presents a novel two-phase hybrid optimization algorithm with hybrid genetic operators to solve the optimal control problem of a single stage hybrid manufacturing system. The proposed hybrid real coded genetic algorithm (HRCGA) is developed in such a way that a simple real coded GA acts as a base level search, which makes a quick decision to direct the search towards the optimal region, and a local search method is next employed to do fine tuning. The hybrid genetic operators involved in the proposed algorithm improve both the quality of the solution and convergence speed. The phase–1 uses conventional real coded genetic algorithm (RCGA), while optimisation by direct search and systematic reduction of the size of search region is employed in the phase – 2. A typical numerical example of an optimal control problem with the number of jobs varying from 10 to 50 is included to illustrate the efficacy of the proposed algorithm. Several statistical analyses are done to compare the validity of the proposed algorithm with the conventional RCGA and PSO techniques. Hypothesis t – test and analysis of variance (ANOVA) test are also carried out to validate the effectiveness of the proposed algorithm. The results clearly demonstrate that the proposed algorithm not only improves the quality but also is more efficient in converging to the optimal value faster. They can outperform the conventional real coded GA (RCGA) and the efficient particle swarm optimisation (PSO) algorithm in quality of the optimal solution and also in terms of convergence to the actual optimum value.
Abstract: Biometric techniques are gaining importance for
personal authentication and identification as compared to the
traditional authentication methods. Biometric templates are
vulnerable to variety of attacks due to their inherent nature. When a
person-s biometric is compromised his identity is lost. In contrast to
password, biometric is not revocable. Therefore, providing security
to the stored biometric template is very crucial. Crypto biometric
systems are authentication systems, which blends the idea of
cryptography and biometrics. Fuzzy vault is a proven crypto
biometric construct which is used to secure the biometric templates.
However fuzzy vault suffer from certain limitations like nonrevocability,
cross matching. Security of the fuzzy vault is affected
by the non-uniform nature of the biometric data. Fuzzy vault when
hardened with password overcomes these limitations. Password
provides an additional layer of security and enhances user privacy.
Retina has certain advantages over other biometric traits. Retinal
scans are used in high-end security applications like access control to
areas or rooms in military installations, power plants, and other high
risk security areas. This work applies the idea of fuzzy vault for
retinal biometric template. Multimodal biometric system
performance is well compared to single modal biometric systems.
The proposed multi modal biometric fuzzy vault includes combined
feature points from retina and fingerprint. The combined vault is
hardened with user password for achieving high level of security.
The security of the combined vault is measured using min-entropy.
The proposed password hardened multi biometric fuzzy vault is
robust towards stored biometric template attacks.
Abstract: This paper proposed a stiffness analysis method for a
3-PRS mechanism for welding thick aluminum plate using FSW
technology. In the molding process, elastic deformation of lead-screws
and links are taken into account. This method is based on the virtual
work principle. Through a survey of the commonly used stiffness
performance indices, the minimum and maximum eigenvalues of the
stiffness matrix are used to evaluate the stiffness of the 3-PRS
mechanism. Furthermore, A FEA model has been constructed to verify
the method. Finally, we redefined the workspace using the stiffness
analysis method.
Abstract: Heat powered solid sorption is a feasible alternative to
electrical vapor compression refrigeration systems. In this paper,
activated carbon (powder type Maxsorb and fiber type ACF-A10)-
CO2 based adsorption cooling cycles are studied using the pressuretemperature-
concentration (P-T-W) diagram. The specific cooling
effect (SCE) and the coefficient of performance (COP) of these two
cooling systems are simulated for the driving heat source
temperatures ranging from 30 ºC to 90 ºC in terms of different
cooling load temperatures with a cooling source temperature of 25
ºC. It is found from the present analysis that Maxsorb-CO2 couple
shows higher cooling capacity and COP. The maximum COPs of
Maxsorb-CO2 and ACF(A10)-CO2 based cooling systems are found
to be 0.15 and 0.083, respectively. The main innovative feature of
this cooling cycle is the ability to utilize low temperature waste heat
or solar energy using CO2 as the refrigerant, which is one of the best
alternative for applications where flammability and toxicity are not
allowed.
Abstract: C-control chart assumes that process nonconformities follow a Poisson distribution. In actuality, however, this Poisson distribution does not always occur. A process control for semiconductor based on a Poisson distribution always underestimates the true average amount of nonconformities and the process variance. Quality is described more accurately if a compound Poisson process is used for process control at this time. A cumulative sum (CUSUM) control chart is much better than a C control chart when a small shift will be detected. This study calculates one-sided CUSUM ARLs using a Markov chain approach to construct a CUSUM control chart with an underlying Poisson-Gamma compound distribution for the failure mechanism. Moreover, an actual data set from a wafer plant is used to demonstrate the operation of the proposed model. The results show that a CUSUM control chart realizes significantly better performance than EWMA.
Abstract: This paper evaluates performances of an adaptive noise
cancelling (ANC) based target detection algorithm on a set of real test
data supported by the Defense Evaluation Research Agency (DERA
UK) for multi-target wideband active sonar echolocation system. The
hybrid algorithm proposed is a combination of an adaptive ANC
neuro-fuzzy scheme in the first instance and followed by an iterative
optimum target motion estimation (TME) scheme. The neuro-fuzzy
scheme is based on the adaptive noise cancelling concept with the
core processor of ANFIS (adaptive neuro-fuzzy inference system) to
provide an effective fine tuned signal. The resultant output is then
sent as an input to the optimum TME scheme composed of twogauge
trimmed-mean (TM) levelization, discrete wavelet denoising
(WDeN), and optimal continuous wavelet transform (CWT) for
further denosing and targets identification. Its aim is to recover the
contact signals in an effective and efficient manner and then determine
the Doppler motion (radial range, velocity and acceleration) at very
low signal-to-noise ratio (SNR). Quantitative results have shown that
the hybrid algorithm have excellent performance in predicting targets-
Doppler motion within various target strength with the maximum
false detection of 1.5%.
Abstract: Control chart pattern recognition is one of the most important tools to identify the process state in statistical process control. The abnormal process state could be classified by the recognition of unnatural patterns that arise from assignable causes. In this study, a wavelet based neural network approach is proposed for the recognition of control chart patterns that have various characteristics. The procedure of proposed control chart pattern recognizer comprises three stages. First, multi-resolution wavelet analysis is used to generate time-shape and time-frequency coefficients that have detail information about the patterns. Second, distance based features are extracted by a bi-directional Kohonen network to make reduced and robust information. Third, a back-propagation network classifier is trained by these features. The accuracy of the proposed method is shown by the performance evaluation with numerical results.
Abstract: This paper proposes a specialized Web robot to automatically collect objectionable Web contents for use in an objectionable Web content classification system, which creates the URL database of objectionable Web contents. It aims at shortening the update period of the DB, increasing the number of URLs in the DB, and enhancing the accuracy of the information in the DB.