Abstract: Kernel function, which allows the formulation of nonlinear variants of any algorithm that can be cast in terms of dot products, makes the Support Vector Machines (SVM) have been successfully applied in many fields, e.g. classification and regression. The importance of kernel has motivated many studies on its composition. It-s well-known that reproducing kernel (R.K) is a useful kernel function which possesses many properties, e.g. positive definiteness, reproducing property and composing complex R.K by simple operation. There are two popular ways to compute the R.K with explicit form. One is to construct and solve a specific differential equation with boundary value whose handicap is incapable of obtaining a unified form of R.K. The other is using a piecewise integral of the Green function associated with a differential operator L. The latter benefits the computation of a R.K with a unified explicit form and theoretical analysis, whereas there are relatively later studies and fewer practical computations. In this paper, a new algorithm for computing a R.K is presented. It can obtain the unified explicit form of R.K in general reproducing kernel Hilbert space. It avoids constructing and solving the complex differential equations manually and benefits an automatic, flexible and rigorous computation for more general RKHS. In order to validate that the R.K computed by the algorithm can be used in SVM well, some illustrative examples and a comparison between R.K and Gaussian kernel (RBF) in support vector regression are presented. The result shows that the performance of R.K is close or slightly superior to that of RBF.
Abstract: Nowadays, the demand for high product quality
focuses extensive attention to the quality of machined surface. The
(CNC) milling machine facilities provides a wide variety of
parameters set-up, making the machining process on the glass
excellent in manufacturing complicated special products compared to
other machining processes. However, the application of grinding
process on the CNC milling machine could be an ideal solution to
improve the product quality, but adopting the right machining
parameters is required. In glass milling operation, several machining
parameters are considered to be significant in affecting surface
roughness. These parameters include the lubrication pressure, spindle
speed, feed rate and depth of cut. In this research work, a fuzzy logic
model is offered to predict the surface roughness of a machined
surface in glass milling operation using CBN grinding tool. Four
membership functions are allocated to be connected with each input
of the model. The predicted results achieved via fuzzy logic model
are compared to the experimental result. The result demonstrated
settlement between the fuzzy model and experimental results with the
93.103% accuracy.
Abstract: In this paper, we study the numerical method for solving second-order fuzzy differential equations using Adomian method under strongly generalized differentiability. And, we present an example with initial condition having four different solutions to illustrate the efficiency of the proposed method under strongly generalized differentiability.
Abstract: This paper argues that a product development exercise
involves in addition to the conventional stages, several decisions
regarding other aspects. These aspects should be addressed
simultaneously in order to develop a product that responds to the
customer needs and that helps realize objectives of the stakeholders
in terms of profitability, market share and the like. We present a
framework that encompasses these different development
dimensions. The framework shows that a product development
methodology such as the Quality Function Deployment (QFD) is the
basic tool which allows definition of the target specifications of a
new product. Creativity is the first dimension that enables the
development exercise to live and end successfully. A number of
group processes need to be followed by the development team in
order to ensure enough creativity and innovation. Secondly,
packaging is considered to be an important extension of the product.
Branding strategies, quality and standardization requirements,
identification technologies, design technologies, production
technologies and costing and pricing are also integral parts to the
development exercise. These dimensions constitute the proposed
framework. The paper also presents a mathematical model used to
calculate the design targets based on the target costing principle. The
framework is used to study a case of a new product development in
the telecommunications services sector.
Abstract: This paper discusses a new, systematic approach to
the synthesis of a NP-hard class of non-regenerative Boolean
networks, described by FON[FOFF]={mi}[{Mi}], where for every
mj[Mj]∈{mi}[{Mi}], there exists another mk[Mk]∈{mi}[{Mi}], such
that their Hamming distance HD(mj, mk)=HD(Mj, Mk)=O(n), (where
'n' represents the number of distinct primary inputs). The method
automatically ensures exact minimization for certain important selfdual
functions with 2n-1 points in its one-set. The elements meant for
grouping are determined from a newly proposed weighted incidence
matrix. Then the binary value corresponding to the candidate pair is
correlated with the proposed binary value matrix to enable direct
synthesis. We recommend algebraic factorization operations as a post
processing step to enable reduction in literal count. The algorithm
can be implemented in any high level language and achieves best
cost optimization for the problem dealt with, irrespective of the
number of inputs. For other cases, the method is iterated to
subsequently reduce it to a problem of O(n-1), O(n-2),.... and then
solved. In addition, it leads to optimal results for problems exhibiting
higher degree of adjacency, with a different interpretation of the
heuristic, and the results are comparable with other methods.
In terms of literal cost, at the technology independent stage, the
circuits synthesized using our algorithm enabled net savings over
AOI (AND-OR-Invert) logic, AND-EXOR logic (EXOR Sum-of-
Products or ESOP forms) and AND-OR-EXOR logic by 45.57%,
41.78% and 41.78% respectively for the various problems.
Circuit level simulations were performed for a wide variety of
case studies at 3.3V and 2.5V supply to validate the performance of
the proposed method and the quality of the resulting synthesized
circuits at two different voltage corners. Power estimation was
carried out for a 0.35micron TSMC CMOS process technology. In
comparison with AOI logic, the proposed method enabled mean
savings in power by 42.46%. With respect to AND-EXOR logic, the
proposed method yielded power savings to the tune of 31.88%, while
in comparison with AND-OR-EXOR level networks; average power
savings of 33.23% was obtained.
Abstract: By using the method of coincidence degree theory and constructing suitable Lyapunov functional, several sufficient conditions are established for the existence and global exponential stability of anti-periodic solutions for Cohen-Grossberg shunting inhibitory neural networks with delays. An example is given to illustrate our feasible results.
Abstract: This paper studies the duration or survival time of commercial banks active in the Moscovian three month Rouble deposits market, during the 1994-1997 period. The privatization process of the Russian commercial banking industry, after the 1988 banking reform, caused a massive entry of new banks followed by a period of high rates of exit. As a consequence, many firms went bankrupt without refunding their deposits. Therefore, both for the banks and for the banks- depositors, it is of interest to analyze which are the significant characteristics that motivate the exit or the closing of the bank. We propose a different methodology based on penalized weighted least squares which represents a very general, flexible and innovative approach for this type of analysis. The more relevant results are that smaller banks exit sooner, banks that enter the market in the last part of the study have shorter durations. As expected, the more experienced banks have a longer duration in the market. In addition, the mean survival time is lower for banks which offer extreme interest rates.
Abstract: In this paper a novel method for multiple one dimensional real valued sinusoidal signal frequency estimation in the presence of additive Gaussian noise is postulated. A computationally simple frequency estimation method with efficient statistical performance is attractive in many array signal processing applications. The prime focus of this paper is to combine the subspace-based technique and a simple peak search approach. This paper presents a variant of the Propagator Method (PM), where a collaborative approach of SUMWE and Propagator method is applied in order to estimate the multiple real valued sine wave frequencies. A new data model is proposed, which gives the dimension of the signal subspace is equal to the number of frequencies present in the observation. But, the signal subspace dimension is twice the number of frequencies in the conventional MUSIC method for estimating frequencies of real-valued sinusoidal signal. The statistical analysis of the proposed method is studied, and the explicit expression of asymptotic (large-sample) mean-squared-error (MSE) or variance of the estimation error is derived. The performance of the method is demonstrated, and the theoretical analysis is substantiated through numerical examples. The proposed method can achieve sustainable high estimation accuracy and frequency resolution at a lower SNR, which is verified by simulation by comparing with conventional MUSIC, ESPRIT and Propagator Method.
Abstract: A water surface slope limiting scheme is tested and
compared with the water depth slope limiter for the solution of one
dimensional shallow water equations with bottom slope source term.
Numerical schemes based on the total variation diminishing Runge-
Kutta discontinuous Galerkin finite element method with slope
limiter schemes based on water surface slope and water depth are
used to solve one-dimensional shallow water equations. For each
slope limiter, three different Riemann solvers based on HLL, LF, and
Roe flux functions are used. The proposed water surface based slope
limiter scheme is easy to implement and shows better conservation
property compared to the slope limiter based on water depth. Of the
three flux functions, the Roe approximation provides the best results
while the LF function proves to be least suitable when used with
either slope limiter scheme.
Abstract: This work presents a new algorithm based on a combination of fuzzy (FUZ), Dynamic Programming (DP), and Genetic Algorithm (GA) approach for capacitor allocation in distribution feeders. The problem formulation considers two distinct objectives related to total cost of power loss and total cost of capacitors including the purchase and installation costs. The novel formulation is a multi-objective and non-differentiable optimization problem. The proposed method of this article uses fuzzy reasoning for sitting of capacitors in radial distribution feeders, DP for sizing and finally GA for finding the optimum shape of membership functions which are used in fuzzy reasoning stage. The proposed method has been implemented in a software package and its effectiveness has been verified through a 9-bus radial distribution feeder for the sake of conclusions supports. A comparison has been done among the proposed method of this paper and similar methods in other research works that shows the effectiveness of the proposed method of this paper for solving optimum capacitor planning problem.
Abstract: In this paper, all variables are supposed to be integer
and positive. In this modern method, objective function is assumed to
be maximized or minimized but constraints are always explained like
less or equal to. In this method, choosing a dual combination of ideal
nonequivalent and omitting one of variables. With continuing this
act, finally, having one nonequivalent with (n-m+1) unknown
quantities in which final nonequivalent, m is counter for constraints,
n is counter for variables of decision.
Abstract: Integrative teaching methodology is based on
connecting and summarizing knowledge from different subjects in
order to create better understanding of different disciplines and
improvement of competences in general. Integrative teaching
methodology was implemented and realised during one academic
year in 17 Latvian schools according with specially worked out
programme by specialists of different fields for adaptation in social
environment of children and young people with learning, cognitive
functions and motor disorders. Implemented integrative teaching
methodology consisted from three subsections which were
specialised for adaptation in social environment, improvement of
cognitive functions and improvement and harmonization of
personality. The results of investigation showed that the use of
integrative teaching methodology is an effective way for
improvement of learning motivation and negotiation of learning
disorders of different age schoolchildren.
Abstract: This paper deals with under actuator dynamic systems such as spring-mass-damper system when the number of control variable is less than the number of state variable. In order to apply optimal control, the controllability must be checked. There are many objective functions to be selected as the goal of the optimal control such as minimum energy, maximum energy and minimum jerk. As the objective function is the first priority, if one like to have the second goal to be applied; however, it could not fit in the objective function format and also avoiding the vector cost for the objective, this paper will illustrate the problem of under actuator dynamic systems with the easiest to deal with comparing between minimum energy and minimum jerk.
Abstract: A universal current-mode biquad is described which
represents an economical variant of well-known KHN (Kerwin,
Huelsman, Newcomb) voltage-mode filter. The circuit consists of
two multiple-output OTAs and of two grounded capacitors. Utilizing
simple splitter of the input current and a pair of jumpers, all the basic
2nd-order transfer functions can be implemented. The principle is
verified by Spice simulation on the level of a CMOS structure of
OTAs.
Abstract: With the increasing number of on-chip components and the critical requirement for processing power, Chip Multiprocessor (CMP) has gained wide acceptance in both academia and industry during the last decade. However, the conventional bus-based onchip communication schemes suffer from very high communication delay and low scalability in large scale systems. Network-on-Chip (NoC) has been proposed to solve the bottleneck of parallel onchip communications by applying different network topologies which separate the communication phase from the computation phase. Observing that the memory bandwidth of the communication between on-chip components and off-chip memory has become a critical problem even in NoC based systems, in this paper, we propose a novel 3D NoC with on-chip Dynamic Random Access Memory (DRAM) in which different layers are dedicated to different functionalities such as processors, cache or memory. Results show that, by using our proposed architecture, average link utilization has reduced by 10.25% for SPLASH-2 workloads. Our proposed design costs 1.12% less execution cycles than the traditional design on average.
Abstract: The system is made with main distributed components:
First Level: Industrial Computers placed in Control Room (monitors thermal and electrical processes based on the data provided by the second level); Second Level: PLCs which collects data from process and transmits information on the first level; also takes commands from this level which are further, passed to execution elements from third
level; Third Level: field elements consisting in 3 categories: data collecting elements; data transfer elements from the third level to the second; execution elements which take commands from the second
level PLCs and executes them after which transmits the confirmation of execution to them. The purpose of the automatic functioning is the optimization of the co-generative electrical energy commissioning in the national
energy system and the commissioning of thermal energy to the consumers.
The integrated system treats the functioning of all the equipments and devices as a whole: Gas Turbine Units (GTU); MT 20kV Medium Voltage Station (MVS); 0,4 kV Low Voltage Station (LVS); Main Hot Water Boilers (MHW); Auxiliary Hot Water Boilers (AHW); Gas Compressor Unit (GCU); Thermal Agent Circulation
Pumping Unit (TPU); Water Treating Station (WTS).
Abstract: Aiming at the problems existing in low-carbon technology of Chinese manufacturing industries, such as irrational energy structure, lack of technological innovation, financial constraints, this paper puts forward the suggestion that the leading role of the government is combined with the roles of enterprises and market. That is, through increasing the governmental funding the adjustment of the industrial structures and enhancement of the legal supervision are supported. Technological innovation is accelerated by the enterprises, and the carbon trading will be promoted so as to trigger the low-carbon revolution in Chinese manufacturing field.
Abstract: Direction of Arrival estimation refers to defining a mathematical function called a pseudospectrum that gives an indication of the angle a signal is impinging on the antenna array. This estimation is an efficient method of improving the quality of service in a communication system by focusing the reception and transmission only in the estimated direction thereby increasing fidelity with a provision to suppress interferers. This improvement is largely dependent on the performance of the algorithm employed in the estimation. Many DOA algorithms exists amongst which are MUSIC, Root-MUSIC and ESPRIT. In this paper, performance of these three algorithms is analyzed in terms of complexity, accuracy as assessed and characterized by the CRLB and memory requirements in various environments and array sizes. It is found that the three algorithms are high resolution and dependent on the operating environment and the array size.
Abstract: Multiple sequence alignment is a fundamental part in
many bioinformatics applications such as phylogenetic analysis.
Many alignment methods have been proposed. Each method gives a
different result for the same data set, and consequently generates a
different phylogenetic tree. Hence, the chosen alignment method
affects the resulting tree. However in the literature, there is no
evaluation of multiple alignment methods based on the comparison of
their phylogenetic trees. This work evaluates the following eight
aligners: ClustalX, T-Coffee, SAGA, MUSCLE, MAFFT, DIALIGN,
ProbCons and Align-m, based on their phylogenetic trees (test trees)
produced on a given data set. The Neighbor-Joining method is used
to estimate trees. Three criteria, namely, the dNNI, the dRF and the
Id_Tree are established to test the ability of different alignment
methods to produce closer test tree compared to the reference one
(true tree). Results show that the method which produces the most
accurate alignment gives the nearest test tree to the reference tree.
MUSCLE outperforms all aligners with respect to the three criteria
and for all datasets, performing particularly better when sequence
identities are within 10-20%. It is followed by T-Coffee at lower
sequence identity (30%), trees scores of all methods
become similar.
Abstract: Although Model Driven Architecture has taken
successful steps toward model-based software development, this
approach still faces complex situations and ambiguous questions
while applying to real world software systems. One of these
questions - which has taken the most interest and focus - is how
model transforms between different abstraction levels, MDA
proposes. In this paper, we propose an approach based on Story
Driven Modeling and Aspect Oriented Programming to ease these
transformations. Service Oriented Architecture is taken as the target
model to test the proposed mechanism in a functional system.
Service Oriented Architecture and Model Driven Architecture [1]
are both considered as the frontiers of their own domain in the
software world. Following components - which was the greatest step
after object oriented - SOA is introduced, focusing on more
integrated and automated software solutions. On the other hand - and
from the designers' point of view - MDA is just initiating another
evolution. MDA is considered as the next big step after UML in
designing domain.