Abstract: In this paper, we present new preconditioned modified accelerated overrelaxation (MAOR) method for solving linear systems. We compare the spectral radii of the iteration matrices of the preconditioned and the original methods. The comparison results show that the preconditioned MAOR method converges faster than the MAOR method whenever the MAOR method is convergent. Finally, we give one numerical example to confirm our theoretical results.
Abstract: In this paper, we mainly study the stability of linear and
interval linear fractional systems with time delay. By applying the
characteristic equations, a necessary and sufficient stability condition
is obtained firstly, and then some sufficient conditions are deserved. In
addition, according to the equivalent relationship of fractional order
systems with order 0 < α ≤ 1 and with order 1 ≤ β < 2, one may
get more relevant theorems. Finally, two examples are provided to
demonstrate the effectiveness of our results.
Abstract: In this paper, we present new preconditioned generalized mixed-type splitting (GMTS) methods for solving weighted linear least square problems. We compare the spectral radii of the iteration matrices of the preconditioned and the original methods. The comparison results show that the preconditioned GMTS methods converge faster than the GMTS method whenever the GMTS method is convergent. Finally, we give a numerical example to confirm our theoretical results.
Abstract: This paper studies the problem of asymptotically
stability for neural networks with time-varying delays.By establishing
a suitable Lyapunov-Krasovskii function and several novel sufficient
conditions are obtained to guarantee the asymptotically stability of the considered system. Finally,two numerical examples are given to illustrate the effectiveness of the proposed main results.
Abstract: We consider the biggest challenge in speech recognition – noise reduction. Traditionally detected transient noise pulses are removed with the corrupted speech using pulse models. In this paper we propose to cope with the problem directly in Dynamic Time Warping domain. Bidirectional Dynamic Time Warping algorithm for the recognition of isolated words impacted by transient noise pulses is proposed. It uses simple transient noise pulse detector, employs bidirectional computation of dynamic time warping and directly manipulates with warping results. Experimental investigation with several alternative solutions confirms effectiveness of the proposed algorithm in the reduction of impact of noise on recognition process – 3.9% increase of the noisy speech recognition is achieved.
Abstract: Celebrities are admired, appreciated and imitated all over the world. As a natural result of this, today many brands choose to work with celebrities for their advertisements. It can be said that the more the brands include celebrities in their marketing communication strategies, the tougher the competition in this field becomes and they allocate a large portion of their marketing budget to this. Brands invest in celebrities who will represent them in order to build the image they want to create.
This study aimed to bring under spotlight the perceptions of Turkish customers regarding the use of celebrities in advertisements and marketing communication and try to understand their possible effects on subsequent purchasing decisions. In addition, consumers’ reactions and perceptions were investigated in the context of the product-celebrity match, to what extent the celebrity conforms to the concept of the advertisement and the celebrity-target audience match.
In order to achieve this purpose, a quantitative research was conducted as a case study concerning Mavi Jeans (textile company). Information was obtained through survey. The results from this case study are supported by relevant theories concerning the main subject. The most valuable result would be that instead of creating an advertisement around a celebrity in demand at the time, using a celebrity that fits the concept of the advertisement and feeds the concept rather than replaces it, that is celebrity endorsement, will lead to more striking and positive results.
Abstract: This paper studies the problem of stability criteria
for neural networks with two additive time-varying delays.A new
Lyapunov-Krasovskii function is constructed and some new delay
dependent stability criterias are derived in the terms of linear
matrix inequalities(LMI), zero equalities and reciprocally convex
approach.The several stability criterion proposed in this paper is
simpler and effective. Finally,numerical examples are provided to
demonstrate the feasibility and effectiveness of our results.
Abstract: In this paper, together with some improved
Lyapunov-Krasovskii functional and effective mathematical
techniques, several sufficient conditions are derived to guarantee the
error system is globally asymptotically stable with H∞
performance, in which both the time-delay and its time variation
can be fully considered. In order to get less conservative results of
the state estimation condition, zero equalities and reciprocally
convex approach are employed. The estimator gain matrix can be
obtained in terms of the solution to linear matrix inequalities. A
numerical example is provided to illustrate the usefulness and
effectiveness of the obtained results.
Abstract: In this paper, we consider the nonlinear delay dynamic system
xΔ(t) = p(t)f1(y(t)), yΔ(t) = −q(t)f2(x(t − τ )).
We obtain some necessary and sufficient conditions for the existence of nonoscillatory solutions with special asymptotic properties of the system. We generalize the known results in the literature. One example is given to illustrate the results.
Abstract: This paper presents partial results of primary research on consumer purchasing behavior in times of crisis. It starts with brief theoretical debate on purchasing behavior and short secondary research related to the issues, which is used for the comparison of results. For purpose of collecting data, questionnaire survey was given to 355 respondents in Moravian-Silesian region. Hypotheses deal with the relationship of the financial situation of the respondents and their purchasing behavior. The research analysis disclosed that consumers change their behavior during crisis and MS region has some specifics compared to other regions.
Abstract: Due to the importance of yield curve and its estimation it is inevitable to have valid methods for yield curve forecasting in cases when there are scarce issues of securities and/or week trade on a secondary market. Therefore in this paper, after the estimation of weekly yield curves on Croatian financial market from October 2011 to August 2012 using Nelson-Siegel and Svensson models, yield curves are forecasted using Vector autoregressive model and Neural networks. In general, it can be concluded that both forecasting methods have good prediction abilities where forecasting of yield curves based on Nelson Siegel estimation model give better results in sense of lower Mean Squared Error than forecasting based on Svensson model Also, in this case Neural networks provide slightly better results. Finally, it can be concluded that most appropriate way of yield curve prediction is Neural networks using Nelson-Siegel estimation of yield curves.
Abstract: This paper deals with the problem of stability of
neural networks with leakage, discrete and distributed delays. A
new Lyapunov functional which contains some new double integral
terms are introduced. By using appropriate model transformation
that shifts the considered systems into the neutral-type time-delay
system, and by making use of some inequality techniques,
delay-dependent criteria are developed to guarantee the stability of
the considered system. Finally, numerical examples are provided to
illustrate the usefulness of the proposed main results.
Abstract: Through the fast growing technologies, design of power factor correction (PFC) circuit is facing several challenges. In this paper, a two-phase interleaved boost converter with ripple steering technique is proposed. Among the various topologies, Interleaved Boost converter (IBC) is considered as superior due to enriched performance, lower ripple content, compact weight and size. A thorough investigation is presented here for the proposed topology. Simulation study for the IBC has been carried out using MATLAB/SIMULINK. Theoretical analysis and hardware prototype has been performed to validate the results.
Abstract: In this paper, the problem of stability criteria for Markovian jumping BAM neural networks with leakage and
discrete delays has been investigated. Some new sufficient condition
are derived based on a novel Lyapunov-Krasovskii functional
approach. These new criteria based on delay partitioning idea are
proved to be less conservative because free-weighting matrices
method and a convex optimization approach are considered. Finally,
one numerical example is given to illustrate the the usefulness and
feasibility of the proposed main results.
Abstract: This paper studies the problem of exponential stability analysis for uncertain neural networks with discrete and distributed time-varying delays. Together with a suitable augmented Lyapunov Krasovskii function, zero equalities, reciprocally convex approach and a novel sufficient condition to guarantee the exponential stability of the considered system. The several exponential stability criterion proposed in this paper is simpler and effective. Finally,numerical examples are provided to demonstrate the feasibility and effectiveness of our results.
Abstract: Recently, ‘play of learning’ becomes important and is
emphasized as a useful learning tool. Therefore, interest in
edutainment contents is growing. Storytelling is considered first as a
method that improves the transmission of information and learner's
interest when planning edutainment contents. In this study, we
designed edutainment contents in the form of an adventure game that
applies the storytelling method. This content provides questions and
items constituted dynamically and reorganized learning contents
through analysis of test results. It allows learners to solve various
questions through effective iterative learning. As a result, the learners
can reach mastery learning.
Abstract: The paper presents an analysis of the innovation performance of small and medium-sized furniture enterprises in Bulgaria, accounting for over 97% of the companies in the sector. It contains advanced features of innovation in enterprises, specific features of the furniture industry in Bulgaria and analysis of the results of studies on the topic. The results from studies of three successive periods - 2006-2008; 2008-2010; 2010-2012, during which were studied 594 small and medium-sized furniture enterprises. There are commonly used in the EU definitions and indicators (European Commission, OECD, Oslo Manual), which allows for the comparability of results.
Abstract: Depending on the big data analysis becomes important, yield prediction using data from the semiconductor process is essential. In general, yield prediction and analysis of the causes of the failure are closely related. The purpose of this study is to analyze pattern affects the final test results using a die map based clustering. Many researches have been conducted using die data from the semiconductor test process. However, analysis has limitation as the test data is less directly related to the final test results. Therefore, this study proposes a framework for analysis through clustering using more detailed data than existing die data. This study consists of three phases. In the first phase, die map is created through fail bit data in each sub-area of die. In the second phase, clustering using map data is performed. And the third stage is to find patterns that affect final test result. Finally, the proposed three steps are applied to actual industrial data and experimental results showed the potential field application.
Abstract: Conical sections and shells made from metal plates are widely used in various industrial applications. 3-roller conical bending process is preferably used to produce such conical sections and shells. Bending mechanics involved in the process is complex and little work is done in this area. In the present paper an analytical model is developed to predict bending force which will be acting during 3-roller conical bending process. To verify the developed model, conical bending experiments are performed. Analytical results and experimental results were compared. Force predicted by analytical model is in close proximity of the experimental results. The error in the prediction is ±10%. Hence the model gives quite satisfactory results. Present model is also compared with the previously published bending force prediction model and it is found that the present model gives better results. The developed model can be used to estimate the bending force during 3-roller bending process and can be useful to the designers for designing the 3-roller conical bending machine.
Abstract: This paper studies the problem of exponential stability analysis for recurrent neural networks with time-varying delay.By establishing a suitable augmented LyapunovCKrasovskii function and a novel sufficient condition is obtained to guarantee the exponential stability of the considered system.In order to get a less conservative results of the condition,zero equalities and reciprocally convex approach are employed. The several exponential stability criterion proposed in this paper is simpler and effective. A numerical example is provided to demonstrate the feasibility and effectiveness of our results.