Abstract: Unlike general-purpose processors, digital signal
processors (DSP processors) are strongly application-dependent. To
meet the needs for diverse applications, a wide variety of DSP
processors based on different architectures ranging from the
traditional to VLIW have been introduced to the market over the
years. The functionality, performance, and cost of these processors
vary over a wide range. In order to select a processor that meets the
design criteria for an application, processor performance is usually
the major concern for digital signal processing (DSP) application
developers. Performance data are also essential for the designers of
DSP processors to improve their design. Consequently, several DSP
performance benchmarks have been proposed over the past decade or
so. However, none of these benchmarks seem to have included recent
new DSP applications.
In this paper, we use a new benchmark that we recently developed
to compare the performance of popular DSP processors from Texas
Instruments and StarCore. The new benchmark is based on the
Selectable Mode Vocoder (SMV), a speech-coding program from the
recent third generation (3G) wireless voice applications. All
benchmark kernels are compiled by the compilers of the respective
DSP processors and run on their simulators. Weighted arithmetic
mean of clock cycles and arithmetic mean of code size are used to
compare the performance of five DSP processors.
In addition, we studied how the performance of a processor is
affected by code structure, features of processor architecture and
optimization of compiler. The extensive experimental data gathered,
analyzed, and presented in this paper should be helpful for DSP
processor and compiler designers to meet their specific design goals.
Abstract: Shipping comb is mounted on Head Stack Assembly
(HSA) to prevent collision of the heads, maintain the gap between
suspensions and protect HSA tips from unintentional contact
damaged in the manufacturing process. Failure analysis of shipping
comb in hard disk drive production processes is proposed .Field
observations were performed to determine the fatal areas on shipping
comb and their failure fraction. Root cause failure analysis (RCFA) is
applied to specify the failure causes subjected to various loading
conditions. For reliability improvement, failure mode and effects
analysis (FMEA) procedure to evaluate the risk priority is performed.
Consequently, the more suitable information design criterions were
obtained.
Abstract: This paper is devoted to a delayed periodic predatorprey system with non-monotonic numerical response on time scales. With the help of a continuation theorem based on coincidence degree theory, we establish easily verifiable criteria for the existence of multiple periodic solutions. As corollaries, some applications are listed. In particular, our results improve and generalize some known ones.
Abstract: Real options theory suggests that managerial flexibility embedded within irreversible investments can account for a significant value in project valuation. Although the argument has become the dominant focus of capital investment theory over decades, yet recent survey literature in capital budgeting indicates that corporate practitioners still do not explicitly apply real options in investment decisions. In this paper, we explore how real options decision criteria can be transformed into equivalent capital budgeting criteria under the consideration of uncertainty, assuming that underlying stochastic process follows a geometric Brownian motion (GBM), a mixed diffusion-jump (MX), or a mean-reverting process (MR). These equivalent valuation techniques can be readily decomposed into conventional investment rules and “option impacts", the latter of which describe the impacts on optimal investment rules with the option value considered. Based on numerical analysis and Monte Carlo simulation, three major findings are derived. First, it is shown that real options could be successfully integrated into the mindset of conventional capital budgeting. Second, the inclusion of option impacts tends to delay investment. It is indicated that the delay effect is the most significant under a GBM process and the least significant under a MR process. Third, it is optimal to adopt the new capital budgeting criteria in investment decision-making and adopting a suboptimal investment rule without considering real options could lead to a substantial loss in value.
Abstract: This paper presents an exploration into the structure of the corporate governance network and interlocking directorates in the Czech Republic. First a literature overview and a basic terminology of the network theory is presented. Further in the text, statistics and other calculations relevant to corporate governance networks are presented. For this purpose an empirical data set consisting of 2 906 joint stock companies in the Czech Republic was examined. Industries with the highest average number of interlocks per company were healthcare, and energy and utilities. There is no observable link between the financial performance of the company and the number of its interlocks. Also interlocks with financial companies are very rare.
Abstract: Soil erosion is the most serious problem faced at
global and local level. So planning of soil conservation measures has
become prominent agenda in the view of water basin managers. To
plan for the soil conservation measures, the information on soil
erosion is essential. Universal Soil Loss Equation (USLE), Revised
Universal Soil Loss Equation 1 (RUSLE1or RUSLE) and Modified
Universal Soil Loss Equation (MUSLE), RUSLE 1.06, RUSLE1.06c,
RUSLE2 are most widely used conventional erosion estimation
methods. The essential drawbacks of USLE, RUSLE1 equations are
that they are based on average annual values of its parameters and so
their applicability to small temporal scale is questionable. Also these
equations do not estimate runoff generated soil erosion. So
applicability of these equations to estimate runoff generated soil
erosion is questionable. Data used in formation of USLE, RUSLE1
equations was plot data so its applicability at greater spatial scale
needs some scale correction factors to be induced. On the other hand
MUSLE is unsuitable for predicting sediment yield of small and large
events. Although the new revised forms of USLE like RUSLE 1.06,
RUSLE1.06c and RUSLE2 were land use independent and they have
almost cleared all the drawbacks in earlier versions like USLE and
RUSLE1, they are based on the regional data of specific area and
their applicability to other areas having different climate, soil, land
use is questionable. These conventional equations are applicable for
sheet and rill erosion and unable to predict gully erosion and spatial
pattern of rills. So the research was focused on development of nonconventional
(other than conventional) methods of soil erosion
estimation. When these non-conventional methods are combined with
GIS and RS, gives spatial distribution of soil erosion. In the present
paper the review of literature on non- conventional methods of soil
erosion estimation supported by GIS and RS is presented.
Abstract: A preconditioned Jacobi (PJ) method is provided for solving fuzzy linear systems whose coefficient matrices are crisp Mmatrices and the right-hand side columns are arbitrary fuzzy number vectors. The iterative algorithm is given for the preconditioned Jacobi method. The convergence is analyzed with convergence theorems. Numerical examples are given to illustrate the procedure and show the effectiveness and efficiency of the method.
Abstract: Application of synthetic antioxidants such as tertbutylhydroquinon
(TBHQ), in spite of their efficiency, is questioned
because of their possible carcinogenic effect. The purpose of this
study was application of mixtures of natural antioxidants that provide
the best oxidative stability for margarine. Antioxidant treatments
included 10 various mixtures (F1- F10) containing 100-500ppm
tocopherol mixture (Toc), 100-200ppm ascorbyl palmitate (AP), 100-
200ppm rosemary extract (Ros) and 1000ppm lecithin(Lec) along
with a control or F0 (with no antioxidant) and F11 with 120ppm
TBHQ. The effect of antioxidant mixtures on the stability of
margarine samples during oven test (60°C), rancimat test at 110°C
and storage at 4°C was evaluated. Final ranking of natural antioxidant
mixtures was as follows: F2,F10>F5,F9>F8>F1,F3,F4>F6, F7.
Considering the results of this research and ranking criteria,
F2(200ppmAp + 200ppmRos) and F10(200ppmRos + 200ppmToc
+1000ppmLec) were recommended as substitutes for TBHQ to
maintain the quality and increase the shelf-life of margarine.
Abstract: In this paper, a delayed predator-prey system with Hassell-Varley-Holling type functional response is studied. A sufficient criterion for the permanence of the system is presented, and further some sufficient conditions for the global attractivity and exponential stability of the system are established. And an example is to show the feasibility of the results by simulation.
Abstract: In this study the mixed mode fracture mechanics
parameters were investigated for high tensile steel butt welded joint
based on modified Arcan test and finite element analysis was used to
evaluate the effect of crack length on fracture criterion. The nondimensional
stress intensity factors, strain energy release rates and Jintegral
energy on crack tip were obtained for various in-plane
loading combinations on Arcan specimen starting from pure mode-I
to pure mode-II loading conditions. The specimen and apparatus were
modeled by finite element method and analyzed under various
loading angles (between 0 to 90 degrees with 15 degree interval) to
simulate the pure mode-I, II and mixed mode fracture. Since the
analytical results are independent from elasticity modules for
isotropic materials, therefore the results in elastic fields can be used
for Arcan specimens. The main objective of this study was to
evaluate the geometric calibration factors for modified Arcan test
specimen in order to obtain fracture toughness under mixed mode
loading conditions.
Abstract: New Growth Theory helps us make sense of the
ongoing shift from a resource-based economy to a knowledge-based
economy. It underscores the point that the economic processes which
create and diffuse new knowledge are critical to shaping the growth
of nations, communities and individual firms. In all too many
contributions to New (Endogenous) Growth Theory – though not in
all – central reference is made to 'a stock of knowledge', a 'stock of
ideas', etc., this variable featuring centre-stage in the analysis. Yet it
is immediately apparent that this is far from being a crystal clear
concept. The difficulty and uncertainty of being able to capture the
value associated with knowledge is a real problem. The intent of this
paper is introducing new thinking and theorizing about the
knowledge and its measurability in new growth theory. Moreover the
study aims to synthesize various strain of the literature with a
practical bearing on knowledge concept. By contribution of
institution framework which is found within NGT, we can indirectly
measure the knowledge concept. Institutions matter because they
shape the environment for production and employment of new
knowledge
Abstract: Most of the academics connect a theory of
multiculturalism with globalization and limit it by last decades of
20th century. However, Kazakh society encountered with this
problem when the Soviet-s rule emerged. As a result of repression,
the Second World War, development of virgin lands representatives
of more than 100 nationalities lives in Kazakhstan. Communist
ideology propagandized internationalism, which would defined
principles of multicultural community but a common ideology
demands a single culture. As a result multicultural society in the
USSR developed under control of Russian culture. Education in the
USSR was conducted in two departments: autochthonous and
Russian. Autochthonous education narrowed student capabilities.
Also because of soviet ideology science was conducted in Russian
Universities provided education in Russian and all science literature
were in Russian. Exceptions were humanitarian fields where Kazakh
departments were admitted. Naturally non-Kazakhs studied in
Russian departments, moreover Kazakhs preferred to study in
Russian as most do nowadays preferring English. As a result Kazakh
society consisted of Kazakhs, Kazakhs who recognized Russian as a
mother tongue and other nationalities who were also Russian
speakers. This aspect continues to distinguish particular qualities of
multicultural community in Kazakhstan.
Abstract: The paper considers the effect of feed plate location
on the interactions in a seven plate binary distillation column. The
mathematical model of the distillation column is deduced based on
the equations of mass and energy balances for each stage, detailed
model for both reboiler and condenser, and heat transfer equations.
The Dynamic Relative Magnitude Criterion, DRMC is used to assess
the interactions in different feed plate locations for a seven plate
(Benzene-Toluene) binary distillation column ( the feed plate is
originally at stage 4). The results show that whenever we go far from
the optimum feed plate position, the level of interaction augments.
Abstract: This paper is concerned with the delay-distributiondependent
stability criteria for bidirectional associative memory
(BAM) neural networks with time-varying delays. Based on the
Lyapunov-Krasovskii functional and stochastic analysis approach,
a delay-probability-distribution-dependent sufficient condition is derived
to achieve the globally asymptotically mean square stable of
the considered BAM neural networks. The criteria are formulated in
terms of a set of linear matrix inequalities (LMIs), which can be
checked efficiently by use of some standard numerical packages. Finally,
a numerical example and its simulation is given to demonstrate
the usefulness and effectiveness of the proposed results.
Abstract: Airport capacity has always been perceived in the
traditional sense as the number of aircraft operations during a
specified time corresponding to a tolerable level of average delay and
it mostly depends on the airside characteristics, on the fleet mix
variability and on the ATM. The adoption of the Directive
2002/30/EC in the EU countries drives the stakeholders to conceive
airport capacity in a different way though. Airport capacity in this
sense is fundamentally driven by environmental criteria, and since
acoustical externalities represent the most important factors, those are
the ones that could pose a serious threat to the growth of airports and
to aviation market itself in the short-medium term. The importance of
the regional airports in the deregulated market grew fast during the
last decade since they represent spokes for network carriers and a
preferential destination for low-fares carriers. Not only regional
airports have witnessed a fast and unexpected growth in traffic but
also a fast growth in the complaints for the nuisance by the people
living near those airports. In this paper the results of a study
conducted in cooperation with the airport of Bologna G. Marconi are
presented in order to investigate airport acoustical capacity as a defacto
constraint of airport growth.
Abstract: A complex valued neural network is a neural network
which consists of complex valued input and/or weights and/or thresholds
and/or activation functions. Complex-valued neural networks
have been widening the scope of applications not only in electronics
and informatics, but also in social systems. One of the most important
applications of the complex valued neural network is in signal
processing. In Neural networks, generalized mean neuron model
(GMN) is often discussed and studied. The GMN includes a new
aggregation function based on the concept of generalized mean of all
the inputs to the neuron. This paper aims to present exhaustive results
of using Generalized Mean Neuron model in a complex-valued neural
network model that uses the back-propagation algorithm (called
-Complex-BP-) for learning. Our experiments results demonstrate the
effectiveness of a Generalized Mean Neuron Model in a complex
plane for signal processing over a real valued neural network. We
have studied and stated various observations like effect of learning
rates, ranges of the initial weights randomly selected, error functions
used and number of iterations for the convergence of error required on
a Generalized Mean neural network model. Some inherent properties
of this complex back propagation algorithm are also studied and
discussed.
Abstract: Overcurrent (OC) relays are the major protection
devices in a distribution system. The operating time of the OC relays
are to be coordinated properly to avoid the mal-operation of the
backup relays. The OC relay time coordination in ring fed
distribution networks is a highly constrained optimization problem
which can be stated as a linear programming problem (LPP). The
purpose is to find an optimum relay setting to minimize the time of
operation of relays and at the same time, to keep the relays properly
coordinated to avoid the mal-operation of relays.
This paper presents two phase simplex method for optimum time
coordination of OC relays. The method is based on the simplex
algorithm which is used to find optimum solution of LPP. The
method introduces artificial variables to get an initial basic feasible
solution (IBFS). Artificial variables are removed using iterative
process of first phase which minimizes the auxiliary objective
function. The second phase minimizes the original objective function
and gives the optimum time coordination of OC relays.
Abstract: The problem of estimating time-varying regression is
inevitably concerned with the necessity to choose the appropriate
level of model volatility - ranging from the full stationarity of instant
regression models to their absolute independence of each other. In the
stationary case the number of regression coefficients to be estimated
equals that of regressors, whereas the absence of any smoothness
assumptions augments the dimension of the unknown vector by the
factor of the time-series length. The Akaike Information Criterion
is a commonly adopted means of adjusting a model to the given
data set within a succession of nested parametric model classes,
but its crucial restriction is that the classes are rigidly defined by
the growing integer-valued dimension of the unknown vector. To
make the Kullback information maximization principle underlying the
classical AIC applicable to the problem of time-varying regression
estimation, we extend it onto a wider class of data models in which
the dimension of the parameter is fixed, but the freedom of its values
is softly constrained by a family of continuously nested a priori
probability distributions.
Abstract: Multiprocessor task scheduling is a NP-hard problem and Genetic Algorithm (GA) has been revealed as an excellent technique for finding an optimal solution. In the past, several methods have been considered for the solution of this problem based on GAs. But, all these methods consider single criteria and in the present work, minimization of the bi-criteria multiprocessor task scheduling problem has been considered which includes weighted sum of makespan & total completion time. Efficiency and effectiveness of genetic algorithm can be achieved by optimization of its different parameters such as crossover, mutation, crossover probability, selection function etc. The effects of GA parameters on minimization of bi-criteria fitness function and subsequent setting of parameters have been accomplished by central composite design (CCD) approach of response surface methodology (RSM) of Design of Experiments. The experiments have been performed with different levels of GA parameters and analysis of variance has been performed for significant parameters for minimisation of makespan and total completion time simultaneously.
Abstract: Rural tourism has many economical, environmental, and socio-cultural benefits. However, the development of rural tourism compared to urban tourism is also faced with several challenges added to the disadvantages of rural tourism. The aim of this study is to design a model of the factors affecting the motivations of rural tourists, in an attempt to improve the understanding of rural tourism motivation for the development of that form of tourism. The proposed model is based on a sound theoretical framework. It was designed following a literature review of tourism motivation theoretical frameworks and of rural tourism motivation factors. The tourism motivation theoretical framework that fitted to the best all rural tourism motivation factors was then chosen as the basis for the proposed model. This study hence found that the push and pull tourism motivation framework and the inner and outer directed values theory are the most adequate theoretical frameworks for the modeling of rural tourism motivation.