Abstract: The main purpose of this paper is to prove the intuitionistic fuzzy contraction properties of the Hutchinson-Barnsley operator on the intuitionistic fuzzy hyperspace with respect to the Hausdorff intuitionistic fuzzy metrics. Also we discuss about the relationships between the Hausdorff intuitionistic fuzzy metrics on the intuitionistic fuzzy hyperspaces. Our theorems generalize and extend some recent results related with Hutchinson-Barnsley operator in the metric spaces to the intuitionistic fuzzy metric spaces.
Abstract: In this paper, we propose a new method to describe fractal shapes using parametric l-systems. First we introduce scaling factors in the production rules of the parametric l-systems grammars. Then we decorticate these grammars with scaling factors using turtle algebra to show the mathematical relation between l-systems and iterated function systems (IFS). We demonstrate that with specific values of the scaling factors, we find the exact relationship established by Prusinkiewicz and Hammel between l-systems and IFS.
Abstract: Analysis of heart rate variability (HRV) has become a
popular non-invasive tool for assessing the activities of autonomic
nervous system. Most of the methods were hired from techniques
used for time series analysis. Currently used methods are time
domain, frequency domain, geometrical and fractal methods. A new
technique, which searches for pattern repeatability in a time series, is
proposed for quantifying heart rate (HR) time series. These set of
indices, which are termed as pattern repeatability measure and
pattern repeatability ratio are able to distinguish HR data clearly
from noise and electroencephalogram (EEG). The results of analysis
using these measures give an insight into the fundamental difference
between the composition of HR time series with respect to EEG and
noise.
Abstract: Calcite aCalcite and aragonite are the two common
polymorphs of CaCO3 observed as biominerals. It is universal that
the sea water contents a high Mg2+ (50mM) relative to Ca2+ (10mM).
In vivo crystallization, Mg2+ inhibits calcite formation. For this
reason, stony corals skeleton may be formed only aragonite crystals
in the biocalcification. It is special in case of soft corals of which
formed only calcite crystal; however, this interesting phenomenon,
still uncharacterized in the marine environment, has been explored in
this study using newly purified cell-free proteins isolated from the
endoskeletal sclerites of soft coral. By recording the decline of pH in
vitro, the control of CaCO3 nucleation and crystal growth by the cellfree
proteins was revealed. Using Atomic Force Microscope, here we
find that these endoskeletal cell-free proteins significantly design the
morphological shape in the molecular-scale kinetics of crystal
formation and those proteins act as surfactants to promote ion
attachment at calcite steps.nd aragonite are the two common polymorphs of CaCO3 observed as biominerals. It is universal that the sea water contents a high Mg2+ (50mM) relative to Ca2+ (10mM). In vivo crystallization, Mg2+ inhibits calcite formation. For this reason, stony corals skeleton may be formed only aragonite crystals in the biocalcification. It is special in case of soft corals of which formed only calcite crystal; however, this interesting phenomenon, still uncharacterized in the marine environment, has been explored in this study using newly purified cell-free proteins isolated from the endoskeletal sclerites of soft coral. By recording the decline of pH in vitro, the control of CaCO3 nucleation and crystal growth by the cell-free proteins was revealed. Using Atomic Force Microscope, here we find that these endoskeletal cell-free proteins significantly design the morphological shape in the molecular-scale kinetics of crystal formation and those proteins act as surfactants to promote ion attachment at calcite steps. KeywordsBiomineralization, Calcite, Cell-free protein, Soft coral
Abstract: International trade involves both large and small firms
engaged in business overseas. Possible drivers that force companies
to enter international markets include increasing competition at the
domestic market, maturing domestic markets, and limited domestic
market opportunities. Technology is an important driving factor in
shaping international marketing strategy as well as in driving force
towards a more global marketplace, especially technology in
communication. It includes telephones, the internet, computer
systems and e-mail. There are three main marketing strategy choices,
namely standardization approach, adaptation approach and middleof-
the-road approach that companies implement to overseas markets.
The decision depends on situations and factors facing the companies
in the international markets. In this paper, the contingency concept is
considered that no single strategy can be effective in all contexts.
The effect of strategy on performance depends on specific situational
variables. Strategic fit is employed to investigate export marketing
strategy adaptation under certain environmental conditions, which in
turn can lead to superior performance.
Abstract: In today scenario, to meet enhanced demand imposed
by domestic, commercial and industrial consumers, various
operational & control activities of Radial Distribution Network
(RDN) requires a focused attention. Irrespective of sub-domains
research aspects of RDN like network reconfiguration, reactive
power compensation and economic load scheduling etc, network
performance parameters are usually estimated by an iterative process
and is commonly known as load (power) flow algorithm. In this
paper, a simple mechanism is presented to implement the load flow
analysis (LFA) algorithm. The reported algorithm utilizes graph
theory principles and is tested on a 69- bus RDN.
Abstract: Water level forecasting using records of past time series is of importance in water resources engineering and management. For example, water level affects groundwater tables in low-lying coastal areas, as well as hydrological regimes of some coastal rivers. Then, a reliable prediction of sea-level variations is required in coastal engineering and hydrologic studies. During the past two decades, the approaches based on the Genetic Programming (GP) and Artificial Neural Networks (ANN) were developed. In the present study, the GP is used to forecast daily water level variations for a set of time intervals using observed water levels. The measurements from a single tide gauge at Urmia Lake, Northwest Iran, were used to train and validate the GP approach for the period from January 1997 to July 2008. Statistics, the root mean square error and correlation coefficient, are used to verify model by comparing with a corresponding outputs from Artificial Neural Network model. The results show that both these artificial intelligence methodologies are satisfactory and can be considered as alternatives to the conventional harmonic analysis.
Abstract: Due to environmental concerns, the recent regulation on automobile fuel economy has been strengthened. The market demand for efficient vehicles is growing and automakers to improve engine fuel efficiency in the industry have been paying a lot of effort. To improve the fuel efficiency, it is necessary to reduce losses or to improve combustion efficiency of the engine. VVA (Variable Valve Actuation) technology enhances the engine's intake air flow, reduce pumping losses and mechanical friction losses. And also, VVA technology is the engine's low speed and high speed operation to implement each of appropriate valve lift. It improves the performance of engine in the entire operating range. This paper presents a design procedure of DC motor and drive for VVA system and shows the validity of the design result by experimental result with prototype.
Abstract: The length of a given rational B'ezier curve is
efficiently estimated. Since a rational B'ezier function is nonlinear,
it is usually impossible to evaluate its length exactly. The
length is approximated by using subdivision and the accuracy
of the approximation n is investigated. In order to improve
the efficiency, adaptivity is used with some length estimator.
A rigorous theoretical analysis of the rate of convergence of
n to is given. The required number of subdivisions to
attain a prescribed accuracy is also analyzed. An application
to CAD parametrization is briefly described. Numerical results
are reported to supplement the theory.
Abstract: In this paper, an optimal design of linear phase digital
high pass finite impulse response (FIR) filter using Particle Swarm
Optimization with Constriction Factor and Inertia Weight Approach
(PSO-CFIWA) has been presented. In the design process, the filter
length, pass band and stop band frequencies, feasible pass band and
stop band ripple sizes are specified. FIR filter design is a multi-modal
optimization problem. The conventional gradient based optimization
techniques are not efficient for digital filter design. Given the filter
specifications to be realized, the PSO-CFIWA algorithm generates a
set of optimal filter coefficients and tries to meet the ideal frequency
response characteristic. In this paper, for the given problem, the
designs of the optimal FIR high pass filters of different orders have
been performed. The simulation results have been compared to those
obtained by the well accepted algorithms such as Parks and
McClellan algorithm (PM), genetic algorithm (GA). The results
justify that the proposed optimal filter design approach using PSOCFIWA
outperforms PM and GA, not only in the accuracy of the
designed filter but also in the convergence speed and solution
quality.
Abstract: The importance of supply chain and logistics
management has been widely recognised. Effective management of
the supply chain can reduce costs and lead times and improve
responsiveness to changing customer demands. This paper proposes a
multi-matrix real-coded Generic Algorithm (MRGA) based
optimisation tool that minimises total costs associated within supply
chain logistics. According to finite capacity constraints of all parties
within the chain, Genetic Algorithm (GA) often produces infeasible
chromosomes during initialisation and evolution processes. In the
proposed algorithm, chromosome initialisation procedure, crossover
and mutation operations that always guarantee feasible solutions
were embedded. The proposed algorithm was tested using three sizes
of benchmarking dataset of logistic chain network, which are typical
of those faced by most global manufacturing companies. A half
fractional factorial design was carried out to investigate the influence
of alternative crossover and mutation operators by varying GA
parameters. The analysis of experimental results suggested that the
quality of solutions obtained is sensitive to the ways in which the
genetic parameters and operators are set.
Abstract: The paper describes a knowledge based system for
analysis of microscopic wear particles. Wear particles contained in
lubricating oil carry important information concerning machine
condition, in particular the state of wear. Experts (Tribologists) in the
field extract this information to monitor the operation of the machine
and ensure safety, efficiency, quality, productivity, and economy of
operation. This procedure is not always objective and it can also be
expensive. The aim is to classify these particles according to their
morphological attributes of size, shape, edge detail, thickness ratio,
color, and texture, and by using this classification thereby predict
wear failure modes in engines and other machinery. The attribute
knowledge links human expertise to the devised Knowledge Based
Wear Particle Analysis System (KBWPAS). The system provides an
automated and systematic approach to wear particle identification
which is linked directly to wear processes and modes that occur in
machinery. This brings consistency in wear judgment prediction
which leads to standardization and also less dependence on
Tribologists.
Abstract: Deep Brain Stimulation or DBS is a surgical treatment for Parkinson-s Disease with three stimulation parameters: frequency, pulse width, and voltage. The parameters should be selected appropriately to achieve effective treatment. This selection now, performs clinically. The aim of this research is to study chaotic behavior of recorded tremor of patients under DBS in order to present a computational method to recognize stimulation optimum voltage. We obtained some chaotic features of tremor signal, and discovered embedding space of it has an attractor, and its largest Lyapunov exponent is positive, which show tremor signal has chaotic behavior, also we found out, in optimal voltage, entropy and embedding space variance of tremor signal have minimum values in comparison with other voltages. These differences can help neurologists recognize optimal voltage numerically, which leads to reduce patients' role and discomfort in optimizing stimulation parameters and to do treatment with high accuracy.
Abstract: Social ideology, cultural values and principles shaping environment are inferred by environment and structural characteristics of construction site. In other words, this inference manifestation also indicates ideology and culture of its foundation and also applies its principles and values and somehow plays an important role in Cultural Revolution. All human behaviors and artifacts are affected and being influenced by culture. Culture is not abstract concept, it is a spiritual domain that an individual and society grow and develop in it. Social behaviors are affected by environmental comprehension, so the architecture work influences on its audience and it is the environment that fosters social behaviors. Indeed, sustainable architecture should be considered as background of culture for establishing optimal sustainable culture. Since unidentified architecture roots in cultural non identity and abnormalities, so the society possesses identity characteristics and life and as a consequence, the society and architecture are changed by transformation of life style. This article aims to investigate the interaction of architecture, society, environment and sustainable architecture formation in its cultural basis and analyzes the results approaching behavior and sustainable culture in recent era.
Abstract: A lot of research has been done in the past decade in the field of audio content analysis for extracting various information from audio signal. One such significant information is the "perceived mood" or the "emotions" related to a music or audio clip. This information is extremely useful in applications like creating or adapting the play-list based on the mood of the listener. This information could also be helpful in better classification of the music database. In this paper we have presented a method to classify music not just based on the meta-data of the audio clip but also include the "mood" factor to help improve the music classification. We propose an automated and efficient way of classifying music samples based on the mood detection from the audio data. We in particular try to classify the music based on mood for Indian bollywood music. The proposed method tries to address the following problem statement: Genre information (usually part of the audio meta-data) alone does not help in better music classification. For example the acoustic version of the song "nothing else matters by Metallica" can be classified as melody music and thereby a person in relaxing or chill out mood might want to listen to this track. But more often than not this track is associated with metal / heavy rock genre and if a listener classified his play-list based on the genre information alone for his current mood, the user shall miss out on listening to this track. Currently methods exist to detect mood in western or similar kind of music. Our paper tries to solve the issue for Indian bollywood music from an Indian cultural context
Abstract: Estimating the reliability of a computer network has been a subject of great interest. It is a well known fact that this problem is NP-hard. In this paper we present a very efficient combinatorial approach for Monte Carlo reliability estimation of a network with unreliable nodes and unreliable edges. Its core is the computation of some network combinatorial invariants. These invariants, once computed, directly provide pure and simple framework for computation of network reliability. As a specific case of this approach we obtain tight lower and upper bounds for distributed network reliability (the so called residual connectedness reliability). We also present some simulation results.
Abstract: In this paper we propose a segmentation system for unconstrained Arabic online handwriting. An essential problem addressed by analytical-based word recognition system. The system is composed of two-stages the first is a newly special designed hidden Markov model (HMM) and the second is a rules based stage. In our system, handwritten words are broken up into characters by simultaneous segmentation-recognition using HMMs of unique design trained using online features most of which are novel. The HMM output characters boundaries represent the proposed segmentation points (PSP) which are then validated by rules-based post stage without any contextual information help to solve different segmentation errors. The HMM has been designed and tested using a self collected dataset (OHASD) [1]. Most errors cases are cured and remarkable segmentation enhancement is achieved. Very promising word and character segmentation rates are obtained regarding the unconstrained Arabic handwriting difficulty and not using context help.
Abstract: Virtual environments are a hot topic in academia and more importantly in courses offered via distance education. Today-s gaming generation view virtual worlds as strong social and interactive mediums for communicating and socializing. And while institutions of higher education are challenged with increasing enrollment while balancing budget cuts, offering effective courses via distance education become a valid option. Educators can utilize virtual worlds to offer students an enhanced learning environment which has the power to alleviate feelings of isolation through the promotion of communication, interaction, collaboration, teamwork, feedback, engagement and constructivists learning activities. This paper focuses on the use of virtual environments to facilitate interaction in distance education courses so as to produce positive learning outcomes for students. Furthermore, the instructional strategies were reviewed and discussed for use in virtual worlds to enhance learning within a social context.
Abstract: The purpose of this paper is to examine the financing
practices of SMEs in Libya in two different phases of business life
cycle: start-up and matured stages. Moreover, SMEs- accessing bank
loan issues is also identified. The study was conducted by taking into
account the aspect of demand. The findings are based on a sample of
76 SMEs in Libya through the adoption of questionnaires. The results
have pinpointed several things- evidently, SMEs use informal
financing sources which prefer personal savings; SME owners are
willing to apply for bank loan, that the most pressing problem has
been identified, not to apply bank loan is loan with interest (religion
factor).
Abstract: In this paper is being described a possible use of
virtualization technology in teaching computer networks. The
virtualization can be used as a suitable tool for creating virtual
network laboratories, supplementing the real laboratories and
network simulation software in teaching networking concepts. It will
be given a short description of characteristic projects in the area of
virtualization technology usage in network simulation, network
experiments and engineering education. A method for implementing
laboratory has also been explained, together with possible laboratory
usage and design of laboratory exercises. At the end, the laboratory
test results of virtual laboratory are presented as well.