Abstract: In this paper smooth trajectories are computed in the Lie group SO(2, 1) as a motion planning problem by assigning a Frenet frame to the rigid body system to optimize the cost function of the elastic energy which is spent to track a timelike curve in Minkowski space. A method is proposed to solve a motion planning problem that minimizes the integral of the Lorentz inner product of Darboux vector of a timelike curve. This method uses the coordinate free Maximum Principle of Optimal control and results in the theory of integrable Hamiltonian systems. The presence of several conversed quantities inherent in these Hamiltonian systems aids in the explicit computation of the rigid body motions.
Abstract: Functionalities and control behavior are both primary
requirements in design of a complex system. Automata theory plays
an important role in modeling behavior of a system. Z is an ideal
notation which is used for describing state space of a system and then
defining operations over it. Consequently, an integration of automata
and Z will be an effective tool for increasing modeling power for a
complex system. Further, nondeterministic finite automata (NFA)
may have different implementations and therefore it is needed to
verify the transformation from diagrams to a code. If we describe
formal specification of an NFA before implementing it, then
confidence over transformation can be increased. In this paper, we
have given a procedure for integrating NFA and Z. Complement of a
special type of NFA is defined. Then union of two NFAs is
formalized after defining their complements. Finally, formal
construction of intersection of NFAs is described. The specification
of this relationship is analyzed and validated using Z/EVES tool.
Abstract: In this study, the problem of discriminating between interictal epileptic and non- epileptic pathological EEG cases, which present episodic loss of consciousness, investigated. We verify the accuracy of the feature extraction method of autocross-correlated coefficients which extracted and studied in previous study. For this purpose we used in one hand a suitable constructed artificial supervised LVQ1 neural network and in other a cross-correlation technique. To enforce the above verification we used a statistical procedure which based on a chi- square control. The classification and the statistical results showed that the proposed feature extraction is a significant accurate method for diagnostic discrimination cases between interictal and non-interictal EEG events and specifically the classification procedure showed that the LVQ neural method is superior than the cross-correlation one.
Abstract: The growing interest on national heritage
preservation has led to intensive efforts on digital documentation of
cultural heritage knowledge. Encapsulated within this effort is the
focus on ontology development that will help facilitate the
organization and retrieval of the knowledge. Ontologies surrounding
cultural heritage domain are related to archives, museum and library
information such as archaeology, artifacts, paintings, etc. The growth
in number and size of ontologies indicates the well acceptance of its
semantic enrichment in many emerging applications. Nowadays,
there are many heritage information systems available for access.
Among others is community-based e-museum designed to support the
digital cultural heritage preservation. This work extends previous
effort of developing the Traditional Malay Textile (TMT) Knowledge
Model where the model is designed with the intention of auxiliary
mapping with CIDOC CRM. Due to its internal constraints, the
model needs to be transformed in advance. This paper addresses the
issue by reviewing the previous harmonization works with CIDOC
CRM as exemplars in refining the facets in the model particularly
involving TMT-Artifact class. The result is an extensible model
which could lead to a common view for automated mapping with
CIDOC CRM. Hence, it promotes integration and exchange of
textile information especially batik-related between communities in
e-museum applications.
Abstract: The study aims to investigate the impact on board and
audit committee characteristics and firm performance before and
after the revision of MCCG (2007) on GLCs over the period 2005-2010. We used Return on Assets (ROA) as a proxy for firm performance. The data consists of two groups; data collected before
and after the amendments of MCCG (2007). Findings show that
boards of directors with accounting / finance qualifications (BEXP)
are statistically significant with performance for period before the amendments. As for audit committee members with accounting or
finance qualifications (ACEXP), correlation results indicate a
negative association and non-significant results for the years before
amendments. However, the years after the amendments show
positive relationship with highly significant correlations (1%) to ROA. This indicates that the amendments of MCCG 2007 on the
audit committee members- literacy in accounting have impacted the governance structures and performance of GLCs.
Abstract: In elliptic curve theory, number of rational points on
elliptic curves and determination of these points is a fairly important
problem. Let p be a prime and Fp be a finite field and k ∈ Fp. It
is well known that which points the curve y2 = x3 + kx has and
the number of rational points of on Fp. Consider the circle family
x2 + y2 = r2. It can be interesting to determine common points of
these two curve families and to find the number of these common
points. In this work we study this problem.
Abstract: Generation of electricity from coal has increased over
the years in the United States and around the world. Burning of coal
results in annual production of upwards of 100 millions tons (United
States only) of coal combustion products (CCPs). Only about a third
of these products are being used to create new products while the
remainder goes to landfills. Application of CCPs mixed with
composted organic materials onto soil can improve the soil-s
physico-chemical conditions and provide essential plant nutritients.
Our objective was to create plant growth media utilizing CCPs and
compost in way which maximizes the use of these products and, at
the same time, maintain good plant growth. Media were formulated
by adding composted organic matter (COM) to CCPs at ratios
ranging from 2:8 to 8:2 (v/v). The quality of these media was
evaluated by measuring their physical and chemical properties and
their effect on plant growth. We tested the media by 1) measuring
their physical and chemical properties and 2) the growth of three
plant species in the experimental media: wheat (Triticum sativum),
tomato (Lycopersicum esculentum) and marigold (Tagetes patula).
We achieved significantly (p < 0.001) higher growth (7-130%) in the
experimental media containing CCPs compared to a commercial mix.
The experimental media supplied adequate plant nutrition as no
fertilization was provided during the experiment. Based on the
results, we recommend the use of CCPs and composts for the
creation of plant growth media.
Abstract: The theatre-auditorium under investigation following
the highly reflective characteristics of materials used in it (marble,
painted wood, smooth plaster, etc), architectural and structural
features of the Protocol and its intended use (very multifunctional:
Auditorium, theatre, cinema, musicals, conference room) from the
analysis of the statement of fact made by the acoustic simulation
software Ramsete and supported by data obtained through a
campaign of acoustic measurements of the state of fact made on the
spot by a Fonomet Svantek model SVAN 957, appears to be
acoustically inadequate. After the completion of the 3D model
according to the specifications necessary software used forecast in
order to be recognized by him, have made three simulations, acoustic
simulation of the state of and acoustic simulation of two design
solutions.
Improved noise characteristics found in the first design solution,
compared to the state in fact consists therefore in lowering
Reverberation Time that you turn most desirable value, while the
Indicators of Clarity, the Baricentric Time, the Lateral Efficiency,
Ratio of Low Tmedia BR and defined the Speech Intelligibility
improved significantly. Improved noise characteristics found instead
in the second design solution, as compared to first design solution, is
finally mostly in a more uniform distribution of Leq and in lowering
Reverberation Time that you turn the optimum values. Indicators of
Clarity, and the Lateral Efficiency improve further but at the expense
of a value slightly worse than the BR. Slightly vary the remaining
indices.
Abstract: In the present study, the oleaginous fungus
Mortierella alpina CBS 754.68 was screened for arachidonic
acidproduction using inexpensive agricultural by-products as
substrate. Four oilcakes were analysed to choose the best substrate
among them. Sunflower oilcake was the most effective substrate for
ARA production followed by soybean, colza and olive oilcakes. In
the next step, seven variables including substrate particle size,
moisture content, time, temperature, yeast extract supply, glucose
supply and glutamate supply were surveyed and effective variables
for ARA production were determined using a Plackett-Burman
screening design. Analysis results showed that time (12 days),
substrate particle size (1-1.4 mm) and temperature (20ºC) were the
most effective variables for the highest level of ARA production
respectively.
Abstract: Epstein-Barr virus (EBV) is implicated in the pathogenesis of the endemic Burkitt-s lymphoma (BL). The EBVpositive BL-derived cell lines initially maintain the original tumor phenotype of EBV infection (latency I, LatI), but most of them drift toward a lymphoblast phenotype of EBV latency III (LatIII) during in vitro culturing. The aim of the present work was to characterize the B-cell subsets in EBV-positive BL cell lines and to verify whether a particular cell subset correlates with the type of EBV infection. The phenotype analysis of two EBV-negative and eleven EBV-positive (three of LatI and eight of LatIII) BL cell lines was performed by polychromatic flow cytomery, based on expression pattern of CD19, CD10, CD38, CD27, and CD5 markers. Two cell subsets, CD19+CD10+ and CD19+CD10-, were defined in LatIII BL cell lines. In both subsets, the CD27 and CD5 cell surface expression was detected in a proportion of the cells.
Abstract: Emotions are related with learning processes and
physiological signals can be used to detect them for the
personalization of learning resources and to control the pace of
instruction. A model of relevant emotions has been developed, where
specific combinations of emotions and cognition processes are
connected and integrated with the concept of 'flow', in order to
improve learning. The cardiac pulse is a reliable signal that carries
useful information about the subject-s emotional condition; it is
detected using a classroom chair adapted with non invasive EMFi
sensor and an acquisition system that generates a ballistocardiogram
(BCG), the signal is processed by an algorithm to obtain
characteristics that match a specific emotional condition. The
complete chair system is presented in this work, along with a
framework for the personalization of learning resources.
Abstract: This article simulates the wind generator set which has
two fault bearing collar rail destruction and the gear box oil leak fault.
The electric current signal which produced by the generator, We use
Empirical Mode Decomposition (EMD) as well as Fast Fourier
Transform (FFT) obtains the frequency range-s signal figure and
characteristic value. The last step is use a kind of Artificial Neural
Network (ANN) classifies which determination fault signal's type and
reason. The ANN purpose of the automatic identification wind
generator set fault..
Abstract: the objective of this study is to measure the levels of
cellulas activity of ostrich GI microorganisms, and comparing it with
the levels of cellulas activity of rumen-s microorganisms, and also to
estimate the probability of increasing enzyme activity with injecting
different dosages (30%, 50% and 70%) of pure anaerobic goat rumen
fungi. The experiment was conducted in laboratory and under a
complete anaerobic condition (in vitro condition). 40 ml of
“CaldWell" medium and 1.4g wheat straw were placed in incubator
for an hour. The cellulase activity of ostrich microorganisms was
compared with other treatments, and then different dosages (30%,
50% and 70%) of pure anaerobic goat rumen fungi were injected to
ostrich microorganism-s media. Due to the results, cattle and goat
with 2.13 and 2.08 I.U (international units) respectively showed the
highest activity and ostrich with 0.91 (I.U) had the lowest cellulose
activity (p < 0.05). Injecting 30% and 50% of anaerobic fungi had no
significant incensement in enzyme activity, but with injecting 70% of
rumen fungi to ostrich microorganisms culture a significant increase
was observed 1.48 I.U. (p < 0.05).
Abstract: A set of Artificial Neural Network (ANN) based methods
for the design of an effective system of speech recognition of
numerals of Assamese language captured under varied recording
conditions and moods is presented here. The work is related to
the formulation of several ANN models configured to use Linear
Predictive Code (LPC), Principal Component Analysis (PCA) and
other features to tackle mood and gender variations uttering numbers
as part of an Automatic Speech Recognition (ASR) system in
Assamese. The ANN models are designed using a combination of
Self Organizing Map (SOM) and Multi Layer Perceptron (MLP)
constituting a Learning Vector Quantization (LVQ) block trained in a
cooperative environment to handle male and female speech samples
of numerals of Assamese- a language spoken by a sizable population
in the North-Eastern part of India. The work provides a comparative
evaluation of several such combinations while subjected to handle
speech samples with gender based differences captured by a microphone
in four different conditions viz. noiseless, noise mixed, stressed
and stress-free.
Abstract: Process planning and production scheduling play
important roles in manufacturing systems. In this paper a multiobjective
mixed integer linear programming model is presented for
the integrated planning and scheduling of multi-product. The aim is
to find a set of high-quality trade-off solutions. This is a
combinatorial optimization problem with substantially large solution
space, suggesting that it is highly difficult to find the best solutions
with the exact search method. To account for it, a PSO-based
algorithm is proposed by fully utilizing the capability of the
exploration search and fast convergence. To fit the continuous PSO
in the discrete modeled problem, a solution representation is used in
the algorithm. The numerical experiments have been performed to
demonstrate the effectiveness of the proposed algorithm.
Abstract: The paper describes a self supervised parallel self organizing neural network (PSONN) architecture for true color image segmentation. The proposed architecture is a parallel extension of the standard single self organizing neural network architecture (SONN) and comprises an input (source) layer of image information, three single self organizing neural network architectures for segmentation of the different primary color components in a color image scene and one final output (sink) layer for fusion of the segmented color component images. Responses to the different shades of color components are induced in each of the three single network architectures (meant for component level processing) by applying a multilevel version of the characteristic activation function, which maps the input color information into different shades of color components, thereby yielding a processed component color image segmented on the basis of the different shades of component colors. The number of target classes in the segmented image corresponds to the number of levels in the multilevel activation function. Since the multilevel version of the activation function exhibits several subnormal responses to the input color image scene information, the system errors of the three component network architectures are computed from some subnormal linear index of fuzziness of the component color image scenes at the individual level. Several multilevel activation functions are employed for segmentation of the input color image scene using the proposed network architecture. Results of the application of the multilevel activation functions to the PSONN architecture are reported on three real life true color images. The results are substantiated empirically with the correlation coefficients between the segmented images and the original images.
Abstract: A property is called persistent if for any many-sorted term rewriting system , has the property if and only if term rewriting system , which results from by omitting its sort information, has the property. In this paper,we show that termination is persistent for non-overlapping term rewriting systems and we give the example as application of this result. Furthermore we obtain that completeness is persistent for non-overlapping term rewriting systems.
Abstract: The present work deals with optimization of cascade refrigeration system using eco friendly refrigerants pair R507A and R23. R507A is azeotropic mixture composed of HFC refrigerants R125/R143a (50%/50% by wt.). R23 is a single component HFC refrigerant used as replacement to CFC refrigerant R13 in low temperature applications. These refrigerants have zero ozone depletion potential and are non-flammable. Optimization of R507AR23 cascade refrigeration system performance parameters such as minimum work required, refrigeration effect, coefficient of performance and exergetic efficiency was carried out in terms of eight operating parameters- combinations using Genetic Algorithm tool. The eight operating parameters include (1) low side evaporator temperature (2) high side condenser temperature (3) temperature difference in the cascade heat exchanger (4) low side condenser temperature (5) low side degree of subcooling (6) high side degree of subcooling (7) low side degree of superheating (8) high side degree of superheating. Results show that for minimum work system should operate at high temperature in low side evaporator, low temperature in high side condenser, low temperature difference in cascade condenser, high temperature in low side condenser and low degree of subcooling and superheating in both side. For maximum refrigeration effect system should operate at high temperature in low side evaporator, high temperature in high side condenser, high temperature difference in cascade condenser, low temperature in low side condenser and higher degree of subcooling in LT and HT side. For maximum coefficient of performance and exergetic efficiency, system should operate at high temperature in low side evaporator, low temperature in high side condenser, low temperature difference in cascade condenser, high temperature in low side condenser and higher degree of subcooling and superheating in low side of the system.
Abstract: In the framework of adaptive parametric modelling of images, we propose in this paper a new technique based on the Chandrasekhar fast adaptive filter for texture characterization. An Auto-Regressive (AR) linear model of texture is obtained by scanning the image row by row and modelling this data with an adaptive Chandrasekhar linear filter. The characterization efficiency of the obtained model is compared with the model adapted with the Least Mean Square (LMS) 2-D adaptive algorithm and with the cooccurrence method features. The comparison criteria is based on the computation of a characterization degree using the ratio of "betweenclass" variances with respect to "within-class" variances of the estimated coefficients. Extensive experiments show that the coefficients estimated by the use of Chandrasekhar adaptive filter give better results in texture discrimination than those estimated by other algorithms, even in a noisy context.
Abstract: Malaysia government had been trying hard in order to
find the most efficient methods in learning. However, it is hard to
actually access and evaluate students whom will then be called an
excellent student. It is because in our realties student who excellent
is only excel in academic. This evaluation becomes a problem
because it not balances in our real life interm of to get an excellent
student in whole area in their involvement of curiculum and cocuriculum.
To overcome this scenario, we designed a module for
Student Idol to evaluate student through three categories which are
academic, co-curiculum and leadership. All the categories have their
own merit point. Using this method, student will be evaluated more
accurate compared to the previously. So, teacher can easily evaluate
their student without having any emotion factor, relation factor and
others. As conclusion this system module will helps the development
of student evaluation more accurate and valid in Student Idol.