Abstract: In this paper, a necessary and sufficient coefficient are given for functions in a class of complex valued meromorphic harmonic univalent functions of the form f = h + g using Salagean operator. Furthermore, distortion theorems, extreme points, convolution condition and convex combinations for this family of meromorphic harmonic functions are obtained.
Abstract: This paper describes the authorization system
architecture for Pervasive Grid environment. It discusses the
characteristics of classical authorization system and requirements of
the authorization system in pervasive grid environment as well.
Based on our analysis of current systems and taking into account the
main requirements of such pervasive environment, we propose new
authorization system architecture as an extension of the existing grid
authorization mechanisms. This architecture not only supports user
attributes but also context attributes which act as a key concept for
context-awareness thought. The architecture allows authorization of
users dynamically when there are changes in the pervasive grid
environment. For this, we opt for hybrid authorization method that
integrates push and pull mechanisms to combine the existing grid
authorization attributes with dynamic context assertions. We will
investigate the proposed architecture using a real testing environment
that includes heterogeneous pervasive grid infrastructures mapped
over multiple virtual organizations. Various scenarios are described
in the last section of the article to strengthen the proposed mechanism
with different facilities for the authorization procedure.
Abstract: Cardiac pulse-related artifacts in the EEG recorded
simultaneously with fMRI are complex and highly variable. Their
effective removal is an unsolved problem. Our aim is to develop an
adaptive removal algorithm based on the matching pursuit (MP)
technique and to compare it to established methods using a visual
evoked potential (VEP). We recorded the VEP inside the static
magnetic field of an MR scanner (with artifacts) as well as in an
electrically shielded room (artifact free). The MP-based artifact
removal outperformed average artifact subtraction (AAS) and
optimal basis set removal (OBS) in terms of restoring the EEG field
map topography of the VEP. Subsequently, a dipole model was fitted
to the VEP under each condition using a realistic boundary element
head model. The source location of the VEP recorded inside the MR
scanner was closest to that of the artifact free VEP after cleaning
with the MP-based algorithm as well as with AAS. While none of the
tested algorithms offered complete removal, MP showed promising
results due to its ability to adapt to variations of latency, frequency
and amplitude of individual artifact occurrences while still utilizing a
common template.
Abstract: The textile industry produces highly coloured
effluents containing polar and non-polar compounds. The textile mill
run by the Assam Polyester Co-operative Society Limited (APOL) is
situated at Rangia, about 55 km from Guwahati (26011' N, 91047' E)
in the northern bank of the river Brahmaputra, Assam (India). This
unit was commissioned in June 1988 and started commercial
production in November 1988. The installed capacity of the weaving
unit was 8000 m/day and that of the processing unit was 20,000
m/day. The mill has its own dyeing unit with a capacity of 1500-2000
kg/day. The western side of the mill consists of vast agricultural land
and the far northern and southern side of the mill has scattered human
population. The eastern side of the mill has a major road for
thoroughfare. The mill releases its effluents into the agricultural land
in the western side of the mill. The present study was undertaken to
assess the impact of the textile mill on surface soil quality in and
around the mill with particular reference to Cr, Mn, Ni and Zn.
Surface soil samples, collected along different directions at 200, 500
and 1000 m were digested and the metals were estimated with
Atomic Absorption Spectrophotometer. The metals were found in the
range of: Cr 50.9 – 105.0 mg kg-1, Mn 19.2- 78.6 mg kg-1, Ni 41.9 –
50.6 mg kg-1 and Zn 187.8 – 1095.8 mg kg-1. The study reveals
enrichment of Cr, Mn, Ni and Zn in the soil near the textile mill.
Abstract: In this paper, a class of generalized bi-directional associative memory (BAM) neural networks with mixed delays is investigated. On the basis of Lyapunov stability theory and contraction mapping theorem, some new sufficient conditions are established for the existence and uniqueness and globally exponential stability of equilibrium, which generalize and improve the previously known results. One example is given to show the feasibility and effectiveness of our results.
Abstract: Automatic currency note recognition invariably
depends on the currency note characteristics of a particular country
and the extraction of features directly affects the recognition ability.
Sri Lanka has not been involved in any kind of research or
implementation of this kind. The proposed system “SLCRec" comes
up with a solution focusing on minimizing false rejection of notes.
Sri Lankan currency notes undergo severe changes in image quality
in usage. Hence a special linear transformation function is adapted to
wipe out noise patterns from backgrounds without affecting the
notes- characteristic images and re-appear images of interest. The
transformation maps the original gray scale range into a smaller
range of 0 to 125. Applying Edge detection after the transformation
provided better robustness for noise and fair representation of edges
for new and old damaged notes. A three layer back propagation
neural network is presented with the number of edges detected in row
order of the notes and classification is accepted in four classes of
interest which are 100, 500, 1000 and 2000 rupee notes. The
experiments showed good classification results and proved that the
proposed methodology has the capability of separating classes
properly in varying image conditions.
Abstract: Design for cost (DFC) is a method that reduces life
cycle cost (LCC) from the angle of designers. Multiple domain
features mapping (MDFM) methodology was given in DFC. Using
MDFM, we can use design features to estimate the LCC. From the
angle of DFC, the design features of family cars were obtained, such
as all dimensions, engine power and emission volume. At the
conceptual design stage, cars- LCC were estimated using back
propagation (BP) artificial neural networks (ANN) method and
case-based reasoning (CBR). Hamming space was used to measure the
similarity among cases in CBR method. Levenberg-Marquardt (LM)
algorithm and genetic algorithm (GA) were used in ANN. The
differences of LCC estimation model between CBR and artificial
neural networks (ANN) were provided. ANN and CBR separately
each method has its shortcomings. By combining ANN and CBR
improved results accuracy was obtained. Firstly, using ANN selected
some design features that affect LCC. Then using LCC estimation
results of ANN could raise the accuracy of LCC estimation in CBR
method. Thirdly, using ANN estimate LCC errors and correct errors in
CBR-s estimation results if the accuracy is not enough accurate.
Finally, economically family cars and sport utility vehicle (SUV) was
given as LCC estimation cases using this hybrid approach combining
ANN and CBR.
Abstract: Symbolic dynamics studies dynamical systems on the basis of the symbol sequences obtained for a suitable partition of the state space. This approach exploits the property that system dynamics reduce to a shift operation in symbol space. This shift operator is a chaotic mapping. In this article we show that in the symbol space exist other chaotic mappings.
Abstract: The advances in location-based data collection
technologies such as GPS, RFID etc. and the rapid reduction of their
costs provide us with a huge and continuously increasing amount of
data about movement of vehicles, people and goods in an urban area.
This explosive growth of geospatially-referenced data has far
outpaced the planner-s ability to utilize and transform the data into
insightful information thus creating an adverse impact on the return
on the investment made to collect and manage this data. Addressing
this pressing need, we designed and developed DIVAD, a dynamic
and interactive visual analytics dashboard to allow city planners to
explore and analyze city-s transportation data to gain valuable
insights about city-s traffic flow and transportation requirements. We
demonstrate the potential of DIVAD through the use of interactive
choropleth and hexagon binning maps to explore and analyze large
taxi-transportation data of Singapore for different geographic and
time zones.
Abstract: A predictive clustering hybrid regression (pCHR)
approach was developed and evaluated using dataset from H2-
producing sucrose-based bioreactor operated for 15 months. The aim
was to model and predict the H2-production rate using information
available about envirome and metabolome of the bioprocess. Selforganizing
maps (SOM) and Sammon map were used to visualize the
dataset and to identify main metabolic patterns and clusters in
bioprocess data. Three metabolic clusters: acetate coupled with other
metabolites, butyrate only, and transition phases were detected. The
developed pCHR model combines principles of k-means clustering,
kNN classification and regression techniques. The model performed
well in modeling and predicting the H2-production rate with mean
square error values of 0.0014 and 0.0032, respectively.
Abstract: The objective of the research was to evaluate the
quality of milk pomade sweet – sherbet packed in different packaging
materials (Multibarrier 60, met.BOPET/PE, Aluthen), by several
packaging technologies – active and modified atmosphere (MAP)
(consisting of 100% CO2), and control – in air ambiance.
Experiments were carried out at the Faculty of Food Technology of
Latvia University of Agriculture. Samples were stored at the room
temperature +21±1 °C. The physiochemical properties – weight
losses, moisture, hardening, colour and changes in headspace
atmosphere concentration (CO2 and O2) of packs were analysed
before packaging and after 2, 4, 6, 8, 10 and 12 storage weeks.
Abstract: This paper presents a sensing system for 3D sensing
and mapping by a tracked mobile robot with an arm-type sensor
movable unit and a laser range finder (LRF). The arm-type sensor
movable unit is mounted on the robot and the LRF is installed at the
end of the unit. This system enables the sensor to change position and
orientation so that it avoids occlusions according to terrain by this
mechanism. This sensing system is also able to change the height of
the LRF by keeping its orientation flat for efficient sensing. In this kind
of mapping, it may be difficult for moving robot to apply mapping
algorithms such as the iterative closest point (ICP) because sets of the
2D data at each sensor height may be distant in a common surface. In
order for this kind of mapping, the authors therefore applied
interpolation to generate plausible model data for ICP. The results of
several experiments provided validity of these kinds of sensing and
mapping in this sensing system.
Abstract: This paper demonstrates a model of an e-Learning
system based on nowadays learning theory and distant education
practice. The relationships in the model are designed to be simple
and functional and do not necessarily represent any particular e-
Learning environments. It is meant to be a generic e-Learning
system model with implications for any distant education course
instructional design. It allows online instructors to move away from
the discrepancy between the courses and body of knowledge. The
interrelationships of four primary sectors that are at the e-Learning
system are presented in this paper. This integrated model includes
[1] pedagogy, [2] technology, [3] teaching, and [4] learning. There
are interactions within each of these sectors depicted by system loop
map.
Abstract: This paper presents an application of Artificial Neural Network (ANN) to forecast actual cost of a project based on the earned value management system (EVMS). For this purpose, some projects randomly selected based on the standard data set , and it is produced necessary progress data such as actual cost ,actual percent complete , baseline cost and percent complete for five periods of project. Then an ANN with five inputs and five outputs and one hidden layer is trained to produce forecasted actual costs. The comparison between real and forecasted data show better performance based on the Mean Absolute Percentage Error (MAPE) criterion. This approach could be applicable to better forecasting the project cost and result in decreasing the risk of project cost overrun, and therefore it is beneficial for planning preventive actions.
Abstract: This paper proposes a new procedure for analyzing means-end chain data in marketing research. Most commonly the collected data is summarized in the Hierarchical Value Map (HVM) illustrating the main attribute-consequence-value linkages. This paper argues that traditionally constructed HVM may give an erroneous impression of the results of a means-end study. To justify the arguments, an alternative procedure to (1) determine the dominant attribute-consequence-value linkages and (2) construct HVM in a precise manner is presented. The current approach makes a contribution to means-end analysis, allowing marketers to address a set of marketing problems, such as advertising strategy.
Abstract: We present a prototype interactive (hyper) map of strategic, tactical, and logistic options for Supply Chain Management. The map comprises an anthology of options, broadly classified within the strategic spectrum of efficiency versus responsiveness, and according to logistic and cross-functional drivers. They are exemplified by cases in diverse industries. We seek to get all these information and ideas organized to help supply chain managers identify effective choices for specific business environments. The key and innovative linkage we introduce is the configuration of competitive forces. Instead of going through seemingly endless and isolated cases and wondering how one can borrow from them, we aim to provide a guide by force comparisons. The premise is that best practices in a different industry facing similar forces may be a most productive resource in supply chain design and planning. A prototype template is demonstrated.
Abstract: There is strong evidence that water channel proteins
'aquaporins (AQPs)' are central components in plant-water relations
as well as a number of other physiological parameters. We had
previously reported the isolation of 24 plasma membrane intrinsic
protein (PIP) type AQPs. However, the gene numbers in rice and the
polyploid nature of bread wheat indicated a high probability of
further genes in the latter. The present work focused on identification
of further AQP isoforms in bread wheat. With the use of altered
primer design, we identified five genes homologous, designated
PIP1;5b, PIP2;9b, TaPIP2;2, TaPIP2;2a, TaPIP2;2b. Sequence
alignments indicate PIP1;5b, PIP2;9b are likely to be homeologues of
two previously reported genes while the other three are new genes
and could be homeologs of each other. The results indicate further
AQP diversity in wheat and the sequence data will enable physical
mapping of these genes to identify their genomes as well as genetic to
determine their association with any quantitative trait loci (QTLs)
associated with plant-water relation such as salinity or drought
tolerance.
Abstract: Low power consumption is a major constraint for battery-powered system like computer notebook or PDA. In the past, specialists usually designed both specific optimized equipments and codes to relief this concern. Doing like this could work for quite a long time, however, in this era, there is another significant restraint, the time to market. To be able to serve along the power constraint while can launch products in shorter production period, objectoriented programming (OOP) has stepped in to this field. Though everyone knows that OOP has quite much more overhead than assembly and procedural languages, development trend still heads to this new world, which contradicts with the target of low power consumption. Most of the prior power related software researches reported that OOP consumed much resource, however, as industry had to accept it due to business reasons, up to now, no papers yet had mentioned about how to choose the best OOP practice in this power limited boundary. This article is the pioneer that tries to specify and propose the optimized strategy in writing OOP software under energy concerned environment, based on quantitative real results. The language chosen for studying is C# based on .NET Framework 2.0 which is one of the trendy OOP development environments. The recommendation gotten from this research would be a good roadmap that can help developers in coding that well balances between time to market and time of battery.
Abstract: In this paper, a second order autoregressive (AR)
model is proposed to discriminate alcoholics using single trial
gamma band Visual Evoked Potential (VEP) signals using 3 different
classifiers: Simplified Fuzzy ARTMAP (SFA) neural network (NN),
Multilayer-perceptron-backpropagation (MLP-BP) NN and Linear
Discriminant (LD). Electroencephalogram (EEG) signals were
recorded from alcoholic and control subjects during the presentation
of visuals from Snodgrass and Vanderwart picture set. Single trial
VEP signals were extracted from EEG signals using Elliptic filtering
in the gamma band spectral range. A second order AR model was
used as gamma band VEP exhibits pseudo-periodic behaviour and
second order AR is optimal to represent this behaviour. This
circumvents the requirement of having to use some criteria to choose
the correct order. The averaged discrimination errors of 2.6%, 2.8%
and 11.9% were given by LD, MLP-BP and SFA classifiers. The
high LD discrimination results show the validity of the proposed
method to discriminate between alcoholic subjects.
Abstract: The environmental impacts caused by the current production and consumption models, together with the impact that the current economic crisis, bring necessary changes in the European industry toward new business models based on sustainability issues that could allow them to innovate and improve their competitiveness. This paper analyzes the key environmental issues and the current and future market trends in one of the most important industrial sectors in Spain, the furniture sector. It also proposes new decision support tools -diagnostic kit, roadmap and guidelines- to guide companies to implement sustainability criteria into their organizations, including eco-design strategies and other economical and social strategies in accordance with the sustainability definition, and other available tools such as eco-labels, environmental management systems, etc., and to use and combine them to obtain the results the company expects to help improve its competitiveness.