Abstract: Iris codes contain bits with different entropy. This
work investigates different strategies to reduce the size of iris
code templates with the aim of reducing storage requirements and
computational demand in the matching process. Besides simple subsampling
schemes, also a binary multi-resolution representation as
used in the JBIG hierarchical coding mode is assessed. We find that
iris code template size can be reduced significantly while maintaining
recognition accuracy. Besides, we propose a two-stage identification
approach, using small-sized iris code templates in a pre-selection
stage, and full resolution templates for final identification, which
shows promising recognition behaviour.
Abstract: This article is to review and understand the new
generation of students to understand their expectations and attitudes.
There are a group of students on school projects, creative work,
educational software and digital signal source, the use of social
networking tools to communicate with friends and a part in the
competition. Today's students have been described as the new
millennium students. They use information and communication
technology in a more creative and innovative at home than at school,
because the information and communication technologies for
different purposes, in the home, usually occur in school. They
collaborate and communicate more effectively when they are at
home. Most children enter school, they will bring about how to use
information and communication technologies, some basic skills and
some tips on how to use information and communication technology
will provide a more advanced than most of the school's expectations.
Many teachers can help students, however, still a lot of work,
"tradition", without a computer, and did not see the "new social
computing networks describe young people to learn and new ways of
working life in the future", in the education system of the benefits of
using a computer.
Abstract: Recent research in neural networks science and
neuroscience for modeling complex time series data and statistical
learning has focused mostly on learning from high input space and
signals. Local linear models are a strong choice for modeling local
nonlinearity in data series. Locally weighted projection regression is
a flexible and powerful algorithm for nonlinear approximation in
high dimensional signal spaces. In this paper, different learning
scenario of one and two dimensional data series with different
distributions are investigated for simulation and further noise is
inputted to data distribution for making different disordered
distribution in time series data and for evaluation of algorithm in
locality prediction of nonlinearity. Then, the performance of this
algorithm is simulated and also when the distribution of data is high
or when the number of data is less the sensitivity of this approach to
data distribution and influence of important parameter of local
validity in this algorithm with different data distribution is explained.
Abstract: Parameters of flow are calculated in vaneless diffusers
with relative width 0,014–0,10. Inlet angles of flow and similarity
criteria were varied. There is information on flow separation,
boundary layer development, configuration of streamlines.
Polytrophic efficiency, loss coefficient and recovery coefficient are
used to compare effectiveness of diffusers. The sample of
optimization of narrow diffuser with conical walls is presented. Three
wide diffusers with narrowing walls are compared. The work is made
in the R&D laboratory “Gas dynamics of turbo machines” of the TU
SPb.
Abstract: There is an evident trend to elevate pressure ratio of a
single stage of a turbo compressors - axial compressors in particular.
Whilst there was an opinion recently that a pressure ratio 1,9 was a
reasonable limit, later appeared information on successful modeling
tested of stages with pressure ratio up to 2,8. The authors recon that
lack of information on high pressure stages makes actual a study of
rational choice of design parameters before high supersonic flow
problems solving. The computer program of an engineering type was
developed. Below is presented a sample of its application to study
possible parameters of the impeller of the stage with pressure ratio
3,0. Influence of two main design parameters on expected efficiency,
periphery blade speed and flow structure is demonstrated. The results
had lead to choose a variant for further analysis and improvement by
CFD methods.
Abstract: Vancron 40, a nitrided powder metallurgical tool
Steel, is used in cold work applications where the predominant failure
mechanisms are adhesive wear or galling. Typical applications of
Vancron 40 are among others fine blanking, cold extrusion, deep
drawing and cold work rolls for cluster mills. Vancron 40 positive
results for cold work rolls for cluster mills and as a tool for some
severe metal forming process makes it competitive compared to other
type of work rolls that require higher precision, among others in cold
rolling of thin stainless steel, which required high surface finish
quality. In this project, three roll materials for cold rolling of stainless
steel strip was examined, Vancron 40, Narva 12B (a high-carbon,
high-chromium tool steel alloyed with tungsten) and Supra 3 (a
Chromium-molybdenum tungsten-vanadium alloyed high speed
steel). The purpose of this project was to study the depth profiles of
the ironed stainless steel strips, emergence of galling and to study the
lubrication performance used by steel industries. Laboratory
experiments were conducted to examine scratch of the strip, galling
and surface roughness of the roll materials under severe tribological
conditions. The critical sliding length for onset of galling was
estimated for stainless steel with four different lubricants. Laboratory
experiments result of performance evaluation of resistance capability
of rolls toward adhesive wear under severe conditions for low and
high reductions. Vancron 40 in combination with cold rolling
lubricant gave good surface quality, prevents galling of
metal surfaces and good bearing capacity.
Abstract: It has experimentally been proved that the
performance of compression ignition (C.I.) engine is spray
characteristics related. In modern diesel engine the spray formation
and the eventual combustion process are the vital processes that offer
more challenges towards enhancing the engine performance. In the
present work the numerical simulation has been carried out for
evaporating diesel sprays using Fluent software. For computational
fluid dynamics simulation “Meshing” is done using Gambit software
before transmitting it into Fluent. The simulation is carried out using
hot bomb conditions under varying chamber conditions such as gas
pressure, nozzle diameter and fuel injection pressure. For comparison
purpose, the numerical simulations the chamber conditions were kept
the same as that of the experimental data. At varying chamber
conditions the spray penetration rates are compared with the existing
experimental results.
Abstract: The number of Ground Motion Prediction Equations
(GMPEs) used for predicting peak ground acceleration (PGA) and
the number of earthquake recordings that have been used for fitting
these equations has increased in the past decades. The current PF-L
database contains 3550 recordings. Since the GMPEs frequently
model the peak ground acceleration the goal of the present study was
to refit a selection of 44 of the existing equation models for PGA in
light of the latest data. The algorithm Levenberg-Marquardt was used
for fitting the coefficients of the equations and the results are
evaluated both quantitatively by presenting the root mean squared
error (RMSE) and qualitatively by drawing graphs of the five best
fitted equations. The RMSE was found to be as low as 0.08 for the
best equation models. The newly estimated coefficients vary from the
values published in the original works.
Abstract: Conventional educational practices, do not offer all
the required skills for teachers to successfully survive in today’s
workplace. Due to poor professional training, a big gap exists across
the curriculum plan and the teacher practices in the classroom. As
such, raising the quality of teaching through ICT-enabled training and
professional development of teachers should be an urgent priority.
‘Mobile Learning’, in that vein, is an increasingly growing field of
educational research and practice across schools and work places. In
this paper, we propose a novel Mobile learning system that allows the
users to learn through an intelligent mobile learning in cooperatively
every-time and every-where. The system will reduce the training cost
and increase consistency, efficiency, and data reliability. To establish
that our system will display neither functional nor performance
failure, the evaluation strategy is based on formal observation of
users interacting with system followed by questionnaires and
structured interviews.
Abstract: Job Scheduling plays an important role for efficient
utilization of grid resources available across different domains and
geographical zones. Scheduling of jobs is challenging and NPcomplete.
Evolutionary / Swarm Intelligence algorithms have been
extensively used to address the NP problem in grid scheduling.
Artificial Bee Colony (ABC) has been proposed for optimization
problems based on foraging behaviour of bees. This work proposes a
modified ABC algorithm, Cluster Heterogeneous Earliest First Min-
Min Artificial Bee Colony (CHMM-ABC), to optimally schedule
jobs for the available resources. The proposed model utilizes a novel
Heterogeneous Earliest Finish Time (HEFT) Heuristic Algorithm
along with Min-Min algorithm to identify the initial food source.
Simulation results show the performance improvement of the
proposed algorithm over other swarm intelligence techniques.
Abstract: The development, operation and maintenance of
Integrated Waste Management Systems (IWMS) affects essentially
the sustainable concern of every region. The features of such systems
have great influence on all of the components of sustainability. In
order to reach the optimal way of processes, a comprehensive
mapping of the variables affecting the future efficiency of the system
is needed such as analysis of the interconnections among the
components and modeling of their interactions. The planning of a
IWMS is based fundamentally on technical and economical
opportunities and the legal framework. Modeling the sustainability
and operation effectiveness of a certain IWMS is not in the scope of
the present research. The complexity of the systems and the large
number of the variables require the utilization of a complex approach
to model the outcomes and future risks. This complex method should
be able to evaluate the logical framework of the factors composing
the system and the interconnections between them. The authors of
this paper studied the usability of the Fuzzy Cognitive Map (FCM)
approach modeling the future operation of IWMS’s. The approach
requires two input data set. One is the connection matrix containing
all the factors affecting the system in focus with all the
interconnections. The other input data set is the time series, a
retrospective reconstruction of the weights and roles of the factors.
This paper introduces a novel method to develop time series by
content analysis.
Abstract: This study examines several critical dimensions of eservice
quality overlooked in the existing literature and proposes a
model and instrument framework for measuring customer perceived
e-service quality in the banking sector. The initial design was derived
from a pool of instrument dimensions and their items from the
existing literature review by content analysis. Based on focused
group discussion, nine dimensions were extracted. An exploratory
factor analysis approach was applied to data from a survey of 323
respondents. The instrument has been designed specifically for the
banking sector. Research data was collected from bank customers
who use electronic banking in a developing economy. A nine-factor
instrument has been proposed to measure the e-service quality. The
instrument has been checked for reliability. The validity and sample
place limited the applicability of the instrument across economies and
service categories. Future research must be conducted to check the
validity. This instrument can help bankers in developing economies
like India to measure the e-service quality and make improvements.
The present study offers a systematic procedure that provides insights
on to the conceptual and empirical comprehension of customer
perceived e-service quality and its constituents.
Abstract: The absorption power generation cycle based on the
ammonia-water mixture has attracted much attention for efficient
recovery of low-grade energy sources. In this paper a thermodynamic
performance analysis is carried out for a Kalina cycle using
ammonia-water mixture as a working fluid for efficient conversion of
low-temperature heat source in the form of sensible energy. The
effects of the source temperature on the system performance are
extensively investigated by using the thermodynamic models. The
results show that the source temperature as well as the ammonia mass
fraction affects greatly on the thermodynamic performance of the
cycle.
Abstract: In this work, we study the behavior of introducing
atomic size vacancy in a graphene nanoribbon superlattice. Our
investigations are based on the density functional theory (DFT) with
the Local Density Approximation in Atomistix Toolkit (ATK). We
show that, in addition to its shape, the position of vacancy has a
major impact on the electrical properties of a graphene nanoribbon
superlattice. We show that the band gap of an armchair graphene
nanoribbon may be tuned by introducing an appropriate periodic
pattern of vacancies. The band gap changes in a zig-zag manner
similar to the variation of band gap of a graphene nanoribbon by
changing its width.
Abstract: This research study is an exploration of the selfdirected
professional development of teachers who teach in public
schools in an era of democracy and educational change in South
Africa. Amidst an ever-changing educational system, the teachers in
this study position themselves as self-directed teacher-learners where
they adopt particular learning practices which enable change within
the broader discourses of public schooling. Life-story interviews
were used to enter into the private and public spaces of five teachers
which offer glimpses of how particular systems shaped their
identities, and how the meanings of self-directed teacher-learner
shaped their learning practices. Through the Multidimensional
Framework of Analysis and Interpretation the teachers’ stories were
analysed through three lenses: restorying the field texts - the self
through story; the teacher-learner in relation to social contexts, and
practices of self-directed learning. This study shows that as teacherlearners
learn for change through self-directed learning practices,
they develop their agency as transformative intellectuals, which is
necessary for the reworking of South African public schools.
Abstract: This paper presents an evolutionary algorithm for
solving multi-objective optimization problems-based artificial neural
network (ANN). The multi-objective evolutionary algorithm used in
this study is genetic algorithm while ANN used is radial basis
function network (RBFN). The proposed algorithm named memetic
elitist Pareto non-dominated sorting genetic algorithm-based RBFN
(MEPGAN). The proposed algorithm is implemented on medical
diseases problems. The experimental results indicate that the
proposed algorithm is viable, and provides an effective means to
design multi-objective RBFNs with good generalization capability
and compact network structure. This study shows that MEPGAN
generates RBFNs coming with an appropriate balance between
accuracy and simplicity, comparing to the other algorithms found in
literature.
Abstract: Text mining techniques are generally applied for
classifying the text, finding fuzzy relations and structures in data
sets. This research provides plenty text mining capabilities. One
common application is text classification and event extraction,
which encompass deducing specific knowledge concerning incidents
referred to in texts. The main contribution of this paper is the
clarification of a concept graph generation mechanism, which is based
on a text classification and optimal fuzzy relationship extraction.
Furthermore, the work presented in this paper explains the application
of fuzzy relationship extraction and branch and bound (BB) method
to simplify the texts.
Abstract: In and around Erode District, it is estimated that more
than 1250 chemical and allied textile processing fabric industries are
affected, partially closed and shut off for various reasons such as poor
management, poor supplier performance, lack of planning for
productivity, fluctuation of output, poor investment, waste analysis,
labor problems, capital/labor ratio, accumulation of stocks, poor
maintenance of resources, deficiencies in the quality of fabric, low
capacity utilization, age of plant and equipment, high investment and
input but low throughput, poor research and development, lack of
energy, workers’ fear of loss of jobs, work force mix and work ethic.
The main objective of this work is to analyze the existing conditions
in textile fabric sector, validate the break even of Total Productivity
(TP), analyze, design and implement fuzzy sets and mathematical
programming for improvement of productivity and quality
dimensions in the fabric processing industry. It needs to be
compatible with the reality of textile and fabric processing industries.
The highly risk events from productivity and quality dimension were
found by fuzzy systems and results are wrapped up among the textile
fabric processing industry.
Abstract: Assembly line balancing problem is aimed to divide
the tasks among the stations in assembly lines and optimize some
objectives. In assembly lines the workload on stations is different
from each other due to different tasks times and the difference in
workloads between stations can cause blockage or starvation in some
stations in assembly lines. Buffers are used to store the semi-finished
parts between the stations and can help to smooth the assembly
production. The assembly line balancing and buffer sizing problem
can affect the throughput of the assembly lines. Assembly line
balancing and buffer sizing problems have been studied separately in
literature and due to their collective contribution in throughput rate of
assembly lines, balancing and buffer sizing problem are desired to
study simultaneously and therefore they are considered concurrently
in current research. Current research is aimed to maximize
throughput, minimize total size of buffers in assembly line and
minimize workload variations in assembly line simultaneously. A
multi objective optimization objective is designed which can give
better Pareto solutions from the Pareto front and a simple example
problem is solved for assembly line balancing and buffer sizing
simultaneously. Current research is significant for assembly line
balancing research and it can be significant to introduce optimization
approaches which can optimize current multi objective problem in
future.
Abstract: Prior to quantifying the variables of the information
model for using school terminology in Croatia's region of Dalmatia
from 1884 to 2014, the most relevant model variables had to be
determined: historical circumstances, standard of living, education
system, linguistic situation, and media. The research findings show
that there was no significant transfer of the 1884 school terms into
1949 usage; likewise, the 1949 school terms were not widely used in
2014. On the other hand, the research revealed that the meaning of
school terms changed over the decades. The quantification of the
variables will serve as the groundwork for creating an information
model for using school terminology in Dalmatia from 1884 to 2014
and for defining direct growth rates in further research.