Abstract: This study explores perceptions of English as a Foreign
Language (EFL) learners on using computer mediated communication
technology in their learner of English. The data consists of
observations of both synchronous and asynchronous communication
participants engaged in for over a period of 4 months, which included
online, and offline communication protocols, open-ended interviews
and reflection papers composed by participants.
Content analysis of interview data and the written documents listed
above, as well as, member check and triangulation techniques are the
major data analysis strategies. The findings suggest that participants
generally do not benefit from computer-mediated communication in
terms of its effect in learning a foreign language. Participants regarded
the nature of CMC as artificial, or pseudo communication that did not
aid their authentic communicational skills in English. The results of
this study sheds lights on insufficient and inconclusive findings, which
most quantitative CMC studies previously generated.
Abstract: This paper proposes new enhancement models to the
methods of nonlinear anisotropic diffusion to greatly reduce speckle
and preserve image features in medical ultrasound images. By
incorporating local physical characteristics of the image, in this case
scatterer density, in addition to the gradient, into existing tensorbased
image diffusion methods, we were able to greatly improve the
performance of the existing filtering methods, namely edge
enhancing (EE) and coherence enhancing (CE) diffusion. The new
enhancement methods were tested using various ultrasound images,
including phantom and some clinical images, to determine the
amount of speckle reduction, edge, and coherence enhancements.
Scatterer density weighted nonlinear anisotropic diffusion
(SDWNAD) for ultrasound images consistently outperformed its
traditional tensor-based counterparts that use gradient only to weight
the diffusivity function. SDWNAD is shown to greatly reduce
speckle noise while preserving image features as edges, orientation
coherence, and scatterer density. SDWNAD superior performances
over nonlinear coherent diffusion (NCD), speckle reducing
anisotropic diffusion (SRAD), adaptive weighted median filter
(AWMF), wavelet shrinkage (WS), and wavelet shrinkage with
contrast enhancement (WSCE), make these methods ideal
preprocessing steps for automatic segmentation in ultrasound
imaging.
Abstract: Human skull is shown to exhibit numerous sexually dimorphic traits. Estimation of sex is a challenging task especially when a part of skull is brought for medicolegal investigation. The present research was planned to evaluate the sexing potential of the dimensions of foramen magnum in forensic identification by craniometric analysis. Length and breadth of the foramen magnum was measured using Vernier calipers and the area of foramen magnum was calculated. The length, breadth, and area of foramen magnum were found to be larger in males than females. Sexual dimorphism index was calculated to estimate the sexing potential of each variable. The study observations are suggestive of the limited utility of the craniometric analysis of foramen magnum during the examination of skull and its parts in estimation of sex.
Abstract: Automatic segmentation of skin lesions is the first step
towards the automated analysis of malignant melanoma. Although
numerous segmentation methods have been developed, few studies
have focused on determining the most effective color space for
melanoma application. This paper proposes an automatic segmentation
algorithm based on color space analysis and clustering-based histogram
thresholding, a process which is able to determine the optimal
color channel for detecting the borders in dermoscopy images. The
algorithm is tested on a set of 30 high resolution dermoscopy images.
A comprehensive evaluation of the results is provided, where borders
manually drawn by four dermatologists, are compared to automated
borders detected by the proposed algorithm, applying three previously
used metrics of accuracy, sensitivity, and specificity and a new metric
of similarity. By performing ROC analysis and ranking the metrics,
it is demonstrated that the best results are obtained with the X and
XoYoR color channels, resulting in an accuracy of approximately
97%. The proposed method is also compared with two state-of-theart
skin lesion segmentation methods.
Abstract: A laboratory study on the influence of compactive
effort on expansive black cotton specimens treated with up to 8%
ordinary Portland cement (OPC) admixed with up to 8% bagasse ash
(BA) by dry weight of soil and compacted using the energies of the
standard Proctor (SP), West African Standard (WAS) or
“intermediate” and modified Proctor (MP) were undertaken. The
expansive black cotton soil was classified as A-7-6 (16) or CL using
the American Association of Highway and Transportation Officials
(AASHTO) and Unified Soil Classification System (USCS),
respectively. The 7day unconfined compressive strength (UCS)
values of the natural soil for SP, WAS and MP compactive efforts are
286, 401 and 515kN/m2 respectively, while peak values of 1019,
1328 and 1420kN/m2 recorded at 8% OPC/ 6% BA, 8% OPC/ 2% BA
and 6% OPC/ 4% BA treatments, respectively were less than the
UCS value of 1710kN/m2 conventionally used as criterion for
adequate cement stabilization. The soaked California bearing ratio
(CBR) values of the OPC/BA stabilized soil increased with higher
energy level from 2, 4 and 10% for the natural soil to Peak values of
55, 18 and 8% were recorded at 8% OPC/4% BA 8% OPC/2% BA
and 8% OPC/4% BA, treatments when SP, WAS and MP compactive
effort were used, respectively. The durability of specimens was
determined by immersion in water. Soils treatment at 8% OPC/ 4%
BA blend gave a value of 50% resistance to loss in strength value
which is acceptable because of the harsh test condition of 7 days
soaking period specimens were subjected instead of the 4 days
soaking period that specified a minimum resistance to loss in strength
of 80%. Finally An optimal blend of is 8% OPC/ 4% BA is
recommended for treatment of expansive black cotton soil for use as
a sub-base material.
Abstract: The objective of the paper is to develop the forecast
model for the HW flows. The methodology of the research included
6 modules: historical data, assumptions, choose of indicators, data
processing, and data analysis with STATGRAPHICS, and forecast
models. The proposed methodology was validated for the case study
for Latvia. Hypothesis on the changes in HW for time period of
2010-2020 have been developed and mathematically described with
confidence level of 95.0% and 50.0%. Sensitivity analysis for the
analyzed scenarios was done. The results show that the growth of
GDP affects the total amount of HW in the country. The total amount
of the HW is projected to be within the corridor of – 27.7% in the
optimistic scenario up to +87.8% in the pessimistic scenario with
confidence level of 50.0% for period of 2010-2020. The optimistic
scenario has shown to be the least flexible to the changes in the GDP
growth.
Abstract: The Knowledge Management (KM) Criteria is an
essential foundation to evaluate KM outcomes. Different sets of
criteria were developed and tailored by many researchers to
determine the results of KM initiatives. However, literature review
has emphasized on incomplete set of criteria for evaluating KM
outcomes. Hence, this paper tried to address the problem of
determining the criteria for measuring knowledge management
outcomes among different types of Malaysian organizations.
Successively, this paper was assumed to develop widely accepted
criteria to measure success of knowledge management efforts for
Malaysian organizations. Our analysis approach was based on the
ANOVA procedure to compare a set of criteria among different types
of organizations. This set of criteria was exploited from literature
review. It is hoped that this study provides a better picture for
different types of Malaysian organizations to establish a
comprehensive set of criteria due to measure results of KM programs.
Abstract: The upgrading of low quality crude natural gas (NG) is attracting interest due to high demand of pipeline-grade gas in recent years. Membrane processes are commercially proven technology for the removal of impurities like carbon dioxide from NG. In this work, cross flow mathematical model has been suggested to be incorporated with ASPEN HYSYS as a user defined unit operation in order to design the membrane system for CO2/CH4 separation. The effect of operating conditions (such as feed composition and pressure) and membrane selectivity on the design parameters (methane recovery and total membrane area required for the separation) has been studied for different design configurations. These configurations include single stage (with and without recycle) and double stage membrane systems (with and without permeate or retentate recycle). It is shown that methane recovery can be improved by recycling permeate or retentate stream as well as by using double stage membrane systems. The ASPEN HYSYS user defined unit operation proposed in the study has potential to be applied for complex membrane system design and optimization.
Abstract: Education, as the most important resource in any country, has multiplying effects on all facets of development in a society. The new social realities, particularly the interplay between democratization of education; unprecedented developments in IT sector; emergence of knowledge society, liberalization of economy and globalization have greatly influenced the educational process of all nations. This turbulence entails upon education to undergo dramatic changes to keep up with the new expectations. Growth of entrepreneurship among Indian women is highly important for empowering them and this is highly essential for socio-economic development of a society. Unfortunately in India there is poor acceptance of entrepreneurship among women as unfounded myths and fears restrain them to be enterprising. To remove these inhibitions, education system needs to be re-engineered to make entrepreneurship more acceptable. This paper empirically analyses the results of a survey done on around 500 female graduates in North India to measure and evaluate various entrepreneurial traits present in them. A formative model has been devised in this context, which should improve the teaching-learning process in our education system, which can lead to sustainable growth of women entrepreneurship in India.
Abstract: The growing interest in the issue of intangible assets not only in the scientific community but also in some professional bodies internationally can be explained by several points of view. From the business perspective, enterprises are increasingly motivated by external and internal forces to measure and proactively manage their intangibles. With respect to the issue of intangibles, goodwill has been debated in many countries throughout the world. Despite the numerous efforts and the existence of international accounting standards there is not yet a common accepted accounting treatment for goodwill. This study attempts on the one hand to impress the accounting treatment of goodwill internationally, on the other hand analyses the major subjects in relation to the accounting treatment of goodwill in Greece, since 2005, year where the international accounting standards have been in use for the Greek listed companies. The results indicate that the accounting treatment for the goodwill in Greece, despite the effort for accounting harmonization in Europe from 2005, sustains many differences especially for the no listed companies.
Abstract: This paper focuses on issues of engagement by staff in professional development related to the delivery of e-learning. The paper reports on findings drawn from a New Zealand research project which is producing a sector-wide framework for professional development in tertiary e-learning. The research findings indicate that staff engaged in e-learning in tertiary institutions is not making the most effective use of the professional development opportunities available to them; rather they seem to gain their knowledge and support from a variety of informal means. This is despite an emphasis on the provision of professional development opportunities by both Government Policies and Institutions themselves. The conclusion drawn from the findings is that institutional approaches to professional development for e-learning do not yet fully reflect the demands and constraints that working in a digital context impose.
Abstract: Motion capturing technology has been used for quite a
while and several research has been done within this area. Nevertheless,
we discovered open issues within current motion capturing
environments. In this paper we provide a state-of-the-art overview of
the addressed research areas and show issues with current motion
capturing environments. Observations, interviews and questionnaires
have been used to reveal the challenges actors are currently facing in
a motion capturing environment. Furthermore, the idea to create a
more immersive motion capturing environment to improve the acting
performances and motion capturing outcomes as a potential solution
is introduced. It is hereby the goal to explain the found open issues
and the developed ideas which shall serve for further research as a
basis. Moreover, a methodology to address the interaction and
systems design issues is proposed. A future outcome could be that
motion capture actors are able to perform more naturally, especially
if using a non-body-worn solution.
Abstract: In this study, a Loop Back Algorithm for component
connected labeling for detecting objects in a digital image is
presented. The approach is using loop back connected component
labeling algorithm that helps the system to distinguish the object
detected according to their label. Deferent than whole window
scanning technique, this technique reduces the searching time for
locating the object by focusing on the suspected object based on
certain features defined. In this study, the approach was also
implemented for a face detection system. Face detection system is
becoming interesting research since there are many devices or
systems that require detecting the face for certain purposes. The input
can be from still image or videos, therefore the sub process of this
system has to be simple, efficient and accurate to give a good result.
Abstract: Rapid growth of distance learning resulted in
importance to conduct research on students- satisfaction with distance
learning because differences in students- satisfaction might influence
educational opportunities for learning in a relevant Web-based
environment. In line with this, this paper deals with satisfaction of
students with distance module at Faculty of organizational sciences
(FOS) in Serbia as well as some factors affecting differences in their
satisfaction . We have conducted a research on a population of 68
first-year students of distance learning studies at FOS. Using
statistical techniques, we have found out that there is no significant
difference in students- satisfaction with distance learning module
between men and women. In the same way, we also concluded that
there is a difference in satisfaction with distance learning module
regarding to student-s perception of opportunity to gain knowledge as
the classic students.
Abstract: In the present communication, the existing measures of
fuzzy entropy are reviewed. A generalized parametric exponential
fuzzy entropy is defined.Our study of the four essential and some
other properties of the proposed measure, clearly establishes the
validity of the measure as an entropy.
Abstract: Cloud computing is becoming more and more matured over the last few years and consequently the demands for better cloud services is increasing rapidly. One of the research topics to improve cloud services is the desktop computing in virtualized environment. This paper aims at the development of an adaptive virtual desktop service in cloud computing platform based on our previous research on the virtualization technology. We implement cloud virtual desktop and application software streaming technology that make it possible for providing Virtual Desktop as a Service (VDaaS). Given the development of remote desktop virtualization, it allows shifting the user’s desktop from the traditional PC environment to the cloud-enabled environment, which is stored on a remote virtual machine rather than locally. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for online cloud service. Users no longer need to burden the platform maintenances and drastically reduces the overall cost of hardware and software licenses. Moreover, this flexible remote desktop service represents the next significant step to the mobile workplace, and it lets users access their desktop environments from virtually anywhere.
Abstract: In this paper the problem of face recognition under variable illumination conditions is considered. Most of the works in the literature exhibit good performance under strictly controlled acquisition conditions, but the performance drastically drop when changes in pose and illumination occur, so that recently number of approaches have been proposed to deal with such variability. The aim of this work is to introduce an efficient local appearance feature extraction method based steerable pyramid (SP) for face recognition. Local information is extracted from SP sub-bands using LBP(Local binary Pattern). The underlying statistics allow us to reduce the required amount of data to be stored. The experiments carried out on different face databases confirm the effectiveness of the proposed approach.
Abstract: This paper describes a practical approach to design
and develop a hybrid learning with acceleration feedback control
(HLC) scheme for input tracking and end-point vibration suppression
of flexible manipulator systems. Initially, a collocated proportionalderivative
(PD) control scheme using hub-angle and hub-velocity
feedback is developed for control of rigid-body motion of the system.
This is then extended to incorporate a further hybrid control scheme
of the collocated PD control and iterative learning control with
acceleration feedback using genetic algorithms (GAs) to optimize the
learning parameters. Experimental results of the response of the
manipulator with the control schemes are presented in the time and
frequency domains. The performance of the HLC is assessed in terms
of input tracking, level of vibration reduction at resonance modes and
robustness with various payloads.
Abstract: The most planted cover crops in the Czech Republic
are mustard (Sinapis alba) and phacelia (Phacelia tanacetifolia
Benth.). A field trial was executed to evaluate root system size (RSS)
in eight varieties of mustard and five varieties of phacelia on two
locations, in three BBCH phases and in two years. The relationship
between RSS and aboveground biomass was inquired. The root
system was assessed by measuring its electric capacity. Aboveground
mass and root samples to be evaluated by means of a digital image
analysis were recovered in the BBCH phase 70. The yield of
aboveground biomass of mustard was always statistically
significantly higher than that of phacelia. Mustard showed a
statistically significant negative correlation between root length
density (RLD) within 10 cm and aboveground biomass weight (r = -
0.46*). Phacelia featured a statistically significant correlation
between aboveground biomass production and nitrate nitrogen
content in soil (r=0.782**).
Abstract: The aim of this paper is to rank the impact of Object
Oriented(OO) metrics in fault prediction modeling using Artificial
Neural Networks(ANNs). Past studies on empirical validation of
object oriented metrics as fault predictors using ANNs have focused
on the predictive quality of neural networks versus standard
statistical techniques. In this empirical study we turn our attention to
the capability of ANNs in ranking the impact of these explanatory
metrics on fault proneness. In ANNs data analysis approach, there is
no clear method of ranking the impact of individual metrics. Five
ANN based techniques are studied which rank object oriented
metrics in predicting fault proneness of classes. These techniques are
i) overall connection weights method ii) Garson-s method iii) The
partial derivatives methods iv) The Input Perturb method v) the
classical stepwise methods. We develop and evaluate different
prediction models based on the ranking of the metrics by the
individual techniques. The models based on overall connection
weights and partial derivatives methods have been found to be most
accurate.