Abstract: This paper aims to link together the concepts of job
satisfaction, work engagement, trust, job meaningfulness and loyalty
to the organisation focusing on specific type of employment –
academic jobs. The research investigates the relationships between
job satisfaction, work engagement and loyalty as well as the impact
of trust and job meaningfulness on the work engagement and loyalty.
The survey was conducted in one of the largest Latvian higher
education institutions and the sample was drawn from academic staff
(n=326). Structured questionnaire with 44 reflective type questions
was developed to measure the constructs. Data was analysed using
SPSS and Smart-PLS software. Variance based structural equation
modelling (PLS-SEM) technique was used to test the model and to
predict the most important factors relevant to employee engagement
and loyalty. The first order model included two endogenous
constructs (loyalty and intention to stay and recommend to work in
this organisation, and employee engagement), as well as six
exogenous constructs (feeling of fair treatment and trust in
management; career growth opportunities; compensation, pay and
benefits; management; colleagues and teamwork; and finally job
meaningfulness). Job satisfaction was developed as second order
construct and both: first and second order models were designed for
data analysis. It was found that academics are more engaged than
satisfied with their work and main reason for that was found to be job
meaningfulness, which is significant predictor for work engagement,
but not for job satisfaction. Compensation is not significantly related
to work engagement, but only to job satisfaction. Trust was not
significantly related neither to engagement, nor to satisfaction,
however, it appeared to be significant predictor of loyalty and
intentions to stay with the University. Paper revealed academic jobs
as specific kind of employment where employees can be more
engaged than satisfied and highlighted the specific role of job
meaningfulness in the University settings.
Abstract: We have aimed to produce a self-cleaning transparent
polymer coating with polyurethane (PU) matrix as the latter is highly
solvent, chemical and weather resistant having good mechanical
properties. Nano-silica modified by 1H, 1H, 2H, 2Hperflurooctyltriethoxysilane
was incorporated into the PU matrix for
attaining self-cleaning ability through hydrophobicity. The
modification was confirmed by particle size analysis and scanning
electron microscopy (SEM). Thermo-gravimetric (TGA) studies were
carried to ascertain the grafting of silane onto the silica. Several
coating formulations were prepared by varying the silica loading
content and compared to a commercial equivalent. The effect of
dispersion and the morphology of the coated films were assessed by
SEM analysis. All coating standardized tests like solvent resistance,
adhesion, flexibility, acid, alkali, gloss etc. have been performed as
per ASTM standards. Water contact angle studies were conducted to
analyze the hydrophobic character of the coating. In addition, the
coatings were also subjected to salt spray and accelerated weather
testing to analyze the durability of the coating.
Abstract: Fractal based digital image compression is a specific
technique in the field of color image. The method is best suited for
irregular shape of image like snow bobs, clouds, flame of fire; tree
leaves images, depending on the fact that parts of an image often
resemble with other parts of the same image. This technique has
drawn much attention in recent years because of very high
compression ratio that can be achieved. Hybrid scheme incorporating
fractal compression and speedup techniques have achieved high
compression ratio compared to pure fractal compression. Fractal
image compression is a lossy compression method in which selfsimilarity
nature of an image is used. This technique provides high
compression ratio, less encoding time and fart decoding process. In
this paper, fractal compression with quad tree and DCT is proposed
to compress the color image. The proposed hybrid schemes require
four phases to compress the color image. First: the image is
segmented and Discrete Cosine Transform is applied to each block of
the segmented image. Second: the block values are scanned in a
zigzag manner to prevent zero co-efficient. Third: the resulting image
is partitioned as fractals by quadtree approach. Fourth: the image is
compressed using Run length encoding technique.
Abstract: Myoelectric control system is the fundamental
component of modern prostheses, which uses the myoelectric signals
from an individual’s muscles to control the prosthesis movements.
The surface electromyogram signal (sEMG) being noninvasive has
been used as an input to prostheses controllers for many years.
Recent technological advances has led to the development of
implantable myoelectric sensors which enable the internal
myoelectric signal (MES) to be used as input to these prostheses
controllers. The intramuscular measurement can provide focal
recordings from deep muscles of the forearm and independent signals
relatively free of crosstalk thus allowing for more independent
control sites. However, little work has been done to compare the two
inputs. In this paper we have compared the classification accuracy of
six pattern recognition based myoelectric controllers which use
surface myoelectric signals recorded using untargeted (symmetric)
surface electrode arrays to the same controllers with multichannel
intramuscular myolectric signals from targeted intramuscular
electrodes as inputs. There was no significant enhancement in the
classification accuracy as a result of using the intramuscular EMG
measurement technique when compared to the results acquired using
the surface EMG measurement technique. Impressive classification
accuracy (99%) could be achieved by optimally selecting only five
channels of surface EMG.
Abstract: The purpose of the research described in this work is
to answer how to measure the rheologic (viscoelastic) properties
tendo–deformational characteristics of soft tissue. The method would
also resemble muscle palpation examination as it is known in clinical
practice. For this purpose, an instrument with the working name
“myotonometer” has been used. At present, there is lack of objective methods for assessing the
muscle tone by viscous and elastic properties of soft tissue. That is
why we decided to focus on creating or finding quantitative and
qualitative methodology capable to specify muscle tone.
Abstract: This paper presents a fault-tolerant implementation for
adder schemes using the dual duplication code. To prove the
efficiency of the proposed method, the circuit is simulated in double
pass transistor CMOS 32nm technology and some transient faults are
voluntary injected in the Layout of the circuit. This fully differential
implementation requires only 20 transistors which mean that the
proposed design involves 28.57% saving in transistor count
compared to standard CMOS technology.
Abstract: Energy has a prominent role for development of
nations. Countries which have energy resources also have strategic
power in the international trade of energy since it is essential for all
stages of production in the economy. Thus, it is important for
countries to analyze the weaknesses and strength of the system. On
the other side, international trade is one of the fields that are analyzed
as a complex network via network analysis. Complex network is one
of the tools to analyze complex systems with heterogeneous agents
and interaction between them. A complex network consists of nodes
and the interactions between these nodes. Total properties which
emerge as a result of these interactions are distinct from the sum of
small parts (more or less) in complex systems. Thus, standard
approaches to international trade are superficial to analyze these
systems. Network analysis provides a new approach to analyze
international trade as a network. In this network, countries constitute
nodes and trade relations (export or import) constitute edges. It
becomes possible to analyze international trade network in terms of
high degree indicators which are specific to complex networks such
as connectivity, clustering, assortativity/disassortativity, centrality,
etc. In this analysis, international trade of crude oil and coal which
are types of fossil fuel has been analyzed from 2005 to 2014 via
network analysis. First, it has been analyzed in terms of some
topological parameters such as density, transitivity, clustering etc.
Afterwards, fitness to Pareto distribution has been analyzed via
Kolmogorov-Smirnov test. Finally, weighted HITS algorithm has
been applied to the data as a centrality measure to determine the real
prominence of countries in these trade networks. Weighted HITS
algorithm is a strong tool to analyze the network by ranking countries
with regards to prominence of their trade partners. We have
calculated both an export centrality and an import centrality by
applying w-HITS algorithm to the data. As a result, impacts of the
trading countries have been presented in terms of high-degree
indicators.
Abstract: In order to retrieve images efficiently from a large
database, a unique method integrating color and texture features
using genetic programming has been proposed. Opponent color
histogram which gives shadow, shade, and light intensity invariant
property is employed in the proposed framework for extracting color
features. For texture feature extraction, fast discrete curvelet
transform which captures more orientation information at different
scales is incorporated to represent curved like edges. The recent
scenario in the issues of image retrieval is to reduce the semantic gap
between user’s preference and low level features. To address this
concern, genetic algorithm combined with relevance feedback is
embedded to reduce semantic gap and retrieve user’s preference
images. Extensive and comparative experiments have been conducted
to evaluate proposed framework for content based image retrieval on
two databases, i.e., COIL-100 and Corel-1000. Experimental results
clearly show that the proposed system surpassed other existing
systems in terms of precision and recall. The proposed work achieves
highest performance with average precision of 88.2% on COIL-100
and 76.3% on Corel, the average recall of 69.9% on COIL and 76.3%
on Corel. Thus, the experimental results confirm that the proposed
content based image retrieval system architecture attains better
solution for image retrieval.
Abstract: Scripts are one of the basic text resources to understand
broadcasting contents. Topic modeling is the method to get the
summary of the broadcasting contents from its scripts. Generally,
scripts represent contents descriptively with directions and speeches,
and provide scene segments that can be seen as semantic units.
Therefore, a script can be topic modeled by treating a scene segment
as a document. Because scene segments consist of speeches mainly,
however, relatively small co-occurrences among words in the scene
segments are observed. This causes inevitably the bad quality of
topics by statistical learning method. To tackle this problem, we
propose a method to improve topic quality with additional word
co-occurrence information obtained using scene similarities. The
main idea of improving topic quality is that the information that
two or more texts are topically related can be useful to learn high
quality of topics. In addition, more accurate topical representations
lead to get information more accurate whether two texts are related
or not. In this paper, we regard two scene segments are related
if their topical similarity is high enough. We also consider that
words are co-occurred if they are in topically related scene segments
together. By iteratively inferring topics and determining semantically
neighborhood scene segments, we draw a topic space represents
broadcasting contents well. In the experiments, we showed the
proposed method generates a higher quality of topics from Korean
drama scripts than the baselines.
Abstract: This work aims to investigate the structure–property
relationship in ternary nanocomposites consisting of polypropylene
as the matrix, polyamide 66 as the minor phase and treated nanoclay
DELLITE 67G as the reinforcement. All PP/PA66/Nanoclay systems
with polypropylene grafted maleic anhydride PP-g-MAH as a
compatibilizer were prepared via melt compounding and
characterized in terms of nanoclay content. Morphological structure
was investigated by scanning electron microscopy. The rheological
behavior of the nanocomposites was determined by various methods,
viz melt flow index (MFI) and parallel plate rheological
measurements. The PP/PP-g-MAH/PA66 nanocomposites showed a homogeneous
morphology supporting the compatibility improvement between PP,
PA66, and nanoclay. SEM results revealed the formation of
nanocomposites as the nanoclay was intercalated and exfoliated. In
the ternary nanocomposites, the rheological behavior showed that, the
complex viscosity is increased with increasing the nanoclay. The results showed that the use of nanoclay affects the variations
of storage modulus (G′), loss modulus (G″) and the melt elasticity.
Abstract: This paper presents the effects of mixing procedures
on mechanical properties of flyash-based geopolymer matrices
containing nanosilica (NS) at 0.5%, 1.0%, 2.0%, and 3.0% by weight.
Comparison is made with conventional mechanical dry-mixing of NS
with flyash and wet-mixing of NS in alkaline solutions. Physical and
mechanical properties are investigated using X-Ray Diffraction
(XRD) and Scanning Electron Microscope (SEM). Results show that
generally the addition of NS particles enhanced the microstructure
and improved flexural and compressive strengths of geopolymer
nanocomposites. However, samples, prepared using dry-mixing
approach, demonstrate better physical and mechanical properties
comparing to wet-mixing samples.
Abstract: Advances in spatial and spectral resolution of satellite
images have led to tremendous growth in large image databases. The
data we acquire through satellites, radars, and sensors consists of
important geographical information that can be used for remote
sensing applications such as region planning, disaster management.
Spatial data classification and object recognition are important tasks
for many applications. However, classifying objects and identifying
them manually from images is a difficult task. Object recognition is
often considered as a classification problem, this task can be
performed using machine-learning techniques. Despite of many
machine-learning algorithms, the classification is done using
supervised classifiers such as Support Vector Machines (SVM) as the
area of interest is known. We proposed a classification method,
which considers neighboring pixels in a region for feature extraction
and it evaluates classifications precisely according to neighboring
classes for semantic interpretation of region of interest (ROI). A
dataset has been created for training and testing purpose; we
generated the attributes by considering pixel intensity values and
mean values of reflectance. We demonstrated the benefits of using
knowledge discovery and data-mining techniques, which can be on
image data for accurate information extraction and classification from
high spatial resolution remote sensing imagery.
Abstract: This research work is an experimental study, through
development of an adhesive from Prosopis africana endosperm. The
prosopis seed for this work were obtained from Enugu State in the
South East part of Nigeria. The seeds were prepared by separating the
endosperm from the seed coat and cotyledon. Three methods were
used to separate them, which are acidic method, roasting method and
boiling method. 20g of seed were treated with different
concentrations (25, 40, 55, 70, and 85% w/w) at 100°C and constant
time (30 minutes), under continuous stirring with magnetic stirrer.
Also 20g of seed were treated with sulphuric acid of concentrations
40% w/w at 100°C with different time (10, 15, 20, 25, 30 minutes),
under continuous stirring with magnetic stirrer. Finally, 20g of seed
were treated with sulphuric acid of concentrations 40% w/w at
different temperature (20°C, 40°C, 60°C, 80°C, and 100°C) with
constant time (30 minutes), under continuous stirring with magnetic
stirrer. The whole endosperm extracted was adhesive. The physical
properties of the adhesive were determined (appearance, odour, taste,
solubility, pH, size, and binding strength). The percentage of the
adhesive yield makes the commercialization of the seed in Nigeria
possible and profitable. The very high viscosity attained at low
concentrations makes prosopis adhesive an excellent thickener in the
food industry.
Abstract: Manufacturing process has been considered as one of
the most important activity in business process. It correlates with
productivity and quality of the product so industries could fulfill
customer’s demand. With the increasing demand from customer,
industries must improve their manufacturing ability such as shorten
lead-time and reduce wastes on their process. Lean manufacturing
has been considered as one of the tools to waste elimination in
manufacturing or service industry. Workforce development is one
practice in lean manufacturing that can reduce waste generated from
operator such as waste of unnecessary motion. Anthropometric
approach is proposed to determine the recommended measurement in
operator’s work area. The method will get some dimensions from
Indonesia people that related to piston workstation. The result from
this research can be obtained new design for the work area
considering ergonomic aspect.
Abstract: This study evaluated to facilitate separation of ABS
plastics from other waste plastics by froth flotation after surface
hydrophilization of ABS with heat treatment. The mild heat treatment
at 100oC for 60s could selectively increase the hydrophilicity of the
ABS plastics surface (i.e., ABS contact angle decreased from 79o to
65.8o) among other plastics mixture. The SEM and XPS results of
plastic samples sufficiently supported the increase in hydrophilic
functional groups and decrease contact angle on ABS surface, after
heat treatment. As a result of the froth flotation (at mixing speed 150
rpm and airflow rate 0.3 L/min) after heat treatment, about 85% of
ABS was selectively separated from other heavy plastics with 100%
of purity. The effect of optimum treatment condition and detailed
mechanism onto separation efficiency in the froth floatation was also
investigated. This research is successful in giving a simple, effective,
and inexpensive method for ABS separation from waste plastics.
Abstract: Cadmium oxide (CdO) nanoparticles have been
prepared by chemical coprecipitation method. The synthesized
nanoparticles were characterized by X-ray diffraction analysis
(XRD), scanning electron microscopy (SEM), transmission electron
microscopy (TEM), UV analysis, and dielectric studies. The
crystalline nature and particle size of the CdO nanoparticles were
characterized by Powder X-ray diffraction analysis (XRD). The
morphology of prepared CdO nanoparticles was studied by scanning
electron microscopy. The particle size was studied using the
transmission electron microscopy (TEM).The optical properties were
obtained from UV-Vis absorption spectrum. The dielectric properties
of CdO nanoparticles were studied in the frequency range of 50 Hz–5
MHz at different temperatures. The frequency dependence of the
dielectric constant and dielectric loss is found to decrease with an
increase in the frequency at different temperatures. The ac
conductivity of CdO nanoparticle has been studied.
Abstract: This article discusses the passage of RDB to XML
documents (schema and data) based on metadata and semantic
enrichment, which makes the RDB under flattened shape and is
enriched by the object concept. The integration and exploitation of
the object concept in the XML uses a syntax allowing for the
verification of the conformity of the document XML during the
creation. The information extracted from the RDB is therefore
analyzed and filtered in order to adjust according to the structure of
the XML files and the associated object model. Those implemented
in the XML document through a SQL query are built dynamically. A
prototype was implemented to realize automatic migration, and so
proves the effectiveness of this particular approach.
Abstract: Social networking sites such as Twitter and Facebook
attracts over 500 million users across the world, for those users, their
social life, even their practical life, has become interrelated. Their
interaction with social networking has affected their life forever.
Accordingly, social networking sites have become among the main
channels that are responsible for vast dissemination of different kinds
of information during real time events. This popularity in Social
networking has led to different problems including the possibility of
exposing incorrect information to their users through fake accounts
which results to the spread of malicious content during life events.
This situation can result to a huge damage in the real world to the
society in general including citizens, business entities, and others. In this paper, we present a classification method for detecting the
fake accounts on Twitter. The study determines the minimized set of
the main factors that influence the detection of the fake accounts on
Twitter, and then the determined factors are applied using different
classification techniques. A comparison of the results of these
techniques has been performed and the most accurate algorithm is
selected according to the accuracy of the results. The study has been
compared with different recent researches in the same area; this
comparison has proved the accuracy of the proposed study. We claim
that this study can be continuously applied on Twitter social network
to automatically detect the fake accounts; moreover, the study can be
applied on different social network sites such as Facebook with minor
changes according to the nature of the social network which are
discussed in this paper.
Abstract: Highly stable and homogeneously dispersed amino
acid coated silver nanoparticles (ANP) of ≈ 10 nm diameter, ranging
from 420 to 430 nm are prepared on AgNO3 solution addition to gum
of Azadirachta indica solution at 373.15 K. The amino acids were
selected based on their polarity. The synthesized nanoparticles were
characterized by UV-Vis, FTIR spectroscopy, HR-TEM, XRD, SEM
and 1H-NMR. The coated nanoparticles were used as catalyst for the
reduction of methylene blue dye in presence of Sn(II) in aqueous,
anionic and cationic micellar media. The rate of reduction of dye was
determined by measuring the absorbance at 660 nm,
spectrophotometrically and followed the order: Kcationic > Kanionic >
Kwater. After 12 min and in absence of the ANP, only 2%, 3% and 6%
of the dye reduction was completed in aqueous, anionic and cationic
micellar media respectively while, in presence of ANP coated by
polar neutral amino acid with non-polar -R group, the reduction
completed to 84%, 95% and 98% respectively. The ANP coated with
polar neutral amino acid having non-polar -R group, increased the
rate of reduction of the dye by 94, 3205 and 6370 folds in aqueous,
anionic and cationic micellar media respectively. Also, the rate of
reduction of the dye increased by three folds when the micellar media
was changed from anionic to cationic when the ANP is coated by a
polar neutral amino acid having a non-polar -R group.
Abstract: Bezier curves have useful properties for path
generation problem, for instance, it can generate the reference
trajectory for vehicles to satisfy the path constraints. Both algorithms
join cubic Bezier curve segment smoothly to generate the path. Some
of the useful properties of Bezier are curvature. In mathematics,
curvature is the amount by which a geometric object deviates from
being flat, or straight in the case of a line. Another extrinsic example
of curvature is a circle, where the curvature is equal to the reciprocal
of its radius at any point on the circle. The smaller the radius, the
higher the curvature thus the vehicle needs to bend sharply. In this
study, we use Bezier curve to fit highway-like curve. We use
different approach to find the best approximation for the curve so that
it will resembles highway-like curve. We compute curvature value by
analytical differentiation of the Bezier Curve. We will then compute
the maximum speed for driving using the curvature information
obtained. Our research works on some assumptions; first, the Bezier
curve estimates the real shape of the curve which can be verified
visually. Even though, fitting process of Bezier curve does not
interpolate exactly on the curve of interest, we believe that the
estimation of speed are acceptable. We verified our result with the
manual calculation of the curvature from the map.