Abstract: The main aim of the current study was to examine the
effect of emotional intelligence on retention. The study also aimed at
analyzing the role of job involvement, as a moderator, in the effect of
emotional intelligence on retention. Using data gathered from 241
employees working with hotels and tourism corporations listed in
Amman Stock Exchange in Jordan, emotional intelligence, job
involvement and retention were measured. Hierarchical regression
analyses were used to test the three main hypotheses. Results
indicated that retention was related to emotional intelligence.
Moreover, the study yielded support for the claim that job
involvement had a moderating effect on the relationship between
emotional intelligence and retention.
Abstract: Chlorine is one of the most abundant elements in
nature, which undergoes a complex biogeochemical cycle. Chlorine
bound in some substances is partly responsible for atmospheric ozone
depletion and contamination of some ecosystems. As due to
international regulations anthropogenic burden of volatile
organochlorines (VOCls) in atmosphere decreases, natural sources
(plants, soil, abiotic formation) are expected to dominate VOCl
production in the near future. Examples of plant VOCl production are
methyl chloride, and bromide emission from (sub)tropical ferns,
chloroform, 1,1,1-trichloroethane and tetrachloromethane emission
from temperate forest fern and moss. Temperate forests are found to
emit in addition to the previous compounds tetrachloroethene, and
brominated volatile compounds. VOCls can be taken up and further
metabolized in plants. The aim of this work is to identify and
quantitatively analyze the formed VOCls in temperate forest
ecosystems by a cryofocusing/GC-ECD detection method, hence
filling a gap of knowledge in the biogeochemical cycle of chlorine.
Abstract: Mobile IP has been developed to provide the
continuous information network access to mobile users. In IP-based
mobile networks, location management is an important component of
mobility management. This management enables the system to track
the location of mobile node between consecutive communications. It
includes two important tasks- location update and call delivery.
Location update is associated with signaling load. Frequent updates
lead to degradation in the overall performance of the network and the
underutilization of the resources. It is, therefore, required to devise
the mechanism to minimize the update rate. Mobile IPv6 (MIPv6)
and Hierarchical MIPv6 (HMIPv6) have been the potential
candidates for deployments in mobile IP networks for mobility
management. HMIPv6 through studies has been shown with better
performance as compared to MIPv6. It reduces the signaling
overhead traffic by making registration process local. In this paper,
we present performance analysis of MIPv6 and HMIPv6 using an
analytical model. Location update cost function is formulated based
on fluid flow mobility model. The impact of cell residence time, cell
residence probability and user-s mobility is investigated. Numerical
results are obtained and presented in graphical form. It is shown that
HMIPv6 outperforms MIPv6 for high mobility users only and for low
mobility users; performance of both the schemes is almost equivalent
to each other.
Abstract: The one-class support vector machine “support vector
data description” (SVDD) is an ideal approach for anomaly or outlier
detection. However, for the applicability of SVDD in real-world
applications, the ease of use is crucial. The results of SVDD are
massively determined by the choice of the regularisation parameter C
and the kernel parameter of the widely used RBF kernel. While for
two-class SVMs the parameters can be tuned using cross-validation
based on the confusion matrix, for a one-class SVM this is not
possible, because only true positives and false negatives can occur
during training. This paper proposes an approach to find the optimal
set of parameters for SVDD solely based on a training set from
one class and without any user parameterisation. Results on artificial
and real data sets are presented, underpinning the usefulness of the
approach.
Abstract: Injection molding is a very complicated process to
monitor and control. With its high complexity and many process
parameters, the optimization of these systems is a very challenging
problem. To meet the requirements and costs demanded by the
market, there has been an intense development and research with the
aim to maintain the process under control. This paper outlines the
latest advances in necessary algorithms for plastic injection process
and monitoring, and also a flexible data acquisition system that
allows rapid implementation of complex algorithms to assess their
correct performance and can be integrated in the quality control
process. This is the main topic of this paper. Finally, to demonstrate
the performance achieved by this combination, a real case of use is
presented.
Abstract: Due to today-s fierce competition, companies have to
be proactive creators of the future by effectively developing
innovations. Especially radical innovations allow high profit margins
– but they also entail high risks. One possibility to realize radical
innovations and reduce the risk of failure is cross-industry innovation
(CII). CII brings together problems and solution ideas from different
industries. However, there is a lack of systematic ways towards CII.
Bridging this gap, the present paper provides a systematic approach
towards planned CII. Starting with the analysis of potentials, the
definition of promising search strategies is crucial. Subsequently,
identified solution ideas need to be assessed. For the most promising
ones, the adaption process has to be systematically planned –
regarding the risk affinity of a company. The introduced method is
explained on a project from the furniture industry.
Abstract: Small cracks or chips of a product appear very
frequently in the course of continuous production of an automatic
press process system. These phenomena become the cause of not only
defective product but also damage of a press mold. In order to solve
this problem AE system was introduced. AE system was expected to
be very effective to real time detection of the defective product and to
prevention of the damage of the press molds.
In this study, for pick and analysis of AE signals generated from the
press process, AE sensors/pre-amplifier/analysis and processing board
were used as frequently found in the other similar cases. For analysis
and processing the AE signals picked in real time from the good or bad
products, specialized software called cdm8 was used. As a result of
this work it was conformed that intensity and shape of the various AE
signals differ depending on the weight and thickness of metal sheet
and process type.
Abstract: Much research into handwritten Thai character
recognition have been proposed, such as comparing heads of
characters, Fuzzy logic and structure trees, etc. This paper presents a
system of handwritten Thai character recognition, which is based on
the Ant-minor algorithm (data mining based on Ant colony
optimization). Zoning is initially used to determine each character.
Then three distinct features (also called attributes) of each character
in each zone are extracted. The attributes are Head zone, End point,
and Feature code. All attributes are used for construct the
classification rules by an Ant-miner algorithm in order to classify
112 Thai characters. For this experiment, the Ant-miner algorithm is
adapted, with a small change to increase the recognition rate. The
result of this experiment is a 97% recognition rate of the training set
(11200 characters) and 82.7% recognition rate of unseen data test
(22400 characters).
Abstract: Champs Bourcin black grape originated from
Aquitaine, France and planted in Sapa, Lao cai provice, exhibited
high total acidity (11.72 g/L). After 9 days of alcoholic fermentation
at 25oC using Saccharomyces cerevisiae UP3OY5 strain, the ethanol
concentration of wine was 11.5% v/v, however the sharp sour taste of
wine has been found. The malolactic fermentation (MLF) was carried
out by Oenococcus oeni ATCCBAA-1163 strain which had been preadapted
to acid (pH 3-4) and ethanol (8-12%v/v) conditions. We
obtained the highest vivability (83.2%) upon malolactic fermentation
after 5 days at 22oC with early stationary phase O. oeni cells preadapted
to pH 3.5 and 8% v/v ethanol in MRS medium. The malic
acid content in wine was decreased from 5.82 g/L to 0.02 g/L after
MLF (21 days at 22oC). The sensory quality of wine was
significantly improved.
Abstract: In this paper, the details of an experimental method to measure the clamping force value at bolted connections due to application of wrenching torque to tighten the nut have been presented. A simplified bolted joint including a holed plate with a single bolt was considered to carry out the experiments. This method was designed based on Hooke-s law by measuring compressive axial strain of a steel bush placed between the nut and the plate. In the experimental procedure, the values of clamping force were calculated for seven different levels of applied torque, and this process was repeated three times for each level of the torque. Moreover, the effect of lubrication of threads on the clamping value was studied using the same method. In both conditions (dry and lubricated threads), relation between the torque and the clamping force have been displayed in graphs.
Abstract: The authors report a case of swine urolithiasis caused
by improper administration of sulfamonomethoxine and which was
diagnosed by examination of urinary sediments and analyzing the
composition of the uroliths. The chemical composition of urinary
calculi obtained from affected pigs with urolithiasis was further
confimed as sulfamonomethoxine by fourier transform infrared
(FTIR). It is suggested that appearance of typical fanlike or wheat
bunchy crystals in urinary sediments under observation of lightmicroscope
and determination by FTIR for the crystals are helpful in
diagnosing sulfa calculi causced swine urolithiasis.
Abstract: The aim of this in vitro study was to evaluate the possible interference of a Nectandra membranacea extract (i) on the labeling of blood cells (BC), (ii) on the labeling process of BC and plasma (P) proteins with technetium-99m (Tc-99m) and (iii) on the morphology of red blood cells (RBC). Blood samples were incubated with a Nectandra membranacea crude extract, stannous chloride, Tc- 99m (sodium pertechnetate) was added, and soluble (SF) and insoluble (IF) fractions were isolated. Morphometry studies were performed with blood samples incubated with Nectandra membranacea extract. The results show that the Nectandra membranacea extract does not promote significant alteration of the labeling of BC, IF-P and IF-BC. The Nectandra membranacea extract was able to alter the erythrocyte membrane morphology, but these morphological changes were not capable to interfere on the labeling of blood constituents with Tc-99m.
Abstract: A novel PDE solver using the multidimensional wave
digital filtering (MDWDF) technique to achieve the solution of a 2D
seismic wave system is presented. In essence, the continuous physical
system served by a linear Kirchhoff circuit is transformed to an
equivalent discrete dynamic system implemented by a MD wave
digital filtering (MDWDF) circuit. This amounts to numerically
approximating the differential equations used to describe elements of a
MD passive electronic circuit by a grid-based difference equations
implemented by the so-called state quantities within the passive
MDWDF circuit. So the digital model can track the wave field on a
dense 3D grid of points. Details about how to transform the continuous
system into a desired discrete passive system are addressed. In
addition, initial and boundary conditions are properly embedded into
the MDWDF circuit in terms of state quantities. Graphic results have
clearly demonstrated some physical effects of seismic wave (P-wave
and S–wave) propagation including radiation, reflection, and
refraction from and across the hard boundaries. Comparison between
the MDWDF technique and the finite difference time domain (FDTD)
approach is also made in terms of the computational efficiency.
Abstract: Bovine viral diarrhea virus (BVDV) can cause lifelong
persistent infection. One reason for the phenomena is attributed to
BVDV infection to placenta tissue. However the mechanisms that
BVDV invades into placenta tissue remain unclear. To clarify the
molecular mechanisms, we investigated the possible means that
BVDV entered into bovine trophoblast cells (TPC). Yeast two-hybrid
system was used to identify proteins extracted from TPC, which
interact with BVDV envelope glycoprotein E2. A PGbkt7-E2 yeast
expression vector and TPC cDNA library were constructed. Through
two rounds of screening, three positive clones were identified.
Sequencing analysis indicated that all the three positive clones
encoded the same protein clathrin. Physical interaction between
clathrin and BVDV E2 protein was further confirmed by
coimmunoprecipitation experiments. This result suggested that the
clathrin might play a critical role in the process of BVDV entry into
placenta tissue and might be a novel antiviral target for preventing
BVDV infection.
Abstract: The new framework the Higher Education is
immersed in involves a complete change in the way lecturers must
teach and students must learn. Whereas the lecturer was the main
character in traditional education, the essential goal now is to
increase the students' participation in the process. Thus, one of the
main tasks of lecturers in this new context is to design activities of
different nature in order to encourage such participation. Seminars
are one of the activities included in this environment. They are active
sessions that enable going in depth into specific topics as support of
other activities. They are characterized by some features such as
favoring interaction between students and lecturers or improving
their communication skills. Hence, planning and organizing strategic
seminars is indeed a great challenge for lecturers with the aim of
acquiring knowledge and abilities. This paper proposes a method
using Artificial Intelligence techniques to obtain student profiles
from their marks and preferences. The goal of building such profiles
is twofold. First, it facilitates the task of splitting the students into
different groups, each group with similar preferences and learning
difficulties. Second, it makes it easy to select adequate topics to be a
candidate for the seminars. The results obtained can be either a
guarantee of what the lecturers could observe during the development
of the course or a clue to reconsider new methodological strategies in
certain topics.
Abstract: The performance of adaptive beamforming degrades
substantially in the presence of steering vector mismatches. This
degradation is especially severe in the near-field, for the
3-dimensional source location is more difficult to estimate than the
2-dimensional direction of arrival in far-field cases. As a solution, a
novel approach of near-field robust adaptive beamforming (RABF) is
proposed in this paper. It is a natural extension of the traditional
far-field RABF and belongs to the class of diagonal loading
approaches, with the loading level determined based on worst-case
performance optimization. However, different from the methods
solving the optimal loading by iteration, it suggests here a simple
closed-form solution after some approximations, and consequently,
the optimal weight vector can be expressed in a closed form. Besides
simplicity and low computational cost, the proposed approach reveals
how different factors affect the optimal loading as well as the weight
vector. Its excellent performance in the near-field is confirmed via a
number of numerical examples.
Abstract: Long term rainfall analysis and prediction is a
challenging task especially in the modern world where the impact of
global warming is creating complications in environmental issues.
These factors which are data intensive require high performance
computational modeling for accurate prediction. This research paper
describes a prototype which is designed and developed on grid
environment using a number of coupled software infrastructural
building blocks. This grid enabled system provides the demanding
computational power, efficiency, resources, user-friendly interface,
secured job submission and high throughput. The results obtained
using sequential execution and grid enabled execution shows that
computational performance has enhanced among 36% to 75%, for
decade of climate parameters. Large variation in performance can be
attributed to varying degree of computational resources available for
job execution.
Grid Computing enables the dynamic runtime selection, sharing
and aggregation of distributed and autonomous resources which plays
an important role not only in business, but also in scientific
implications and social surroundings. This research paper attempts to
explore the grid enabled computing capabilities on weather indices
from HOAPS data for climate impact modeling and change
detection.
Abstract: An end-member selection method for spectral unmixing that is based on Particle Swarm Optimization (PSO) is developed in this paper. The algorithm uses the K-means clustering algorithm and a method of dynamic selection of end-members subsets to find the appropriate set of end-members for a given set of multispectral images. The proposed algorithm has been successfully applied to test image sets from various platforms such as LANDSAT 5 MSS and NOAA's AVHRR. The experimental results of the proposed algorithm are encouraging. The influence of different values of the algorithm control parameters on performance is studied. Furthermore, the performance of different versions of PSO is also investigated.
Abstract: Enzymatic saccharification of biomass for reducing
sugar production is one of the crucial processes in biofuel production
through biochemical conversion. In this study, enzymatic
saccharification of dilute potassium hydroxide (KOH) pre-treated
Tetraselmis suecica biomass was carried out by using cellulase
enzyme obtained from Trichoderma longibrachiatum. Initially, the
pre-treatment conditions were optimised by changing alkali reagent
concentration, retention time for reaction, and temperature. The T.
suecica biomass after pre-treatment was also characterized using
Fourier Transform Infrared Spectra and Scanning Electron
Microscope. These analyses revealed that the functional group such
as acetyl and hydroxyl groups, structure and surface of T. suecica
biomass were changed through pre-treatment, which is favourable for
enzymatic saccharification process. Comparison of enzymatic
saccharification of untreated and pre-treated microalgal biomass
indicated that higher level of reducing sugar can be obtained from
pre-treated T. suecica. Enzymatic saccharification of pre-treated T.
suecica biomass was optimised by changing temperature, pH, and
enzyme concentration to solid ratio ([E]/[S]). Highest conversion of
carbohydrate into reducing sugar of 95% amounted to reducing sugar
yield of 20 (wt%) from pre-treated T. suecica was obtained from
saccharification, at temperature: 40°C, pH: 4.5 and [E]/[S] of 0.1
after 72 h of incubation. Hydrolysate obtained from enzymatic
saccharification of pretreated T. suecica biomass was further
fermented into biobutanol using Clostridium saccharoperbutyliticum
as biocatalyst. The results from this study demonstrate a positive
prospect of application of dilute alkaline pre-treatment to enhance
enzymatic saccharification and biobutanol production from
microalgal biomass.
Abstract: The Mobile Ad-hoc Network (MANET) is a collection of self-configuring and rapidly deployed mobile nodes (routers) without any central infrastructure. Routing is one of the potential issues. Many routing protocols are reported but it is difficult to decide which one is best in all scenarios. In this paper on demand routing protocols DSR and DYMO based on IEEE 802.11 DCF MAC protocol are examined and characteristic summary of these routing protocols is presented. Their performance is analyzed and compared on performance measuring metrics throughput, dropped packets due to non availability of routes, duplicate RREQ generated for route discovery and normalized routing load by varying CBR data traffic load using QualNet 5.0.2 network simulator.