Abstract: Due to the increasing efforts on saving our natural
environment a change in the structure of energy resources can be
observed - an increasing fraction of a renewable energy sources.
In many countries traditional underground coal mining loses its
significance but there are still countries, like Poland or Germany, in
which the coal based technologies have the greatest fraction in a total
energy production. This necessitates to make an effort to limit the
costs and negative effects of underground coal mining. The longwall
complex is as essential part of the underground coal mining. The
safety and the effectiveness of the work is strongly dependent of the
diagnostic state of powered roof supports.
The building of a useful and reliable diagnostic system requires
a lot of data. As the acquisition of a data of any possible operating
conditions it is important to have a possibility to generate a demanded
artificial working characteristics. In this paper a new approach of
modelling a leg pressure in the single unit of powered roof support.
The model is a result of the analysis of a typical working cycles.
Abstract: The grain quality of chickpea in Iran is low and
instable, which may be attributed to the evolution of cultivars with a
narrow genetic base making them vulnerable to biotic stresses. Four
chickpea varieties from diverse geographic origins were chosen and
arranged in a randomized complete block design. Mesorhizobium sp.
cicer strain SW7 was added to all the chickpea seeds. Chickpea seeds
were planted on October 9, 2013. Each genotype was sown 5 m in
length, with 35 cm inter-row spacing, in 3 rows. Weeds were
removed manually in all plots. Results showed that Analysis of
variance on the studied traits showed significant differences among
genotypes for N, P, K and Fe contents of chickpea, but there is not a
significant difference among Ca, Zn and Mg continents of chickpea.
The experimental coefficient of variation (CV) varied from 7.3 to
15.8. In general, the CV value lower than 20% is considered to be
good, indicating the accuracy of conducted experiments. The highest
grain N was observed in Hashem and Jam cultivars. The highest grain
P was observed in Jam cultivar. Phosphorus content (mg/100g)
ranged from 142.3 to 302.3 with a mean value of 221.3. The negative
correlation (-0.126) was observed between the N and P of chickpea
cultivars. The highest K and Fe contents were observed in Jam
cultivar.
Abstract: A simple adaptive voice activity detector (VAD) is
implemented using Gabor and gammatone atomic decomposition of
speech for high Gaussian noise environments. Matching pursuit is
used for atomic decomposition, and is shown to achieve optimal
speech detection capability at high data compression rates for low
signal to noise ratios. The most active dictionary elements found by
matching pursuit are used for the signal reconstruction so that the
algorithm adapts to the individual speakers dominant time-frequency
characteristics. Speech has a high peak to average ratio enabling
matching pursuit greedy heuristic of highest inner products to isolate
high energy speech components in high noise environments. Gabor
and gammatone atoms are both investigated with identical
logarithmically spaced center frequencies, and similar bandwidths.
The algorithm performs equally well for both Gabor and gammatone
atoms with no significant statistical differences. The algorithm
achieves 70% accuracy at a 0 dB SNR, 90% accuracy at a 5 dB SNR
and 98% accuracy at a 20dB SNR using 30d B SNR as a reference
for voice activity.
Abstract: The objectives of this study are to study Chinese
tourist’s Behaviors towards travel and shopping in Bangkok. The
research methodology was a quantitative research. The sample of this
research was 400 Chinese tourists in Bangkok chosen by the
accidental sampling and the purposive sampling. Inferential Statistics
Analysis by using the Chi-square statistics. As for the results of this
study the researcher found that differences between personal, social
and cultural information, i.e., gender, age, place of residence,
educational level, occupation, income, family, and main objectives of
tourism with behaviors of Chinese tourists in Bangkok towards travel
and shopping in Bangkok.
Abstract: Margin-Based Principle has been proposed for a long
time, it has been proved that this principle could reduce the
structural risk and improve the performance in both theoretical
and practical aspects. Meanwhile, feed-forward neural network is
a traditional classifier, which is very hot at present with a deeper
architecture. However, the training algorithm of feed-forward neural
network is developed and generated from Widrow-Hoff Principle that
means to minimize the squared error. In this paper, we propose
a new training algorithm for feed-forward neural networks based
on Margin-Based Principle, which could effectively promote the
accuracy and generalization ability of neural network classifiers
with less labelled samples and flexible network. We have conducted
experiments on four UCI open datasets and achieved good results
as expected. In conclusion, our model could handle more sparse
labelled and more high-dimension dataset in a high accuracy while
modification from old ANN method to our method is easy and almost
free of work.
Abstract: Fruit juices play important roles in human health as
being a key part of nutrition. Juice and nectar are two categories of
drinks with so many variations for consumers, regardless of age,
lifestyle and taste preferences, which they can find their favorites.
Juices contain 100% pulp when pulp content of ‘nectar’ changes
between 25%-50%. In this study, potassium (K), magnesium (Mg),
and phosphorus (P) contents in orange juice and nectar is determined
for conscious consumption. For this purpose inductively coupled
plasma optical emission spectrometry (ICP-OES) is used to find out
potassium (K), magnesium (Mg), and phosphorus (P) contents in
orange juices and nectar. Furthermore, the daily intake of elements
from orange juice and nectar that affects human health is also
investigated. From the results of experiments K, Mg and P contents
are found in orange juice as 1351; 73,25; 89,27 ppm and in orange
nectar as 986; 33,76; 51,30 respectively.
Abstract: This work studied the isomerization of 1-butene over
hydrotalcite catalyst. The experiments were conducted at various gas
hourly space velocity (GHSV), reaction temperature and feed
concentration. No catalyst deactivation was observed over the
reaction time of 16 hours. Two major reaction products were trans-2-
butene and cis-2-butene. The reaction temperature played an
important role on the reaction selectivity. At high operating
temperatures, the selectivity of trans-2-butene was higher than the
selectivity of cis-2-butene while it was opposite at lower reaction
temperature. In the range of operating condition, the maximum
conversion of 1-butene was found at 74% when T = 673 K and GHSV
= 4 m3/h/kg-cat with trans- and cis-2-butene selectivities of 54% and
46%, respectively. Finally, the kinetic parameters of the reaction
were determined.
Abstract: The changes of the optical and structural properties of
Bismuth-Boro-Tellurite glasses pre and post gamma irradiation were
studied. Six glass samples, with different composition [(TeO2)0.7
(B2O3)0.3]1-x (Bi2O3)x prepared by melt quenching method were
irradiated with 25kGy gamma radiation at room temperature. The
Fourier Transform Infrared Spectroscopy (FTIR) was used to explore
the structural bonding in the prepared glass samples due to exposure,
while UV-VIS Spectrophotometer was used to evaluate the changes
in the optical properties before and after irradiation. Gamma
irradiation causes profound changes in the peak intensity as shown by
FTIR spectra which is due to the breaking of the network bonding.
Before gamma irradiation, the optical band gap, Eg value decreased
from 2.44 eV to 2.15 eV with the addition of Bismuth content. The
value kept decreasing (from 2.18 eV to 2.00 eV) following exposure
to gamma radiation due to the increase of non-bridging oxygen
(NBO) and the increase of defect in the glass. In conclusion, the glass
with high content of Bi2O3 (0.30Bi) give smallest Eg and show less
changes in FTIR spectra after gamma irradiation which indicate that
this glass is more resistant to gamma radiation compared to other
glasses.
Abstract: The atmospheres in many cities along the coastal lines
in the world have been rapidly changed to coastal-industrial
atmosphere. Hence, it is vital to investigate the corrosion behavior of
steel exposed to this kind of environment. In this present study,
Electrochemical Impedance Spectrography (EIS) and film thickness
measurement were applied to monitor the corrosion behavior of
weathering steel covered with a thin layer of the electrolyte in a
wet-dry cyclic condition, simulating a coastal-industrial environment
at 25oC and 60% RH. The results indicate that in all cycles, the
corrosion rate increases during the drying process due to an increase in
anion concentration and an acceleration of oxygen diffusion enhanced
by the effect of the thinning out of the electrolyte. During the wet-dry
cyclic corrosion test, the long-term corrosion behavior of this steel
depends on the periods of exposure. Corrosion process is first
accelerated and then decelerated. The decelerating corrosion process is
contributed to the formation of the protective rust, favored by the
wet-dry cycle and the acid regeneration process during the rusting
process.
Abstract: In Hungary, the society has changed a lot for the past
25 years, and these changes could be detected in educational
situations as well. The number and the intensity of conflicts have
been increased in most fields of life, as well as at schools. Teachers
have difficulties to be able to handle school conflicts. What is more,
the new net generation, generation Z has values and behavioural
patterns different from those of the previous one, which might
generate more serious conflicts at school, especially with teachers
who were mainly socialising in a traditional teacher – student
relationship.
In Hungary, the bill CCIV of 2011 declared the foundation of
Institutes of Teacher Training in higher education institutes. One of
the tasks of the Institutes is to survey the competences and needs of
teachers working in public education and to provide further trainings
and services for them according to their needs and requirements. This
job is supported by the Social Renewal Operative Programs 4.1.2.B.
The professors of a college carried out a questionnaire and surveyed
the needs and the requirements of teachers working in the region.
Based on the results, the professors of the Institute of Teacher
Training decided to meet the requirements of teachers and to launch
short teacher further training courses in spring 2015. One of the
courses is going to focus on school conflict management through
mediation.
The aim of the pilot course is to provide conflict management
techniques for teachers and to present different mediation techniques
to them. The theoretical part of the course (5 hours) will enable
participants to understand the main points and the advantages of
mediation, while the practical part (10 hours) will involve teachers in
role plays to learn how to cope with conflict situations applying
mediation. We hope if conflicts could be reduced, it would influence
school atmosphere in a positive way and the teaching – learning
process could be more successful and effective.
Abstract: The problems arising from unbalanced data sets
generally appear in real world applications. Due to unequal class
distribution, many researchers have found that the performance of
existing classifiers tends to be biased towards the majority class. The
k-nearest neighbors’ nonparametric discriminant analysis is a method
that was proposed for classifying unbalanced classes with good
performance. In this study, the methods of discriminant analysis are
of interest in investigating misclassification error rates for classimbalanced
data of three diabetes risk groups. The purpose of this
study was to compare the classification performance between
parametric discriminant analysis and nonparametric discriminant
analysis in a three-class classification of class-imbalanced data of
diabetes risk groups. Data from a project maintaining healthy
conditions for 599 employees of a government hospital in Bangkok
were obtained for the classification problem. The employees were
divided into three diabetes risk groups: non-risk (90%), risk (5%),
and diabetic (5%). The original data including the variables of
diabetes risk group, age, gender, blood glucose, and BMI were
analyzed and bootstrapped for 50 and 100 samples, 599 observations
per sample, for additional estimation of the misclassification error
rate. Each data set was explored for the departure of multivariate
normality and the equality of covariance matrices of the three risk
groups. Both the original data and the bootstrap samples showed nonnormality
and unequal covariance matrices. The parametric linear
discriminant function, quadratic discriminant function, and the
nonparametric k-nearest neighbors’ discriminant function were
performed over 50 and 100 bootstrap samples and applied to the
original data. Searching the optimal classification rule, the choices of
prior probabilities were set up for both equal proportions (0.33: 0.33:
0.33) and unequal proportions of (0.90:0.05:0.05), (0.80: 0.10: 0.10)
and (0.70, 0.15, 0.15). The results from 50 and 100 bootstrap samples
indicated that the k-nearest neighbors approach when k=3 or k=4 and
the defined prior probabilities of non-risk: risk: diabetic as 0.90:
0.05:0.05 or 0.80:0.10:0.10 gave the smallest error rate of
misclassification. The k-nearest neighbors approach would be
suggested for classifying a three-class-imbalanced data of diabetes
risk groups.
Abstract: In this work, we explore the capability of the mean
shift algorithm as a powerful preprocessing tool for improving the
quality of spatial data, acquired from airborne scanners, from densely
built urban areas. On one hand, high resolution image data corrupted
by noise caused by lossy compression techniques are appropriately
smoothed while at the same time preserving the optical edges and, on
the other, low resolution LiDAR data in the form of normalized
Digital Surface Map (nDSM) is upsampled through the joint mean
shift algorithm. Experiments on both the edge-preserving smoothing
and upsampling capabilities using synthetic RGB-z data show that the
mean shift algorithm is superior to bilateral filtering as well as to
other classical smoothing and upsampling algorithms. Application of
the proposed methodology for 3D reconstruction of buildings of a
pilot region of Athens, Greece results in a significant visual
improvement of the 3D building block model.
Abstract: Networking is important among students to achieve
better understanding. Social networking plays an important role in the
education. Realizing its huge potential, various organizations,
including institutions of higher learning have moved to the area of
social networks to interact with their students especially through
Facebook. Therefore, measuring the effectiveness of Facebook as a
learning tool has become an area of interest to academicians and
researchers. Therefore, this study tried to integrate and propose new
theoretical and empirical evidences by linking the western idea of
adopting Facebook as an alternative learning platform from a
Malaysian perspective. This study, thus, aimed to fill a gap by being
among the pioneering research that tries to study the effectiveness of
adopting Facebook as a learning platform across other cultural
settings, namely Malaysia. Structural equation modeling was
employed for data analysis and hypothesis testing. This study finding
has provided some insights that would likely affect students’
awareness towards using Facebook as an alternative learning
platform in the Malaysian higher learning institutions. At the end,
future direction is proposed.
Abstract: Prosperity of electronic equipment in photocopying
environment not only has improved work efficiency, but also has
changed indoor air quality. Considering the number of photocopying
employed, indoor air quality might be worse than in general office
environments. Determining the contribution from any type of
equipment to indoor air pollution is a complex matter. Non-methane
hydrocarbons are known to have an important role on air quality due
to their high reactivity. The presence of hazardous pollutants in
indoor air has been detected in one photocopying shop in Novi Sad,
Serbia. Air samples were collected and analyzed for five days, during
8-hr working time in three time intervals, whereas three different
sampling points were determined. Using multiple linear regression
model and software package STATISTICA 10 the concentrations of
occupational hazards and microclimates parameters were mutually
correlated. Based on the obtained multiple coefficients of
determination (0.3751, 0.2389 and 0.1975), a weak positive
correlation between the observed variables was determined. Small
values of parameter F indicated that there was no statistically
significant difference between the concentration levels of nonmethane
hydrocarbons and microclimates parameters. The results
showed that variable could be presented by the general regression
model: y = b0 + b1xi1+ b2xi2. Obtained regression equations allow to
measure the quantitative agreement between the variables and thus
obtain more accurate knowledge of their mutual relations.
Abstract: The purpose of this study was to develop a descriptive
profile of the adapted physical activity research using single subject
experimental designs. All research articles using single subject
experimental designs published in the journal of Adapted Physical
Activity Quarterly from 1984 to 2013 were employed as the data
source. Each of the articles was coded in a subcategory of seven
categories: (a) the size of sample; (b) the age of participants; (c) the
type of disabilities; (d) the type of data analysis; (e) the type of
designs, (f) the independent variable, and (g) the dependent variable.
Frequencies, percentages, and trend inspection were used to analyze
the data and develop a profile. The profile developed characterizes a
small portion of research articles used single subject designs, in
which most researchers used a small sample size, recruited children
as subjects, emphasized learning and behavior impairments, selected
visual inspection with descriptive statistics, preferred a multiple
baseline design, focused on effects of therapy, inclusion, and
strategy, and measured desired behaviors more often, with a
decreasing trend over years.
Abstract: The growth in the volume of text data such as books
and articles in libraries for centuries has imposed to establish
effective mechanisms to locate them. Early techniques such as
abstraction, indexing and the use of classification categories have
marked the birth of a new field of research called "Information
Retrieval". Information Retrieval (IR) can be defined as the task of
defining models and systems whose purpose is to facilitate access to
a set of documents in electronic form (corpus) to allow a user to find
the relevant ones for him, that is to say, the contents which matches
with the information needs of the user. This paper presents a new
semantic indexing approach of a documentary corpus. The indexing
process starts first by a term weighting phase to determine the
importance of these terms in the documents. Then the use of a
thesaurus like Wordnet allows moving to the conceptual level.
Each candidate concept is evaluated by determining its level of
representation of the document, that is to say, the importance of the
concept in relation to other concepts of the document. Finally, the
semantic index is constructed by attaching to each concept of the
ontology, the documents of the corpus in which these concepts are
found.
Abstract: Microscopic simulation tool kits allow for
consideration of the two processes of railway operations and the
previous timetable production. Block occupation conflicts on both
process levels are often solved by using defined train priorities. These
conflict resolutions (dispatching decisions) generate reactionary
delays to the involved trains. The sum of reactionary delays is
commonly used to evaluate the quality of railway operations, which
describes the timetable robustness. It is either compared to an
acceptable train performance or the delays are appraised
economically by linear monetary functions. It is impossible to
adequately evaluate dispatching decisions without a well-founded
objective function. This paper presents a new approach for the
evaluation of dispatching decisions. The approach uses mode choice
models and considers the behaviour of the end-customers. These
models evaluate the reactionary delays in more detail and consider
other competing modes of transport. The new approach pursues the
coupling of a microscopic model of railway operations with the
macroscopic choice mode model. At first, it will be implemented for
railway operations process but it can also be used for timetable
production. The evaluation considers the possibility for the customer
to interchange to other transport modes. The new approach starts to
look at rail and road, but it can also be extended to air travel. The
result of mode choice models is the modal split. The reactions by the
end-customers have an impact on the revenue of the train operating
companies. Different purposes of travel have different payment
reserves and tolerances towards late running. Aside from changes to
revenues, longer journey times can also generate additional costs.
The costs are either time- or track-specific and arise from required
changes to rolling stock or train crew cycles. Only the variable values
are summarised in the contribution margin, which is the base for the
monetary evaluation of delays. The contribution margin is calculated
for different possible solutions to the same conflict. The conflict
resolution is optimised until the monetary loss becomes minimal. The
iterative process therefore determines an optimum conflict resolution
by monitoring the change to the contribution margin. Furthermore, a
monetary value of each dispatching decision can also be derived.
Abstract: In more complex systems, such as automotive
gearbox, a rigorous treatment of the data is necessary because there
are several moving parts (gears, bearings, shafts, etc.), and in this
way, there are several possible sources of errors and also noise. The
basic objective of this work is the detection of damage in automotive
gearbox. The detection methods used are the wavelet method, the
bispectrum; advanced filtering techniques (selective filtering) of
vibrational signals and mathematical morphology. Gearbox vibration
tests were performed (gearboxes in good condition and with defects)
of a production line of a large vehicle assembler. The vibration
signals are obtained using five accelerometers in different positions
of the sample. The results obtained using the kurtosis, bispectrum,
wavelet and mathematical morphology showed that it is possible to
identify the existence of defects in automotive gearboxes.
Abstract: The aim of this exploratory research is to understand
further how organisations can evaluate their activities, which
generate knowledge creation, to meet changing stakeholder
expectations. A Scale of Knowledge (SoK) Framework is proposed
which links knowledge management and organisational activities to
changing stakeholder expectations. The framework was informed by
the knowledge management literature, as well as empirical work
conducted via a single case study of a multi-site hospital organisation
in Saudi Arabia. Eight in-depth semi-structured interviews were
conducted with managers from across the organisation regarding
current and future stakeholder expectations, organisational
strategy/activities and knowledge management. Data were analysed
using thematic analysis and a hierarchical value map technique to
identify activities that can produce further knowledge and
consequently impact on how stakeholder expectations are met.
The SoK Framework developed may be useful to practitioners as
an analytical aid to determine if current organisational activities
produce organisational knowledge which helps them meet
(increasingly higher levels of) stakeholder expectations. The
limitations of the research and avenues for future development of the
proposed framework are discussed.
Abstract: High density electrical prospecting has been widely
used in groundwater investigation, civil engineering and
environmental survey. For efficient inversion, the forward modeling
routine, sensitivity calculation, and inversion algorithm must be
efficient. This paper attempts to provide a brief summary of the past
and ongoing developments of the method. It includes reviews of the
procedures used for data acquisition, processing and inversion of
electrical resistivity data based on compilation of academic literature.
In recent times there had been a significant evolution in field survey
designs and data inversion techniques for the resistivity method. In
general 2-D inversion for resistivity data is carried out using the
linearized least-square method with the local optimization technique
.Multi-electrode and multi-channel systems have made it possible to
conduct large 2-D, 3-D and even 4-D surveys efficiently to resolve
complex geological structures that were not possible with traditional
1-D surveys. 3-D surveys play an increasingly important role in very
complex areas where 2-D models suffer from artifacts due to off-line
structures. Continued developments in computation technology, as
well as fast data inversion techniques and software, have made it
possible to use optimization techniques to obtain model parameters to
a higher accuracy. A brief discussion on the limitations of the
electrical resistivity method has also been presented.