Abstract: The aim of this paper is to present the concept of an
agile enterprise model and to initiate discussion on the research
assumptions of the model presented. The implementation of the
research project "The agility of enterprises in the process of adapting
to the environment and its changes" began in August 2014 and is
planned to last three years. The article has the form of a work-inprogress
paper which aims to verify and initiate a debate over the
proposed research model. In the literature there are very few
publications relating to research into agility; it can be concluded that
the most controversial issue in this regard is the method of measuring
agility. In previous studies the operationalization of agility was often
fragmentary, focusing only on selected areas of agility, for example
manufacturing, or analysing only selected sectors. As a result the
measures created to date can only be treated as contributory to the
development of precise measurement tools. This research project
aims to fill a cognitive gap in the literature with regard to the
conceptualization and operationalization of an agile company. Thus,
the original contribution of the author of this project is the
construction of a theoretical model that integrates manufacturing
agility (consisting mainly in adaptation to the environment) and
strategic agility (based on proactive measures). The author of this
research project is primarily interested in the attributes of an agile
enterprise which indicate that the company is able to rapidly adapt to
changing circumstances and behave pro-actively.
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: 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: 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: 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: Press-hardened profiles are used e.g. for automotive
applications in order to improve light weight construction due to the
high reachable strength. The application of interior water-air spray
cooling contributes to significantly reducing the cycle time in the
production of heat-treated tubes. This paper describes a new
manufacturing method for producing press-hardened hollow profiles
by means of an additional interior cooling based on a water-air spray.
Furthermore, this paper provides the results of thorough
investigations on the properties of press-hardened tubes in
dependence of varying spray parameters.
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: In the Hierarchical Temporal Memory (HTM) paradigm
the effect of overlap between inputs on the activation of columns in
the spatial pooler is studied. Numerical results suggest that similar
inputs are represented by similar sets of columns and dissimilar inputs
are represented by dissimilar sets of columns. It is shown that the
spatial pooler produces these results under certain conditions for
the connectivity and proximal thresholds. Following the discussion
of the initialization of parameters for the thresholds, corresponding
qualitative arguments about the learning dynamics of the spatial
pooler are discussed.
Abstract: In order to produce lead free piezoceramics with
optimum piezoelectric and dielectric properties, KNN modified with
Li+ (as an A site dopant) and Sb5+ (as a B site dopant)
(K0.49Na0.49Li0.02) (Nb0.96Sb0.04) O3 (referred as KNLNS in this paper)
have been synthesized using solid state reaction method and
conventional sintering technique. The ceramics were sintered in the
narrow range of 1050°C-1090°C for 2-3 h to get precise information
about sintering parameters. Detailed study of dependence of
microstructural, dielectric and piezoelectric properties on sintering
conditions was then carried out. The study suggests that the volatility
of the highly hygroscopic KNN ceramics is not only sensitive to
sintering temperatures but also to sintering durations. By merely
reducing the sintering duration for a given sintering temperature we
saw an increase in the density of the samples which was supported by
the increase in dielectric constants of the ceramics. And since density
directly or indirectly affects almost all the associated properties, other
dielectric and piezoelectric properties were also enhanced as we
approached towards the most suitable sintering temperature and
duration combination. The detailed results are reported in this paper.
Abstract: In this study, we proposed two techniques to track the
maximum power point (MPPT) of a photovoltaic system. The first is
an intelligent control technique, and the second is robust used for
variable structure system. In fact the characteristics I-V and P–V of
the photovoltaic generator depends on the solar irradiance and
temperature. These climate changes cause the fluctuation of
maximum power point; a maximum power point tracking technique
(MPPT) is required to maximize the output power. For this we have
adopted a control by fuzzy logic (FLC) famous for its stability and
robustness. And a Siding Mode Control (SMC) widely used for
variable structure system. The system comprises a photovoltaic panel
(PV), a DC-DC converter, which is considered as an adaptation stage
between the PV and the load. The modelling and simulation of the
system is developed using MATLAB/Simulink. SMC technique
provides a good tracking speed in fast changing irradiation and when
the irradiation changes slowly or it is constant the panel power of
FLC technique presents a much smoother signal with less
fluctuations.
Abstract: The use of engineered nanomaterials has increased as
a result of their positive impact on many sectors of the economy,
including agriculture. Silver nanoparticles (AgNPs) are now used to
enhance seed germination, plant growth, and photosynthetic quantum
efficiency and as antimicrobial agents to control plant diseases. In
this study, we examined the effect of AgNP dosage on the seed
germination of three plant species: corn (Zea mays L.), watermelon
(Citrullus lanatus [Thunb.] Matsum. & Nakai) and zucchini
(Cucurbita pepo L.). This experiment was designed to study the
effect of AgNPs on germination percentage, germination rate, mean
germination time, root length and fresh and dry weight of seedlings
for the three species. Seven concentrations (0.05, 0.1, 0.5, 1, 1.5, 2
and 2.5 mg/ml) of AgNPs were examined at the seed germination
stage. The three species had different dose responses to AgNPs in
terms of germination parameters and the measured growth
characteristics. The germination rates of the three plants were
enhanced in response to AgNPs. Significant enhancement of the
germination percentage values was observed after treatment of the
watermelon and zucchini plants with AgNPs in comparison with
untreated seeds. AgNPs showed a toxic effect on corn root
elongation, whereas watermelon and zucchini seedling growth were
positively affected by certain concentrations of AgNPs. This study
showed that exposure to AgNPs caused both positive and negative
effects on plant growth and germination.
Abstract: This paper presents the development of a robot car
that can track the motion of an object by detecting its color through
an Android device. The employed computer vision algorithm uses the
OpenCV library, which is embedded into an Android application of a
smartphone, for manipulating the captured image of the object. The
captured image of the object is subjected to color conversion and is
transformed to a binary image for further processing after color
filtering. The desired object is clearly determined after removing
pixel noise by applying image morphology operations and contour
definition. Finally, the area and the center of the object are
determined so that object’s motion to be tracked. The smartphone
application has been placed on a robot car and transmits by Bluetooth
to an Arduino assembly the motion directives so that to follow
objects of a specified color. The experimental evaluation of the
proposed algorithm shows reliable color detection and smooth
tracking characteristics.
Abstract: The seismic risk mitigation from the perspective of
the old buildings stock is truly essential in Algerian urban areas,
particularly those located in seismic prone regions, such as Annaba
city, and which the old buildings present high levels of degradation
associated with no seismic strengthening and/or rehabilitation
concerns. In this sense, the present paper approaches the issue of the
seismic vulnerability assessment of old masonry building stocks
through the adaptation of a simplified methodology developed for a
European context area similar to that of Annaba city, Algeria.
Therefore, this method is used for the first level of seismic
vulnerability assessment of the masonry buildings stock of the old
city center of Annaba. This methodology is based on a vulnerability
index that is suitable for the evaluation of damage and for the
creation of large-scale loss scenarios. Over 380 buildings were
evaluated in accordance with the referred methodology and the
results obtained were then integrated into a Geographical Information
System (GIS) tool. Such results can be used by the Annaba city
council for supporting management decisions, based on a global view
of the site under analysis, which led to more accurate and faster
decisions for the risk mitigation strategies and rehabilitation plans.