Abstract: One of the major problems being faced by human society is that the global temperature is believed to be rising due to human activity that releases carbon IV Oxide (CO2) to the atmosphere. Carbon IV Oxide is the most important greenhouse gas influencing global warming and possible climate change. With climate change becoming alarming, reducing CO2 in our atmosphere has become a primary goal of international efforts. Forest lands are major sink and could absorb large quantities of carbon if the trees are judiciously managed. The study aims at estimating the carbon sequestration capacity of Pinus caribaea (pine) and Tectona grandis (Teak) under the prevailing environmental conditions and exploring tree growth variables that influences the carbon sequestration capacity in Omo Forest Reserve, Ogun State, Nigeria. Improving forest management by manipulating growth characteristics that influences carbon sequestration could be an adaptive strategy of forestry to climate change. Random sampling was used to select Temporary Sample Plots (TSPs) in the study area from where complete enumeration of growth variables was carried out within the plots. The data collected were subjected to descriptive and correlational analyses. The results showed that average carbon stored by Pine and Teak are 994.4±188.3 Kg and 1350.7±180.6 Kg respectively. The difference in carbon stored in the species is significant enough to consider choice of species relevant in climate change adaptation strategy. Tree growth variables influence the capacity of the tree to sequester carbon. Height, diameter, volume, wood density and age are positively correlated to carbon sequestration. These tree growth variables could be manipulated by the forest manager as an adaptive strategy for climate change while plantations of high wood density species could be relevant for management strategy to increase carbon storage.
Abstract: Unsatisfactory experiences due to an information shortage regarding the future pay-offs of actual choices, yield satisficing decision-making. This research will examine, for the first time in the literature, the motivation behind suboptimal decisions due to uncertainty by subjecting Adam Smith’s and Jeremy Bentham’s assumptions about the nature of the actions that lead to satisficing behavior, in order to clarify the theoretical background of a “consumption-based satisfactory time” concept. The contribution of this paper with respect to the existing literature is threefold: firstly, it is showed in this paper that Adam Smith’s uncertainty is related to the problem of the constancy of ideas and not related directly to beliefs. Secondly, possessions, as in Jeremy Bentham’s oeuvre, are assumed to be just as pleasing, as protecting and improving the actual or expected quality of life, so long as they reduce any displeasure due to the undesired outcomes of uncertainty. Finally, each consumption decision incurs its own satisfactory time period, owed to not feeling hungry, being healthy, not having transportation…etc. This reveals that the level of satisfaction is indeed a behavioral phenomenon where its value would depend on the simultaneous satisfaction derived from all activities.
Abstract: One of the most critical decision points in the design of a
face recognition system is the choice of an appropriate face representation.
Effective feature descriptors are expected to convey sufficient, invariant
and non-redundant facial information. In this work we propose a set of
Hahn moments as a new approach for feature description. Hahn moments
have been widely used in image analysis due to their invariance, nonredundancy
and the ability to extract features either globally and locally.
To assess the applicability of Hahn moments to Face Recognition we
conduct two experiments on the Olivetti Research Laboratory (ORL)
database and University of Notre-Dame (UND) X1 biometric collection.
Fusion of the global features along with the features from local facial
regions are used as an input for the conventional k-NN classifier. The
method reaches an accuracy of 93% of correctly recognized subjects for
the ORL database and 94% for the UND database.
Abstract: The purpose of this study is the discrimination of 28
postmenopausal with osteoporotic femoral fractures from an agematched
control group of 28 women using texture analysis based on
fractals. Two pre-processing approaches are applied on radiographic
images; these techniques are compared to highlight the choice of the
pre-processing method. Furthermore, the values of the fractal
dimension are compared to those of the fractal signature in terms of
the classification of the two populations. In a second analysis, the
BMD measure at proximal femur was compared to the fractal
analysis, the latter, which is a non-invasive technique, allowed a
better discrimination; the results confirm that the fractal analysis of
texture on calcaneus radiographs is able to discriminate osteoporotic
patients with femoral fracture from controls. This discrimination was
efficient compared to that obtained by BMD alone. It was also
present in comparing subgroups with overlapping values of BMD.
Abstract: Traditionally, the embodied energy of design choices
which reduce operational energy were assumed to have a negligible
impact on the life cycle energy of buildings. However with new
buildings having considerably lower operational energy, the
significance of embodied energy increases. A life cycle assessment of
a population of house designs was conducted in a mild and mixed
climate zone. It was determined not only that embodied energy
dominates life cycle energy, but that the impact on embodied of
design choices was of equal significance to the impact on operational
energy.
Abstract: The purpose of this study is to determine whether paper assessment especially in the subject mathematics will ever be completely replaced by online assessment using Learning Management System and Content Management System such as blackboard. Testing students has moved from the traditional scribbling and sketching on paper towards working online on a screen and keyboard. It is found that online assessment by using selective types of questions like multiple choices, true or false and final answer questions don’t reflect the actual understanding of students in solving the problems and teachers can’t determine the weakness points of students. In addition, it is showed that OBMCQs are a very good tool for self-assessment and when teachers are testing for knowledge and facts. But when it comes to the skills, OBMCQs are poor tools for measuring the ability to apply knowledge to complex math problem.
Abstract: The venture capital becomes more and more advanced
and effective source of the innovation project financing, connected
with a high-risk level. In the developed countries, it plays a key role
in transforming innovation projects into successful businesses and
creating the prosperity of the modern economy. In Russia, there are
many necessary preconditions for creation of the effective venture
investment system: the network of the public institutes for innovation
financing operates; there is a significant number of the small and
medium-sized enterprises, capable to sell production with good
market potential. However, the current system does not confirm the
necessary level of efficiency in practice that can be substantially
explained by the absence of the accurate plan of action to form the
national venture model and by the lack of experience of successful
venture deals with profitable exits in Russian economy. This paper
studies the influence of various factors on the venture industry
development by the example of the IT-sector in Russia. The choice of
the sector is based on the fact, that this segment is the main driver of
the venture capital market growth in Russia, and the necessary set of
data exists. The size of investment of the second round is used as the
dependent variable. To analyse the influence of the previous round,
such determinant as the volume of the previous (first) round
investments is used. There is also used a dummy variable in
regression to examine that the participation of an investor with high
reputation and experience in the previous round can influence the size
of the next investment round. The regression analysis of short-term
interrelations between studied variables reveals prevailing influence
of the volume of the first round investments on the venture
investments volume of the second round. The most important
determinant of the value of the second-round investment is the value
of first–round investment, so it means that the most competitive on
the Russian market are the start-up teams that can attract more money
on the start, and the target market growth is not the factor of crucial
importance. This supports the point of view that VC in Russia is
driven by endogenous factors and not by exogenous ones that are
based on global market growth.
Abstract: Froth flotation remains to date as one of the most used
metallurgical processes for concentrating metal-bearing minerals in
ores. Oxide ores are relatively less amenable to froth flotation and
require a judicious choice of reagents for the recovery of metals to be
optimised. Laboratory batch flotation tests were conducted to
determine the effect of two types of gasoil-rinkalore mixtures on the
flotation response of a copper cobalt oxide ore sample. The head
assay conducted on the initial ore sample showed that it contained
about 2.90% of Cu, 0.12% of Co.
Upon the flotation test work, the results obtained indicated that the
concentrate obtained with use of the mixture gazoil-rinkalore RX
yielded 8.24% Cu and 0.22% Co concentrate grades with recoveries
of 76.0% Cu and 78.0% Co respectively. But, the concentrate
obtained by use of the mixture gazoil-rinkalore RX3 yielded
relatively bad results with 5.92% Cu and 0.18% Cu concentrate
grades with recoveries of 70.3% Cu and 65.3% Co respectively.
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: 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: The introduction of degradable plastic materials into
agricultural sectors has represented a promising alternative to
promote green agriculture and environmental friendly of modern
farming practices. Major challenges of developing degradable
agricultural films are to identify the most feasible types of
degradation mechanisms, composition of degradable polymers and
related processing techniques. The incorrect choice of degradable
mechanisms to be applied during the degradation process will cause
premature losses of mechanical performance and strength. In order to
achieve controlled process of agricultural film degradation, the
compositions of degradable agricultural film also important in order
to stimulate degradation reaction at required interval of time and to
achieve sustainability of the modern agricultural practices. A set of
photodegradable polyethylene based agricultural film was developed
and produced, following the selective optimization of processing
parameters of the agricultural film manufacturing system. Example of
agricultural films application for oil palm seedlings cultivation is
presented.
Abstract: This study analyzes the innovative orientation of the
Croatian entrepreneurs. Innovative orientation is represented by the
perceived extent to which an entrepreneur’s product or service or
technology is new, and no other businesses offer the same product.
The sample is extracted from the GEM Croatia Adult Population
Survey dataset for the years 2003-2013. We apply descriptive
statistics, t-test, Chi-square test and logistic regression. Findings
indicate that innovative orientations vary with personal, firm, meso
and macro level variables, and between different stages in
entrepreneurship process. Significant predictors are occupation of the
entrepreneurs, size of the firm and export aspiration for both early
stage and established entrepreneurs. In addition, fear of failure,
expecting to start a new business and seeing an entrepreneurial career
as a desirable choice are predictors of innovative orientation among
early stage entrepreneurs.
Abstract: Applications of the Hausdorff space and its mappings
into tangent spaces are outlined, including their fractal dimensions
and self-similarities. The paper details this theory set up and further
describes virtualizations and atomization of manufacturing processes.
It demonstrates novel concurrency principles that will guide
manufacturing processes and resources configurations. Moreover,
varying levels of details may be produced by up folding and breaking
down of newly introduced generic models. This choice of layered
generic models for units and systems aspects along specific aspects
allows research work in parallel to other disciplines with the same
focus on all levels of detail. More credit and easier access are granted
to outside disciplines for enriching manufacturing grounds. Specific
mappings and the layers give hints for chances for interdisciplinary
outcomes and may highlight more details for interoperability
standards, as already worked on the international level. The new rules
are described, which require additional properties concerning all
involved entities for defining distributed decision cycles, again on the
base of self-similarity. All properties are further detailed and assigned
to a maturity scale, eventually displaying the smartness maturity of a
total shopfloor or a factory. The paper contributes to the intensive
ongoing discussion in the field of intelligent distributed
manufacturing and promotes solid concepts for implementations of
Cyber Physical Systems and the Internet of Things into
manufacturing industry, like industry 4.0, as discussed in German-speaking
countries.
Abstract: Teaching art by digital means is a big challenge for
the majority of teachers of art and design in primary schools, yet it
allows relationships between art, technology and creativity to be
clearly identified. The aim of this article is to present a modern way
of teaching art, using digital tools in the art classroom to improve
creative ability in pupils aged between nine and eleven years. It also
presents a conceptual model for creativity based on digital art. The
model could be useful for pupils interested in learning to draw by
using an e-drawing package, and for teachers who are interested in
teaching modern digital art in order to improve children’s creativity.
By illustrating the strategy of teaching art through technology, this
model may also help education providers to make suitable choices
about which technological approaches are most effective in
enhancing students’ creative ability, and which digital art tools can
benefit children by developing their technical skills. It is also
expected that use of this model will help to develop skills of social
interaction, which may in turn improve intellectual ability.
Abstract: The Algeria by its location offers a rich and diverse
vegetation. A large number of aromatic and medicinal plants grow
spontaneously. The interest in these plants has continued to grow in
recent years. Their particular properties due to the essential oil
fraction can be utilized to treat microbial infections. To this end, and
in the context of the valuation of the Algerian flora, we became
interested in the species of the family Lamiaceae which is one of the
most used as a global source of spices. The plant on which we have
based our choice is a species of sage "Salvia officinalis" from the
Isser localized region within the province of Boumerdes. This work
focuses on the study of the antimicrobial activity of essential oil
extracted from the leaves of Salvia officinalis. The extraction is
carried out by essential oil hydrodistillation and reveals a yield of
1.06℅. The study of the antimicrobial activity of the essential oil by
the method of at aromatogramme shown that Gram positive bacteria
are most susceptible (Staphylococcus aureus and Bacillus subtilis)
with a strong inhibition of growth. The yeast Candida albicans
fungus Aspergillus niger and have shown moderately sensitive.
Abstract: This paper introduces a proposal scheme for an
Intelligent System applied to Pedagogical Advising using Case-Based
Reasoning, to find consolidated solutions before used for the new
problems, making easier the task of advising students to the
pedagogical staff. We do intend, through this work, introduce the
motivation behind the choices for this system structure, justifying the
development of an incremental and smart web system who learns
bests solutions for new cases when it’s used, showing technics and
technology.
Abstract: The building sector is responsible, in many
industrialized countries, for about 40% of the total energy
requirements, so it seems necessary to devote some efforts in this
area in order to achieve a significant reduction of energy
consumption and of greenhouse gases emissions.
The paper presents a study aiming at providing a design
methodology able to identify the best configuration of the system
building/plant, from a technical, economic and environmentally point
of view.
Normally, the classical approach involves a building's energy
loads analysis under steady state conditions, and subsequent selection
of measures aimed at improving the energy performance, based on
previous experience made by architects and engineers in the design
team. Instead, the proposed approach uses a sequence of two wellknown
scientifically validated calculation methods (TRNSYS and
RETScreen), that allow quite a detailed feasibility analysis.
To assess the validity of the calculation model, an existing,
historical building in Central Italy, that will be the object of
restoration and preservative redevelopment, was selected as a casestudy.
The building is made of a basement and three floors, with a
total floor area of about 3,000 square meters.
The first step has been the determination of the heating and
cooling energy loads of the building in a dynamic regime by means,
which allows simulating the real energy needs of the building in
function of its use. Traditional methodologies, based as they are on
steady-state conditions, cannot faithfully reproduce the effects of
varying climatic conditions and of inertial properties of the structure.
With this model is possible to obtain quite accurate and reliable
results that allow identifying effective combinations building-HVAC
system.
The second step has consisted of using output data obtained as
input to the calculation model, which enables to compare different
system configurations from the energy, environmental and financial
point of view, with an analysis of investment, and operation and
maintenance costs, so allowing determining the economic benefit of
possible interventions.
The classical methodology often leads to the choice of
conventional plant systems, while our calculation model provides a
financial-economic assessment for innovative energy systems and
low environmental impact.
Computational analysis can help in the design phase, particularly
in the case of complex structures with centralized plant systems, by
comparing the data returned by the calculation model for different
design options.
Abstract: This study investigated some results of the use of
digital art tools by junior school children in order to discover if these
tools could promote artistic ability and creativity. The study considers
the ease of use and usefulness of the tools as well as how to assess
artwork produced by digital means. As the use of these tools is a
relatively new development in Art education, this study may help
educators in their choice of which tools to use and when to use them.
The study also aims to present a model for the assessment of
students’ artistic development and creativity by studying their artistic
activity. This model can help in determining differences in students’
creative ability and could be useful both for teachers, as a means of
assessing digital artwork, and for students, by providing the
motivation to use the tools to their fullest extent. Sixteen students
aged nine to ten years old were observed and recorded while they
used the digital drawing tools. The study found that, according to the
students’ own statements, it was not the ease of use but the successful
effects the tools provided which motivated the children to use them.
Abstract: The decision-making process is theoretically clearly
defined. Generally, it includes the problem identification and
analysis, data gathering, goals and criteria setting, alternatives
development and optimal alternative choice and its implementation.
In practice however, various modifications of the theoretical
decision-making process can occur. The managers can consider some
of the phases to be too complicated or unfeasible and thus they do not
carry them out and conversely some of the steps can be
overestimated.
The aim of the paper is to reveal and characterize the perception of
the individual phases of decision-making process by the managers.
The research is concerned with managers in the military environment
– commanders. Quantitative survey is focused cross-sectionally in the
individual levels of management of the Ministry of Defence of the
Czech Republic. On the total number of 135 respondents the analysis
focuses on which of the decision-making process phases are
problematic or not carried out in practice and which are again
perceived to be the easiest. Then it is examined the reasons of the
findings.
Abstract: ESPRIT-TLS method appears a good choice for high
resolution fault detection in induction machines. It has a very high
effectiveness in the frequency and amplitude identification.
Contrariwise, it presents a high computation complexity which
affects its implementation in real time fault diagnosis. To avoid this
problem, a Fast-ESPRIT algorithm that combined the IIR band-pass
filtering technique, the decimation technique and the original
ESPRIT-TLS method was employed to enhance extracting accurately
frequencies and their magnitudes from the wind stator current with
less computation cost. The proposed algorithm has been applied to
verify the wind turbine machine need in the implementation of an online,
fast, and proactive condition monitoring. This type of remote
and periodic maintenance provides an acceptable machine lifetime,
minimize its downtimes and maximize its productivity. The
developed technique has evaluated by computer simulations under
many fault scenarios. Study results prove the performance of Fast-
ESPRIT offering rapid and high resolution harmonics recognizing
with minimum computation time and less memory cost.