Abstract: This paper presents powerful techniques for the
development of a new monitoring method based on multi-scale
entropy (MSE) in order to characterize the behaviour of the
concentrations of different gases present in the synthesis of Ammonia
and soft-sensor based on Principal Component Analysis (PCA).
Abstract: Presently, it is necessary to ensure the sustainable
development of passenger and freight transport. Increasing
performance of road freight has had a negative impact to environment
and society. It is therefore necessary to increase the competitiveness
of intermodal transport, which is more environmentally friendly. The
study describes the effectiveness of logistical centers realization for
companies and society and research how the partial internalization of
external costs reflected in the efficient use of these centers and
increase the competitiveness of intermodal transport to road freight.
In our research, we use the method of comparative analysis and
market research to describe the advantages of logistic centers for their
users as well as for society as a whole. Method normal costing is used
for calculation infrastructure and total costs, method of conversion
costing for determine the external costs. We modelled total society
costs for road freight transport and inter modal transport chain (we
assumed that most of the traffic is carried by rail) with different
loading schemes for condition in the Slovak Republic. Our research
has shown that higher utilization of inter modal transport chain do
good not only for society, but for companies providing freight
services too. Increase in use of inter modal transport chain can bring
many benefits to society that do not bring direct immediate financial
return. They often bring the multiplier effects, such as greater use of
environmentally friendly transport mode and reduce the total society
costs.
Abstract: Over the past few years, the online multimedia
collection has grown at a fast pace. Several companies showed
interest to study the different ways to organise the amount of audio
information without the need of human intervention to generate
metadata. In the past few years, many applications have emerged on
the market which are capable of identifying a piece of music in a
short time. Different audio effects and degradation make it much
harder to identify the unknown piece. In this paper, an audio
fingerprinting system which makes use of a non-parametric based
algorithm is presented. Parametric analysis is also performed using
Gaussian Mixture Models (GMMs). The feature extraction methods
employed are the Mel Spectrum Coefficients and the MPEG-7 basic
descriptors. Bin numbers replaced the extracted feature coefficients
during the non-parametric modelling. The results show that nonparametric
analysis offer potential results as the ones mentioned in
the literature.
Abstract: Natural hydrocarbon seepage has helped petroleum
exploration as a direct indicator of gas and/or oil subsurface
accumulations. Surface macro-seeps are generally an indication of a
fault in an active Petroleum Seepage System belonging to a Total
Petroleum System. This paper describes a case study in which
multiple analytical techniques were used to identify and characterize
trace petroleum-related hydrocarbons and other volatile organic
compounds in groundwater samples collected from Sousse aquifer
(Central Tunisia). The analytical techniques used for analyses of
water samples included gas chromatography-mass spectrometry (GCMS),
capillary GC with flame-ionization detection, Compound
Specific Isotope Analysis, Rock Eval Pyrolysis. The objective of the
study was to confirm the presence of gasoline and other petroleum
products or other volatile organic pollutants in those samples in order
to assess the respective implication of each of the potentially
responsible parties to the contamination of the aquifer. In addition,
the degree of contamination at different depths in the aquifer was also
of interest. The oil and gas seeps have been investigated using
biomarker and stable carbon isotope analyses to perform oil-oil and
oil-source rock correlations. The seepage gases are characterized by
high CH4 content, very low δ13CCH4 values (-71,9 ‰) and high
C1/C1–5 ratios (0.95–1.0), light deuterium–hydrogen isotope ratios (-
198 ‰) and light δ13CC2 and δ13CCO2 values (-23,8‰ and-23,8‰
respectively) indicating a thermogenic origin with the contribution of
the biogenic gas. An organic geochemistry study was carried out on
the more ten oil seep samples. This study includes light hydrocarbon
and biomarkers analyses (hopanes, steranes, n-alkanes, acyclic
isoprenoids, and aromatic steroids) using GC and GC-MS. The
studied samples show at least two distinct families, suggesting two
different types of crude oil origins: the first oil seeps appears to be
highly mature, showing evidence of chemical and/or biological
degradation and was derived from a clay-rich source rock deposited
in suboxic conditions. It has been sourced mainly by the lower
Fahdene (Albian) source rocks. The second oil seeps was derived
from a carbonate-rich source rock deposited in anoxic conditions,
well correlated with the Bahloul (Cenomanian-Turonian) source rock.
Abstract: Multi-Level Inverter technology has been developed in the area of high-power medium-voltage energy scheme, because of their advantages such as devices of lower rating can be used thereby enabling the schemes to be used for high voltage applications. Reduced Total Harmonic Distortion (THD).Since the dv/dt is low; the Electromagnetic Interference from the scheme is low. To avoid the switching losses Lower switching frequencies can be used. In this paper present a survey of various topologies, control strategy and modulation techniques used by these inverters. Here the regenerative and superior topologies are also discussed.
Abstract: Evaluated nuclear decay data for the 217Po nuclide is
presented in the present work. These data include recommended
values for the half-life T1/2, α-, β-- and γ-ray emission energies and
probabilities. Decay data from 221Rn α and 217Bi β—decays are
presented. Q(α) has been updated based on the recent published work
of the Atomic Mass Evaluation AME2012. In addition, the logft
values were calculated using the Logft program from the ENSDF
evaluation package. Moreover, the total internal conversion electrons
and the K-shell to L-shell and L-shell to M-shell and to N-shell
conversion electrons ratios K/L, L/M and L/N have been calculated
using Bricc program. Meanwhile, recommendation values or the
multi-polarities have been assigned based on recently measurement
yield a better intensity balance at the 254 keV and 264 keV gamma
transitions.
Abstract: Game theory is the study of how people interact and
make decisions to handle competitive situations. It has mainly been
developed to study decision making in complex situations. Humans
routinely alter their behaviour in response to changes in their social
and physical environment. As a consequence, the outcomes of
decisions that depend on the behaviour of multiple decision makers
are difficult to predict and require highly adaptive decision-making
strategies. In addition to the decision makers may have preferences
regarding consequences to other individuals and choose their actions
to improve or reduce the well-being of others. Nash equilibrium is a
fundamental concept in the theory of games and the most widely used
method of predicting the outcome of a strategic interaction in the
social sciences. A Nash Equilibrium exists when there is no unilateral
profitable deviation from any of the players involved. On the other
hand, no player in the game would take a different action as long as
every other player remains the same.
Abstract: The aim of this paper is to select the most accurate
forecasting method for predicting the future values of the
unemployment rate in selected European countries. In order to do so,
several forecasting techniques adequate for forecasting time series
with trend component, were selected, namely: double exponential
smoothing (also known as Holt`s method) and Holt-Winters` method
which accounts for trend and seasonality. The results of the empirical
analysis showed that the optimal model for forecasting
unemployment rate in Greece was Holt-Winters` additive method. In
the case of Spain, according to MAPE, the optimal model was double
exponential smoothing model. Furthermore, for Croatia and Italy the
best forecasting model for unemployment rate was Holt-Winters`
multiplicative model, whereas in the case of Portugal the best model
to forecast unemployment rate was Double exponential smoothing
model. Our findings are in line with European Commission
unemployment rate estimates.
Abstract: We propose a code acquisition scheme called improved
multiple-shift (IMS) for optical code division multiple access
systems, where the optical orthogonal code is used instead of the
pseudo noise code. Although the IMS algorithm has a similar process
to that of the conventional MS algorithm, it has a better code
acquisition performance than the conventional MS algorithm. We
analyze the code acquisition performance of the IMS algorithm and
compare the code acquisition performances of the MS and the IMS
algorithms in single-user and multi-user environments.
Abstract: Future mobile networks following 5th generation will
be characterized by one thousand times higher gains in capacity;
connections for at least one hundred billion devices; user experience
capable of extremely low latency and response times. To be close to
the capacity requirements and higher reliability, advanced
technologies have been studied, such as multiple connectivity, small
cell enhancement, heterogeneous networking, and advanced
interference and mobility management. This paper is focused on the
multiple connectivity in heterogeneous cellular networks. We
investigate the performance of coverage and user throughput in several
deployment scenarios. Using the stochastic geometry approach, the
SINR distributions and the coverage probabilities are derived in case
of dual connection. Also, to compare the user throughput enhancement
among the deployment scenarios, we calculate the spectral efficiency
and discuss our results.
Abstract: IEEE 802.11a/b/g standards provide multiple
transmission rates, which can be changed dynamically according to the
channel condition. Cooperative communications were introduced to
improve the overall performance of wireless LANs with the help of
relay nodes with higher transmission rates. The cooperative
communications are based on the fact that the transmission is much
faster when sending data packets to a destination node through a relay
node with higher transmission rate, rather than sending data directly to
the destination node at low transmission rate. To apply the cooperative
communications in wireless LAN, several MAC protocols have been
proposed. Some of them can result in collisions among relay nodes in a
dense network. In order to solve this problem, we propose a new
protocol. Relay nodes are grouped based on their transmission rates.
And then, relay nodes only in the highest group try to get channel
access. Performance evaluation is conducted using simulation, and
shows that the proposed protocol significantly outperforms the
previous protocol in terms of throughput and collision probability.
Abstract: Absorptive capacity generally facilitates the adoption
of innovation. How does this relationship change when economic
return is not the sole driver of innovation uptake? We investigate
whether absorptive capacity facilitates the adoption of green
innovation based on a survey of 79 construction companies in
Scotland. Based on the results of multiple regression analyses, we
confirm that existing knowledge utilisation (EKU), knowledge
building (KB) and external knowledge acquisition (EKA) are
significant predictors of green process GP), green administrative
(GA) and green technical innovation (GT), respectively. We discuss
the implications for theories of innovation adoption and knowledge
enhancement associated with environmentally-friendly practices.
Abstract: This paper develops and extended eclectic paradigm
to fit the firm internationalization process with the real international
business world. The approach is based on Dunning´s, introducing
new concepts like mode of entry, international joint venture o
international mergers and acquisitions. At the same time is presented
a model to describe the Spanish international mergers and
acquisitions in order to determinate the most important factor that
influence in this type of foreign direct investment.
Abstract: There has been a significant decline in active travel
and a massive increase in the use of car dependent travel in many
countries during the past two decades. Evidential risks for people’s
physical and mental health problems are correlated with this
increased use of motorized travel. These health related problems
range from overweight and obesity to increased air pollution. In
response to these rising concerns health professionals, traffic planers,
local authorities and others have introduced a variety of initiatives to
counterbalance the dominance of cars for daily journeys.
However, the nature of travel behavior change interventions,
which aim to reduce car use, are very complex and challenging
regarding their interactions with human behavior. To change travel
behavior at least two aspects have to be taken into consideration.
First, how to alter attitudes and perceptions toward the sustainable
and healthy modes of travel, in competition with experiences of
private car use. And second, how to make these behavior change
processes irreversible and sustainable. There are no comprehensive
models available to guide policy interventions to increase the level of
success of travel behavior change interventions across both these
dimensions.
A comprehensive theoretical framework is required in the effort to
optimize how to facilitate and guide the processes of data collection
and analysis to achieve the best possible guidelines for policy
makers. Regarding the gaps in the travel behavior change research
literature, this paper attempted to identify and suggest a
multidimensional framework in order to facilitate planning the
implemented travel behavior change interventions. A structured
mixed-method model is suggested to improve the analytic power of
the results according to the complexity of human behavior.
In order to recognize people’s attitudes towards a specific travel
mode, the Theory of Planned Behavior (TPB) was operationalized.
But in order to capture decision making processes the Transtheoretical
model of Behavior Change (TTM) was also used.
Consequently, the combination of these two theories (TTM and TPB)
has resulted in a synthesis with appropriate concepts to identify and
design an implemented travel behavior change interventions.
Abstract: The rhizome of Java grass, Cyperus rotundus was
extracted different organic polar and non-polar solvents and
performed the in vitro antiviral and immunostimulant activities
against White Spot Syndrome Virus (WSSV) and Vibrio harveyi
respectively. Based on the initial screening the ethyl acetate extract of
C. rotundus was strong activities and further it was purified through
silica column chromatography and the fractions were screened again
for antiviral and immunostimulant activity. Among the different
fractions screened against the WSSV and V. harveyi, the fractions, FIII
to FV had strong activities. In order to study the in vivo influence
of C. rotundus, the fractions (F-III to FV) were pooled and delivered
to the F. indicus through artificial feed for 30 days. After the feeding
trail the experimental and control diet fed F. indicus were challenged
with virulent WSSV and studied the survival, molecular diagnosis,
biochemical, haematological, and immunological parameters.
Surprisingly, the pooled fractions (F-IV to FVI) incorporated diets
helped to significantly (P
Abstract: This experimental study evaluates the effect of using
Cognitive-Behavioral Therapy (CBT) and Multidimensional Self-
Concept Model (MSCM) in a drug prevention programme to increase
resiliency and reduce aggression among at-risk youth in Malaysia. A
number of 60 (N=60) university students who were at-risk of taking
drugs were involved in this study. Participants were identified with
self-rating scales, Adolescent Resilience Attitude Scale (ARAS) and
Aggression Questionnaire. Based on the mean score of these
instruments, the participants were divided into the treatment group,
and the control group. Data were analyzed using t-test. The finding
showed that the mean score of resiliency was increased in the
treatment group compared to the control group. It also shows that the
mean score of aggression was reduced in the treatment group
compared to the control group. Drug Prevention Programme was
found to help in enhancing resiliency and reducing aggression among
participants in the treatment group compared to the controlled group.
Implications were given regarding the preventive actions on drug
abuse among youth in Malaysia.
Abstract: The aim of this work is to build a model based on
tissue characterization that is able to discriminate pathological and
non-pathological regions from three-phasic CT images. With our
research and based on a feature selection in different phases, we are
trying to design a neural network system with an optimal neuron
number in a hidden layer. Our approach consists of three steps:
feature selection, feature reduction, and classification. For each
region of interest (ROI), 6 distinct sets of texture features are
extracted such as: first order histogram parameters, absolute gradient,
run-length matrix, co-occurrence matrix, autoregressive model, and
wavelet, for a total of 270 texture features. When analyzing more
phases, we show that the injection of liquid cause changes to the high
relevant features in each region. Our results demonstrate that for
detecting HCC tumor phase 3 is the best one in most of the features
that we apply to the classification algorithm. The percentage of
detection between pathology and healthy classes, according to our
method, relates to first order histogram parameters with accuracy of
85% in phase 1, 95% in phase 2, and 95% in phase 3.
Abstract: The wide use of the Internet-based applications bring many challenges to the researchers to guarantee the continuity of the connections needed by the mobile hosts and provide reliable Internet access for them. One of proposed solutions by Internet Engineering Task Force (IETF) is to connect the local, multi-hop, and infrastructure-less Mobile Ad hoc Network (MANET) with Internet structure. This connection is done through multi-interface devices known as Internet Gateways. Many issues are related to this connection like gateway discovery, handoff, address auto-configuration and selecting the optimum gateway when multiple gateways exist. Many studies were done proposing gateway selection schemes with a single selection criterion or weighted multiple criteria. In this research, a review of some of these schemes is done showing the differences, the features, the challenges and the drawbacks of each of them.
Abstract: Development of a method to estimate gene functions is
an important task in bioinformatics. One of the approaches for the
annotation is the identification of the metabolic pathway that genes are
involved in. Since gene expression data reflect various intracellular
phenomena, those data are considered to be related with genes’
functions. However, it has been difficult to estimate the gene function
with high accuracy. It is considered that the low accuracy of the
estimation is caused by the difficulty of accurately measuring a gene
expression. Even though they are measured under the same condition,
the gene expressions will vary usually. In this study, we proposed a
feature extraction method focusing on the variability of gene
expressions to estimate the genes' metabolic pathway accurately. First,
we estimated the distribution of each gene expression from replicate
data. Next, we calculated the similarity between all gene pairs by KL
divergence, which is a method for calculating the similarity between
distributions. Finally, we utilized the similarity vectors as feature
vectors and trained the multiclass SVM for identifying the genes'
metabolic pathway. To evaluate our developed method, we applied the
method to budding yeast and trained the multiclass SVM for
identifying the seven metabolic pathways. As a result, the accuracy
that calculated by our developed method was higher than the one that
calculated from the raw gene expression data. Thus, our developed
method combined with KL divergence is useful for identifying the
genes' metabolic pathway.
Abstract: A Disaster Management System (DMS) is very important for countries with multiple disasters, such as Chile. In the world (also in Chile)different disasters (earthquakes, tsunamis, volcanic eruption, fire or other natural or man-made disasters) happen and have an effect on the population. It is also possible that two or more disasters occur at the same time. This meansthata multi-risk situation must be mastered. To handle such a situation a Decision Support System (DSS) based on multiagents is a suitable architecture. The most known DMSs are concernedwith only a singledisaster (sometimes thecombination of earthquake and tsunami) and often with a particular disaster. Nevertheless, a DSS helps for a better real-time response. Analyze the existing systems in the literature and expand them for multi-risk disasters to construct a well-organized system is the proposal of our work. The here shown work is an approach of a multi-risk system, which needs an architecture and well defined aims. In this moment our study is a kind of case study to analyze the way we have to follow to create our proposed system in the future.