Abstract: This work proposes a data-driven multiscale based
quantitative measures to reveal the underlying complexity of
electroencephalogram (EEG), applying to a rodent model of
hypoxic-ischemic brain injury and recovery. Motivated by that real
EEG recording is nonlinear and non-stationary over different
frequencies or scales, there is a need of more suitable approach over
the conventional single scale based tools for analyzing the EEG data.
Here, we present a new framework of complexity measures
considering changing dynamics over multiple oscillatory scales. The
proposed multiscale complexity is obtained by calculating entropies of
the probability distributions of the intrinsic mode functions extracted
by the empirical mode decomposition (EMD) of EEG. To quantify
EEG recording of a rat model of hypoxic-ischemic brain injury
following cardiac arrest, the multiscale version of Tsallis entropy is
examined. To validate the proposed complexity measure, actual EEG
recordings from rats (n=9) experiencing 7 min cardiac arrest followed
by resuscitation were analyzed. Experimental results demonstrate that
the use of the multiscale Tsallis entropy leads to better discrimination
of the injury levels and improved correlations with the neurological
deficit evaluation after 72 hours after cardiac arrest, thus suggesting an
effective metric as a prognostic tool.
Abstract: Subspace channel estimation methods have been
studied widely, where the subspace of the covariance matrix is
decomposed to separate the signal subspace from noise subspace. The
decomposition is normally done by using either the eigenvalue
decomposition (EVD) or the singular value decomposition (SVD) of
the auto-correlation matrix (ACM). However, the subspace
decomposition process is computationally expensive. This paper
considers the estimation of the multipath slow frequency hopping
(FH) channel using noise space based method. In particular, an
efficient method is proposed to estimate the multipath time delays by
applying multiple signal classification (MUSIC) algorithm which is
based on the null space extracted by the rank revealing LU (RRLU)
factorization. As a result, precise information is provided by the
RRLU about the numerical null space and the rank, (i.e., important
tool in linear algebra). The simulation results demonstrate the
effectiveness of the proposed novel method by approximately
decreasing the computational complexity to the half as compared
with RRQR methods keeping the same performance.
Abstract: This paper provides a quantitative measure of the
time-varying multiunit neuronal spiking activity using an entropy
based approach. To verify the status embedded in the neuronal activity
of a population of neurons, the discrete wavelet transform (DWT) is
used to isolate the inherent spiking activity of MUA. Due to the
de-correlating property of DWT, the spiking activity would be
preserved while reducing the non-spiking component. By evaluating
the entropy of the wavelet coefficients of the de-noised MUA, a
multiresolution Shannon entropy (MRSE) of the MUA signal is
developed. The proposed entropy was tested in the analysis of both
simulated noisy MUA and actual MUA recorded from cortex in rodent
model. Simulation and experimental results demonstrate that the
dynamics of a population can be quantified by using the proposed
entropy.
Abstract: The aim of this paper is to present the optimization
methodology developed in the frame of a Coastal Transport
Information System. The system will be used for the effective design
of coastal transportation lines and incorporates subsystems that
implement models, tools and techniques that may support the design
of improved networks. The role of the optimization and decision
subsystem is to provide the user with better and optimal scenarios
that will best fulfill any constrains, goals or requirements posed. The
complexity of the problem and the large number of parameters and
objectives involved led to the adoption of an evolutionary method
(Genetic Algorithms). The problem model and the subsystem
structure are presented in detail, and, its support for simulation is also
discussed.
Abstract: The aim of this paper is to understand emerging
learning conditions, when a visual analytics is implemented and used
in K 12 (education). To date, little attention has been paid to the role
visual analytics (digital media and technology that highlight visual
data communication in order to support analytical tasks) can play in
education, and to the extent to which these tools can process
actionable data for young students. This study was conducted in three
public K 12 schools, in four social science classes with students aged
10 to 13 years, over a period of two to four weeks at each school.
Empirical data were generated using video observations and analyzed
with help of metaphors within Actor-network theory (ANT). The
learning conditions are found to be distinguished by broad
complexity, characterized by four dimensions. These emerge from
the actors’ deeply intertwined relations in the activities. The paper
argues in relation to the found dimensions that novel approaches to
teaching and learning could benefit students’ knowledge building as
they work with visual analytics, analyzing visualized data.
Abstract: Real bronchial tree is very complicated piping system.
Analysis of flow and pressure losses in this system is very difficult.
Due to the complex geometry and the very small size in the lower
generations is examination by CFD possible only in the central part
of bronchial tree. For specify the pressure losses of lower generations
is necessary to provide a mathematical equation. Determination of
mathematical formulas for calculation of pressure losses in the real
lungs is time consuming and inefficient process due to its complexity
and diversity. For these calculations is necessary to slightly simplify
the geometry of lungs (same cross-section over the length of
individual generation) or use one of the idealized models of lungs
(Horsfield, Weibel). The article compares the values of pressure
losses obtained from CFD simulation of air flow in the central part of
the real bronchial tree with the values calculated in a slightly
simplified real lungs by using a mathematical relationship derived
from the Bernoulli and continuity equations. The aim of the article is
to analyse the accuracy of the analytical method and its possibility of
use for the calculation of pressure losses in lower generations, which
is difficult to solve by numerical method due to the small geometry.
Abstract: We address the integer frequency offset (IFO)
estimation under the influence of the timing offset (TO) in orthogonal
frequency division multiplexing (OFDM) systems. Incorporating the
IFO and TO into the symbol set used to represent the received
OFDM symbol, we investigate the influence of the TO on the IFO,
and then, propose a combining method between two consecutive
OFDM correlations, reducing the influence. The proposed scheme
has almost the same complexity as that of the conventional
schemes, whereas it does not need the TO knowledge contrary to
the conventional schemes. From numerical results it is confirmed
that the proposed scheme is insensitive to the TO, consequently,
yielding an improvement of the IFO estimation performance over
the conventional schemes when the TO exists.
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: 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.
Abstract: The Blue Nile Basin is the most important tributary of
the Nile River. Egypt and Sudan are almost dependent on water
originated from the Blue Nile. This multi-dependency creates
conflicts among the three countries Egypt, Sudan, and Ethiopia
making the management of these conflicts as an international issue.
Good assessment of the water resources of the Blue Nile is an
important to help in managing such conflicts. Hydrological models
are good tool for such assessment. This paper presents a critical
review of the nature and variability of the climate and hydrology of
the Blue Nile Basin as a first step of using hydrological modeling to
assess the water resources of the Blue Nile. Many several attempts
are done to develop basin-scale hydrological modeling on the Blue
Nile. Lumped and semi distributed models used averages of
meteorological inputs and watershed characteristics in hydrological
simulation, to analyze runoff for flood control and water resource
management. Distributed models include the temporal and spatial
variability of catchment conditions and meteorological inputs to
allow better representation of the hydrological process. The main
challenge of all used models was to assess the water resources of the
basin is the shortage of the data needed for models calibration and
validation. It is recommended to use distributed model for their
higher accuracy to cope with the great variability and complexity of
the Blue Nile basin and to collect sufficient data to have more
sophisticated and accurate hydrological modeling.
Abstract: The development, operation and maintenance of
Integrated Waste Management Systems (IWMS) affects essentially
the sustainable concern of every region. The features of such systems
have great influence on all of the components of sustainability. In
order to reach the optimal way of processes, a comprehensive
mapping of the variables affecting the future efficiency of the system
is needed such as analysis of the interconnections among the
components and modeling of their interactions. The planning of a
IWMS is based fundamentally on technical and economical
opportunities and the legal framework. Modeling the sustainability
and operation effectiveness of a certain IWMS is not in the scope of
the present research. The complexity of the systems and the large
number of the variables require the utilization of a complex approach
to model the outcomes and future risks. This complex method should
be able to evaluate the logical framework of the factors composing
the system and the interconnections between them. The authors of
this paper studied the usability of the Fuzzy Cognitive Map (FCM)
approach modeling the future operation of IWMS’s. The approach
requires two input data set. One is the connection matrix containing
all the factors affecting the system in focus with all the
interconnections. The other input data set is the time series, a
retrospective reconstruction of the weights and roles of the factors.
This paper introduces a novel method to develop time series by
content analysis.
Abstract: In medical imaging, segmentation of different areas of
human body like bones, organs, tissues, etc. is an important issue.
Image segmentation allows isolating the object of interest for further
processing that can lead for example to 3D model reconstruction of
whole organs. Difficulty of this procedure varies from trivial for
bones to quite difficult for organs like liver. The liver is being
considered as one of the most difficult human body organ to segment.
It is mainly for its complexity, shape versatility and proximity of
other organs and tissues. Due to this facts usually substantial user
effort has to be applied to obtain satisfactory results of the image
segmentation. Process of image segmentation then deteriorates from
automatic or semi-automatic to fairly manual one. In this paper,
overview of selected available software applications that can handle
semi-automatic image segmentation with further 3D volume
reconstruction of human liver is presented. The applications are being
evaluated based on the segmentation results of several consecutive
DICOM images covering the abdominal area of the human body.
Abstract: Reverse Logistics (RL) Network is considered as
complex and dynamic network that involves many stakeholders such
as: suppliers, manufactures, warehouse, retails and costumers, this
complexity is inherent in such process due to lack of perfect
knowledge or conflicting information. Ontologies on the other hand
can be considered as an approach to overcome the problem of sharing
knowledge and communication among the various reverse logistics
partners. In this paper we propose a semantic representation based on
hybrid architecture for building the Ontologies in ascendant way, this
method facilitates the semantic reconciliation between the
heterogeneous information systems that support reverse logistics
processes and product data.
Abstract: Steganography is the art and science that hides the information in an appropriate cover carrier like image, text, audio and video media. In this work the authors propose a new image based steganographic method for hiding information within the complex bit planes of the image. After slicing into bit planes the cover image is analyzed to extract the most complex planes in decreasing order based on their bit plane complexity. The complexity function next determines the complex noisy blocks of the chosen bit plane and finally pixel mapping method (PMM) has been used to embed secret bits into those regions of the bit plane. The novel approach of using pixel mapping method (PMM) in bit plane domain adaptively embeds data on most complex regions of image, provides high embedding capacity, better imperceptibility and resistance to steganalysis attack.
Abstract: Structured Query Language (SQL) is the standard de facto language to access and manipulate data in a relational database. Although SQL is a language that is simple and powerful, most novice users will have trouble with SQL syntax. Thus, we are presenting SQL generator tool which is capable of translating actions and displaying SQL commands and data sets simultaneously. The tool was developed based on Model-View-Controller (MVC) pattern. The MVC pattern is a widely used software design pattern that enforces the separation between the input, processing, and output of an application. Developers take full advantage of it to reduce the complexity in architectural design and to increase flexibility and reuse of code. In addition, we use White-Box testing for the code verification in the Model module.
Abstract: In this paper, the formulation of a new group explicit
method with a fourth order accuracy is described in solving the two
dimensional Helmholtz equation. The formulation is based on the
nine-point fourth order compact finite difference approximation
formula. The complexity analysis of the developed scheme is also
presented. Several numerical experiments were conducted to test the
feasibility of the developed scheme. Comparisons with other existing
schemes will be reported and discussed. Preliminary results indicate
that this method is a viable alternative high accuracy solver to the
Helmholtz equation.
Abstract: Many studies have revealed the fact of the complexity
of ontology building process. Therefore there is a need for a new
approach which one of that addresses the socio-technical aspects in the
collaboration to reach a consensus. Meta-design approach is
considered applicable as a method in the methodological model of
socio-technical ontology engineering. Principles in the meta-design
framework are applied in the construction phases of the ontology. A
web portal is developed to support the meta-design principles
requirements. To validate the methodological model semantic web
applications were developed and integrated in the portal and also used
as a way to show the usefulness of the ontology. The knowledge based
system will be filled with data of Indonesian medicinal plants. By
showing the usefulness of the developed ontology in a semantic web
application, we motivate all stakeholders to participate in the
development of knowledge based system of medicinal plants in
Indonesia.
Abstract: In a highly competitive environment, it becomes more
important to shorten the whole business process while delivering or
even enhancing the business value to the customers and suppliers.
Although the workflow management systems receive much attention
for its capacity to practically support the business process enactment,
the effective workflow modeling method remain still challenging and
the high degree of process complexity makes it more difficult to gain
the short lead time. This paper presents a workflow structuring method
in a holistic way that can reduce the process complexity using
activity-needs and formal concept analysis, which eventually enhances
the key performance such as quality, delivery, and cost in business
process.
Abstract: Software reusability is an essential characteristic of
Component-Based Software (CBS). The component reusability is an
important assess for the effective reuse of components in CBS. The
attributes of reusability proposed by various researchers are studied
and four of them are identified as potential factors affecting
reusability. This paper proposes metric for reusability estimation of
black-box software component along with metrics for Interface
Complexity, Understandability, Customizability and Reliability. An
experiment is performed for estimation of reusability through a case
study on a sample web application using a real world component.
Abstract: This paper presents a method for the efficient
implementation of a unidirectional or bidirectional DC/DC converter.
The DC/DC converter is used essentially for energy exchange
between the low voltage service battery and a high voltage battery
commonly found in Electric Vehicle applications. In these
applications, apart from cost, efficiency of design is an important
characteristic. A useful way to reduce the size of electronic
equipment in the electric vehicles is proposed in this paper. The
technique simplifies the mechanical complexity and maximizes the
energy usage using the latest converter control techniques. Moreover
a bidirectional battery charger for hybrid electric vehicles is also
implemented in this paper. Several simulations on the test system
have been carried out in Matlab/Simulink environment. The results
exemplify the robustness of the proposed design methodology in case
of a 1.5 KW DC-DC converter.