Abstract: An experiment to verify the relationships between
physiological indexes of an e-learner and the presence or absence of an
operation during e-learning is described. Electroencephalogram
(EEG), hemoencephalography (HEG), skin conductance (SC), and
blood volume pulse (BVP) values were measured while participants
performed experimental learning tasks. The results show that there are
significant differences between the SC values when reading with
clicking on learning materials and the SC values when reading without
clicking, and between the HEG ratio when reading (with and without
clicking) and the HEG ratio when resting for four of five participants.
We conclude that the SC signals can be used to estimate whether or not
a learner is performing an active task and that the HEG ratios can be
used to estimate whether a learner is learning.
Abstract: In this paper, we present the design of the
super-ellipsoidal potential function (SEPF), that can be used for
autonomous collision avoidance of an unmanned aerial vehicle (UAV)
in a 3-dimensional space. In the design of SEPF, we have the
full control over the shape and size of the potential function. In
particular, we can adjust the length, width, height, and the amount
of flattening at the tips of the potential function so that the collision
avoidance motion vector generated from the potential function can
be adjusted accordingly. Based on the idea of the SEPF, we also
propose an approach for the local autonomy of a UAV for its collision
avoidance when the UAV is teleoperated by a human operator. In
our proposed approach, a teleoperated UAV can not only avoid
collision autonomously with other surrounding objects but also track
the operator’s control input as closely as possible. As a result, an
operator can always be in control of the UAV for his/her high-level
guidance and navigation task without worrying too much about
the UAVs collision avoidance while it is being teleoperated. The
effectiveness of the proposed approach is demonstrated through a
human-in-the-loop simulation of quadrotor UAV teleoperation using
virtual robot experimentation platform (v-rep) and Matlab programs.
Abstract: This paper discusses the intake of combining multi-criteria
decision analysis (MCDA) with OLAP systems, to generate
an integrated analysis process dealing with complex multi-criteria
decision-making situations. In this context, a multi-agent modeling is
presented for decision support systems by combining multi-criteria
decision analysis (MCDA) with OLAP systems. The proposed
modeling which consists in performing the multi-agent system
(MAS) architecture, procedure and protocol of the negotiation model
is elaborated as a decision support tool for complex decision-making
environments. Our objective is to take advantage from the multi-agent
system which distributes resources and computational
capabilities across interconnected agents, and provide a problem
modeling in terms of autonomous interacting component-agents.
Thus, the identification and evaluation of criteria as well as the
evaluation and ranking of alternatives in a decision support situation
will be performed by organizing tasks and user preferences between
different agents in order to reach the right decision. At the end, an
illustrative example is conducted to demonstrate the function and
effectiveness of our MAS modeling.
Abstract: The maintenance of work rolls in hot strip processing
has been lengthy and difficult tasks for hot strip manufacturer
because heavy work rolls have to be taken out of the production line,
which could take hours. One way to increase the time between
maintenance is to improve the effectiveness of the work roll cooling
system such that the wear and tear more slowly occurs, while the
operation cost is kept low. Therefore, this study aims to improve the
work roll cooling system by providing the manufacturer the
relationship between the work-roll temperature reduced by cooling
and the water flow that can help manufacturer determining the more
effective water flow of the cooling system. The relationship is found
using simulation with a systematic process adjustment so that the
satisfying quality of product is achieved. Results suggest that the
manufacturer could reduce the water flow by 9% with roughly the
same performance. With the same process adjustment, the feasibility
of finishing-mill-stand reduction is also investigated. Results suggest
its possibility.
Abstract: Advances in spatial and spectral resolution of satellite
images have led to tremendous growth in large image databases. The
data we acquire through satellites, radars, and sensors consists of
important geographical information that can be used for remote
sensing applications such as region planning, disaster management.
Spatial data classification and object recognition are important tasks
for many applications. However, classifying objects and identifying
them manually from images is a difficult task. Object recognition is
often considered as a classification problem, this task can be
performed using machine-learning techniques. Despite of many
machine-learning algorithms, the classification is done using
supervised classifiers such as Support Vector Machines (SVM) as the
area of interest is known. We proposed a classification method,
which considers neighboring pixels in a region for feature extraction
and it evaluates classifications precisely according to neighboring
classes for semantic interpretation of region of interest (ROI). A
dataset has been created for training and testing purpose; we
generated the attributes by considering pixel intensity values and
mean values of reflectance. We demonstrated the benefits of using
knowledge discovery and data-mining techniques, which can be on
image data for accurate information extraction and classification from
high spatial resolution remote sensing imagery.
Abstract: Test automation allows performing difficult and time
consuming manual software testing tasks efficiently, quickly and
repeatedly. However, development and maintenance of automated
tests is expensive, so it needs a proper prioritization what to automate
first. This paper describes a simple yet efficient approach for such
prioritization of test cases based on the effort needed for both manual
execution and software test automation. The suggested approach is
very flexible because it allows working with a variety of assessment
methods, and adding or removing new candidates at any time. The
theoretical ideas presented in this article have been successfully
applied in real world situations in several software companies by the
authors and their colleagues including testing of real estate websites,
cryptographic and authentication solutions, OSGi-based middleware
framework that has been applied in various systems for smart homes,
connected cars, production plants, sensors, home appliances, car head
units and engine control units (ECU), vending machines, medical
devices, industry equipment and other devices that either contain or
are connected to an embedded service gateway.
Abstract: Online measurement of the product quality is a
challenging task in cement production, especially in the production of
Celitement, a novel environmentally friendly hydraulic binder. The
mineralogy and chemical composition of clinker in ordinary Portland
cement production is measured by X-ray diffraction (XRD) and
X-ray fluorescence (XRF), where only crystalline constituents can be
detected. But only a small part of the Celitement components can be
measured via XRD, because most constituents have an amorphous
structure. This paper describes the development of algorithms
suitable for an on-line monitoring of the final processing step of
Celitement based on NIR-data. For calibration intermediate products
were dried at different temperatures and ground for variable
durations. The products were analyzed using XRD and
thermogravimetric analyses together with NIR-spectroscopy to
investigate the dependency between the drying and the milling
processes on one and the NIR-signal on the other side. As a result,
different characteristic parameters have been defined. A short
overview of the Celitement process and the challenging tasks of the
online measurement and evaluation of the product quality will be
presented. Subsequently, methods for systematic development of
near-infrared calibration models and the determination of the final
calibration model will be introduced. The application of the model on
experimental data illustrates that NIR-spectroscopy allows for a quick
and sufficiently exact determination of crucial process parameters.
Abstract: Average temperatures worldwide are expected to
continue to rise. At the same time, major cities in developing
countries are becoming increasingly populated and polluted.
Governments are tasked with the problem of overheating and air
quality in residential buildings. This paper presents the development
of a model, which is able to estimate the occupant exposure
to extreme temperatures and high air pollution within domestic
buildings. Building physics simulations were performed using the
EnergyPlus building physics software. An accurate metamodel is
then formed by randomly sampling building input parameters and
training on the outputs of EnergyPlus simulations. Metamodels are
used to vastly reduce the amount of computation time required when
performing optimisation and sensitivity analyses. Neural Networks
(NNs) have been compared to a Radial Basis Function (RBF)
algorithm when forming a metamodel. These techniques were
implemented using the PyBrain and scikit-learn python libraries,
respectively. NNs are shown to perform around 15% better than RBFs
when estimating overheating and air pollution metrics modelled by
EnergyPlus.
Abstract: The aim of this paper is to propose a general
framework for storing, analyzing, and extracting knowledge from
two-dimensional echocardiographic images, color Doppler images,
non-medical images, and general data sets. A number of high
performance data mining algorithms have been used to carry out this
task. Our framework encompasses four layers namely physical
storage, object identification, knowledge discovery, user level.
Techniques such as active contour model to identify the cardiac
chambers, pixel classification to segment the color Doppler echo
image, universal model for image retrieval, Bayesian method for
classification, parallel algorithms for image segmentation, etc., were
employed. Using the feature vector database that have been
efficiently constructed, one can perform various data mining tasks
like clustering, classification, etc. with efficient algorithms along
with image mining given a query image. All these facilities are
included in the framework that is supported by state-of-the-art user
interface (UI). The algorithms were tested with actual patient data
and Coral image database and the results show that their performance
is better than the results reported already.
Abstract: Increase of emergency incidents and crisis situations
requires proactive crisis management of authorities and for its
solution. Application Business Continuity Management helps the
crisis management authorities to quickly and responsibly respond to
threats. It also helps effectively and efficiently planning powers and
resources. The main goal of this article is describing Military
Continuity Management System (MCMS) based on the principles of
Business Continuity Management System (BCMS) for dealing with
floods in the territory of the selected municipalities. There are
explained steps of loading, running and evaluating activities in the
software application MCMS. Software MCMS provides complete
control over the tasks, contribute a comprehensive and responsible
approach solutions to solution floods in the municipality.
Abstract: We regard forecasting of energy consumption by
private production areas of a large industrial facility as well as by the
facility itself. As for production areas, the forecast is made based on
empirical dependencies of the specific energy consumption and the
production output. As for the facility itself, implementation of the
task to minimize the energy consumption forecasting error is based
on adjustment of the facility’s actual energy consumption values
evaluated with the metering device and the total design energy
consumption of separate production areas of the facility. The
suggested procedure of optimal energy consumption was tested based
on the actual data of core product output and energy consumption by
a group of workshops and power plants of the large iron and steel
facility. Test results show that implementation of this procedure gives
the mean accuracy of energy consumption forecasting for winter
2014 of 0.11% for the group of workshops and 0.137% for the power
plants.
Abstract: The photovoltaic and the semiconductor industries are
in growth and it is necessary to supply a large amount of silicon to
maintain this growth. Since silicon is still the best material for the
manufacturing of solar cells and semiconductor components so the
pure silicon like solar grade and semiconductor grade materials are
demanded. There are two main routes for silicon production:
metallurgical and chemical. In this article, we reviewed the
electrotecnological installations and systems for semiconductor
manufacturing. The main task is to design the installation which can
produce SOG Silicon from river sand by one work unit.
Abstract: Multiprocessor task scheduling problem for dependent
and independent tasks is computationally complex problem. Many
methods are proposed to achieve optimal running time. As the
multiprocessor task scheduling is NP hard in nature, therefore, many
heuristics are proposed which have improved the makespan of the
problem. But due to problem specific nature, the heuristic method
which provide best results for one problem, might not provide good
results for another problem. So, Simulated Annealing which is meta
heuristic approach is considered. It can be applied on all types of
problems. However, due to many runs, meta heuristic approach takes
large computation time. Hence, the hybrid approach is proposed by
combining the Duplication Scheduling Heuristic and Simulated
Annealing (SA) and the makespan results of Simple Simulated
Annealing and Hybrid approach are analyzed.
Abstract: The agenda of showing the scheduled time for
performing certain tasks is known as timetabling. It is widely used in
many departments such as transportation, education, and production.
Some difficulties arise to ensure all tasks happen in the time and
place allocated. Therefore, many researchers invented various
programming models to solve the scheduling problems from several
fields. However, the studies in developing the general integer
programming model for many timetabling problems are still
questionable. Meanwhile, this thesis describes about creating a
general model which solves different types of timetabling problems
by considering the basic constraints. Initially, the common basic
constraints from five different fields are selected and analyzed. A
general basic integer programming model was created and then
verified by using the medium set of data obtained randomly which is
much similar to realistic data. The mathematical software, AIMMS
with CPLEX as a solver has been used to solve the model. The model
obtained is significant in solving many timetabling problems easily
since it is modifiable to all types of scheduling problems which have
same basic constraints.
Abstract: The contemporary battlefield creates a demand for
more costly and highly advanced munitions. Training personnel
responsible for operations as well as immediate execution of combat
tasks which engage real asset is unrealistic and economically not
feasible. Owing to a wide array of exploited simulators and various
types of imitators, it is possible to reduce the costs. One of the
effective elements of training, which can be applied in the training of
all service branches, is imitator of aerial targets. This research serves
as an introduction to the commencement of design analysis over a
real aerial target imitator. Within the project, the basic aerodynamic
calculations were made, which enabled to determine its geometry,
design layout, performance as well as mass balance of individual
components. The conducted calculations of the parameters of flight
characteristics come closer to the real performance of such
Unmanned Aerial Vehicles.
Abstract: Wireless Sensor Networks (WSNs), which sense
environmental data with battery-powered nodes, require multi-hop
communication. This power-demanding task adds an extra workload
that is unfairly distributed across the network. As a result, nodes run
out of battery at different times: this requires an impractical
individual node maintenance scheme. Therefore we investigate a new
Cooperative Sensing approach that extends the WSN operational life
and allows a more practical network maintenance scheme (where all
nodes deplete their batteries almost at the same time). We propose a
novel cooperative algorithm that derives a piecewise representation
of the sensed signal while controlling approximation accuracy.
Simulations show that our algorithm increases WSN operational life
and spreads communication workload evenly. Results convey a
counterintuitive conclusion: distributing workload fairly amongst
nodes may not decrease the network power consumption and yet
extend the WSN operational life. This is achieved as our cooperative
approach decreases the workload of the most burdened cluster in the
network.
Abstract: This paper focuses on the orbit avoidance strategy of
the optical remote sensing satellite. The optical remote sensing
satellite, moving along the Sun-synchronous orbit, is equipped with
laser warning equipment to alert CCD camera from laser attacks. This
paper explores the strategy of satellite avoidance to protect the CCD
camera and also the satellite. The satellite could evasive to several
target points in the orbital coordinates of virtual satellite. The so-called
virtual satellite is a passive vehicle which superposes the satellite at the
initial stage of avoidance. The target points share the consistent cycle
time and the same semi-major axis with the virtual satellite, which
ensures the properties of the satellite’s Sun-synchronous orbit remain
unchanged. Moreover, to further strengthen the avoidance capability
of satellite, it can perform multi-target-points avoid maneuvers. On
occasions of fulfilling the satellite orbit tasks, the orbit can be restored
back to virtual satellite through orbit maneuvers. There into, the avoid
maneuvers adopts pulse guidance. In addition, the fuel consumption is
optimized. The avoidance strategy discussed in this article is
applicable to optical remote sensing satellite when it is encountered
with hostile attack of space-based laser anti-satellite.
Abstract: In this paper, we present an application of Riemannian
geometry for processing non-Euclidean image data. We consider the
image as residing in a Riemannian manifold, for developing a new
method to brain edge detection and brain extraction. Automating this
process is a challenge due to the high diversity in appearance brain
tissue, among different patients and sequences. The main contribution, in this paper, is the use of an edge-based
anisotropic diffusion tensor for the segmentation task by integrating
both image edge geometry and Riemannian manifold (geodesic,
metric tensor) to regularize the convergence contour and extract
complex anatomical structures. We check the accuracy of the
segmentation results on simulated brain MRI scans of single
T1-weighted, T2-weighted and Proton Density sequences. We
validate our approach using two different databases: BrainWeb
database, and MRI Multiple sclerosis Database (MRI MS DB). We
have compared, qualitatively and quantitatively, our approach with
the well-known brain extraction algorithms. We show that using
a Riemannian manifolds to medical image analysis improves the
efficient results to brain extraction, in real time, outperforming the
results of the standard techniques.
Abstract: The article deals with the readiness of military
professionals for challenging situations. It discusses higher
requirements on the psychical endurance of military professionals
arising from the specific nature of the military occupation, which is
typical for being very difficult to maintain regularity, which is in
accordance with the hygiene of work alternated by relaxation. The
soldier must be able to serve in the long term and constantly intense
performance that goes beyond human tolerance to stress situations. A
challenging situation is always associated with overcoming
difficulties, obstacles and complicated circumstances or using
unusual methods, ways and means to achieve the desired (expected)
objectives, performing a given task or satisfying an important need.
This paper describes the categories of challenging situations, their
classification and characteristics. Attention is also paid to the
formation of personality in challenging situations, coping with stress
in challenging situations, Phases of solutions of stressful situations,
resistance to challenging life situations and its factors. Finally, the
article is focused on increasing the readiness of military professionals
for challenging situations.
Abstract: From the start, the importance of having a plan to
sustain tourism was acknowledged. The correct methods to monitor
that type of tourism have been researched. Thus, we propose in this
work to analyze the applicability of a monitoring and assistance
method on the understanding of the tourism sustainability in a small
size destiny or getaway. In this study, the subject is Lagoa da
Confusão, in the state of Tocantins and the analysis was carried out
through the efficiency of the local indicators, according to the WOT
approach. We concluded that the sustainable tourism key points that
were analyzed demonstrated to be important evaluation and
quantification tools for the proposed tasks to be developed in the
mentioned destiny. This is a study of an interdisciplinary character
and the deductive method was chosen as the guiding line.