Abstract: In its attempt to offer new ways into autonomy for a
large population of disabled people, assistive technology has largely
been inspired by robotics engineering. Recent human-like robots
carry new hopes that it seems to us necessary to analyze by means of
a specific theory of anthropomorphism. We propose to distinguish a
functional anthropomorphism which is the one of actual wheelchairs
from a structural anthropomorphism based on a mimicking of human
physiological systems. If functional anthropomorphism offers the
main advantage of eliminating the physiological systems
interdependence issue, the highly link between the robot for disabled
people and their human-built environment would lead to privilege in
the future the anthropomorphic structural way. In this future
framework, we highlight a general interdependence principle : any
partial or local structural anthropomorphism generates new
anthropomorphic needs due to the physiological systems
interdependency, whose effects can be evaluated by means of
specific anthropomorphic criterions derived from a set theory-based
approach of physiological systems.
Abstract: Physical education (PE) is still neglected in schools
despite its academic, social, psychological, and health benefits.
Based on the assumption that Information and Communication
Technologies (ICTs) can contribute to the development of PE in
schools, this study aims to design a model of the factors affecting the
adoption of ICTs for PE in schools. The proposed model is based on
a sound theoretical framework. It was designed following a literature
review of technology adoption theories and of ICT adoption factors
for physical education. The technology adoption model that fitted to
the best all ICT adoption factors was then chosen as the basis for the
proposed model. It was found that the Unified Theory of Acceptance
and Use of Technology (UTAUT) is the most adequate theoretical
framework for the modeling of ICT adoption factors for physical
education.
Abstract: Chlorine is one of the most abundant elements in
nature, which undergoes a complex biogeochemical cycle. Chlorine
bound in some substances is partly responsible for atmospheric ozone
depletion and contamination of some ecosystems. As due to
international regulations anthropogenic burden of volatile
organochlorines (VOCls) in atmosphere decreases, natural sources
(plants, soil, abiotic formation) are expected to dominate VOCl
production in the near future. Examples of plant VOCl production are
methyl chloride, and bromide emission from (sub)tropical ferns,
chloroform, 1,1,1-trichloroethane and tetrachloromethane emission
from temperate forest fern and moss. Temperate forests are found to
emit in addition to the previous compounds tetrachloroethene, and
brominated volatile compounds. VOCls can be taken up and further
metabolized in plants. The aim of this work is to identify and
quantitatively analyze the formed VOCls in temperate forest
ecosystems by a cryofocusing/GC-ECD detection method, hence
filling a gap of knowledge in the biogeochemical cycle of chlorine.
Abstract: In this paper, we present a new algorithm for clustering data in large datasets using image processing approaches. First the dataset is mapped into a binary image plane. The synthesized image is then processed utilizing efficient image processing techniques to cluster the data in the dataset. Henceforth, the algorithm avoids exhaustive search to identify clusters. The algorithm considers only a small set of the data that contains critical boundary information sufficient to identify contained clusters. Compared to available data clustering techniques, the proposed algorithm produces similar quality results and outperforms them in execution time and storage requirements.
Abstract: The one-class support vector machine “support vector
data description” (SVDD) is an ideal approach for anomaly or outlier
detection. However, for the applicability of SVDD in real-world
applications, the ease of use is crucial. The results of SVDD are
massively determined by the choice of the regularisation parameter C
and the kernel parameter of the widely used RBF kernel. While for
two-class SVMs the parameters can be tuned using cross-validation
based on the confusion matrix, for a one-class SVM this is not
possible, because only true positives and false negatives can occur
during training. This paper proposes an approach to find the optimal
set of parameters for SVDD solely based on a training set from
one class and without any user parameterisation. Results on artificial
and real data sets are presented, underpinning the usefulness of the
approach.
Abstract: Small cracks or chips of a product appear very
frequently in the course of continuous production of an automatic
press process system. These phenomena become the cause of not only
defective product but also damage of a press mold. In order to solve
this problem AE system was introduced. AE system was expected to
be very effective to real time detection of the defective product and to
prevention of the damage of the press molds.
In this study, for pick and analysis of AE signals generated from the
press process, AE sensors/pre-amplifier/analysis and processing board
were used as frequently found in the other similar cases. For analysis
and processing the AE signals picked in real time from the good or bad
products, specialized software called cdm8 was used. As a result of
this work it was conformed that intensity and shape of the various AE
signals differ depending on the weight and thickness of metal sheet
and process type.
Abstract: The aim of this in vitro study was to evaluate the possible interference of a Nectandra membranacea extract (i) on the labeling of blood cells (BC), (ii) on the labeling process of BC and plasma (P) proteins with technetium-99m (Tc-99m) and (iii) on the morphology of red blood cells (RBC). Blood samples were incubated with a Nectandra membranacea crude extract, stannous chloride, Tc- 99m (sodium pertechnetate) was added, and soluble (SF) and insoluble (IF) fractions were isolated. Morphometry studies were performed with blood samples incubated with Nectandra membranacea extract. The results show that the Nectandra membranacea extract does not promote significant alteration of the labeling of BC, IF-P and IF-BC. The Nectandra membranacea extract was able to alter the erythrocyte membrane morphology, but these morphological changes were not capable to interfere on the labeling of blood constituents with Tc-99m.
Abstract: In networks, mainly small and medium-sized businesses benefit from the knowledge, experiences and solutions offered by experts from industry and science or from the exchange with practitioners. Associations which focus, among other things, on networking, information and knowledge transfer and which are interested in supporting such cooperations are especially well suited to provide such networks and the appropriate web platforms. Using METORA as an example – a project developed and run by the Federal Association for Information Economy, Telecommunications and New Media e.V. (BITKOM) for the Federal Ministry of Economics and Technology (BMWi) – This paper will discuss how associations and other network organizations can achieve this task and what conditions they have to consider.
Abstract: A novel PDE solver using the multidimensional wave
digital filtering (MDWDF) technique to achieve the solution of a 2D
seismic wave system is presented. In essence, the continuous physical
system served by a linear Kirchhoff circuit is transformed to an
equivalent discrete dynamic system implemented by a MD wave
digital filtering (MDWDF) circuit. This amounts to numerically
approximating the differential equations used to describe elements of a
MD passive electronic circuit by a grid-based difference equations
implemented by the so-called state quantities within the passive
MDWDF circuit. So the digital model can track the wave field on a
dense 3D grid of points. Details about how to transform the continuous
system into a desired discrete passive system are addressed. In
addition, initial and boundary conditions are properly embedded into
the MDWDF circuit in terms of state quantities. Graphic results have
clearly demonstrated some physical effects of seismic wave (P-wave
and S–wave) propagation including radiation, reflection, and
refraction from and across the hard boundaries. Comparison between
the MDWDF technique and the finite difference time domain (FDTD)
approach is also made in terms of the computational efficiency.
Abstract: The new framework the Higher Education is
immersed in involves a complete change in the way lecturers must
teach and students must learn. Whereas the lecturer was the main
character in traditional education, the essential goal now is to
increase the students' participation in the process. Thus, one of the
main tasks of lecturers in this new context is to design activities of
different nature in order to encourage such participation. Seminars
are one of the activities included in this environment. They are active
sessions that enable going in depth into specific topics as support of
other activities. They are characterized by some features such as
favoring interaction between students and lecturers or improving
their communication skills. Hence, planning and organizing strategic
seminars is indeed a great challenge for lecturers with the aim of
acquiring knowledge and abilities. This paper proposes a method
using Artificial Intelligence techniques to obtain student profiles
from their marks and preferences. The goal of building such profiles
is twofold. First, it facilitates the task of splitting the students into
different groups, each group with similar preferences and learning
difficulties. Second, it makes it easy to select adequate topics to be a
candidate for the seminars. The results obtained can be either a
guarantee of what the lecturers could observe during the development
of the course or a clue to reconsider new methodological strategies in
certain topics.
Abstract: Every day human life experiences new equipments
more automatic and with more abilities. So the need for faster
processors doesn-t seem to finish. Despite new architectures and
higher frequencies, a single processor is not adequate for many
applications. Parallel processing and networks are previous solutions
for this problem. The new solution to put a network of resources on a
chip is called NOC (network on a chip). The more usual topology for
NOC is mesh topology. There are several routing algorithms suitable
for this topology such as XY, fully adaptive, etc. In this paper we
have suggested a new algorithm named Intermittent X, Y (IX/Y). We
have developed the new algorithm in simulation environment to
compare delay and power consumption with elders' algorithms.
Abstract: Long term rainfall analysis and prediction is a
challenging task especially in the modern world where the impact of
global warming is creating complications in environmental issues.
These factors which are data intensive require high performance
computational modeling for accurate prediction. This research paper
describes a prototype which is designed and developed on grid
environment using a number of coupled software infrastructural
building blocks. This grid enabled system provides the demanding
computational power, efficiency, resources, user-friendly interface,
secured job submission and high throughput. The results obtained
using sequential execution and grid enabled execution shows that
computational performance has enhanced among 36% to 75%, for
decade of climate parameters. Large variation in performance can be
attributed to varying degree of computational resources available for
job execution.
Grid Computing enables the dynamic runtime selection, sharing
and aggregation of distributed and autonomous resources which plays
an important role not only in business, but also in scientific
implications and social surroundings. This research paper attempts to
explore the grid enabled computing capabilities on weather indices
from HOAPS data for climate impact modeling and change
detection.
Abstract: This paper studies the mean square exponential synchronization problem of a class of stochastic neutral type chaotic neural networks with mixed delay. On the Basis of Lyapunov stability theory, some sufficient conditions ensuring the mean square exponential synchronization of two identical chaotic neural networks are obtained by using stochastic analysis and inequality technique. These conditions are expressed in the form of linear matrix inequalities (LMIs), whose feasibility can be easily checked by using Matlab LMI Toolbox. The feedback controller used in this paper is more general than those used in previous literatures. One simulation example is presented to demonstrate the effectiveness of the derived results.
Abstract: In the automotive industry test drives are being conducted
during the development of new vehicle models or as a part of
quality assurance of series-production vehicles. The communication
on the in-vehicle network, data from external sensors, or internal
data from the electronic control units is recorded by automotive
data loggers during the test drives. The recordings are used for fault
analysis. Since the resulting data volume is tremendous, manually
analysing each recording in great detail is not feasible.
This paper proposes to use machine learning to support domainexperts
by preventing them from contemplating irrelevant data and
rather pointing them to the relevant parts in the recordings. The
underlying idea is to learn the normal behaviour from available
recordings, i.e. a training set, and then to autonomously detect
unexpected deviations and report them as anomalies.
The one-class support vector machine “support vector data description”
is utilised to calculate distances of feature vectors. SVDDSUBSEQ
is proposed as a novel approach, allowing to classify subsequences
in multivariate time series data. The approach allows to
detect unexpected faults without modelling effort as is shown with
experimental results on recordings from test drives.
Abstract: The trends of design and development of information systems have undergone a variety of ongoing phases and stages. These variations have been evolved due to brisk changes in user requirements and business needs. To meet these requirements and needs, a flexible and agile business solution was required to come up with the latest business trends and styles. Another obstacle in agility of information systems was typically different treatment of same diseases of two patients: business processes and information services. After the emergence of information technology, the business processes and information systems have become counterparts. But these two business halves have been treated under totally different standards. There is need to streamline the boundaries of these both pillars that are equally sharing information system's burdens and liabilities. In last decade, the object orientation has evolved into one of the major solutions for modern business needs and now, SOA is the solution to shift business on ranks of electronic platform. BPM is another modern business solution that assists to regularize optimization of business processes. This paper discusses how object orientation can be conformed to incorporate or embed SOA in BPM for improved information systems.
Abstract: Every organization is continually subject to new damages and threats which can be resulted from their operations or their goal accomplishment. Methods of providing the security of space and applied tools have been widely changed with increasing application and development of information technology (IT). From this viewpoint, information security management systems were evolved to construct and prevent reiterating the experienced methods. In general, the correct response in information security management systems requires correct decision making, which in turn requires the comprehensive effort of managers and everyone involved in each plan or decision making. Obviously, all aspects of work or decision are not defined in all decision making conditions; therefore, the possible or certain risks should be considered when making decisions. This is the subject of risk management and it can influence the decisions. Investigation of different approaches in the field of risk management demonstrates their progress from quantitative to qualitative methods with a process approach.
Abstract: We present a system that finds road boundaries and
constructs the virtual lane based on fusion data from a laser and a
monocular sensor, and detects forward vehicle position even in no lane
markers or bad environmental conditions. When the road environment
is dark or a lot of vehicles are parked on the both sides of the road, it is
difficult to detect lane and road boundary. For this reason we use
fusion of laser and vision sensor to extract road boundary to acquire
three dimensional data. We use parabolic road model to calculate road
boundaries which is based on vehicle and sensors state parameters and
construct virtual lane. And then we distinguish vehicle position in each
lane.
Abstract: Knowledge sharing in general and the contextual
access to knowledge in particular, still represent a key challenge in
the knowledge management framework. Researchers on semantic
web and human machine interface study techniques to enhance this
access. For instance, in semantic web, the information retrieval is
based on domain ontology. In human machine interface, keeping
track of user's activity provides some elements of the context that can
guide the access to information. We suggest an approach based on
these two key guidelines, whilst avoiding some of their weaknesses.
The approach permits a representation of both the context and the
design rationale of a project for an efficient access to knowledge. In
fact, the method consists of an information retrieval environment
that, in the one hand, can infer knowledge, modeled as a semantic
network, and on the other hand, is based on the context and the
objectives of a specific activity (the design). The environment we
defined can also be used to gather similar project elements in order to
build classifications of tasks, problems, arguments, etc. produced in a
company. These classifications can show the evolution of design
strategies in the company.
Abstract: This Classifying Bird Sounds (chip notes) project-s
purpose is to reduce the unwanted noise from recorded bird sound
chip notes, design a scheme to detect differences and similarities
between recorded chip notes, and classify bird sound chip notes. The
technologies of determining the similarities of sound waves have
been used in communication, sound engineering and wireless sound
applications for many years. Our research is focused on the similarity
of chip notes, which are the sounds from different birds. The program
we use is generated by Microsoft Cµ.
Abstract: Results of Chilean wine classification based on the
information provided by an electronic nose are reported in this paper.
The classification scheme consists of two parts; in the first stage,
Principal Component Analysis is used as feature extraction method to
reduce the dimensionality of the original information. Then, Radial
Basis Functions Neural Networks is used as pattern recognition
technique to perform the classification. The objective of this study is
to classify different Cabernet Sauvignon, Merlot and Carménère wine
samples from different years, valleys and vineyards of Chile.