Abstract: In this paper we propose an NLP-based method for
Ontology Population from texts and apply it to semi automatic
instantiate a Generic Knowledge Base (Generic Domain Ontology) in
the risk management domain. The approach is semi-automatic and
uses a domain expert intervention for validation. The proposed
approach relies on a set of Instances Recognition Rules based on
syntactic structures, and on the predicative power of verbs in the
instantiation process. It is not domain dependent since it heavily
relies on linguistic knowledge.
A description of an experiment performed on a part of the
ontology of the PRIMA1 project (supported by the European
community) is given. A first validation of the method is done by
populating this ontology with Chemical Fact Sheets from
Environmental Protection Agency2. The results of this experiment
complete the paper and support the hypothesis that relying on the
predicative power of verbs in the instantiation process improves the
performance.
Abstract: Shape memory alloy (SMA) actuators have found a
wide range of applications due to their unique properties such as high
force, small size, lightweight and silent operation. This paper presents
the development of compact (SMA) actuator and cooling system in
one unit. This actuator is developed for multi-fingered hand. It
consists of nickel-titanium (Nitinol) SMA wires in compact forming.
The new arrangement insulates SMA wires from the human body by
housing it in a heat sink and uses a thermoelectric device for rejecting
heat to improve the actuator performance. The study uses
optimization methods for selecting the SMA wires geometrical
parameters and the material of a heat sink. The experimental work
implements the actuator prototype and measures its response.
Abstract: This study is concerned with the investigation of the
suitability of several empirical and semi-empirical drying models
available in the literature to define drying behavior of viscose yarn
bobbins. For this purpose, firstly, experimental drying behaviour of
viscose bobbins was determined on an experimental dryer setup
which was designed and manufactured based on hot-air bobbin
dryers used in textile industry. Afterwards, drying models considered
were fitted to the experimentally obtained moisture ratios. Drying
parameters were drying temperature and bobbin diameter. The fit
was performed by selecting the values for constants in the models in
such a way that these values make the sum of the squared differences
between the experimental and the model results for moisture ratio
minimum. Suitability of fitting was specified as comparing the
correlation coefficient, standard error and mean square deviation.
The results show that the most appropriate model in describing the
drying curves of viscose bobbins is the Page model.
Abstract: The ability of the brain to organize information and generate the functional structures we use to act, think and communicate, is a common and easily observable natural phenomenon. In object-oriented analysis, these structures are represented by objects. Objects have been extensively studied and documented, but the process that creates them is not understood. In this work, a new class of discrete, deterministic, dissipative, host-guest dynamical systems is introduced. The new systems have extraordinary self-organizing properties. They can host information representing other physical systems and generate the same functional structures as the brain does. A simple mathematical model is proposed. The new systems are easy to simulate by computer, and measurements needed to confirm the assumptions are abundant and readily available. Experimental results presented here confirm the findings. Applications are many, but among the most immediate are object-oriented engineering, image and voice recognition, search engines, and Neuroscience.
Abstract: Describes the current situation of educational Robotics
"the State of the art" its concept, its evolution their niches of
opportunity, academic and business and the importance of education
and academic outreach. It shows that the development of high-tech
automated educational materials influence the teaching-learning
process and that communication between machines and humans is a
reality.
Abstract: In this paper, the gain spectrum of EDFA has been broadened by implementing HTE configuration for S and C band. On using this configuration an amplification bandwidth of 76nm ranging from 1479nm to 1555nm with a peak gain of 26dB has been obtained.
Abstract: Although face recognition seems as an easy task for
human, automatic face recognition is a much more challenging task
due to variations in time, illumination and pose. In this paper, the
influence of time-lapse on visible and thermal images is examined.
Orthogonal moment invariants are used as a feature extractor to
analyze the effect of time-lapse on thermal and visible images and the
results are compared with conventional Principal Component
Analysis (PCA). A new triangle square ratio criterion is employed
instead of Euclidean distance to enhance the performance of nearest
neighbor classifier. The results of this study indicate that the ideal
feature vectors can be represented with high discrimination power
due to the global characteristic of orthogonal moment invariants.
Moreover, the effect of time-lapse has been decreasing and enhancing
the accuracy of face recognition considerably in comparison with
PCA. Furthermore, our experimental results based on moment
invariant and triangle square ratio criterion show that the proposed
approach achieves on average 13.6% higher in recognition rate than
PCA.
Abstract: As in today's semiconductor industries test costs can make up to 50 percent of the total production costs, an efficient test error detection becomes more and more important. In this paper, we present a new machine learning approach to test error detection that should provide a faster recognition of test system faults as well as an improved test error recall. The key idea is to learn a classifier ensemble, detecting typical test error patterns in wafer test results immediately after finishing these tests. Since test error detection has not yet been discussed in the machine learning community, we define central problem-relevant terms and provide an analysis of important domain properties. Finally, we present comparative studies reflecting the failure detection performance of three individual classifiers and three ensemble methods based upon them. As base classifiers we chose a decision tree learner, a support vector machine and a Bayesian network, while the compared ensemble methods were simple and weighted majority vote as well as stacking. For the evaluation, we used cross validation and a specially designed practical simulation. By implementing our approach in a semiconductor test department for the observation of two products, we proofed its practical applicability.
Abstract: The impact of noise upon live quality has become an
important aspect to make both urban and environmental policythroughout
Europe and in Turkey. Concern over the quality of urban
environments, including noise levels and declining quality of green
space, is over the past decade with increasing emphasis on designing
livable and sustainable communities. According to the World Health
Organization, noise pollution is the third most hazardous
environmental type of pollution which proceeded by only air (gas
emission) and water pollution. The research carried out in two
phases, the first stage of the research noise and plant types providing
the suction of noise was evaluated through literature study and at the
second stage, definite types (Juniperus horizontalis L., Spirea
vanhouetti Briot., Cotoneaster dammerii C.K., Berberis thunbergii
D.C., Pyracantha coccinea M. etc.) were selected for the city of
Konya. Trials were conducted on the highway of Konya. The biggest
value of noise reduction was 6.3 dB(A), 4.9 dB(A), 6.2 dB(A) value
with compared to the control which includes the group that formed
by the bushes at the distance of 7m, 11m, 20m from the source and
5m, 9m, 20m of plant width, respectively. In this paper, definitions
regarding to noise and its sources were made and the precautions
were taken against to noise that mentioned earlier with the adverse
effects of noise. Plantation design approaches and suggestions
concerning to the diversity to be used, which are peculiar to roadside,
were developed to discuss the role and the function of plant material
to reduce the noise of the traffic.
Abstract: In this study, the Multi-Layer Perceptron (MLP)with Back-Propagation learning algorithm are used to classify to effective diagnosis Parkinsons disease(PD).It-s a challenging problem for medical community.Typically characterized by tremor, PD occurs due to the loss of dopamine in the brains thalamic region that results in involuntary or oscillatory movement in the body. A feature selection algorithm along with biomedical test values to diagnose Parkinson disease.Clinical diagnosis is done mostly by doctor-s expertise and experience.But still cases are reported of wrong diagnosis and treatment. Patients are asked to take number of tests for diagnosis.In many cases,not all the tests contribute towards effective diagnosis of a disease.Our work is to classify the presence of Parkinson disease with reduced number of attributes.Original,22 attributes are involved in classify.We use Information Gain to determine the attributes which reduced the number of attributes which is need to be taken from patients.The Artificial neural networks is used to classify the diagnosis of patients.Twenty-Two attributes are reduced to sixteen attributes.The accuracy is in training data set is 82.051% and in the validation data set is 83.333%.
Abstract: This paper deals with stakeholders’ decisions within energy neutral urban redevelopment processes. The decisions of these stakeholders during the process will make or break energy neutral ambitions. An extensive form of game theory model gave insight in the behavioral differences of stakeholders regarding energy neutral ambitions and the effects of the changing legislation. The results show that new legislation regarding spatial planning slightly influences the behavior of stakeholders. An active behavior of the municipality will still result in the best outcome. Nevertheless, the municipality becomes more powerful when acting passively and can make the use of planning tools to provide governance towards energy neutral urban redevelopment. Moreover, organizational support, recognizing the necessity for energy neutrality, keeping focused and collaboration among stakeholders are crucial elements to achieve the objective of an energy neutral urban (re)development.
Abstract: In this paper we use exponential particle swarm
optimization (EPSO) to cluster data. Then we compare between
(EPSO) clustering algorithm which depends on exponential variation
for the inertia weight and particle swarm optimization (PSO)
clustering algorithm which depends on linear inertia weight. This
comparison is evaluated on five data sets. The experimental results
show that EPSO clustering algorithm increases the possibility to find
the optimal positions as it decrease the number of failure. Also show
that (EPSO) clustering algorithm has a smaller quantization error
than (PSO) clustering algorithm, i.e. (EPSO) clustering algorithm
more accurate than (PSO) clustering algorithm.
Abstract: The flow field over a three dimensional pole barn
characterized by a cylindrical roof has been numerically investigated.
Wind pressure and viscous loads acting on the agricultural building
have been analyzed for several incoming wind directions, so as to
evaluate the most critical load condition on the structure. A constant
wind velocity profile, based on the maximum reference wind speed in
the building site (peak gust speed worked out for 50 years return
period) and on the local roughness coefficient, has been simulated.
In order to contemplate also the hazard due to potential air
wedging between the stored hay and the lower part of the ceiling, the
effect of a partial filling of the barn has been investigated.
The distribution of wind-induced loads on the structure have been
determined, allowing a numerical quantification of the effect of wind
direction on the induced stresses acting on a hemicylindrical roof.
Abstract: True integration of multimedia services over wired or
wireless networks increase the productivity and effectiveness in
today-s networks. IP Multimedia Subsystems are Next Generation
Network architecture to provide the multimedia services over fixed
or mobile networks. This paper proposes an extended SIP-based QoS
Management architecture for IMS services over underlying IP access
networks. To guarantee the end-to-end QoS for IMS services in
interconnection backbone, SIP based proxy Modules are introduced
to support the QoS provisioning and to reduce the handoff disruption
time over IP access networks. In our approach these SIP Modules
implement the combination of Diffserv and MPLS QoS mechanisms
to assure the guaranteed QoS for real-time multimedia services. To
guarantee QoS over access networks, SIP Modules make QoS
resource reservations in advance to provide best QoS to IMS users
over heterogeneous networks. To obtain more reliable multimedia
services, our approach allows the use of SCTP protocol over SIP
instead of UDP due to its multi-streaming feature. This architecture
enables QoS provisioning for IMS roaming users to differentiate IMS
network from other common IP networks for transmission of realtime
multimedia services. To validate our approach simulation
models are developed on short scale basis. The results show that our
approach yields comparable performance for efficient delivery of
IMS services over heterogeneous IP access networks.
Abstract: This study presents a mathematical modeling approach to the planning of HIV therapies on an individual basis. The model replicates clinical data from typical-progressors to AIDS for all stages of the disease with good agreement. Clinical data from rapid-progressors and long-term non-progressors is also matched by estimation of immune system parameters only. The ability of the model to reproduce these phenomena validates the formulation, a fact which is exploited in the investigation of effective therapies. The therapy investigation suggests that, unlike continuous therapy, structured treatment interruptions (STIs) are able to control the increase in both the drug-sensitive and drug-resistant virus population and, hence, prevent the ultimate progression from HIV to AIDS. The optimization results further suggest that even patients characterised by the same progression type can respond very differently to the same treatment and that the latter should be designed on a case-by-case basis. Such a methodology is presented here.
Abstract: We propose a downlink multiple-input multipleoutput
(MIMO) multi-carrier code division multiple access (MCCDMA)
system with adaptive beamforming algorithm for smart
antennas. The algorithm used in this paper is based on the Least
Mean Square (LMS), with pilot channel estimation (PCE) and the
zero forcing equalizer (ZFE) in the receiver, requiring reference
signal and no knowledge channel. MC-CDMA is studied in a
multiple antenna context in order to efficiently exploit robustness
against multipath effects and multi-user flexibility of MC-CDMA and
channel diversity offered by MIMO systems for radio mobile
channels. Computer simulations, considering multi-path Rayleigh
Fading Channel, interference inter symbol and interference are
presented to verify the performance. Simulation results show that the
scheme achieves good performance in a multi-user system.
Abstract: Rapid advancement in computing technology brings
computers and humans to be seamlessly integrated in future. The
emergence of smartphone has driven computing era towards
ubiquitous and pervasive computing. Recognizing human activity has
garnered a lot of interest and has raised significant researches-
concerns in identifying contextual information useful to human
activity recognition. Not only unobtrusive to users in daily life,
smartphone has embedded built-in sensors that capable to sense
contextual information of its users supported with wide range
capability of network connections. In this paper, we will discuss the
classification algorithms used in smartphone-based human activity.
Existing technologies pertaining to smartphone-based researches in
human activity recognition will be highlighted and discussed. Our
paper will also present our findings and opinions to formulate
improvement ideas in current researches- trends. Understanding
research trends will enable researchers to have clearer research
direction and common vision on latest smartphone-based human
activity recognition area.
Abstract: A novel circuit for generating a signal embedded with
features about data from three sensors is presented. This suggested
circuit is making use of a resistance-to-time converter employing a
bridge amplifier, an integrator and a comparator. The second resistive
sensor (Rz) is transformed into duty cycle. Another bridge with
varying resistor, (Ry) in the feedback of an OP AMP is added in
series to change the amplitude of the resulting signal in a proportional
relationship while keeping the same frequency and duty cycle
representing proportional changes in resistors Rx and Rz already
mentioned. The resultant output signal carries three types of
information embedded as variations of its frequency, duty cycle and
amplitude.
Abstract: This paper presents a NDT by infrared thermography with excitation CO2 Laser, wavelength of 10.6 μm. This excitation is the controllable heating beam, confirmed by a preliminary test on a wooden plate 1.2 m x 0.9 m x 1 cm. As the first practice, this method is applied to detecting the defect in CFRP heated by the Laser 300 W during 40 s. Two samples 40 cm x 40 cm x 4.5 cm are prepared, one with defect, another one without defect. The laser beam passes through the lens of a deviation device, and heats the samples placed at a determinate position and area. As a result, the absence of adhesive can be detected. This method displays prominently its application as NDT with the composite materials. This work gives a good perspective to characterize the laser beam, which is very useful for the next detection campaigns.
Abstract: This paper will discuss about an active power generator scheduling method in order to increase the limit level of steady state systems. Some power generator optimization methods such as Langrange, PLN (Indonesian electricity company) Operation, and the proposed Z-Thevenin-based method will be studied and compared in respect of their steady state aspects. A method proposed in this paper is built upon the thevenin equivalent impedance values between each load respected to each generator. The steady state stability index obtained with the REI DIMO method. This research will review the 500kV-Jawa-Bali interconnection system. The simulation results show that the proposed method has the highest limit level of steady state stability compared to other optimization techniques such as Lagrange, and PLN operation. Thus, the proposed method can be used to create the steady state stability limit of the system especially in the peak load condition.