Abstract: Until recently, researchers have developed various
tools and methodologies for effective clinical decision-making.
Among those decisions, chest pain diseases have been one of
important diagnostic issues especially in an emergency department. To
improve the ability of physicians in diagnosis, many researchers have
developed diagnosis intelligence by using machine learning and data
mining. However, most of the conventional methodologies have been
generally based on a single classifier for disease classification and
prediction, which shows moderate performance. This study utilizes an
ensemble strategy to combine multiple different classifiers to help
physicians diagnose chest pain diseases more accurately than ever.
Specifically the ensemble strategy is applied by using the integration
of decision trees, neural networks, and support vector machines. The
ensemble models are applied to real-world emergency data. This study
shows that the performance of the ensemble models is superior to each
of single classifiers.
Abstract: This paper To get the angle value with a MEMS rate
gyroscope in some specific field, the usual method is to make an
integral operation to the rate output, which will lead the error
cumulating effect. So the rate gyro is not suitable. MEMS rate
integrating gyroscope (MRIG) will solve this problem. A DSP system
has been developed to implement the control arithmetic. The system
can measure the angle of rotation directly by the control loops that
make the sensor work in whole-angle mode. Modeling the system with
MATLAB, desirable results of angle outputs are got, which prove the
feasibility of the control arithmetic.
Abstract: This paper investigates the problem of tracking spa¬tiotemporal changes of a satellite image through the use of Knowledge Discovery in Database (KDD). The purpose of this study is to help a given user effectively discover interesting knowledge and then build prediction and decision models. Unfortunately, the KDD process for spatiotemporal data is always marked by several types of imperfections. In our paper, we take these imperfections into consideration in order to provide more accurate decisions. To achieve this objective, different KDD methods are used to discover knowledge in satellite image databases. Each method presents a different point of view of spatiotemporal evolution of a query model (which represents an extracted object from a satellite image). In order to combine these methods, we use the evidence fusion theory which considerably improves the spatiotemporal knowledge discovery process and increases our belief in the spatiotemporal model change. Experimental results of satellite images representing the region of Auckland in New Zealand depict the improvement in the overall change detection as compared to using classical methods.
Abstract: Electro-hydraulic power steering (EHPS) system for
the fuel rate reduction and steering feel improvement is comprised of
ECU including the logic which controls the steering system and BL
DC motor and produces the best suited cornering force, BLDC motor,
high pressure pump integrated module and basic oil-hydraulic circuit
of the commercial HPS system.
Electro-hydraulic system can be studied in two ways such as
experimental and computer simulation. To get accurate results in
experimental study of EHPS system, the real boundary management is
necessary which is difficult task. And the accuracy of the experimental
results depends on the preparation of the experimental setup and
accuracy of the data collection. The computer simulation gives
accurate and reliable results if the simulation is carried out considering
proper boundary conditions. So, in this paper, each component of
EHPS was modeled, and the model-based analysis and control logic
was designed by using AMESim
Abstract: In this study, ZnO nano rods and ZnO ultrafine particles were synthesized by Gel-casting method. The synthesized ZnO powder has a hexagonal zincite structure. The ZnO aggregates with rod-like morphology are typically 1.4 μm in length and 120 nm in diameter, which consist of many small nanocrystals with diameters of 10 nm. Longer wires connected by many hexahedral ZnO nanocrystals were obtained after calcinations at the temperature over 600° C.The crystalline structures and morphologies of the powder have been characterized by X-ray diffraction(XRD) and Scaning electron microscopy (SEM).The result shows that the different preparation conditions such as concentration H2O, calcinations time and calcinations temperature have a lot of influences upon the properties of nano ZnO powders, an increase in the temperature of the calcinations results in an increase of the grain size and also the increase of the calcinations time in high temperature makes the size of the grains bigger. The existences of extra watter prevent nano grains from improving like rod morphology. We have obtained the smallest grain size of ZnO powder by controlling the process conditions. Finally In a suitable condition, a novel nanostructure, namely bi-rod-like ZnO nano rods was found which is different from known ZnO nanostructures.
Abstract: Alkali Activated Slag Concrete (AASC) mixes are manufactured by activating ground granulated blast furnace slag (GGBFS) using sodium hydroxide and sodium silicate solutions. The aim of the present experimental research was to investigate the effect of increasing the dosages of sodium oxide (Na2O, in the range of 4 to 8%) and the activator modulus (Ms) (i.e. the SiO2/Na2O ratio, in the range of 0.5 to 1.5) of the alkaline solutions, on the workability and strength characteristics of self-cured (air-cured) alkali activated Indian slag concrete mixes. Further the split tensile and flexure strengths for optimal mixes were studied for each dosage of Na2O.It is observed that increase in Na2O concentration increases the compressive, split-tensile and flexural strengths, both at the early and later-ages, while increase in Ms, decreases the workability of the mixes. An optimal Ms of 1.25 is found at various Na2O dosages. No significant differences in the strength performances were observed between AASCs manufactured with alkali solutions prepared using either of potable and de-ionized water.
Abstract: Green Roofs offers numerous advantages, including lowering ambient temperature, which is of increasing interest due to global warming concerns. However, there are technical problems pertaining to waterproofing to be resolved. Currently, the only recognized green roof waterproofing test is the German standard FLL. This paper examines the potential of replicating the test in tropical climate and reducing the test duration by using pre-grown plants. A three year old sample and a new setup were used for this experimental study. The new setup was prepared with close reference to the FLL standards and was compared against the three year old sample. Results showed that the waterproofing membrane was damaged by plant roots in both setups. Joints integrity was also challenged.
Abstract: Parametric models have been quite popular for
studying human growth, particularly in relation to biological
parameters such as peak size velocity and age at peak size velocity.
Longitudinal data are generally considered to be vital for fittinga
parametric model to individual-specific data, and for studying the
distribution of these biological parameters in a human population.
However, cross-sectional data are easier to obtain than longitudinal
data. In this paper, we present a method of combining longitudinal
and cross-sectional data for the purpose of estimating the distribution
of the biological parameters. We demonstrate, through simulations in
the special case ofthePreece Baines model, how estimates based on
longitudinal data can be improved upon by harnessing the
information contained in cross-sectional data.We study the extent of
improvement for different mixes of the two types of data, and finally
illustrate the use of the method through data collected by the Indian
Statistical Institute.
Abstract: Industrial robots play a vital role in automation
however only little effort are taken for the application of robots in
machining work such as Grinding, Cutting, Milling, Drilling,
Polishing etc. Robot parallel manipulators have high stiffness,
rigidity and accuracy, which cannot be provided by conventional
serial robot manipulators. The aim of this paper is to perform the
modeling and the workspace analysis of a 3 DOF Parallel
Manipulator (3 DOF PM). The 3 DOF PM was modeled and
simulated using 'ADAMS'. The concept involved is based on the
transformation of motion from a screw joint to a spherical joint
through a connecting link. This paper work has been planned to
model the Parallel Manipulator (PM) using screw joints for very
accurate positioning. A workspace analysis has been done for the
determination of work volume of the 3 DOF PM. The position of the
spherical joints connected to the moving platform and the
circumferential points of the moving platform were considered for
finding the workspace. After the simulation, the position of the joints
of the moving platform was noted with respect to simulation time and
these points were given as input to the 'MATLAB' for getting the
work envelope. Then 'AUTOCAD' is used for determining the work
volume. The obtained values were compared with analytical
approach by using Pappus-Guldinus Theorem. The analysis had been
dealt by considering the parameters, link length and radius of the
moving platform. From the results it is found that the radius of
moving platform is directly proportional to the work volume for a
constant link length and the link length is also directly proportional
to the work volume, at a constant radius of the moving platform.
Abstract: The development of wearable sensing technologies is a great challenge which is being addressed by the Proetex FP6 project (www.proetex.org). Its main aim is the development of wearable sensors to improve the safety and efficiency of emergency personnel. This will be achieved by continuous, real-time monitoring of vital signs, posture, activity, and external hazards surrounding emergency workers. We report here the development of carbon dioxide (CO2) sensing boot by incorporating commercially available CO2 sensor with a wireless platform into the boot assembly. Carefully selected commercially available sensors have been tested. Some of the key characteristics of the selected sensors are high selectivity and sensitivity, robustness and the power demand. This paper discusses some of the results of CO2 sensor tests and sensor integration with wireless data transmission
Abstract: The influence of lactulose and inulin on rheological
properties of fermented milk during storage was studied.Pasteurized
milk, freeze-dried starter culture Bb-12 (Bifidobacterium lactis, Chr.
Hansen, Denmark), inulin – RAFTILINE®HP (ORAFI, Belgium) and
syrup of lactulose (Duphalac®, the Netherlands) were used for
experiments. The fermentation process was realized at 37 oC for 16
hours and the storage of products was provided at 4 oC for 7 days.
Measurements were carried out by BROOKFIELD standard methods
and the flow curves were described by Herschel-Bulkley model.
The results of dispersion analysis have shown that both the
concentration of prebiotics (p=0.04
Abstract: Optimum communication and performance in
Wireless Sensor Networks, constitute multi-facet challenges due to
the specific networking characteristics as well as the scarce resource
availability. Furthermore, it is becoming increasingly apparent that
isolated layer based approaches often do not meet the demands posed
by WSNs applications due to omission of critical inter-layer
interactions and dependencies. As a counterpart, cross-layer is
receiving high interest aiming to exploit these interactions and
increase network performance. However, in order to clearly identify
existing dependencies, comprehensive performance studies are
required evaluating the effect of different critical network parameters
on system level performance and behavior.This paper-s main
objective is to address the need for multi-parametric performance
evaluations considering critical network parameters using a well
known network simulator, offering useful and practical conclusions
and guidelines. The results reveal strong dependencies among
considered parameters which can be utilized by and drive future
research efforts, towards designing and implementing highly efficient
protocols and architectures.
Abstract: This paper proposes a low-voltage and low-power
fully integrated digitally tuned continuous-time channel selection
filter for WiMAX applications. A 5th-order elliptic low-pass filter is
realized in a Gm-C topology. The bandwidth of the fully differential
filter is reconfigurable from 2.5MHz to 20MHz (8x) for different
requirements in WiMAX applications. The filter is simulated in a
standard 90nm CMOS process. Simulation results show the THD
(@Vout =100mVpp) is less than -66dB. The in-band ripple of the
filter is about 0.15dB. The filter consumes 1.5mW from a supply
voltage of 0.9V.
Abstract: Occurrences of spurious crests on the troughs of large,
relatively steep second-order Stokes waves are anomalous and not an
inherent characteristic of real waves. Here, the effects of such
occurrences on the statistics described by the standard second-order
stochastic model are examined theoretically and by way of
simulations. Theoretical results and simulations indicate that when
spurious occurrences are sufficiently large, the standard model leads
to physically unrealistic surface features and inaccuracies in the
statistics of various surface features, in particular, the troughs and
thus zero-crossing heights of large waves. Whereas inaccuracies can
be fairly noticeable for long-crested waves in both deep and
shallower depths, they tend to become relatively insignificant in
directional waves.
Abstract: In the context of large volume Big Divisor (nearly)
SLagy D3/D7 μ-Split SUSY [1], after an explicit identification
of first generation of SM leptons and quarks with fermionic superpartners
of four Wilson line moduli, we discuss the identification of
gravitino as a potential dark matter candidate by explicitly calculating
the decay life times of gravitino (LSP) to be greater than age of
universe and lifetimes of decays of the co-NLSPs (the first generation
squark/slepton and a neutralino) to the LSP (the gravitino) to be
very small to respect BBN constraints. Interested in non-thermal
production mechanism of gravitino, we evaluate the relic abundance
of gravitino LSP in terms of that of the co-NLSP-s by evaluating
their (co-)annihilation cross sections and hence show that the former
satisfies the requirement for a potential Dark Matter candidate. We
also show that it is possible to obtain a 125 GeV light Higgs in our
setup.
Abstract: For decades, the defense business has been plagued by
not having a reliable, deterministic method to know when the Kalman
filter solution for passive ranging application is reliable for use by the
fighter pilot. This has made it hard to accurately assess when the
ranging solution can be used for situation awareness and weapons
use. To date, we have used ad hoc rules-of-thumb to assess when we
think the estimate of the Kalman filter standard deviation on range is
reliable. A reliable algorithm has been developed at BAE Systems
Electronics & Integrated Solutions that monitors the Kalman gain
matrix elements – and a patent is pending. The “settling" of the gain
matrix elements relates directly to when we can assess the time when
the passive ranging solution is within the 10 percent-of-truth value.
The focus of the paper is on surface-based passive ranging – but the
method is applicable to airborne targets as well.
Abstract: A registration framework for image-guided robotic
surgery is proposed for three emergency neurosurgical procedures,
namely Intracranial Pressure (ICP) Monitoring, External Ventricular
Drainage (EVD) and evacuation of a Chronic Subdural Haematoma
(CSDH). The registration paradigm uses CT and white light as
modalities. This paper presents two simulation studies for a
preliminary evaluation of the registration protocol: (1) The loci of the
Target Registration Error (TRE) in the patient-s axial, coronal and
sagittal views were simulated based on a Fiducial Localisation Error
(FLE) of 5 mm and (2) Simulation of the actual framework using
projected views from a surface rendered CT model to represent white
light images of the patient. Craniofacial features were employed as
the registration basis to map the CT space onto the simulated
intraoperative space. Photogrammetry experiments on an artificial
skull were also performed to benchmark the results obtained from the
second simulation. The results of both simulations show that the
proposed protocol can provide a 5mm accuracy for these
neurosurgical procedures.
Abstract: Countries in recession, among them Croatia, have
lower tax revenues as a result of unfavorable economic situation,
which is decrease of the economic activities and unemployment. The
global tax base has decreased. In order to create larger state revenues,
states use the institute of tax authorities. By controlling transfer
pricing in the international companies and using certain techniques,
tax authorities can create greater tax obligations for the companies in
a short period of time.
Abstract: The dynamics of the Autonomous Underwater
Vehicles (AUVs) are highly nonlinear and time varying and the hydrodynamic coefficients of vehicles are difficult to estimate
accurately because of the variations of these coefficients with
different navigation conditions and external disturbances. This study presents the on-line system identification of AUV dynamics to obtain
the coupled nonlinear dynamic model of AUV as a black box. This black box has an input-output relationship based upon on-line
adaptive fuzzy model and adaptive neural fuzzy network (ANFN)
model techniques to overcome the uncertain external disturbance and
the difficulties of modelling the hydrodynamic forces of the AUVs instead of using the mathematical model with hydrodynamic parameters estimation. The models- parameters are adapted according
to the back propagation algorithm based upon the error between the
identified model and the actual output of the plant. The proposed
ANFN model adopts a functional link neural network (FLNN) as the
consequent part of the fuzzy rules. Thus, the consequent part of the
ANFN model is a nonlinear combination of input variables. Fuzzy
control system is applied to guide and control the AUV using both
adaptive models and mathematical model. Simulation results show
the superiority of the proposed adaptive neural fuzzy network
(ANFN) model in tracking of the behavior of the AUV accurately
even in the presence of noise and disturbance.
Abstract: XML is a markup language which is becoming the
standard format for information representation and data exchange. A
major purpose of XML is the explicit representation of the logical
structure of a document. Much research has been performed to
exploit logical structure of documents in information retrieval in
order to precisely extract user information need from large
collections of XML documents. In this paper, we describe an XML
information retrieval weighting scheme that tries to find the most
relevant elements in XML documents in response to a user query.
We present this weighting model for information retrieval systems
that utilize plausible inferences to infer the relevance of elements in
XML documents. We also add to this model the Dempster-Shafer
theory of evidence to express the uncertainty in plausible inferences
and Dempster-Shafer rule of combination to combine evidences
derived from different inferences.