Abstract: Representing objects in a dynamic domain is essential
in commonsense reasoning under some circumstances. Classical logics
and their nonmonotonic consequences, however, are usually not
able to deal with reasoning with dynamic domains due to the fact that
every constant in the logical language denotes some existing object
in the static domain. In this paper, we explore a logical formalization
which allows us to represent nonexisting objects in commonsense
reasoning. A formal system named N-theory is proposed for this
purpose and its possible application in computer security is briefly
discussed.
Abstract: Recurrent event data is a special type of multivariate
survival data. Dynamic and frailty models are one of the approaches
that dealt with this kind of data. A comparison between these two
models is studied using the empirical standard deviation of the
standardized martingale residual processes as a way of assessing the
fit of the two models based on the Aalen additive regression model.
Here we found both approaches took heterogeneity into account and
produce residual standard deviations close to each other both in the
simulation study and in the real data set.
Abstract: The study of tourist activities and the mapping of their routes in space and time has become an important issue in tourism management. Here we represent space-time paths for the tourism industry by visualizing individual tourist activities and the paths followed using a 3D Geographic Information System (GIS). Considerable attention has been devoted to the measurement of accessibility to shopping, eating, walking and other services at the tourist destination. I turns out that GIS is a useful tool for studying the spatial behaviors of tourists in the area. The value of GIS is especially advantageous for space-time potential path area measures, especially for the accurate visualization of possible paths through existing city road networks. This study seeks to apply space-time concepts with a detailed street network map obtained from Google Maps to measure tourist paths both spatially and temporally. These paths are further determined based on data obtained from map questionnaires regarding the trip activities of 40 individuals. The analysis of the data makes it possible to determining the locations of the more popular paths. The results can be visualized using 3D GIS to show the areas and potential activity opportunities accessible to tourists during their travel time.
Abstract: In this paper, a new technique of signal detection has been proposed for detecting the orthogonal frequency-division multiplexing (OFDM) signal in the presence of nonlinear distortion.There are several advantages of OFDM communications system.However, one of the existing problems is remain considered as the nonlinear distortion generated by high-power-amplifier at the transmitter end due to the large dynamic range of an OFDM signal. The proposed method is the maximum likelihood detection with the symbol estimation. When the training data are available, the neural network has been used to learn the characteristic of received signal and to estimate the new positions of the transmitted symbol which are provided to the maximum likelihood detector. Resulting in the system performance, the nonlinear distortions of a traveling wave tube amplifier with OFDM signal are considered in this paper.Simulation results of the bit-error-rate performance are obtained with 16-QAM OFDM systems.
Abstract: Although many studies on the assembly technology of
the bridge construction have dealt mostly with on the pier, girder or the
deck of the bridge, studies on the prefabricated barrier have rarely been
performed. For understanding structural characteristics and
application of the concrete barrier in the modular bridge, which is an
assembly of structure members, static loading test was performed.
Structural performances as a road barrier of the three methods,
conventional cast-in-place(ST), vertical bolt connection(BVC) and
horizontal bolt connection(BHC) were evaluated and compared
through the analyses of load-displacement curves, strain curves of the
steel, concrete strain curves and the visual appearances of crack
patterns. The vertical bolt connection(BVC) method demonstrated
comparable performance as an alternative to conventional
cast-in-place(ST) while providing all the advantages of prefabricated
technology. Necessities for the future improvement in nuts
enforcement as well as legal standard and regulation are also
addressed.
Abstract: Dengue disease is an infectious vector-borne viral
disease that is commonly found in tropical and sub-tropical regions,
especially in urban and semi-urban areas, around the world and
including Malaysia. There is no currently available vaccine or
chemotherapy for the prevention or treatment of dengue disease.
Therefore prevention and treatment of the disease depend on vector
surveillance and control measures. Disease risk mapping has been
recognized as an important tool in the prevention and control
strategies for diseases. The choice of statistical model used for
relative risk estimation is important as a good model will
subsequently produce a good disease risk map. Therefore, the aim of
this study is to estimate the relative risk for dengue disease based
initially on the most common statistic used in disease mapping called
Standardized Morbidity Ratio (SMR) and one of the earliest
applications of Bayesian methodology called Poisson-gamma model.
This paper begins by providing a review of the SMR method, which
we then apply to dengue data of Perak, Malaysia. We then fit an
extension of the SMR method, which is the Poisson-gamma model.
Both results are displayed and compared using graph, tables and
maps. Results of the analysis shows that the latter method gives a
better relative risk estimates compared with using the SMR. The
Poisson-gamma model has been demonstrated can overcome the
problem of SMR when there is no observed dengue cases in certain
regions. However, covariate adjustment in this model is difficult and
there is no possibility for allowing spatial correlation between risks in
adjacent areas. The drawbacks of this model have motivated many
researchers to propose other alternative methods for estimating the
risk.
Abstract: This paper presents an effective traffic lights
recognition method at the daytime. First, Potential Traffic Lights
Detector (PTLD) use whole color source of YCbCr channel image and
make each binary image of green and red traffic lights. After PTLD
step, Shape Filter (SF) use to remove noise such as traffic sign, street
tree, vehicle, and building. At this time, noise removal properties
consist of information of blobs of binary image; length, area, area of
boundary box, etc. Finally, after an intermediate association step witch
goal is to define relevant candidates region from the previously
detected traffic lights, Adaptive Multi-class Classifier (AMC) is
executed. The classification method uses Haar-like feature and
Adaboost algorithm. For simulation, we are implemented through Intel
Core CPU with 2.80 GHz and 4 GB RAM and tested in the urban and
rural roads. Through the test, we are compared with our method and
standard object-recognition learning processes and proved that it
reached up to 94 % of detection rate which is better than the results
achieved with cascade classifiers. Computation time of our proposed
method is 15 ms.
Abstract: The objective of this study is to propose an observer design for nonlinear systems by using an augmented linear system derived by application of a formal linearization method. A given nonlinear differential equation is linearized by the formal linearization method which is based on Taylor expansion considering up to the higher order terms, and a measurement equation is transformed into an augmented linear one. To this augmented dimensional linear system, a linear estimation theory is applied and a nonlinear observer is derived. As an application of this method, an estimation problem of transient state of electric power systems is studied, and its numerical experiments indicate that this observer design shows remarkable performances for nonlinear systems.
Abstract: This study investigated the relationship between
exercise imagery use and level of physical activity within a wide
range of exercisers in Klang valley, Malaysia. One hundred and
twenty four respondents (Mage = 28.92, SD = 9.34) completed two
sets of questionnaires (Exercise Imagery Inventory and Leisure-Time
Exercise Questionnaire) that measure the use of imagery and exercise
frequency of participants. From the result obtained, exercise imagery
is found to be significantly correlated to level of physical activity.
Besides that, variables such as gender, age and ethnicity that may
affect the use of imagery and exercise frequency were also being
assessed in this study. Among all variables, only ethnicity showed
significant difference in level of physical activity (p < 0.05). Findings
in this study suggest that further investigation should be done on
other variables such as socioeconomic, educational level, and selfefficacy
that may affect the imagery use and frequency of physical
activity among exercisers.
Abstract: Topics Disaster and Emergency Management are highly debated among experts. Fast communication will help to deal with emergencies. Problem is with the network connection and data exchange. The paper suggests a solution, which allows possibilities and perspectives of new flexible communication platform to the protection of communication systems for crisis management. This platform is used for everyday communication and communication in crisis situations too.
Abstract: The crop rice is the staple food of most Sierra Leone
with no close substitute. However, its cultivation has been on its last
legs over the years. The decline in the domestic rice cultivation has
had vicious socio-economic implications such as hiking consumer
prices, balance of payment dilemmas with debt burden. The objective
of this study is thus, to assess the effect of the shift of rural labour
towards non-agricultural sectors on rice cultivation. The tools utilized
for analyzing the problem under consideration involved a thorough
descriptive statistics and generalized linear model using OLS
technique. Increased rural population was established positive and
significant in affecting rice cultivation. Fertilizer utilization was
insignificant in rice cultivation. For reducing the shift of rural labor
force towards nonagricultural sectors, the government should make
the agricultural sector very lucrative.
Abstract: In recent years, a number of works proposing the
combination of multiple classifiers to produce a single
classification have been reported in remote sensing literature. The
resulting classifier, referred to as an ensemble classifier, is
generally found to be more accurate than any of the individual
classifiers making up the ensemble. As accuracy is the primary
concern, much of the research in the field of land cover
classification is focused on improving classification accuracy. This
study compares the performance of four ensemble approaches
(boosting, bagging, DECORATE and random subspace) with a
univariate decision tree as base classifier. Two training datasets,
one without ant noise and other with 20 percent noise was used to
judge the performance of different ensemble approaches. Results
with noise free data set suggest an improvement of about 4% in
classification accuracy with all ensemble approaches in
comparison to the results provided by univariate decision tree
classifier. Highest classification accuracy of 87.43% was achieved
by boosted decision tree. A comparison of results with noisy data
set suggests that bagging, DECORATE and random subspace
approaches works well with this data whereas the performance of
boosted decision tree degrades and a classification accuracy of
79.7% is achieved which is even lower than that is achieved (i.e.
80.02%) by using unboosted decision tree classifier.
Abstract: Minimally invasive surgery (MIS) is now being widely used as a preferred choice for various types of operations. The need to detect various tactile properties, justifies the key role of tactile sensing that is currently missing in MIS. In this regard, Laparoscopy is one of the methods of minimally invasive surgery that can be used in kidney stone removal surgeries. At this moment, determination of the exact location of stone during laparoscopy is one of the limitations of this method that no scientific solution has been found for so far. Artificial tactile sensing is a new method for obtaining the characteristics of a hard object embedded in a soft tissue. Artificial palpation is an important application of artificial tactile sensing that can be used in different types of surgeries. In this study, a new method for determining the exact location of stone during laparoscopy is presented. In the present study, the effects of stone existence on the surface of kidney were investigated using conceptual 3D model of kidney containing a simulated stone. Having imitated palpation and modeled it conceptually, indications of stone existence that appear on the surface of kidney were determined. A number of different cases were created and solved by the software and using stress distribution contours and stress graphs, it is illustrated that the created stress patterns on the surface of kidney show not only the existence of stone inside, but also its exact location. So three-dimensional analysis leads to a novel method of predicting the exact location of stone and can be directly applied to the incorporation of tactile sensing in artificial palpation, helping surgeons in non-invasive procedures.
Abstract: In this paper, different approaches to solve the
forward kinematics of a three DOF actuator redundant hydraulic
parallel manipulator are presented. On the contrary to series
manipulators, the forward kinematic map of parallel manipulators
involves highly coupled nonlinear equations, which are almost
impossible to solve analytically. The proposed methods are using
neural networks identification with different structures to solve the
problem. The accuracy of the results of each method is analyzed in
detail and the advantages and the disadvantages of them in
computing the forward kinematic map of the given mechanism is
discussed in detail. It is concluded that ANFIS presents the best
performance compared to MLP, RBF and PNN networks in this
particular application.
Abstract: Heart failure is the most common reason of death
nowadays, but if the medical help is given directly, the patient-s life
may be saved in many cases. Numerous heart diseases can be
detected by means of analyzing electrocardiograms (ECG). Artificial
Neural Networks (ANN) are computer-based expert systems that
have proved to be useful in pattern recognition tasks. ANN can be
used in different phases of the decision-making process, from
classification to diagnostic procedures. This work concentrates on a
review followed by a novel method.
The purpose of the review is to assess the evidence of healthcare
benefits involving the application of artificial neural networks to the
clinical functions of diagnosis, prognosis and survival analysis, in
ECG signals. The developed method is based on a compound neural
network (CNN), to classify ECGs as normal or carrying an
AtrioVentricular heart Block (AVB). This method uses three
different feed forward multilayer neural networks. A single output
unit encodes the probability of AVB occurrences. A value between 0
and 0.1 is the desired output for a normal ECG; a value between 0.1
and 1 would infer an occurrence of an AVB. The results show that
this compound network has a good performance in detecting AVBs,
with a sensitivity of 90.7% and a specificity of 86.05%. The accuracy
value is 87.9%.
Abstract: In this study, we propose a network architecture for
providing secure access to information resources of enterprise
network from remote locations in a wireless fashion. Our proposed
architecture offers a very promising solution for organizations which
are in need of a secure, flexible and cost-effective remote access
methodology. Security of the proposed architecture is based on
Virtual Private Network technology and a special role based access
control mechanism with location and time constraints. The flexibility
mainly comes from the use of Internet as the communication medium
and cost-effectiveness is due to the possibility of in-house
implementation of the proposed architecture.
Abstract: This paper presents a system overview of Mobile to Server Face Recognition, which is a face recognition application developed specifically for mobile phones. Images taken from mobile phone cameras lack of quality due to the low resolution of the cameras. Thus, a prototype is developed to experiment the chosen method. However, this paper shows a result of system backbone without the face recognition functionality. The result demonstrated in this paper indicates that the interaction between mobile phones and server is successfully working. The result shown before the database is completely ready. The system testing is currently going on using real images and a mock-up database to test the functionality of the face recognition algorithm used in this system. An overview of the whole system including screenshots and system flow-chart are presented in this paper. This paper also presents the inspiration or motivation and the justification in developing this system.
Abstract: The study in this paper underlines the importance of
correct joint selection of the spreading codes for uplink of multicarrier
code division multiple access (MC-CDMA) at the transmitter
side and detector at the receiver side in the presence of nonlinear
distortion due to high power amplifier (HPA). The bit error rate
(BER) of system for different spreading sequences (Walsh code, Gold
code, orthogonal Gold code, Golay code and Zadoff-Chu code) and
different kinds of receivers (minimum mean-square error receiver
(MMSE-MUD) and microstatistic multi-user receiver (MSF-MUD))
is compared by means of simulations for MC-CDMA transmission
system. Finally, the results of analysis will show, that the application
of MSF-MUD in combination with Golay codes can outperform
significantly the other tested spreading codes and receivers for all
mostly used models of HPA.
Abstract: This article presents the simulation, parameterization and optimization of an electromagnet with the C–shaped configuration, intended for the study of magnetic properties of materials. The electromagnet studied consists of a C-shaped yoke, which provides self–shielding for minimizing losses of magnetic flux density, two poles of high magnetic permeability and power coils wound on the poles. The main physical variable studied was the static magnetic flux density in a column within the gap between the poles, with 4cm2 of square cross section and a length of 5cm, seeking a suitable set of parameters that allow us to achieve a uniform magnetic flux density of 1x104 Gaussor values above this in the column, when the system operates at room temperature and with a current consumption not exceeding 5A. By means of a magnetostatic analysis by the finite element method, the magnetic flux density and the distribution of the magnetic field lines were visualized and quantified. From the results obtained by simulating an initial configuration of electromagnet, a structural optimization of the geometry of the adjustable caps for the ends of the poles was performed. The magnetic permeability effect of the soft magnetic materials used in the poles system, such as low– carbon steel (0.08% C), Permalloy (45% Ni, 54.7% Fe) and Mumetal (21.2% Fe, 78.5% Ni), was also evaluated. The intensity and uniformity of the magnetic field in the gap showed a high dependence with the factors described above. The magnetic field achieved in the column was uniform and its magnitude ranged between 1.5x104 Gauss and 1.9x104 Gauss according to the material of the pole used, with the possibility of increasing the magnetic field by choosing a suitable geometry of the cap, introducing a cooling system for the coils and adjusting the spacing between the poles. This makes the device a versatile and scalable tool to generate the magnetic field necessary to perform magnetic characterization of materials by techniques such as vibrating sample magnetometry (VSM), Hall-effect, Kerr-effect magnetometry, among others. Additionally, a CAD design of the modules of the electromagnet is presented in order to facilitate the construction and scaling of the physical device.
Abstract: In this paper, an adaptive radio resource allocation
(RRA) algorithm applying to multiple traffic OFDMA system is
proposed, which distributes sub-carrier and loading bits among users
according to their different QoS requirements and traffic class. By
classifying and prioritizing the users based on their traffic
characteristic and ensuring resource for higher priority users, the
scheme decreases tremendously the outage probability of the users
requiring a real time transmission without impact on the spectrum
efficiency of system, as well as the outage probability of data users is
not increased compared with the RRA methods published.