Abstract: We see in the present day scenario that the Global
positioning system (GPS) has been an effective tool to track the
vehicle. However the adverse part of it is that it can only track a
vehicle-s position. Our present work provides a better platform to
track and disable a vehicle using wireless technology. In our system
we embed a microcomputer which monitors the series of automotive
systems like engine, fuel and braking system. The external USB
modem is connected with the microcomputer to provide 24 x 7
internet accesses. The microcomputer is synchronized with the
owner-s multimedia mobile by means of a software tool “REMOTE
DESKTOP". A unique username and password is provided to the
software tool, so that the owner can only access the microcomputer
through the internet on owner-s mobile. The key fact is that our
design is placed such that it is known only to the owner.
Abstract: Minor law breaking seems more and more to be a part
of adolescence behavior. An important risk factor which seems to
influence delinquency appears to be the socio-economic one.
According to Romanian statistics, during the first six months of 2012,
1,378 minors have committed various crimes, the most common
being theft, sexual offenses and violent assaults. Drug-related
offenses did not reach the gravity of those from high income
countries of the European Union, but have a continuous upward
during the last years.
The aim of our research was to examine whether delinquency in
adolescence is correlated to mental disorders or socio-economic and
familial factors. Forensic psychiatric expertise was performed to 79
adolescents who committed offenses between 01 January 2012 and
31 December 2012. Teenagers, with ages between 12 and 17, were
examined by day hospitalization in the University Clinic of
Psychiatry Craiova.
Abstract: This paper proposes a novel stereo vision technique
for top view book scanners which provide us with dense 3d point
clouds of page surfaces. This is a precondition to dewarp bound
volumes independent of 2d information on the page. Our method is
based on algorithms, which normally require the projection of pattern
sequences with structured light. We use image sequences of the
moving stripe lighting of the top view scanner instead of an additional
light projection. Thus the stereo vision setup is simplified without
losing measurement accuracy. Furthermore we improve a surface
model dewarping method through introducing a difference vector
based on real measurements. Although our proposed method is hardly
expensive neither in calculation time nor in hardware requirements
we present good dewarping results even for difficult examples.
Abstract: The direct implementation of interleaver functions
in WiMAX is not hardware efficient due to presence of complex
functions. Also the conventional method i.e. using memories for
storing the permutation tables is silicon consuming. This work
presents a 2-D transformation for WiMAX channel interleaver
functions which reduces the overall hardware complexity to
compute the interleaver addresses on the fly. A fully reconfigurable
architecture for address generation in WiMAX
channel interleaver is presented, which consume 1.1 k-gates in
total. It can be configured for any block size and any modulation
scheme in WiMAX. The presented architecture can run at a
frequency of 200 MHz, thus fully supporting high bandwidth
requirements for WiMAX.
Abstract: Based on assumptions of neo-classical economics and
rational choice / public choice theory, this paper investigates the
regulation of industrial land use in Taiwan by homeowners
associations (HOAs) as opposed to traditional government
administration. The comparison, which applies the transaction cost
theory and a polynomial regression analysis, manifested that HOAs
are superior to conventional government administration in terms of
transaction costs and overall efficiency. A case study that compares
Taiwan-s commonhold industrial park, NangKang Software Park, to
traditional government counterparts using limited data on the costs
and returns was analyzed. This empirical study on the relative
efficiency of governmental and private institutions justified the
important theoretical proposition. Numerical results prove the
efficiency of the established model.
Abstract: The benefits of rooftop greenery systems (such as
energy savings, reduction of greenhouse gas emission for mitigating
climate change and maintaining sustainable development, indoor
temperature control etc.) in buildings are well recognized, however
there remains very little research conducted for quantifying the
benefits in subtropical climates such as in Australia. This study
mainly focuses on measuring/determining temperature profile and air
conditioning energy savings by implementing rooftop greenery
systems in subtropical Central Queensland in Australia. An
experimental set-up was installed at Rockhampton campus of Central
Queensland University, where two standard shipping containers (6m
x 2.4m x 2.4m) were converted into small offices, one with green
roof and one without. These were used for temperature, humidity and
energy consumption data collection. The study found that an energy
savings of up to 11.70% and temperature difference of up to 4°C can
be achieved in March in subtropical Central Queensland climate in
Australia. It is expected that more energy can be saved in peak
summer days (December/February) as temperature difference
between green roof and non-green roof is higher in December-
February.
Abstract: The ElectroEncephaloGram (EEG) is useful for
clinical diagnosis and biomedical research. EEG signals often
contain strong ElectroOculoGram (EOG) artifacts produced
by eye movements and eye blinks especially in EEG recorded
from frontal channels. These artifacts obscure the underlying
brain activity, making its visual or automated inspection
difficult. The goal of ocular artifact removal is to remove
ocular artifacts from the recorded EEG, leaving the underlying
background signals due to brain activity. In recent times,
Independent Component Analysis (ICA) algorithms have
demonstrated superior potential in obtaining the least
dependent source components. In this paper, the independent
components are obtained by using the JADE algorithm (best
separating algorithm) and are classified into either artifact
component or neural component. Neural Network is used for
the classification of the obtained independent components.
Neural Network requires input features that exactly represent
the true character of the input signals so that the neural
network could classify the signals based on those key
characters that differentiate between various signals. In this
work, Auto Regressive (AR) coefficients are used as the input
features for classification. Two neural network approaches
are used to learn classification rules from EEG data. First, a
Polynomial Neural Network (PNN) trained by GMDH (Group
Method of Data Handling) algorithm is used and secondly,
feed-forward neural network classifier trained by a standard
back-propagation algorithm is used for classification and the
results show that JADE-FNN performs better than JADEPNN.
Abstract: The objective of our work is to develop a new approach for discovering knowledge from a large mass of data, the result of applying this approach will be an expert system that will serve as diagnostic tools of a phenomenon related to a huge information system. We first recall the general problem of learning Bayesian network structure from data and suggest a solution for optimizing the complexity by using organizational and optimization methods of data. Afterward we proposed a new heuristic of learning a Multi-Entities Bayesian Networks structures. We have applied our approach to biological facts concerning hereditary complex illnesses where the literatures in biology identify the responsible variables for those diseases. Finally we conclude on the limits arched by this work.
Abstract: Information hiding, especially watermarking is a
promising technique for the protection of intellectual property rights.
This technology is mainly advanced for multimedia but the same has
not been done for text. Web pages, like other documents, need a
protection against piracy. In this paper, some techniques are
proposed to show how to hide information in web pages using some
features of the markup language used to describe these pages. Most
of the techniques proposed here use the white space to hide
information or some varieties of the language in representing
elements. Experiments on a very small page and analysis of five
thousands web pages show that these techniques have a wide
bandwidth available for information hiding, and they might form a
solid base to develop a robust algorithm for web page watermarking.
Abstract: In this paper, we present user pattern learning
algorithm based MDSS (Medical Decision support system) under
ubiquitous. Most of researches are focus on hardware system, hospital
management and whole concept of ubiquitous environment even
though it is hard to implement. Our objective of this paper is to design
a MDSS framework. It helps to patient for medical treatment and
prevention of the high risk patient (COPD, heart disease, Diabetes).
This framework consist database, CAD (Computer Aided diagnosis
support system) and CAP (computer aided user vital sign prediction
system). It can be applied to develop user pattern learning algorithm
based MDSS for homecare and silver town service. Especially this
CAD has wise decision making competency. It compares current vital
sign with user-s normal condition pattern data. In addition, the CAP
computes user vital sign prediction using past data of the patient. The
novel approach is using neural network method, wireless vital sign
acquisition devices and personal computer DB system. An intelligent
agent based MDSS will help elder people and high risk patients to
prevent sudden death and disease, the physician to get the online
access to patients- data, the plan of medication service priority (e.g.
emergency case).
Abstract: This study was investigated on sampling and
analyzing water quality in water reservoir & water tower installed in
two kind of residential buildings and school facilities. Data of water
quality was collected for correlation analysis with frequency of
sanitization of water reservoir through questioning managers of
building about the inspection charts recorded on equipment for water
reservoir. Statistical software packages (SPSS) were applied to the
data of two groups (cleaning frequency and water quality) for
regression analysis to determine the optimal cleaning frequency of
sanitization. The correlation coefficient (R) in this paper represented
the degree of correlation, with values of R ranging from +1 to -1.After
investigating three categories of drinking water users; this study found
that the frequency of sanitization of water reservoir significantly
influenced the water quality of drinking water. A higher frequency of
sanitization (more than four times per 1 year) implied a higher quality
of drinking water. Results indicated that sanitizing water reservoir &
water tower should at least twice annually for achieving the aim of
safety of drinking water.
Abstract: Ethanol is generally used as a therapeutic reagent against Hepatocellular carcinoma (HCC or hepatoma) worldwide, as it can induce Hepatocellular carcinoma cell apoptosis at low concentration through a multifactorial process regulated by several unknown proteins. This paper provides a simple and available proteomic strategy for exploring differentially expressed proteins in the apoptotic pathway. The appropriate concentrations of ethanol required to induce HepG2 cell apoptosis were first assessed by MTT assay, Gisma and fluorescence staining. Next, the central proteins involved in the apoptosis pathway processs were determined using 2D-PAGE, SDS-PAGE, and bio-software analysis. Finally the downregulation of two proteins, AFP and survivin, were determined by immunocytochemistry and reverse transcriptase PCR (RT-PCR) technology. The simple, useful method demonstrated here provides a new approach to proteomic analysis in key bio-regulating process including proliferation, differentiation, apoptosis, immunity and metastasis.
Abstract: This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of pulping problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified odified problem M-1 Ax= M-1b where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.
Abstract: Chronic conditions carry with them strong emotions
and often lead to charged relationships between patients and their
health providers and, by extension, patients and health researchers.
Persons are both autonomous and relational and a purely cognitive
model of autonomy neglects the social and relational basis of chronic
illness. Ensuring genuine informed consent in research requires a
thorough understanding of how participants perceive a study and
their reasons for participation. Surveys may not capture the
complexities of reasoning that underlies study participation.
Contradictory reasons for participation, for instance an initial claim
of altruism as rationale and a subsequent claim of personal benefit
(therapeutic misconception), affect the quality of informed consent.
Individuals apply principles through the filter of personal values and
lived experience. Authentic autonomy, and hence authentic consent
to research, occurs within the context of patients- unique life
narratives and illness experiences.
Abstract: Grid composite structures have many applications in aerospace industry in which deal with transverse loadings abundantly. In present paper a stiffened composite cylindrical shell with clamped-free boundary condition under transverse end load experimentally and numerically was studied. Some electrical strain gauges were employed to measure the strains. Also a finite element analysis was done for validation of experimental result. The FEM software used was ANSYS11. In addition, the results between stiffened composite shell and unstiffened composite shell were compared. It was observed that intersection of two stiffeners has an important effect in decrease of stress in the shell. Fairly good agreements were observed between the numerical and the measured results. According to recent studies about grid composite structures, it should be noted that any investigation like this research has not been reported.
Abstract: Recent years have seen a growing trend towards the
integration of multiple information sources to support large-scale
prediction of protein-protein interaction (PPI) networks in model
organisms. Despite advances in computational approaches, the
combination of multiple “omic" datasets representing the same type
of data, e.g. different gene expression datasets, has not been
rigorously studied. Furthermore, there is a need to further investigate
the inference capability of powerful approaches, such as fullyconnected
Bayesian networks, in the context of the prediction of PPI
networks. This paper addresses these limitations by proposing a
Bayesian approach to integrate multiple datasets, some of which
encode the same type of “omic" data to support the identification of
PPI networks. The case study reported involved the combination of
three gene expression datasets relevant to human heart failure (HF).
In comparison with two traditional methods, Naive Bayesian and
maximum likelihood ratio approaches, the proposed technique can
accurately identify known PPI and can be applied to infer potentially
novel interactions.
Abstract: Since 1984 many schemes have been proposed for
digital signature protocol, among them those that based on discrete
log and factorizations. However a new identification scheme based
on iterated function (IFS) systems are proposed and proved to be
more efficient. In this study the proposed identification scheme is
transformed into a digital signature scheme by using a one way hash
function. It is a generalization of the GQ signature schemes. The
attractor of the IFS is used to obtain public key from a private one,
and in the encryption and decryption of a hash function. Our aim is
to provide techniques and tools which may be useful towards
developing cryptographic protocols. Comparisons between the
proposed scheme and fractal digital signature scheme based on RSA
setting, as well as, with the conventional Guillou-Quisquater
signature, and RSA signature schemes is performed to prove that, the
proposed scheme is efficient and with high performance.
Abstract: Autism Spectrum Disorder (ASD) is a pervasive developmental disorder which affects individuals with varying degrees of impairment. Currently, there has been ample research done in serious game for autism children. Although serious games are traditionally associated with software developments, developing them in the autism field involves studying the associated technology and paying attention to aspects related to interaction with the game. Serious Games for autism cover matters related to education, therapy for communication, psychomotor treatment and social behavior enhancement. In this paper, a systematic review sets out the lines of development and research currently being conducted into serious games which pursue some form of benefit in the field of autism. This paper includes a literature review of relevant serious game developments since in year 2007 and examines new trends.
Abstract: Grid computing provides an effective infrastructure for massive computation among flexible and dynamic collection of individual system for resource discovery. The major challenge for grid computing is to prevent breaches and secure the data from trespassers. To overcome such conflicts a semantic approach can be designed which will filter the access requests of peers by checking the resource description specifying the data and the metadata as factual statements. Between every node in the grid a semantic firewall as a middleware will be present The intruder will be required to present an application specifying there needs to the firewall and hence accordingly the system will grant or deny the application request.
Abstract: Using vision based solution in intelligent vehicle application often needs large memory to handle video stream and image process which increase complexity of hardware and software. In this paper, we present a FPGA implement of a vision based lane departure warning system. By taking frame of videos, the line gradient of line is estimated and the lane marks are found. By analysis the position of lane mark, departure of vehicle will be detected in time. This idea has been implemented in Xilinx Spartan6 FPGA. The lane departure warning system used 39% logic resources and no memory of the device. The average availability is 92.5%. The frame rate is more than 30 frames per second (fps).