Abstract: The study investigated the hydrophilic to hydrophobic
transition of modified polyacrylamide hydrogel with the inclusion of
N-isopropylacrylamide (NIAM). The modification was done by
mimicking micellar polymerization, which resulted in better
arrangement of NIAM chains in the polyacrylamide network. The
degree of NIAM arrangement is described by NH number. The
hydrophilic to hydrophobic transition was measured through the
partition coefficient, K, of Orange II and Methylene Blue in hydrogel
and in water. These dyes were chosen as a model for solutes with
different degree of hydrophobicity. The study showed that the
hydrogel with higher NH values resulted in better solubility of both
dyes. Moreover, in temperature above the lower critical solution
temperature (LCST) of Poly(N-isopropylacrylamide) (PNIAM)also
caused the collapse of NIPAM chains which results in a more
hydrophobic environment that increases the solubility of Methylene
Blue and decreases the solubility of Orange II in the hydrogels with
NIPAM present.
Abstract: Traffic management in an urban area is highly facilitated by the knowledge of the traffic conditions in every street or highway involved in the vehicular mobility system. Aim of the paper is to propose a neuro-fuzzy approach able to compute the main parameters of a traffic system, i.e., car density, velocity and flow, by using the images collected by the web-cams located at the crossroads of the traffic network. The performances of this approach encourage its application when the traffic system is far from the saturation. A fuzzy model is also outlined to evaluate when it is suitable to use more accurate, even if more time consuming, algorithms for measuring traffic conditions near to saturation.
Abstract: The paper proposes a methodology to process the signals coming from the Transcranial Magnetic Stimulation (TMS) in order to identify the pathology and evaluate the therapy to treat the patients affected by demency diseases. In particular, a fuzzy model is developed to identify the demency of the patients affected by Subcortical Ischemic Vascular Dementia (SIVD) and to measure the effect of a repetitive TMS on their motor performances. A tool is also presented to support the mentioned analysis.
Abstract: These days wireless local area networks has become
very popular, when the initial IEEE802.11 is the standard for
providing wireless connectivity to automatic machinery, equipment
and stations that require rapid deployment, which may be portable,
handheld or which may be mounted on moving vehicles within a
local area. IEEE802.11 Wireless local area network is a sharedmedium
communication network that transmits information over
wireless links for all IEEE802.11 stations in its transmission range to
receive. When a user is moving from one location to another, how
the other user knows about the required station inside WLAN. For
that we designed and implemented a system to locate a mobile user
inside the wireless local area network based on RSSI with the help of
four specially designed architectures. These architectures are based
on statistical or we can say manual configuration of mapping and
radio map of indoor and outdoor location with the help of available
Sniffer based and cluster based techniques. We found a better
location of a mobile user in WLAN. We tested this work in indoor
and outdoor environments with different locations with the help of
Pamvotis, a simulator for WLAN.
Abstract: Robustness is one of the primary performance criteria for an Intelligent Video Surveillance (IVS) system. One of the key factors in enhancing the robustness of dynamic video analysis is,providing accurate and reliable means for shadow detection. If left undetected, shadow pixels may result in incorrect object tracking and classification, as it tends to distort localization and measurement information. Most of the algorithms proposed in literature are computationally expensive; some to the extent of equalling computational requirement of motion detection. In this paper, the homogeneity property of shadows is explored in a novel way for shadow detection. An adaptive division image (which highlights homogeneity property of shadows) analysis followed by a relatively simpler projection histogram analysis for penumbra suppression is the key novelty in our approach.
Abstract: this article proposed a methodology for computer
numerical control (CNC) machine scoring. The case study company
is a manufacturer of hard disk drive parts in Thailand. In this
company, sample of parts manufactured from CNC machine are
usually taken randomly for quality inspection. These inspection data
were used to make a decision to shut down the machine if it has
tendency to produce parts that are out of specification. Large amount
of data are produced in this process and data mining could be very
useful technique in analyzing them. In this research, data mining
techniques were used to construct a machine scoring model called
'machine priority assessment model (MPAM)'. This model helps to
ensure that the machine with higher risk of producing defective parts
be inspected before those with lower risk. If the defective prone
machine is identified sooner, defective part and rework could be
reduced hence improving the overall productivity. The results
showed that the proposed method can be successfully implemented
and approximately 351,000 baht of opportunity cost could have
saved in the case study company.
Abstract: Power consumption of nodes in ad hoc networks is a
critical issue as they predominantly operate on batteries. In order to
improve the lifetime of an ad hoc network, all the nodes must be
utilized evenly and the power required for connections must be
minimized. In this project a link layer algorithm known as Power
Aware medium Access Control (PAMAC) protocol is proposed
which enables the network layer to select a route with minimum total
power requirement among the possible routes between a source and a
destination provided all nodes in the routes have battery capacity
above a threshold. When the battery capacity goes below a
predefined threshold, routes going through these nodes will be
avoided and these nodes will act only as source and destination.
Further, the first few nodes whose battery power drained to the set
threshold value are pushed to the exterior part of the network and the
nodes in the exterior are brought to the interior. Since less total
power is required to forward packets for each connection. The
network layer protocol AOMDV is basically an extension to the
AODV routing protocol. AOMDV is designed to form multiple
routes to the destination and it also avoid the loop formation so that it
reduces the unnecessary congestion to the channel. In this project, the
performance of AOMDV is evaluated using PAMAC as a MAC layer
protocol and the average power consumption, throughput and
average end to end delay of the network are calculated and the results
are compared with that of the other network layer protocol AODV.
Abstract: Ireland developed a National Strategy 2030 that
argued for the creation of a new form of higher education institution,
a Technological University. The research reported here reviews the
first stage of this partnership development. The study found that
national policy can create system capacity and change, but that
individual partners may have more to gain or lose in collaborating.
When presented as a zero-sum activity, fear among partners is high.
The level of knowledge and networking within the higher education
system possessed by each partner contributed to decisions to
participate or not in a joint proposal for collaboration. Greater
success resulted when there were gains for all partners. This research
concludes that policy mandates can provide motivation to
collaborate, but that the partnership needs to be built more on shared
values versus coercion by mandates.
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: In this paper an approaches for increasing the
effectiveness of error detection in computer network channels with
Pulse-Amplitude Modulation (PAM) has been proposed. Proposed
approaches are based on consideration of special feature of errors,
which are appearances in line with PAM. The first approach consists
of CRC modification specifically for line with PAM. The second
approach is base of weighted checksums using. The way for
checksum components coding has been developed. It has been shown
that proposed checksum modification ensure superior digital data
control transformation reliability for channels with PAM in compare
to CRC.
Abstract: In this paper we propose a family of algorithms based
on 3rd and 4th order cumulants for blind single-input single-output
(SISO) Non-Minimum Phase (NMP) Finite Impulse Response (FIR)
channel estimation driven by non-Gaussian signal. The input signal
represents the signal used in 10GBASE-T (or IEEE 802.3an-2006)
as a Tomlinson-Harashima Precoded (THP) version of random
Pulse-Amplitude Modulation with 16 discrete levels (PAM-16). The
proposed algorithms are tested using three non-minimum phase
channel for different Signal-to-Noise Ratios (SNR) and for different
data input length. Numerical simulation results are presented to
illustrate the performance of the proposed 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: A novel thermo-sensitive superabsorbent hydrogel
with salt- and pH-responsiveness properties was obtained by grafting
of mixtures of acrylic acid (AA) and N-isopropylacrylamide
(NIPAM) monomers onto kappa-carrageenan, kC, using ammonium
persulfate (APS) as a free radical initiator in the presence of
methylene bisacrylamide (MBA) as a crosslinker. Infrared
spectroscopy was carried out to confirm the chemical structure of the
hydrogel. Moreover, morphology of the samples was examined by
scanning electron microscopy (SEM). The effect of MBA
concentration and AA/NIPAM weight ratio on the water absorbency
capacity has been investigated. The swelling variations of hydrogels
were explained according to swelling theory based on the hydrogel
chemical structure. The hydrogels exhibited salt-sensitivity and
cation exchange properties. The temperature- and pH-reversibility
properties of the hydrogels make the intelligent polymers as good
candidates for considering as potential carriers for bioactive agents,
e.g. drugs.
Abstract: A complex valued neural network is a neural network, which consists of complex valued input and/or weights and/or thresholds and/or activation functions. Complex-valued neural networks have been widening the scope of applications not only in electronics and informatics, but also in social systems. One of the most important applications of the complex valued neural network is in image and vision processing. In Neural networks, radial basis functions are often used for interpolation in multidimensional space. A Radial Basis function is a function, which has built into it a distance criterion with respect to a centre. Radial basis functions have often been applied in the area of neural networks where they may be used as a replacement for the sigmoid hidden layer transfer characteristic in multi-layer perceptron. This paper aims to present exhaustive results of using RBF units in a complex-valued neural network model that uses the back-propagation algorithm (called 'Complex-BP') for learning. Our experiments results demonstrate the effectiveness of a Radial basis function in a complex valued neural network in image recognition over a real valued neural network. We have studied and stated various observations like effect of learning rates, ranges of the initial weights randomly selected, error functions used and number of iterations for the convergence of error on a neural network model with RBF units. Some inherent properties of this complex back propagation algorithm are also studied and discussed.
Abstract: The problem of spam has been seriously troubling the Internet community during the last few years and currently reached an alarming scale. Observations made at CERN (European Organization for Nuclear Research located in Geneva, Switzerland) show that spam mails can constitute up to 75% of daily SMTP traffic. A naïve Bayesian classifier based on a Bag Of Words representation of an email is widely used to stop this unwanted flood as it combines good performance with simplicity of the training and classification processes. However, facing the constantly changing patterns of spam, it is necessary to assure online adaptability of the classifier. This work proposes combining such a classifier with another NBC (naïve Bayesian classifier) based on pairs of adjacent words. Only the latter will be retrained with examples of spam reported by users. Tests are performed on considerable sets of mails both from public spam archives and CERN mailboxes. They suggest that this architecture can increase spam recall without affecting the classifier precision as it happens when only the NBC based on single words is retrained.
Abstract: A 10bit, 40 MSps, sample and hold, implemented in 0.18-μm CMOS technology with 3.3V supply, is presented for application in the front-end stage of an analog-to-digital converter. Topology selection, biasing, compensation and common mode feedback are discussed. Cascode technique has been used to increase the dc gain. The proposed opamp provides 149MHz unity-gain bandwidth (wu), 80 degree phase margin and a differential peak to peak output swing more than 2.5v. The circuit has 55db Total Harmonic Distortion (THD), using the improved fully differential two stage operational amplifier of 91.7dB gain. The power dissipation of the designed sample and hold is 4.7mw. The designed system demonstrates relatively suitable response in different process, temperature and supply corners (PVT corners).
Abstract: The bit error rate (BER) performance for ultra-wide
band (UWB) indoor communication with impact of metallic furniture
is investigated. The impulse responses of different indoor
environments for any transmitter and receiver location are computed
by shooting and bouncing ray/image and inverse Fourier transform
techniques. By using the impulse responses of these multipath
channels, the BER performance for binary pulse amplitude
modulation (BPAM) impulse radio UWB communication system are
calculated. Numerical results have shown that the multi-path effect
by the metallic cabinets is an important factor for BER performance.
Also the outage probability for the UWB multipath environment with
metallic cabinets is more serious (about 18%) than with wooden
cabinets. Finally, it is worth noting that in these cases the present
work provides not only comparative information but also quantitative
information on the performance reduction.
Abstract: As the disfunctions of the information society and
social development progress, intrusion problems such as malicious
replies, spam mail, private information leakage, phishing, and
pharming, and side effects such as the spread of unwholesome
information and privacy invasion are becoming serious social
problems. Illegal access to information is also becoming a problem as
the exchange and sharing of information increases on the basis of the
extension of the communication network. On the other hand, as the
communication network has been constructed as an international,
global system, the legal response against invasion and cyber-attack
from abroad is facing its limit. In addition, in an environment where
the important infrastructures are managed and controlled on the basis
of the information communication network, such problems pose a
threat to national security. Countermeasures to such threats are
developed and implemented on a yearly basis to protect the major
infrastructures of information communication. As a part of such
measures, we have developed a methodology for assessing the
information protection level which can be used to establish the
quantitative object setting method required for the improvement of the
information protection level.
Abstract: In recent times, the problem of Unsolicited Bulk
Email (UBE) or commonly known as Spam Email, has increased at a
tremendous growth rate. We present an analysis of survey based on
classifications of UBE in various research works. There are many
research instances for classification between spam and non-spam
emails but very few research instances are available for classification
of spam emails, per se. This paper does not intend to assert some
UBE classification to be better than the others nor does it propose
any new classification but it bemoans the lack of harmony on number
and definition of categories proposed by different researchers. The
paper also elaborates on factors like intent of spammer, content of
UBE and ambiguity in different categories as proposed in related
research works of classifications of UBE.
Abstract: Educational institutions often implement policies with
the intention of influencing how learning and teaching occur.
Generally, such policies are not as effective as their makers would
like; changing the behavior of third-level teachers proves difficult.
Nevertheless, a policy instituted in 2006 at the Dublin Institute of
Technology has met with success: each newly hired faculty member
must have a post-graduate qualification in “Learning and Teaching"
or successfully complete one within the first two years of
employment. The intention is to build teachers- knowledge about
student-centered pedagogies and their capacity to implement them.
As a result of this policy (and associated programs that support it),
positive outcomes are readily apparent. Individual teachers who have
completed the programs have implemented significant change at the
course and program levels. This paper introduces the policy,
identifies outcomes in relation to existing theory, describes research
underway, and pinpoints areas where organizational learning has
occurred.