Abstract: Wireless sensor networks (WSN) are currently
receiving significant attention due to their unlimited potential. These
networks are used for various applications, such as habitat
monitoring, automation, agriculture, and security. The efficient nodeenergy
utilization is one of important performance factors in wireless
sensor networks because sensor nodes operate with limited battery
power. In this paper, we proposed the MiSense hierarchical cluster
based routing algorithm (MiCRA) to extend the lifetime of sensor
networks and to maintain a balanced energy consumption of nodes.
MiCRA is an extension of the HEED algorithm with two levels of
cluster heads. The performance of the proposed protocol has been
examined and evaluated through a simulation study. The simulation
results clearly show that MiCRA has a better performance in terms of
lifetime than HEED. Indeed, MiCRA our proposed protocol can
effectively extend the network lifetime without other critical
overheads and performance degradation. It has been noted that there
is about 35% of energy saving for MiCRA during the clustering
process and 65% energy savings during the routing process compared
to the HEED algorithm.
Abstract: Migration in breast cancer cell wound healing assay
had been studied using image fractal dimension analysis. The
migration of MDA-MB-231 cells (highly motile) in a wound healing
assay was captured using time-lapse phase contrast video microscopy
and compared to MDA-MB-468 cell migration (moderately motile).
The Higuchi fractal method was used to compute the fractal
dimension of the image intensity fluctuation along a single pixel
width region parallel to the wound. The near-wound region fractal
dimension was found to decrease three times faster in the MDA-MB-
231 cells initially as compared to the less cancerous MDA-MB-468
cells. The inner region fractal dimension was found to be fairly
constant for both cell types in time and suggests a wound influence
range of about 15 cell layer. The box-counting fractal dimension
method was also used to study region of interest (ROI). The MDAMB-
468 ROI area fractal dimension was found to decrease
continuously up to 7 hours. The MDA-MB-231 ROI area fractal
dimension was found to increase and is consistent with the behavior
of a HGF-treated MDA-MB-231 wound healing assay posted in the
public domain. A fractal dimension based capacity index has been
formulated to quantify the invasiveness of the MDA-MB-231 cells in
the perpendicular-to-wound direction. Our results suggest that image
intensity fluctuation fractal dimension analysis can be used as a tool
to quantify cell migration in terms of cancer severity and treatment
responses.
Abstract: The hydrolysis kinetics of polycrystalline lithium hydride (LiH) in argon at various low humidities was measured by gravimetry and Raman spectroscopy with ambient water concentration ranging from 200 to 1200 ppm. The results showed that LiH hydrolysis curve revealed a paralinear shape, which was attributed to two different reaction stages that forming different products as explained by the 'Layer Diffusion Control' model. Based on the model, a novel two-stage rate equation for LiH hydrolysis reactions was developed and used to fit the experimental data for determination of Li2O steady thickness Hs and the ultimate hydrolysis rate vs. The fitted data presented a rise of Hs as ambient water concentration cw increased. However, in spite of the negative effect imposed by Hs increasing, the upward trend of vs remained, which implied that water concentration, rather than Li2O thickness, played a predominant role in LiH hydrolysis kinetics. In addition, the proportional relationship between vsHs and cw predicted by rate equation and confirmed by gravimetric data validated the model in such conditions.
Abstract: The quest of providing more secure identification
system has led to a rise in developing biometric systems. Dorsal
hand vein pattern is an emerging biometric which has attracted the
attention of many researchers, of late. Different approaches have
been used to extract the vein pattern and match them. In this work,
Principle Component Analysis (PCA) which is a method that has
been successfully applied on human faces and hand geometry is
applied on the dorsal hand vein pattern. PCA has been used to obtain
eigenveins which is a low dimensional representation of vein pattern
features. Low cost CCD cameras were used to obtain the vein
images. The extraction of the vein pattern was obtained by applying
morphology. We have applied noise reduction filters to enhance the
vein patterns. The system has been successfully tested on a database
of 200 images using a threshold value of 0.9. The results obtained are
encouraging.
Abstract: Context awareness is a capability whereby mobile
computing devices can sense their physical environment and adapt
their behavior accordingly. The term context-awareness, in
ubiquitous computing, was introduced by Schilit in 1994 and has
become one of the most exciting concepts in early 21st-century
computing, fueled by recent developments in pervasive computing
(i.e. mobile and ubiquitous computing). These include computing
devices worn by users, embedded devices, smart appliances, sensors
surrounding users and a variety of wireless networking technologies.
Context-aware applications use context information to adapt
interfaces, tailor the set of application-relevant data, increase the
precision of information retrieval, discover services, make the user
interaction implicit, or build smart environments. For example: A
context aware mobile phone will know that the user is currently in a
meeting room, and reject any unimportant calls. One of the major
challenges in providing users with context-aware services lies in
continuously monitoring their contexts based on numerous sensors
connected to the context aware system through wireless
communication. A number of context aware frameworks based on
sensors have been proposed, but many of them have neglected the
fact that monitoring with sensors imposes heavy workloads on
ubiquitous devices with limited computing power and battery. In this
paper, we present CALEEF, a lightweight and energy efficient
context aware framework for resource limited ubiquitous devices.
Abstract: An unsupervised classification algorithm is derived
by modeling observed data as a mixture of several mutually
exclusive classes that are each described by linear combinations of
independent non-Gaussian densities. The algorithm estimates the
data density in each class by using parametric nonlinear functions
that fit to the non-Gaussian structure of the data. This improves
classification accuracy compared with standard Gaussian mixture
models. When applied to textures, the algorithm can learn basis
functions for images that capture the statistically significant structure
intrinsic in the images. We apply this technique to the problem of
unsupervised texture classification and segmentation.
Abstract: This paper discusses a new, systematic approach to
the synthesis of a NP-hard class of non-regenerative Boolean
networks, described by FON[FOFF]={mi}[{Mi}], where for every
mj[Mj]∈{mi}[{Mi}], there exists another mk[Mk]∈{mi}[{Mi}], such
that their Hamming distance HD(mj, mk)=HD(Mj, Mk)=O(n), (where
'n' represents the number of distinct primary inputs). The method
automatically ensures exact minimization for certain important selfdual
functions with 2n-1 points in its one-set. The elements meant for
grouping are determined from a newly proposed weighted incidence
matrix. Then the binary value corresponding to the candidate pair is
correlated with the proposed binary value matrix to enable direct
synthesis. We recommend algebraic factorization operations as a post
processing step to enable reduction in literal count. The algorithm
can be implemented in any high level language and achieves best
cost optimization for the problem dealt with, irrespective of the
number of inputs. For other cases, the method is iterated to
subsequently reduce it to a problem of O(n-1), O(n-2),.... and then
solved. In addition, it leads to optimal results for problems exhibiting
higher degree of adjacency, with a different interpretation of the
heuristic, and the results are comparable with other methods.
In terms of literal cost, at the technology independent stage, the
circuits synthesized using our algorithm enabled net savings over
AOI (AND-OR-Invert) logic, AND-EXOR logic (EXOR Sum-of-
Products or ESOP forms) and AND-OR-EXOR logic by 45.57%,
41.78% and 41.78% respectively for the various problems.
Circuit level simulations were performed for a wide variety of
case studies at 3.3V and 2.5V supply to validate the performance of
the proposed method and the quality of the resulting synthesized
circuits at two different voltage corners. Power estimation was
carried out for a 0.35micron TSMC CMOS process technology. In
comparison with AOI logic, the proposed method enabled mean
savings in power by 42.46%. With respect to AND-EXOR logic, the
proposed method yielded power savings to the tune of 31.88%, while
in comparison with AND-OR-EXOR level networks; average power
savings of 33.23% was obtained.
Abstract: Water is the main component of biological processes.
Water management is important to obtain higher productivity. In this
study, some of the yield components were investigated together with
different drought levels. Four chickpea genotypes (CDC Frontier,
CDC Luna, Sawyer and Sierra) were grown in pots with 3 different
irrigation levels (a dose of 17.5 ml, 35 ml and 70 ml for each pot per
day) after three weeks from sowing. In the research, flowering, pod
set, pod per plant, fertile pod, double seed/pod, stem diameter, plant
weight, seed per plant, 1000 seed weight, seed diameter, vegetation
length and weekly plant height were measured. Consequently,
significant differences were observed on all the investigated
characteristics owing to genotypes (except double seed/pod and stem
diameter), water levels (except first pod, seed weight and height on
3rd week) and genotype x water level interaction (except first pod,
double seed/pod, seed weight and height).
Abstract: The crystalline quality of the AlGaN/GaN high electron mobility transistor (HEMT) structure grown on a 200 mm silicon substrate has been investigated using UV-visible micro- Raman scattering and photoluminescence (PL). The visible Raman scattering probes the whole nitride stack with the Si substrate and shows the presence of a small component of residual in-plane stress in the thick GaN buffer resulting from a wafer bowing, while the UV micro-Raman indicates a tensile interfacial stress induced at the top GaN/AlGaN/AlN layers. PL shows a good crystal quality GaN channel where the yellow band intensity is very low compared to that of the near-band-edge transition. The uniformity of this sample is shown by measurements from several points across the epiwafer.
Abstract: Content-based music retrieval generally involves analyzing, searching and retrieving music based on low or high level features of a song which normally used to represent artists, songs or music genre. Identifying them would normally involve feature extraction and classification tasks. Theoretically the greater features analyzed, the better the classification accuracy can be achieved but with longer execution time. Technique to select significant features is important as it will reduce dimensions of feature used in classification and contributes to the accuracy. Artificial Immune System (AIS) approach will be investigated and applied in the classification task. Bio-inspired audio content-based retrieval framework (B-ACRF) is proposed at the end of this paper where it embraces issues that need further consideration in music retrieval performances.
Abstract: This paper examines the interplay of policy options
and cost-effective technology in providing sustainable distance
education. A case study has been conducted among the learners and
teachers. The emergence of learning technologies through CD,
internet, and mobile is increasingly adopted by distance institutes for
quick delivery and cost-effective factors. Their sustainability is
conditioned by the structure of learners and well as the teaching
community. The structure of learners in terms of rural and urban
background revealed similarity in adoption and utilization of mobile
learning. In other words, the technology transcended the rural-urban
dichotomy. The teaching community was divided into two groups on
policy issues. This study revealed both cost-effective as well as
sustainability impacts on different learners groups divided by rural
and urban location.
Abstract: In this paper, subtractive clustering based fuzzy inference system approach is used for early detection of faults in the function oriented software systems. This approach has been tested with real time defect datasets of NASA software projects named as PC1 and CM1. Both the code based model and joined model (combination of the requirement and code based metrics) of the datasets are used for training and testing of the proposed approach. The performance of the models is recorded in terms of Accuracy, MAE and RMSE values. The performance of the proposed approach is better in case of Joined Model. As evidenced from the results obtained it can be concluded that Clustering and fuzzy logic together provide a simple yet powerful means to model the earlier detection of faults in the function oriented software systems.
Abstract: In this paper the concept of strongly (λM)p - Ces'aro
summability of a sequence of fuzzy numbers and strongly λM- statistically convergent sequences of fuzzy numbers is introduced.
Abstract: Stress Concentration Factors are significant in
machine design as it gives rise to localized stress when any change in
the design of surface or abrupt change in the cross section occurs.
Almost all machine components and structural members contain
some form of geometrical or microstructural discontinuities. These
discontinuities are very dangerous and lead to failure. So, it is very
much essential to analyze the stress concentration factors for critical
applications like Turbine Rotors. In this paper Finite Element
Analysis (FEA) with extremely fine mesh in the vicinity of the
blades of Steam Turbine Rotor is applied to determine stress
concentration factors. A model of Steam Turbine Rotor is shown in
Fig. 1.
Abstract: In this paper the concept of strongly (λM)p - Ces'aro
summability of a sequence of fuzzy numbers and strongly λM- statistically convergent sequences of fuzzy numbers is introduced.
Abstract: A diamond-like carbon (DLC) based solid-lubricant
film was designed and DLC films were successfully prepared using a
microwave plasma enhanced magnetron sputtering deposition
technology. Post-test characterizations including Raman
spectrometry, X-ray diffraction, nano-indentation test, adhesion test,
friction coefficient test were performed to study the influence of
substrate bias voltage on the mechanical properties of the W- and
S-doped DLC films. The results indicated that the W- and S-doped
DLC films also had the typical structure of DLC films and a better
mechanical performance achieved by the application of a substrate
bias of -200V.
Abstract: In an interval graph G = (V,E) the distance between two vertices u, v is de£ned as the smallest number of edges in a path joining u and v. The eccentricity of a vertex v is the maximum among distances from all other vertices of V . The diameter (δ) and radius (ρ) of the graph G is respectively the maximum and minimum among all the eccentricities of G. The center of the graph G is the set C(G) of vertices with eccentricity ρ. In this context our aim is to establish the relation ρ = δ 2 for an interval graph and to determine the center of it.
Abstract: This paper discusses two observers, which are used
for the estimation of parameters of PMSM. Former one, reduced
order observer, which is used to estimate the inaccessible parameters
of PMSM. Later one, full order observer, which is used to estimate
all the parameters of PMSM even though some of the parameters are
directly available for measurement, so as to meet with the
insensitivity to the parameter variation. However, the state space
model contains some nonlinear terms i.e. the product of different
state variables. The asymptotic state observer, which approximately
reconstructs the state vector for linear systems without uncertainties,
was presented by Luenberger. In this work, a modified form of such
an observer is used by including a non-linear term involving the
speed. So, both the observers are designed in the framework of
nonlinear control; their stability and rate of convergence is discussed.
Abstract: Post growth annealing of solution grown ZnO
nanowire array is performed under controlled oxygen ambience. The
role of annealing over surface defects and their consequence on
dark/photo-conductivity and photosensitivity of nanowire array is
investigated. Surface defect properties are explored using various
measurement tools such as contact angle, photoluminescence, Raman
spectroscopy and XPS measurements. The contact angle of the NW
films reduces due to oxygen annealing and nanowire film surface
changes from hydrophobic (96°) to hydrophilic (16°). Raman and
XPS spectroscopy reveal that oxygen annealing improves the crystal
quality of the nanowire films. The defect band emission intensity
(relative to band edge emission, ID/IUV) reduces from 1.3 to 0.2 after
annealing at 600 °C at 10 SCCM flow of oxygen. An order
enhancement in dark conductivity is observed in O2 annealed
samples, while photoconductivity is found to be slightly reduced due
to lower concentration of surface related oxygen defects.
Abstract: We present a new approach to evaluation of Cyber Security in Power Systems using the method of modeling the power systems Infrastructure using software agents. Interfaces between module and the home smart meter are recognized as the primary points of intrusion.