Abstract: As smartphones are equipped with various sensors,
there have been many studies focused on using these sensors to create
valuable applications. Human activity recognition is one such
application motivated by various welfare applications, such as the
support for the elderly, measurement of calorie consumption, lifestyle
and exercise patterns analyses, and so on. One of the challenges one
faces when using smartphone sensors for activity recognition is that
the number of sensors should be minimized to save battery power. In
this paper, we show that a fairly accurate classifier can be built that
can distinguish ten different activities by using only a single sensor
data, i.e., the smartphone accelerometer data. The approach that we
adopt to deal with this twelve-class problem uses various methods.
The features used for classifying these activities include not only the
magnitude of acceleration vector at each time point, but also the
maximum, the minimum, and the standard deviation of vector
magnitude within a time window. The experiments compared the
performance of four kinds of basic multi-class classifiers and the
performance of four kinds of ensemble learning methods based on
three kinds of basic multi-class classifiers. The results show that
while the method with the highest accuracy is ECOC based on
Random forest.
Abstract: These days, the industrial trend is moving away from heavy and bulky passive components to power converter systems that use more and more semiconductor elements. Also, it is difficult to connect the traditional converters to the high and medium voltage. For these reasons, a new family of multilevel inverters has appeared as a solution for working with higher voltage levels. Different modulation topologies like Sinusoidal Pulse Width Modulation (SPWM), Selective Harmonic Elimination Pulse Width Modulation (SHE-PWM) are available for multilevel inverters. In this work, different hybrid modulation techniques which are combination of fundamental frequency modulation and multilevel sinusoidal-modulation are compared. The main characteristic of these modulations are reduction of switching losses with good harmonic performance and balanced power loss dissipation among the device. The proposed hybrid modulation schemes are developed and simulated in Matlab/Simulink for cascaded H-bridge inverter. The results validate the applicability of the proposed schemes for cascaded multilevel inverter.
Abstract: This paper treats different aspects of entropy measure
in classical information theory and statistical quantum mechanics, it
presents the possibility of extending the definition of Von Neumann
entropy to image and array processing. In the first part, we generalize
the quantum entropy using singular values of arbitrary rectangular
matrices to measure the randomness and the quality of denoising
operation, this new definition of entropy can be implemented to
compare the performance analysis of filtering methods. In the second
part, we apply the concept of pure state in quantum formalism
to generalize the maximum entropy method for narrowband and
farfield source localization problem. Several computer simulation
results are illustrated to demonstrate the effectiveness of the proposed
techniques.
Abstract: Batch production plants provide a wide range of
scheduling problems. In pharmaceutical industries a batch process
is usually described by a recipe, consisting of an ordering of tasks
to produce the desired product. In this research work we focused
on pharmaceutical production processes requiring the culture of
a microorganism population (i.e. bacteria, yeasts or antibiotics).
Several sources of uncertainty may influence the yield of the culture
processes, including (i) low performance and quality of the cultured
microorganism population or (ii) microbial contamination. For
these reasons, robustness is a valuable property for the considered
application context. In particular, a robust schedule will not collapse
immediately when a cell of microorganisms has to be thrown away
due to a microbial contamination. Indeed, a robust schedule should
change locally in small proportions and the overall performance
measure (i.e. makespan, lateness) should change a little if at all.
In this research work we formulated a constraint programming
optimization (COP) model for the robust planning of antibiotics
production. We developed a discrete-time model with a multi-criteria
objective, ordering the different criteria and performing a
lexicographic optimization. A feasible solution of the proposed
COP model is a schedule of a given set of tasks onto available
resources. The schedule has to satisfy tasks precedence constraints,
resource capacity constraints and time constraints. In particular
time constraints model tasks duedates and resource availability
time windows constraints. To improve the schedule robustness, we
modeled the concept of (a, b) super-solutions, where (a, b) are input
parameters of the COP model. An (a, b) super-solution is one in
which if a variables (i.e. the completion times of a culture tasks)
lose their values (i.e. cultures are contaminated), the solution can be
repaired by assigning these variables values with a new values (i.e.
the completion times of a backup culture tasks) and at most b other
variables (i.e. delaying the completion of at most b other tasks).
The efficiency and applicability of the proposed model is
demonstrated by solving instances taken from a real-life
pharmaceutical company. Computational results showed that
the determined super-solutions are near-optimal.
Abstract: Commercial banks in Nigeria adopted many strategies
to attract fresh deposits including the use of high deposit rate.
However, pricing of banking services moved in favor of the banks at
the expense of customers, resulting in their seeking other investment
alternatives rather than saving their money in the bank. Both deposit
and lending rates were greatly influenced by the Central Bank of
Nigeria (CBN) decision on interest rate. Therefore, commercial bank
effort to attract deposits via manipulation of her rates was greatly
limited, otherwise the banks will be giving out more than it earned.
The study aimed at examining the relationship between interest rate
and fixed fund deposit of commercial banks, how policy-controlled
interest rate affected commercial bank’s fixed fund deposit The
researcher employed ordinary least square technique, using, multiple
linear regression, unrestricted vector auto-regression, correlation
matrix test, granger causality and impulse response graph in the
analysis. Commercial bank’s interest rates affected commercial
bank’s fixed fund deposit significantly while policy-controlled
interest rate did not significantly transmit through the commercial
bank’s interest rates to affect fixed fund deposit. While commercial
banks seek creative ways to expand their fixed fund deposit, policy
authorities in Nigeria should better coordinate interest rate fluctuation
and induce competition in the entire financial sector.
Abstract: Speaker Identification (SI) is the task of establishing
identity of an individual based on his/her voice characteristics. The SI
task is typically achieved by two-stage signal processing: training and
testing. The training process calculates speaker specific feature
parameters from the speech and generates speaker models
accordingly. In the testing phase, speech samples from unknown
speakers are compared with the models and classified. Even though
performance of speaker identification systems has improved due to
recent advances in speech processing techniques, there is still need of
improvement. In this paper, a Closed-Set Tex-Independent Speaker
Identification System (CISI) based on a Multiple Classifier System
(MCS) is proposed, using Mel Frequency Cepstrum Coefficient
(MFCC) as feature extraction and suitable combination of vector
quantization (VQ) and Gaussian Mixture Model (GMM) together
with Expectation Maximization algorithm (EM) for speaker
modeling. The use of Voice Activity Detector (VAD) with a hybrid
approach based on Short Time Energy (STE) and Statistical
Modeling of Background Noise in the pre-processing step of the
feature extraction yields a better and more robust automatic speaker
identification system. Also investigation of Linde-Buzo-Gray (LBG)
clustering algorithm for initialization of GMM, for estimating the
underlying parameters, in the EM step improved the convergence rate
and systems performance. It also uses relative index as confidence
measures in case of contradiction in identification process by GMM
and VQ as well. Simulation results carried out on voxforge.org
speech database using MATLAB highlight the efficacy of the
proposed method compared to earlier work.
Abstract: This paper deals with nonlinear vibration analysis
using finite element method for frame structures consisting of elastic
and viscoelastic damping layers supported by multiple nonlinear
concentrated springs with hysteresis damping. The frame is supported
by four nonlinear concentrated springs near the four corners. The
restoring forces of the springs have cubic non-linearity and linear
component of the nonlinear springs has complex quantity to represent
linear hysteresis damping. The damping layer of the frame structures
has complex modulus of elasticity. Further, the discretized equations in
physical coordinate are transformed into the nonlinear ordinary
coupled differential equations using normal coordinate corresponding
to linear natural modes. Comparing shares of strain energy of the
elastic frame, the damping layer and the springs, we evaluate the
influences of the damping couplings on the linear and nonlinear impact
responses. We also investigate influences of damping changed by
stiffness of the elastic frame on the nonlinear coupling in the damped
impact responses.
Abstract: In this paper, we report the development of the device
for diagnostics of cardiovascular system state and associated
automated workstation for large-scale medical measurement data
collection and analysis. It was shown that optimal design for the
monitoring device is wristband as it represents engineering trade-off
between accuracy and usability. Monitoring device is based on the
infrared reflective photoplethysmographic sensor, which allows
collecting multiple physiological parameters, such as heart rate and
pulsing wave characteristics. Developed device uses BLE interface
for medical and supplementary data transmission to the coupled
mobile phone, which processes it and send it to the doctor's
automated workstation. Results of this experimental model
approbation confirmed the applicability of the proposed approach.
Abstract: Low Temperature Matrix Isolation - Electron
Paramagnetic Resonance (LTMI-EPR) Spectroscopy was utilized to
identify the species of iron oxide nanoparticles generated during the
oxidative pyrolysis of 1-methylnaphthalene (1-MN). The otherwise
gas-phase reactions of 1--MN were impacted by a polypropylenimine
tetra-hexacontaamine dendrimer complexed with iron (III) nitrate
nonahydrate diluted in air under atmospheric conditions. The EPR
fine structure of Fe (III)2O3 nanoparticles clusters, characterized by gfactors
of 2.00, 2.28, 3.76 and 4.37 were detected on a cold finger
maintained at 77 K after accumulation over a multitude of
experiments. Additionally, a high valence Fe (IV) paramagnetic
intermediate and superoxide anion-radicals, O2•- adsorbed on
nanoparticle surfaces in the form of Fe (IV) --- O2•- were detected
from the quenching area of Zone 1 in the gas-phase.
Abstract: Studying on the response of vegetation phenology to
climate change at different temporal and spatial scales is important for
understanding and predicting future terrestrial ecosystem dynamics
and the adaptation of ecosystems to global change. In this study, the
Moderate Resolution Imaging Spectroradiometer (MODIS)
Normalized Difference Vegetation Index (NDVI) dataset and climate
data were used to analyze the dynamics of grassland phenology as well
as their correlation with climatic factors in different eco-geographic
regions and elevation units across the Tibetan Plateau. The results
showed that during 2003–2012, the start of the grassland greening
season (SOS) appeared later while the end of the growing season
(EOS) appeared earlier following the plateau’s precipitation and heat
gradients from southeast to northwest. The multi-year mean value of
SOS showed differences between various eco-geographic regions and
was significantly impacted by average elevation and regional average
precipitation during spring. Regional mean differences for EOS were
mainly regulated by mean temperature during autumn. Changes in
trends of SOS in the central and eastern eco-geographic regions were
coupled to the mean temperature during spring, advancing by about
7d/°C. However, in the two southwestern eco-geographic regions,
SOS was delayed significantly due to the impact of spring
precipitation. The results also showed that the SOS occurred later with
increasing elevation, as expected, with a delay rate of 0.66 d/100m.
For 2003–2012, SOS showed an advancing trend in low-elevation
areas, but a delayed trend in high-elevation areas, while EOS was
delayed in low-elevation areas, but advanced in high-elevation areas.
Grassland SOS and EOS changes may be influenced by a variety of
other environmental factors in each eco-geographic region.
Abstract: In this study, a multi objective optimization for end
milling of Al 6061 alloy has been presented to provide better
surface quality and higher Material Removal Rate (MRR). The input
parameters considered for the analysis are spindle speed, depth of cut
and feed. The experiments were planned as per Taguchis design of
experiment, with L27 orthogonal array. The Grey Relational Analysis
(GRA) has been used for transforming multiple quality responses
into a single response and the weights of the each performance
characteristics are determined by employing the Principal Component
Analysis (PCA), so that their relative importance can be properly and
objectively described. The results reveal that Taguchi based G-PCA
can effectively acquire the optimal combination of cutting parameters.
Abstract: Liquid-Liquid Equilibrium (LLE) data are measured
for the ternary mixtures of water + 1-butanol + butyl acetate and
quaternary mixtures of water + 1-butanol + butyl acetate + glycerol at
atmospheric pressure at 313.15 K. In addition, isothermal
vapor–liquid–liquid equilibrium (VLLE) data are determined
experimentally at 333.15 K. The region of heterogeneity is found to
increase as the hydrophilic agent (glycerol) is introduced into the
aqueous mixtures. The experimental data are correlated with the
NRTL model. The predicted results from the solution model with the
model parameters determined from the constituent binaries are also
compared with the experimental values.
Abstract: In this paper, analysis of an infinite beam resting on
multilayer tensionless extensible geosynthetic reinforced granular
fill-poor soil system overlying soft soil strata under moving load with
constant velocity is presented. The beam is subjected to a
concentrated load moving with constant velocity. The upper
reinforced granular bed is modeled by a rough membrane embedded
in Pasternak shear layer overlying a series of compressible nonlinear
winkler springs representing the underlying the very poor soil. The
multilayer tensionless extensible geosynthetic layer has been
assumed to deform such that at interface the geosynthetic and the soil
have some deformation. Nonlinear behaviour of granular fill and the
very poor soil has been considered in the analysis by means of
hyperbolic constitutive relationships. Governing differential
equations of the soil foundation system have been obtained and
solved with the help of appropriate boundary conditions. The solution
has been obtained by employing finite difference method by means of
Gauss-Siedal iterative scheme. Detailed parametric study has been
conducted to study the influence of various parameters on the
response of soil–foundation system under consideration by means of
deflection and bending moment in the beam and tension mobilized in
the geosynthetic layer. These parameters include magnitude of
applied load, velocity of load, damping, ultimate resistance of poor
soil and granular fill layer. Range of values of parameters has been
considered as per Indian Railway conditions. This study clearly
observed that the comparisons of multilayer tensionless extensible
geosynthetic reinforcement with poor foundation soil and magnitude
of applied load, relative compressibility of granular fill and ultimate
resistance of poor soil has significant influence on the response of
soil–foundation system.
Abstract: Workflow scheduling is an important part of cloud
computing and based on different criteria it decides cost, execution
time, and performances. A cloud workflow system is a platform
service facilitating automation of distributed applications based on
new cloud infrastructure. An aspect which differentiates cloud
workflow system from others is market-oriented business model, an
innovation which challenges conventional workflow scheduling
strategies. Time and Cost optimization algorithm for scheduling
Hybrid Clouds (TCHC) algorithm decides which resource should be
chartered from public providers is combined with a new De-De
algorithm considering that every instance of single and multiple
workflows work without deadlocks. To offset this, two new concepts
- De-De Dodging Algorithm and Priority Based Decisive Algorithm -
combine with conventional deadlock avoidance issues by proposing
one algorithm that maximizes active (not just allocated) resource use
and reduces Makespan.
Abstract: Particle size distribution, the most important
characteristics of aerosols, is obtained through electrical
characterization techniques. The dynamics of charged nanoparticles
under the influence of electric field in Electrical Mobility
Spectrometer (EMS) reveals the size distribution of these particles.
The accuracy of this measurement is influenced by flow conditions,
geometry, electric field and particle charging process, therefore by
the transfer function (transfer matrix) of the instrument. In this work,
a wire-cylinder corona charger was designed and the combined fielddiffusion
charging process of injected poly-disperse aerosol particles
was numerically simulated as a prerequisite for the study of a
multichannel EMS. The result, a cloud of particles with no uniform
charge distribution, was introduced to the EMS. The flow pattern and
electric field in the EMS were simulated using Computational Fluid
Dynamics (CFD) to obtain particle trajectories in the device and
therefore to calculate the reported signal by each electrometer.
According to the output signals (resulted from bombardment of
particles and transferring their charges as currents), we proposed a
modification to the size of detecting rings (which are connected to
electrometers) in order to evaluate particle size distributions more
accurately. Based on the capability of the system to transfer
information contents about size distribution of the injected particles,
we proposed a benchmark for the assessment of optimality of the
design. This method applies the concept of Von Neumann entropy
and borrows the definition of entropy from information theory
(Shannon entropy) to measure optimality. Entropy, according to the
Shannon entropy, is the ''average amount of information contained in
an event, sample or character extracted from a data stream''.
Evaluating the responses (signals) which were obtained via various
configurations of detecting rings, the best configuration which gave
the best predictions about the size distributions of injected particles,
was the modified configuration. It was also the one that had the
maximum amount of entropy. A reasonable consistency was also
observed between the accuracy of the predictions and the entropy
content of each configuration. In this method, entropy is extracted
from the transfer matrix of the instrument for each configuration.
Ultimately, various clouds of particles were introduced to the
simulations and predicted size distributions were compared to the
exact size distributions.
Abstract: The design of Reverse logistics Network has attracted
growing attention with the stringent pressures from both
environmental awareness and business sustainability. Reverse
logistical activities include return, remanufacture, disassemble and
dispose of products can be quite complex to manage. In addition,
demand can be difficult to predict, and decision making is one of the
challenges task in such network. This complexity has amplified the
need to develop an integrated architecture for product return as an
enterprise system. The main purpose of this paper is to design Multi
Agent System (MAS) architecture using the Prometheus
methodology to efficiently manage reverse logistics processes. The
proposed MAS architecture includes five types of agents: Gate
keeping Agent, Collection Agent, Sorting Agent, Processing Agent
and Disposal Agent which act respectively during the five steps of
reverse logistics Network.
Abstract: Mobile Adhoc Networks (MANETs) are
infrastructure-less, dynamic network of collections of wireless mobile
nodes communicating with each other without any centralized
authority. A MANET is a mobile device of interconnections through
wireless links, forming a dynamic topology. Routing protocols have a
big role in data transmission across a network. Routing protocols,
two major classifications are unipath and multipath. This study
evaluates performance of an on-demand multipath routing protocol
named Adhoc On-demand Multipath Distance Vector routing
(AOMDV). This study proposes Energy Aware AOMDV (EAAOMDV)
an extension of AOMDV which decreases energy
consumed on a route.
Abstract: Most of the existing video streaming protocols
provide video services without considering security aspects in
decentralized mobile ad-hoc networks. The security policies adapted
to the currently existing non-streaming protocols, do not comply with
the live video streaming protocols resulting in considerable
vulnerability, high bandwidth consumption and unreliability which
cause severe security threats, low bandwidth and error prone
transmission respectively in video streaming applications. Therefore
a synergized methodology is required to reduce vulnerability and
bandwidth consumption, and enhance reliability in the video
streaming applications in MANET. To ensure the security measures
with reduced bandwidth consumption and improve reliability of the
video streaming applications, a Secure Low-bandwidth Video
Streaming through Reliable Multipath Propagation (SLVRMP)
protocol architecture has been proposed by incorporating the two
algorithms namely Secure Low-bandwidth Video Streaming
Algorithm and Reliable Secure Multipath Propagation Algorithm
using Layered Video Coding in non-overlapping zone routing
network topology. The performances of the proposed system are
compared to those of the other existing secure multipath protocols
Sec-MR, SPREAD using NS 2.34 and the simulation results show
that the performances of the proposed system get considerably
improved.
Abstract: A robust sequential nonparametric method is proposed
for adaptation to background noise parameters for real-time. The
distribution of background noise was modelled like to Huber
contamination mixture. The method is designed to operate as an
adaptation-unit, which is included inside a detection subsystem of an
integrated multichannel monitoring system. The proposed method
guarantees the given size of a nonasymptotic confidence set for noise
parameters. Properties of the suggested method are rigorously
proved. The proposed algorithm has been successfully tested in real
conditions of a functioning C-OTDR monitoring system, which was
designed to monitor railways.
Abstract: Live video streaming is one of the most widely used
service among end users, yet it is a big challenge for the network
operators in terms of quality. The only way to provide excellent
Quality of Experience (QoE) to the end users is continuous
monitoring of live video streaming. For this purpose, there are several
objective algorithms available that monitor the quality of the video in
a live stream. Subjective tests play a very important role in fine
tuning the results of objective algorithms. As human perception is
considered to be the most reliable source for assessing the quality of a
video stream subjective tests are conducted in order to develop more
reliable objective algorithms. Temporal impairments in a live video
stream can have a negative impact on the end users. In this paper we
have conducted subjective evaluation tests on a set of video
sequences containing temporal impairment known as frame freezing.
Frame Freezing is considered as a transmission error as well as a
hardware error which can result in loss of video frames on the
reception side of a transmission system. In our subjective tests, we
have performed tests on videos that contain a single freezing event
and also for videos that contain multiple freezing events. We have
recorded our subjective test results for all the videos in order to give a
comparison on the available No Reference (NR) objective
algorithms. Finally, we have shown the performance of no reference
algorithms used for objective evaluation of videos and suggested the
algorithm that works better. The outcome of this study shows the
importance of QoE and its effect on human perception. The results
for the subjective evaluation can serve the purpose for validating
objective algorithms.