Abstract: Recently, traffic monitoring has attracted the attention
of computer vision researchers. Many algorithms have been
developed to detect and track moving vehicles. In fact, vehicle
tracking in daytime and in nighttime cannot be approached with the
same techniques, due to the extreme different illumination conditions.
Consequently, traffic-monitoring systems are in need of having a
component to differentiate between daytime and nighttime scenes. In
this paper, a HSV-based day/night detector is proposed for traffic
monitoring scenes. The detector employs the hue-histogram and the
value-histogram on the top half of the image frame. Experimental
results show that the extraction of the brightness features along with
the color features within the top region of the image is effective for
classifying traffic scenes. In addition, the detector achieves high
precision and recall rates along with it is feasible for real time
applications.
Abstract: Nowadays, education cannot be imagined without digital technologies. It broadens the horizons of teaching learning processes. Several universities are offering online courses. For evaluation purpose, e-examination systems are being widely adopted in academic environments. Multiple-choice tests are extremely popular. Moving away from traditional examinations to e-examination, Moodle as Learning Management Systems (LMS) is being used. Moodle logs every click that students make for attempting and navigational purposes in e-examination. Data mining has been applied in various domains including retail sales, bioinformatics. In recent years, there has been increasing interest in the use of data mining in e-learning environment. It has been applied to discover, extract, and evaluate parameters related to student’s learning performance. The combination of data mining and e-learning is still in its babyhood. Log data generated by the students during online examination can be used to discover knowledge with the help of data mining techniques. In web based applications, number of right and wrong answers of the test result is not sufficient to assess and evaluate the student’s performance. So, assessment techniques must be intelligent enough. If student cannot answer the question asked by the instructor then some easier question can be asked. Otherwise, more difficult question can be post on similar topic. To do so, it is necessary to identify difficulty level of the questions. Proposed work concentrate on the same issue. Data mining techniques in specific clustering is used in this work. This method decide difficulty levels of the question and categories them as tough, easy or moderate and later this will be served to the desire students based on their performance. Proposed experiment categories the question set and also group the students based on their performance in examination. This will help the instructor to guide the students more specifically. In short mined knowledge helps to support, guide, facilitate and enhance learning as a whole.
Abstract: Although Mobile Wireless Sensor Networks (MWSNs),
which consist of mobile sensor nodes (MSNs), can cover a wide range
of observation region by using a small number of sensor nodes, they
need to construct a network to collect the sensing data on the base
station by moving the MSNs. As an effective method, the network
construction method based on Virtual Rails (VRs), which is referred
to as VR method, has been proposed. In this paper, we propose two
types of effective techniques for the VR method. They can prolong
the operation time of the network, which is limited by the battery
capabilities of MSNs and the energy consumption of MSNs. The
first technique, an effective arrangement of VRs, almost equalizes
the number of MSNs belonging to each VR. The second technique,
an adaptive movement method of MSNs, takes into account the
residual energy of battery. In the simulation, we demonstrate that each
technique can improve the network lifetime and the combination of
both techniques is the most effective.
Abstract: The present study investigates the effectiveness of
newly designed clayey pellets (fired clay pellets diameter sizes of 5
and 8 mm, and unfired clay pellets with the diameter size of 15 mm)
as the beds in the column adsorption process. The adsorption
experiments in the batch mode were performed before the column
experiment with the purpose to determine the order of adsorbent
package in the column which was to be designed in the investigation.
The column experiment was performed by using a known mass of the
clayey beds and the volume of the waste printing developer, which
was purified. The column was filled in the following order: fired clay
pellets of the diameter size of 5 mm, fired clay pellets of the diameter
size of 8 mm, and unfired clay pellets of the diameter size of 15 mm.
The selected order of the adsorbents showed a high removal
efficiency for zinc (97.8%) and copper (81.5%) ions. These
efficiencies were better than those in the case of the already existing
mode adsorption. The obtained experimental data present a good
basis for the selection of an appropriate column fill, but further
testing is necessary in order to obtain more accurate results.
Abstract: Myoelectric control system is the fundamental
component of modern prostheses, which uses the myoelectric signals
from an individual’s muscles to control the prosthesis movements.
The surface electromyogram signal (sEMG) being noninvasive has
been used as an input to prostheses controllers for many years.
Recent technological advances has led to the development of
implantable myoelectric sensors which enable the internal
myoelectric signal (MES) to be used as input to these prostheses
controllers. The intramuscular measurement can provide focal
recordings from deep muscles of the forearm and independent signals
relatively free of crosstalk thus allowing for more independent
control sites. However, little work has been done to compare the two
inputs. In this paper we have compared the classification accuracy of
six pattern recognition based myoelectric controllers which use
surface myoelectric signals recorded using untargeted (symmetric)
surface electrode arrays to the same controllers with multichannel
intramuscular myolectric signals from targeted intramuscular
electrodes as inputs. There was no significant enhancement in the
classification accuracy as a result of using the intramuscular EMG
measurement technique when compared to the results acquired using
the surface EMG measurement technique. Impressive classification
accuracy (99%) could be achieved by optimally selecting only five
channels of surface EMG.
Abstract: The study assessed the effectiveness of Pawpaw
(Carica papaya) wood in reducing the concentrations of heavy
metals in wastewater acting as a bio-sorbent. The following heavy
metals were considered; Zinc, Cadmium, Lead, Copper, Iron,
Selenium, Nickel and Manganese. The physiochemical properties of
Carica papaya stem were studied. The experimental sample was
sourced from the trunk of a felled matured pawpaw tree. Wastewater
for experimental use was prepared by dissolving soil samples
collected from a dump site at Owerri, Imo state of Nigeria in water.
The concentration of each metal remaining in solution as residual
metal after bio-sorption was determined using Atomic absorption
Spectrometer. The effects of pH and initial heavy metal concentration
were studied in a batch reactor. The results of Spectrometer test
showed that there were different functional groups detected in the
Carica papaya stem biomass. There was increase in metal removal as
the pH increased for all the metals considered except for Nickel and
Manganese. Optimum bio-sorption occurred at pH 5.9 with 5g/100ml
solution of bio-sorbent. The results of the study showed that the
treated wastewater is fit for irrigation purpose based on Canada
wastewater quality guideline for the protection of Agricultural
standard. This approach thus provides a cost effective and
environmentally friendly option for treating wastewater.
Abstract: In this work, by replacing the traditional solid spokes with colloidal spokes, a vehicle wheel with a built-in suspension structure is proposed. Following the background and description of the wheel system, firstly, a vibration model of the wheel equipped with colloidal spokes is proposed, and based on such model the equivalent damping coefficients and spring constants are identified. Then, a modified model of a quarter-vehicle moving on a rough pavement is proposed in order to estimate the transmissibility of vibration from the road roughness to vehicle body. In the end, the optimal design of the colloidal spokes and the optimum number of colloidal spokes are decided in order to minimize the transmissibility of vibration, i.e., to maximize the ride comfort of the vehicle.
Abstract: One of the main purposes of designing bucklingrestrained
braces is the fact that the entire lateral load is wasted by
the braces, the entire gravitational load is moved to the foundation
through the beams, and the columns can be moved to the foundation.
In other words, braces are designed for bearing lateral load. In the
implementation of the structure, it should be noted that the
implementation of various parts of the structure must be conducted in
such a way that the buckling-restrained braces would not bear the
gravitational load. Moreover, this type of brace has been investigated
under impact loading, and the design goals of designing method
(direct motion) are controlled under impact loading. The results of
dynamic analysis are shown as the relocation charts of the floors and
switch between the floors. Finally, the results are compared with each
other.
Abstract: Test automation allows performing difficult and time
consuming manual software testing tasks efficiently, quickly and
repeatedly. However, development and maintenance of automated
tests is expensive, so it needs a proper prioritization what to automate
first. This paper describes a simple yet efficient approach for such
prioritization of test cases based on the effort needed for both manual
execution and software test automation. The suggested approach is
very flexible because it allows working with a variety of assessment
methods, and adding or removing new candidates at any time. The
theoretical ideas presented in this article have been successfully
applied in real world situations in several software companies by the
authors and their colleagues including testing of real estate websites,
cryptographic and authentication solutions, OSGi-based middleware
framework that has been applied in various systems for smart homes,
connected cars, production plants, sensors, home appliances, car head
units and engine control units (ECU), vending machines, medical
devices, industry equipment and other devices that either contain or
are connected to an embedded service gateway.
Abstract: Background modeling and subtraction in video
analysis has been widely used as an effective method for moving
objects detection in many computer vision applications. Recently, a
large number of approaches have been developed to tackle different
types of challenges in this field. However, the dynamic background
and illumination variations are the most frequently occurred problems
in the practical situation. This paper presents a favorable two-layer
model based on codebook algorithm incorporated with local binary
pattern (LBP) texture measure, targeted for handling dynamic
background and illumination variation problems. More specifically,
the first layer is designed by block-based codebook combining with
LBP histogram and mean value of each RGB color channel. Because
of the invariance of the LBP features with respect to monotonic
gray-scale changes, this layer can produce block wise detection results
with considerable tolerance of illumination variations. The pixel-based
codebook is employed to reinforce the precision from the output of the
first layer which is to eliminate false positives further. As a result, the
proposed approach can greatly promote the accuracy under the
circumstances of dynamic background and illumination changes.
Experimental results on several popular background subtraction
datasets demonstrate very competitive performance compared to
previous models.
Abstract: The major environmental risk of soil pollution is the
contamination of groundwater by infiltration of organic and inorganic
pollutants which can cause a serious menace. To prevent this risk and
to protect the groundwater, we proceeded in this study to test the
reliability of a biosolid as barrier to prevent the migration of very
dangerous pollutants as ‘Cadmium’ through the different soil layers. In this study, we tried to highlight the effect of several parameters
such as: turbidity (different cycle of Hydration/Dehydration),
rainfall, effect of initial Cd(II) concentration and the type of soil.
These parameters allow us to find the most effective manner to
integrate this barrier in the soil. From the results obtained, we found a
significant effect of the barrier. Indeed, the recorded passing
quantities are lowest for the highest rainfall; we noted also that the
barrier has a better affinity towards higher concentrations; the most
retained amounts of cadmium has been in the top layer of the two
types of soil tested, while the lowest amounts of cadmium are
recorded in the bottom layers of soils.
Abstract: Context-aware technologies provide system
applications with the awareness of environmental conditions,
customer behaviours, object movements, etc. Further, with such
capability system applications can be smart to intelligently adapt their
responses to the changing conditions. In regard to business
operations, this promises businesses that their business processes can
run more intelligently, adaptively and flexibly, and thereby either
improve customer experience, enhance reliability of service delivery,
or lower operational cost, to make the business more competitive and
sustainable. Aiming at realising such context-aware business process
management, this paper firstly explores its potential benefit, and then
identifies some gaps between the current business process
management support and the expected. In addition, some preliminary
solutions are also discussed in regard to context definition, rule-based
process execution, run-time process evolution, etc. A framework is
also presented to give a conceptual architecture of context-aware
business process management system to guide system
implementation.
Abstract: Fluctuations of Schottky diode parameters in a
structure of the mixer are investigated. These fluctuations are
manifested in two ways. At the first, they lead to fluctuations in the
transfer factor that is lead to the amplitude fluctuations in the signal
of intermediate frequency. On the basis of the measurement data of
1/f noise of the diode at forward current, the estimation of a spectrum
of relative fluctuations in transfer factor of the mixer is executed.
Current dependence of the spectrum of relative fluctuations in
transfer factor of the mixer and dependence of the spectrum of
relative fluctuations in transfer factor of the mixer on the amplitude
of the heterodyne signal are investigated. At the second, fluctuations
in parameters of the diode lead to occurrence of 1/f noise in the
output signal of the mixer. This noise limits the sensitivity of the
mixer to the value of received signal.
Abstract: A Friction stir welding tool is a critical component to
the success of the process. The tool typically consists of a rotating
round shoulder and a threaded cylindrical pin that heats the work
piece, mostly by friction, and moves the softened alloy around it to
form the joint. In this research work, an attempt has been made to
investigate the relationship between FSW variables mainly tool
profile, rotating speed, welding speed and the mechanical properties
(tensile strength, yield strength, percentage elongation, and micro
hardness) of friction stir welded aluminum alloy 5083 joints. From
the experimental details, it can be assessed that the joint produced by
using Triflute profile tool has contribute superior mechanical and
structural properties as compared to Tapered unthreaded & Threaded
tool for 1000rpm.
Abstract: The question of legal liability over injury arising out
of the import and the introduction of GM food emerges as a crucial
issue confronting to promote GM food and its derivatives. There is a
greater possibility of commercialized GM food from the exporting
country to enter importing country where status of approval shall not
be same. This necessitates the importance of fixing a liability
mechanism to discuss the damage, if any, occurs at the level of
transboundary movement or at the market. There was a widespread consensus to develop the Cartagena
Protocol on Biosafety and to give for a dedicated regime on liability
and redress in the form of Nagoya Kuala Lumpur Supplementary
Protocol on the Liability and Redress (‘N-KL Protocol’) at the
international context. The national legal frameworks based on this
protocol are not adequately established in the prevailing food
legislations of the developing countries. The developing economy
like India is willing to import GM food and its derivatives after the
successful commercialization of Bt Cotton in 2002. As a party to the
N-KL Protocol, it is indispensable for India to formulate a legal
framework and to discuss safety, liability, and regulatory issues
surrounding GM foods in conformity to the provisions of the
Protocol. The liability mechanism is also important in the case where
the risk assessment and risk management is still in implementing
stage. Moreover, the country is facing GM infiltration issues with its
neighbors Bangladesh. As a precautionary approach, there is a need
to formulate rules and procedure of legal liability to discuss any kind
of damage occurs at transboundary trade. In this context, the
proposed work will attempt to analyze the liability regime in the
existing Food Safety and Standards Act, 2006 from the applicability
and domestic compliance and to suggest legal and policy options for
regulatory authorities.
Abstract: Carbon dioxide is one of the major greenhouse gas
(GHG) contributors. It is an obligation of the industry to reduce the
amount of carbon dioxide emission to the acceptable limits.
Tremendous research and studies are reported in the past and still the
quest to find the suitable and economical solution of this problem
needed to be explored in order to develop the most plausible absorber
for carbon dioxide removal. Amino acids can be potential alternate
solvents for carbon dioxide capture from gaseous streams. This is due
to its ability to resist oxidative degradation, low volatility and its
ionic structure. In addition, the introduction of promoter-like
piperazine to amino acid helps to further enhance the solubility. In
this work, the effect of piperazine on thermo physical properties and
solubility of β-Alanine aqueous solutions were studied for various
concentrations. The measured physicochemical properties data was
correlated as a function of temperature using least-squares method
and the correlation parameters are reported together with it respective
standard deviations. The effect of activator piperazine on the CO2
loading performance of selected amino acid under high-pressure
conditions (1bar to 10bar) at temperature range of (30 to 60)oC was
also studied. Solubility of CO2 decreases with increasing temperature
and increases with increasing pressure. Quadratic representation of
solubility using Response Surface Methodology (RSM) shows that
the most important parameter to optimize solubility is system
pressure. The addition of promoter increases the solubility effect of
the solvent.
Abstract: This report examines the current state of human gait
simulator development based on the human hip joint model. This unit
will create a database of human gait types, useful for setting up and
calibrating Mechano devices, as well as the creation of new systems
of rehabilitation, exoskeletons and walking robots. The system has
many opportunities to configure the dimensions and stiffness, while
maintaining relative simplicity.
Abstract: As one of the convenient and noninvasive sensing
approaches, the automatic limb girth measurement has been applied
to detect intention behind human motion from muscle deformation.
The sensing validity has been elaborated by preliminary researches
but still need more fundamental studies, especially on kinetic
contraction modes. Based on the novel fabric strain sensors, a soft
and smart limb girth measurement system was developed by the
authors’ group, which can measure the limb girth in-motion.
Experiments were carried out on elbow isometric flexion and elbow
isokinetic flexion (biceps’ isokinetic contractions) of 90°/s, 60°/s, and
120°/s for 10 subjects (2 canoeists and 8 ordinary people). After
removal of natural circumferential increments due to elbow position,
the joint torque is found not uniformly sensitive to the limb
circumferential strains, but declining as elbow joint angle rises,
regardless of the angular speed. Moreover, the maximum joint torque
was found as an exponential function of the joint’s angular speed.
This research highly contributes to the application of the automatic
limb girth measuring during kinetic contractions, and it is useful to
predict the contraction level of voluntary skeletal muscles.
Abstract: Both steady and unsteady turbulent mixed convection
heat transfer in a 3D lid-driven enclosure, which has constant heat
flux on the middle of bottom wall and with isothermal moving
sidewalls, is reported in this paper for working fluid with Prandtl
number Pr = 0.71. The other walls are adiabatic and stationary. The
dimensionless parameters used in this research are Reynolds number,
Re = 5000, 10000 and 15000, and Richardson number, Ri = 1 and 10.
The simulations have been done by using different turbulent methods
such as RANS, URANS, and LES. The effects of using different k-ε
models such as standard, RNG and Realizable k-ε model are
investigated. Interesting behaviours of the thermal and flow fields
with changing the Re or Ri numbers are observed. Isotherm and
turbulent kinetic energy distributions and variation of local Nusselt
number at the hot bottom wall are studied as well. The local Nusselt
number is found increasing with increasing either Re or Ri number.
In addition, the turbulent kinetic energy is discernibly affected by
increasing Re number. Moreover, the LES results have shown good
ability of this method in predicting more detailed flow structures in
the cavity.
Abstract: One of the global combinatorial optimization
problems in machine learning is feature selection. It concerned with
removing the irrelevant, noisy, and redundant data, along with
keeping the original meaning of the original data. Attribute reduction
in rough set theory is an important feature selection method. Since
attribute reduction is an NP-hard problem, it is necessary to
investigate fast and effective approximate algorithms. In this paper,
we proposed two feature selection mechanisms based on memetic
algorithms (MAs) which combine the genetic algorithm with a fuzzy
record to record travel algorithm and a fuzzy controlled great deluge
algorithm, to identify a good balance between local search and
genetic search. In order to verify the proposed approaches, numerical
experiments are carried out on thirteen datasets. The results show that
the MAs approaches are efficient in solving attribute reduction
problems when compared with other meta-heuristic approaches.