Abstract: An accident is an unexpected and unplanned situation
that happens and affects human in a negative outcome. The accident
can cause an injury to a human biological organism. Thus, the
provision of initial care for an illness or injury is very important
move to prepare the patients/victims before sending to the doctor. In
this paper, a First Aid Application is developed to give some
directions for preliminary taking care of patient/victim via Android
mobile device. Also, the navigation function using Google Maps API
is implemented in this paper for searching a suitable path to the
nearest hospital. Therefore, in the emergency case, this function can
be activated and navigate patients/victims to the hospital with the
shortest path.
Abstract: In the self-stabilizing algorithmic paradigm, each node has a local view of the system, in a finite amount of time the system converges to a global state with desired property. In a graph G =
(V, E), a subset S C V is a 2-packing if Vi c V: IN[i] n SI
Abstract: Whit the increasing of traffic, noise emanated from
motor vehicles increases as well, which subsequently causes adding
to the stress of modern city. Thus, it is needed to look for most
critical areas in terms of environmental and social impact of noise.
There are several critical situations for noise emanated from motor
vehicles such as stop and go situation which usually occurs near
junctions or at-grade intersections. This study was conducted in two
locations, most common types of intersections, crossroads and Tjunctions.
The highest average noise levels are recorded during Go
phase for T-junction, 64.4 dB, and Drive phase for crossroad, 64 dB.
It implies that the existence of intersection caused the noise level to
increase. The vehicles starting to move produce more sound than
when they travel at a constant speed along the intersection. It is
suggested that special considerations and priority of allocating funds
should be given to these critical spots.
Abstract: The approach based on the wavelet transform has
been widely used for image denoising due to its multi-resolution
nature, its ability to produce high levels of noise reduction and the
low level of distortion introduced. However, by removing noise, high
frequency components belonging to edges are also removed, which
leads to blurring the signal features. This paper proposes a new
method of image noise reduction based on local variance and edge
analysis. The analysis is performed by dividing an image into 32 x 32
pixel blocks, and transforming the data into wavelet domain. Fast
lifting wavelet spatial-frequency decomposition and reconstruction is
developed with the advantages of being computationally efficient and
boundary effects minimized. The adaptive thresholding by local
variance estimation and edge strength measurement can effectively
reduce image noise while preserve the features of the original image
corresponding to the boundaries of the objects. Experimental results
demonstrate that the method performs well for images contaminated
by natural and artificial noise, and is suitable to be adapted for
different class of images and type of noises. The proposed algorithm
provides a potential solution with parallel computation for real time
or embedded system application.
Abstract: Outlier detection in streaming data is very challenging because streaming data cannot be scanned multiple times and also new concepts may keep evolving. Irrelevant attributes can be termed as noisy attributes and such attributes further magnify the challenge of working with data streams. In this paper, we propose an unsupervised outlier detection scheme for streaming data. This scheme is based on clustering as clustering is an unsupervised data mining task and it does not require labeled data, both density based and partitioning clustering are combined for outlier detection. In this scheme partitioning clustering is also used to assign weights to attributes depending upon their respective relevance and weights are adaptive. Weighted attributes are helpful to reduce or remove the effect of noisy attributes. Keeping in view the challenges of streaming data, the proposed scheme is incremental and adaptive to concept evolution. Experimental results on synthetic and real world data sets show that our proposed approach outperforms other existing approach (CORM) in terms of outlier detection rate, false alarm rate, and increasing percentages of outliers.
Abstract: In this paper a new Joint Adaptive Block Matching
Search (JABMS) algorithm is proposed to generate motion vector
and search a best match macro block by classifying the motion vector
movement based on prediction error. Diamond Search (DS)
algorithm generates high estimation accuracy when motion vector is
small and Adaptive Rood Pattern Search (ARPS) algorithm can
handle large motion vector but is not very accurate. The proposed
JABMS algorithm which is capable of considering both small and
large motions gives improved estimation accuracy and the
computational cost is reduced by 15.2 times compared with
Exhaustive Search (ES) algorithm and is 1.3 times less compared
with Diamond search algorithm.
Abstract: One of the main limitations for the resolution of
optical instruments is the size of the sensor-s pixels. In this paper we
introduce a new sub pixel resolution algorithm to enhance the
resolution of images. This method is based on the analysis of multiimages
which are fast recorded during the fine relative motion of
image and pixel arrays of CCDs. It is shown that by applying this
method for a sample noise free image one will enhance the resolution
with 10-14 order of error.
Abstract: The operating control parameters of injection
flushing type of electrical discharge machining process on stainless
steel 304 workpiece with copper tools are being optimized
according to its individual machining characteristic i.e. material
removal rate (MRR). Lower MRR during EDM machining process
may decrease its- machining productivity. Hence, the quality
characteristic for MRR is set to higher-the-better to achieve the
optimum machining productivity. Taguchi method has been used
for the construction, layout and analysis of the experiment for each
of the machining characteristic for the MRR. The use of Taguchi
method in the experiment saves a lot of time and cost of preparing
and machining the experiment samples. Therefore, an L18
Orthogonal array which was the fundamental component in the
statistical design of experiments has been used to plan the
experiments and Analysis of Variance (ANOVA) is used to
determine the optimum machining parameters for this machining
characteristic. The control parameters selected for this
optimization experiments are polarity, pulse on duration, discharge
current, discharge voltage, machining depth, machining diameter
and dielectric liquid pressure. The result had shown that the higher
the discharge voltage, the higher will be the MRR.
Abstract: The purpose of this paper is to present a Dynamic
Time Warping technique which reduces significantly the data
processing time and memory size of multi-dimensional time series
sampled by the biometric smart pen device BiSP. The acquisition
device is a novel ballpoint pen equipped with a diversity of sensors
for monitoring the kinematics and dynamics of handwriting
movement. The DTW algorithm has been applied for time series
analysis of five different sensor channels providing pressure,
acceleration and tilt data of the pen generated during handwriting on
a paper pad. But the standard DTW has processing time and memory
space problems which limit its practical use for online handwriting
recognition. To face with this problem the DTW has been applied to
the sum of the five sensor signals after an adequate down-sampling
of the data. Preliminary results have shown that processing time and
memory size could significantly be reduced without deterioration of
performance in single character and word recognition. Further
excellent accuracy in recognition was achieved which is mainly due
to the reduced dynamic time warping RDTW technique and a novel
pen device BiSP.
Abstract: Overhead conveyor systems are in use in many installations around the world, meeting the widest range of applications possible. Overhead conveyor systems are particularly preferred in automotive industry but also at post offices. Overhead conveyor systems must always be integrated with a logistical process by finding the best way for a cheaper material flow in order to guarantee precise and fast workflows. With their help, any transport can take place without wasting ground and space, without excessive company capacity, lost or damaged products, erroneous delivery, endless travels and without wasting time. Ultra-light overhead conveyor systems are rope-based conveying systems with individually driven vehicles. The vehicles can move automatically on the rope and this can be realized by energy and signals. Crossings are realized by switches. Ultra-light overhead conveyor systems provide optimal material flow, which produces profit and saves time. This article introduces two new ultra-light overhead conveyor designs in logistics and explains their components. According to the explanation of the components, scenarios are created by means of their technical characteristics. The scenarios are visualized with the help of CAD software. After that, assumptions are made for application area. According to these assumptions scenarios are visualized. These scenarios help logistics companies achieve lower development costs as well as quicker market maturity.
Abstract: A vast array of biological materials, especially algae have received increasing attention for heavy metal removal. Algae have been proven to be cheaper, more effective for the removal of metallic elements in aqueous solutions. A fresh water algal strain was isolated from Zoo Lake, Johannesburg, South Africa and identified as Desmodesmus sp. This paper investigates the efficacy of Desmodesmus sp.in removing heavy metals contaminating the Wonderfonteinspruit Catchment Area (WCA) water bodies. The biosorption data fitted the pseudo-second order and Langmuir isotherm models. The Langmuir maximum uptakes gave the sequence: Mn2+>Ni2+>Fe2+. The best results for kinetic study was obtained in concentration 120 ppm for Fe3+ and Mn2+, whilst for Ni2+ was at 20 ppm, which is about the same concentrations found in contaminated water in the WCA (Fe3+115 ppm, Mn2+ 121 ppm and Ni2+ 26.5 ppm).
Abstract: The present study is concerned with the free
convective two dimensional flow and heat transfer, within the
framework of Boussinesq approximation, in anisotropic fluid filled
porous rectangular enclosure subjected to end-to-end temperature
difference have been investigated using Lattice Boltzmann method
fornon-Darcy flow model. Effects of the moving lid direction (top,
bottom, left, and right wall moving in the negative and positive x&ydirections),
number of moving walls (one or two opposite walls), the
sliding wall velocity, and four different constant temperatures
opposite walls cases (two surfaces are being insulated and the
twoother surfaces areimposed to be at constant hot and cold
temperature)have been conducted. The results obtained are discussed
in terms of the Nusselt number, vectors, contours, and isotherms.
Abstract: Cardiac pulse-related artifacts in the EEG recorded
simultaneously with fMRI are complex and highly variable. Their
effective removal is an unsolved problem. Our aim is to develop an
adaptive removal algorithm based on the matching pursuit (MP)
technique and to compare it to established methods using a visual
evoked potential (VEP). We recorded the VEP inside the static
magnetic field of an MR scanner (with artifacts) as well as in an
electrically shielded room (artifact free). The MP-based artifact
removal outperformed average artifact subtraction (AAS) and
optimal basis set removal (OBS) in terms of restoring the EEG field
map topography of the VEP. Subsequently, a dipole model was fitted
to the VEP under each condition using a realistic boundary element
head model. The source location of the VEP recorded inside the MR
scanner was closest to that of the artifact free VEP after cleaning
with the MP-based algorithm as well as with AAS. While none of the
tested algorithms offered complete removal, MP showed promising
results due to its ability to adapt to variations of latency, frequency
and amplitude of individual artifact occurrences while still utilizing a
common template.
Abstract: This study investigates the performance of radial basis function networks (RBFN) in forecasting the monthly CO2 emissions of an electric power utility. We also propose a method for input variable selection. This method is based on identifying the general relationships between groups of input candidates and the output. The effect that each input has on the forecasting error is examined by removing all inputs except the variable to be investigated from its group, calculating the networks parameter and performing the forecast. Finally, the new forecasting error is compared with the reference model. Eight input variables were identified as the most relevant, which is significantly less than our reference model with 30 input variables. The simulation results demonstrate that the model with the 8 inputs selected using the method introduced in this study performs as accurate as the reference model, while also being the most parsimonious.
Abstract: Free Hemoglobin promotes the accumulation of
hydroxyl radicals by the heme iron, which can react with endogenous
hydrogen peroxide to produce free radicals which may cause severe
oxidative cell damage. Haptoglobin binds to Hemoglobin strongly
and Haptoglobin-Hemoglobin binding is irreversible. Peroxidase
activity of Haptoglobin(2-2)-Hemoglobin complex was assayed by
following increase of absorption of produced tetraguaiacol as the
second substrate of Haptoglobin-Hemoglobin complex at 470 nm and
42°C by UV-Vis spectrophotometer. The results have shown that
peroxidase activity of Haptoglobin(2-2)-Hemoglobin complex is
modulated via homotropic effect of hydrogen peroxide as allostric
substrate. On the other hand antioxidant property of Haptoglobin(2-
2)-Hemoglobin was increased via heterotropic effect of the two drugs
(especially ampicillin) on peroxidase activity of the complex. Both
drugs also have mild effect on quality of homotropic property of
peroxidase activity of Haptoglobin(2-2)-Hemoglobin complex.
Therefore, in vitro studies show that the two drugs may help Hp-Hb
complex to remove hydrogen peroxide from serum at pathologic
temperature ature (42 C).
Abstract: The stereophotogrammetry modality is gaining more widespread use in the clinical setting. Registration and visualization of this data, in conjunction with conventional 3D volumetric image modalities, provides virtual human data with textured soft tissue and internal anatomical and structural information. In this investigation computed tomography (CT) and stereophotogrammetry data is acquired from 4 anatomical phantoms and registered using the trimmed iterative closest point (TrICP) algorithm. This paper fully addresses the issue of imaging artifacts around the stereophotogrammetry surface edge using the registered CT data as a reference. Several iterative algorithms are implemented to automatically identify and remove stereophotogrammetry surface edge outliers, improving the overall visualization of the combined stereophotogrammetry and CT data. This paper shows that outliers at the surface edge of stereophotogrammetry data can be successfully removed automatically.
Abstract: This paper proposes a solution to the motion planning
and control problem of a point-mass robot which is required to move
safely to a designated target in a priori known workspace cluttered
with fixed elliptical obstacles of arbitrary position and sizes. A
tailored and unique algorithm for target convergence and obstacle
avoidance is proposed that will work for any number of fixed
obstacles. The control laws proposed in this paper also ensures that
the equilibrium point of the given system is asymptotically stable.
Computer simulations with the proposed technique and applications
to a planar (RP) manipulator will be presented.
Abstract: In the present article, nonlinear vibration analysis of
single layer graphene sheets is presented and the effect of small
length scale is investigated. Using the Hamilton's principle, the three
coupled nonlinear equations of motion are obtained based on the von
Karman geometrical model and Eringen theory of nonlocal
continuum. The solutions of Free nonlinear vibration, based on a one
term mode shape, are found for both simply supported and clamped
graphene sheets. A complete analysis of graphene sheets with
movable as well as immovable in-plane conditions is also carried out.
The results obtained herein are compared with those available in the
literature for classical isotropic rectangular plates and excellent
agreement is seen. Also, the nonlinear effects are presented as
functions of geometric properties and small scale parameter.
Abstract: Knowing about the customer behavior in a grocery has
been a long-standing issue in the retailing industry. The advent of
RFID has made it easier to collect moving data for an individual
shopper's behavior. Most of the previous studies used the traditional
statistical clustering technique to find the major characteristics of
customer behavior, especially shopping path. However, in using the
clustering technique, due to various spatial constraints in the store,
standard clustering methods are not feasible because moving data such
as the shopping path should be adjusted in advance of the analysis,
which is time-consuming and causes data distortion. To alleviate this
problem, we propose a new approach to spatial pattern clustering
based on the longest common subsequence. Experimental results using
real data obtained from a grocery confirm the good performance of the
proposed method in finding the hot spot, dead spot and major path
patterns of customer movements.
Abstract: Durian husk (DH), a fruit waste, was studied for its ability to remove Basic blue 3 (BB3) from aqueous solutions. Batch kinetic studies were carried out to study the sorption characteristics under various experimental conditions. The optimum pH for the dye removal occurred in the pH range of 3-10. Sorption was found to be concentration and agitation dependent. The kinetics of dye sorption fitted a pseudo-second order rate expression. Both Langmuir and Freundlich models appeared to provide reasonable fittings for the sorption data of BB3 on durian husk. Maximum sorption capacity calculated from the Langmuir model is 49.50 mg g-1.