Abstract: This article discusses the problem of estimating the
orientation of inclined ground on which a human subject stands based
on information provided by the vestibular system consisting of the
otolith and semicircular canals. It is assumed that body segments are
not necessarily aligned and thus forming an open kinematic chain.
The semicircular canals analogues to a technical gyrometer provide a
measure of the angular velocity whereas the otolith analogues to a
technical accelerometer provide a measure of the translational
acceleration. Two solutions are proposed and discussed. The first is
based on a stand-alone Kalman filter that optimally fuses the two
measurements based on their dynamic characteristics and their noise
properties. In this case, no body dynamic model is needed. In the
second solution, a central extended disturbance observer that
incorporates a body dynamic model (internal model) is employed.
The merits of both solutions are discussed and demonstrated by
experimental and simulation results.
Abstract: In this study, a novel approach of image embedding is introduced. The proposed method consists of three main steps. First, the edge of the image is detected using Sobel mask filters. Second, the least significant bit LSB of each pixel is used. Finally, a gray level connectivity is applied using a fuzzy approach and the ASCII code is used for information hiding. The prior bit of the LSB represents the edged image after gray level connectivity, and the remaining six bits represent the original image with very little difference in contrast. The proposed method embeds three images in one image and includes, as a special case of data embedding, information hiding, identifying and authenticating text embedded within the digital images. Image embedding method is considered to be one of the good compression methods, in terms of reserving memory space. Moreover, information hiding within digital image can be used for security information transfer. The creation and extraction of three embedded images, and hiding text information is discussed and illustrated, in the following sections.
Abstract: BEAMnrc was used to calculate the spectrum and
HVL for X-ray Beam during low energy X-ray radiation using tube model: SRO 33/100 /ROT 350 Philips. The results of BEAMnrc
simulation and measurements were compared to the IPEM report
number 78 and SpekCalc software. Three energies 127, 103 and 84
Kv were used. In these simulation a tungsten anode with 1.2 mm for
Be window were used as source. HVLs were calculated from
BEAMnrc spectrum with air Kerma method for four different filters.
For BEAMnrc one billion particles were used as original particles for
all simulations. The results show that for 127 kV, there was
maximum 5.2 % difference between BEAMnrc and Measurements
and minimum was 0.7% .the maximum 9.1% difference between
BEAMnrc and IPEM and minimum was 2.3% .The maximum
difference was 3.2% between BEAMnrc and SpekCal and minimum
was 2.8%. The result show BEAMnrc was able to satisfactory predict
the quantities of Low energy Beam as well as high energy X-ray
radiation.
Abstract: High level synthesis (HLS) is a process which
generates register-transfer level design for digital systems from
behavioral description. There are many HLS algorithms and
commercial tools. However, most of these algorithms consider a
behavioral description for the system when a single token is
presented to the system. This approach does not exploit extra
hardware efficiently, especially in the design of digital filters where
common operations may exist between successive tokens. In this
paper, we modify the behavioral description to process multiple
tokens in parallel. However, this approach is unlike the full
processing that requires full hardware replication. It exploits the
presence of common operations between successive tokens. The
performance of the proposed approach is better than sequential
processing and approaches that of full parallel processing as the
hardware resources are increased.
Abstract: This paper proposes a novel hybrid algorithm for feature selection based on a binary ant colony and SVM. The final subset selection is attained through the elimination of the features that produce noise or, are strictly correlated with other already selected features. Our algorithm can improve classification accuracy with a small and appropriate feature subset. Proposed algorithm is easily implemented and because of use of a simple filter in that, its computational complexity is very low. The performance of the proposed algorithm is evaluated through a real Rotary Cement kiln dataset. The results show that our algorithm outperforms existing algorithms.
Abstract: Chikungunya virus (CHICKV) is an arboviruses belonging to family Tagoviridae and is transmitted to human through by mosquito (Aedes aegypti and Aedes albopictus) bite. A large outbreak of chikungunya has been reported in India between 2006 and 2007, along with several other countries from South-East Asia and for the first time in Europe. It was for the first time that the CHICKV outbreak has been reported with mortality from Reunion Island and increased mortality from Asian countries. CHICKV affects all age groups, and currently there are no specific drugs or vaccine to cure the disease. The need of antiviral agents for the treatment of CHICKV infection and the success of virtual screening against many therapeutically valuable targets led us to carry out the structure based drug design against Chikungunya nSP2 protease (PDB: 3TRK). Highthroughput virtual screening of publicly available databases, ZINC12 and BindingDB, has been carried out using the Openeye tools and Schrodinger LLC software packages. Openeye Filter program has been used to filter the database and the filtered outputs were docked using HTVS protocol implemented in GLIDE package of Schrodinger LLC. The top HITS were further used for enriching the similar molecules from the database through vROCS; a shape based screening protocol implemented in Openeye. The approach adopted has provided different scaffolds as HITS against CHICKV protease. Three scaffolds: Indole, Pyrazole and Sulphone derivatives were selected based on the docking score and synthetic feasibility. Derivatives of Pyrazole were synthesized and submitted for antiviral screening against CHICKV.
Abstract: In Geographic Information System, one of the sources
of obtaining needed geographic data is digitizing analog maps and
evaluation of aerial and satellite photos. In this study, a method will
be discussed which can be used to extract vectorial features and
creating vectorized drawing files for aerial photos. At the same time
a software developed for these purpose. Converting from raster to
vector is also known as vectorization and it is the most important step
when creating vectorized drawing files. In the developed algorithm,
first of all preprocessing on the aerial photo is done. These are;
converting to grayscale if necessary, reducing noise, applying some
filters and determining the edge of the objects etc. After these steps,
every pixel which constitutes the photo are followed from upper left
to right bottom by examining its neighborhood relationship and one
pixel wide lines or polylines obtained. The obtained lines have to be
erased for preventing confusion while continuing vectorization
because if not erased they can be perceived as new line, but if erased
it can cause discontinuity in vector drawing so the image converted
from 2 bit to 8 bit and the detected pixels are expressed as a different
bit. In conclusion, the aerial photo can be converted to vector form
which includes lines and polylines and can be opened in any CAD
application.
Abstract: In this paper, we demonstrate the adaptive
least-mean-square (LMS) filter modeling using SystemC. SystemC is
a modeling language that allows designer to model both hardware and
software component and makes it possible to design from high level
system of abstraction to low level system of abstraction. We produced
five adaptive least-mean-square filter models that are classed as five
abstraction levels using SystemC proceeding from the abstract model
to the more concrete model.
Abstract: This paper proposes a low-voltage and low-power
fully integrated digitally tuned continuous-time channel selection
filter for WiMAX applications. A 5th-order elliptic low-pass filter is
realized in a Gm-C topology. The bandwidth of the fully differential
filter is reconfigurable from 2.5MHz to 20MHz (8x) for different
requirements in WiMAX applications. The filter is simulated in a
standard 90nm CMOS process. Simulation results show the THD
(@Vout =100mVpp) is less than -66dB. The in-band ripple of the
filter is about 0.15dB. The filter consumes 1.5mW from a supply
voltage of 0.9V.
Abstract: For decades, the defense business has been plagued by
not having a reliable, deterministic method to know when the Kalman
filter solution for passive ranging application is reliable for use by the
fighter pilot. This has made it hard to accurately assess when the
ranging solution can be used for situation awareness and weapons
use. To date, we have used ad hoc rules-of-thumb to assess when we
think the estimate of the Kalman filter standard deviation on range is
reliable. A reliable algorithm has been developed at BAE Systems
Electronics & Integrated Solutions that monitors the Kalman gain
matrix elements – and a patent is pending. The “settling" of the gain
matrix elements relates directly to when we can assess the time when
the passive ranging solution is within the 10 percent-of-truth value.
The focus of the paper is on surface-based passive ranging – but the
method is applicable to airborne targets as well.
Abstract: In this paper, a new model order reduction
phenomenon is introduced at the design stage of linear phase digital
IIR filter. The complexity of a system can be reduced by adopting the
model order reduction method in their design. In this paper a mixed
method of model order reduction is proposed for linear IIR filter. The
proposed method employs the advantages of factor division technique
to derive the reduced order denominator polynomial and the reduced
order numerator is obtained based on the resultant denominator
polynomial. The order reduction technique is used to reduce the delay
units at the design stage of IIR filter. The validity of the proposed
method is illustrated with design example in frequency domain and
stability is also examined with help of nyquist plot.
Abstract: Financial forecasting using machine learning techniques has received great efforts in the last decide . In this ongoing work, we show how machine learning of graphical models will be able to infer a visualized causal interactions between different banks in the Saudi equities market. One important discovery from such learned causal graphs is how companies influence each other and to what extend. In this work, a set of graphical models named Gaussian graphical models with developed ensemble penalized feature selection methods that combine ; filtering method, wrapper method and a regularizer will be shown. A comparison between these different developed ensemble combinations will also be shown. The best ensemble method will be used to infer the causal relationships between banks in Saudi equities market.
Abstract: This paper introduces the effective speckle reduction of
synthetic aperture radar (SAR) images using inner product spaces in
undecimated wavelet domain. There are two major areas in projection
onto span algorithm where improvement can be made. First is the use
of undecimated wavelet transformation instead of discrete wavelet
transformation. And second area is the use of smoothing filter namely
directional smoothing filter which is an additional step. Proposed
method does not need any noise estimation and thresholding
technique. More over proposed method gives good results on both
single polarimetric and fully polarimetric SAR images.
Abstract: Within the last years, several technologies have been developed to help building e-learning portals. Most of them follow approaches that deliver a vast amount of functionalities, suitable for class-like learning. The SuGI project, as part of the D-Grid (funded by the BMBF), targets on delivering a highly scalable and sustainable learning solution to provide materials (e.g. learning modules, training systems, webcasts, tutorials, etc.) containing knowledge about Grid computing to the D-Grid community. In this article, the process of the development of an e-learning portal focused on the requirements of this special user group is described. Furthermore, it deals with the conceptual and technical design of an e-learning portal, addressing the special needs of heterogeneous target groups. The main focus lies on the quality management of the software development process, Web templates for uploading new contents, the rich search and filter functionalities which will be described from a conceptual as well as a technical point of view. Specifically, it points out best practices as well as concepts to provide a sustainable solution to a relatively unknown and highly heterogeneous community.
Abstract: Polynomial maps offer analytical properties used to obtain better performances in the scope of chaos synchronization under noisy channels. This paper presents a new method to simplify equations of the Exact Polynomial Kalman Filter (ExPKF) given in [1]. This faster algorithm is compared to other estimators showing that performances of all considered observers vanish rapidly with the channel noise making application of chaos synchronization intractable. Simulation of ExPKF shows that saturation drawn on the emitter to keep it stable impacts badly performances for low channel noise. Then we propose a particle filter that outperforms all other Kalman structured observers in the case of noisy channels.
Abstract: Acoustical properties of speech have been shown to
be related to mental states of speaker with symptoms: depression
and remission. This paper describes way to address the issue of
distinguishing depressed patients from remitted subjects based on
measureable acoustics change of their spoken sound. The vocal-tract
related frequency characteristics of speech samples from female
remitted and depressed patients were analyzed via speech
processing techniques and consequently, evaluated statistically by
cross-validation with Support Vector Machine. Our results
comparatively show the classifier's performance with effectively
correct separation of 93% determined from testing with the subjectbased
feature model and 88% from the frame-based model based on
the same speech samples collected from hospital visiting interview
sessions between patients and psychiatrists.
Abstract: Although e-mail is the most efficient and popular communication method, unwanted and mass unsolicited e-mails, also called spam mail, endanger the existence of the mail system. This paper proposes a new algorithm called Dynamic Weighted Majority Concept Drift Detection (DWM-CDD) for content-based filtering. The design purposes of DWM-CDD are first to accurate the performance of the previously proposed algorithms, and second to speed up the time to construct the model. The results show that DWM-CDD can detect both sudden and gradual changes quickly and accurately. Moreover, the time needed for model construction is less than previously proposed algorithms.
Abstract: Segmentation, filtering out of measurement errors and
identification of breakpoints are integral parts of any analysis of
microarray data for the detection of copy number variation (CNV).
Existing algorithms designed for these tasks have had some successes
in the past, but they tend to be O(N2) in either computation time or
memory requirement, or both, and the rapid advance of microarray
resolution has practically rendered such algorithms useless. Here we
propose an algorithm, SAD, that is much faster and much less thirsty
for memory – O(N) in both computation time and memory requirement
-- and offers higher accuracy. The two key ingredients of SAD are the
fundamental assumption in statistics that measurement errors are
normally distributed and the mathematical relation that the product of
two Gaussians is another Gaussian (function). We have produced a
computer program for analyzing CNV based on SAD. In addition to
being fast and small it offers two important features: quantitative
statistics for predictions and, with only two user-decided parameters,
ease of use. Its speed shows little dependence on genomic profile.
Running on an average modern computer, it completes CNV analyses
for a 262 thousand-probe array in ~1 second and a 1.8 million-probe
array in 9 seconds
Abstract: This paper introduces a low cost INS/GPS algorithm for
land vehicle navigation application. The data fusion process is done
with an extended Kalman filter in cascade configuration mode. In
order to perform numerical simulations, MATLAB software has been
developed. Loosely coupled configuration is considered. The results
obtained in this work demonstrate that a low-cost INS/GPS navigation
system is partially capable of meeting the performance requirements
for land vehicle navigation. The relative effectiveness of the kalman
filter implementation in integrated GPS/INS navigation algorithm is
highlighted. The paper also provides experimental results; field test
using a car is carried out.
Abstract: This study proposes a new recommender system based on the collaborative folksonomy. The purpose of the proposed system is to recommend Internet resources (such as books, articles, documents, pictures, audio and video) to users. The proposed method includes four steps: creating the user profile based on the tags, grouping the similar users into clusters using an agglomerative hierarchical clustering, finding similar resources based on the user-s past collections by using content-based filtering, and recommending similar items to the target user. This study examines the system-s performance for the dataset collected from “del.icio.us," which is a famous social bookmarking website. Experimental results show that the proposed tag-based collaborative and content-based filtering hybridized recommender system is promising and effectiveness in the folksonomy-based bookmarking website.