Abstract: Cluster analysis is the name given to a diverse collection of techniques that can be used to classify objects (e.g. individuals, quadrats, species etc). While Kohonen's Self-Organizing Feature Map (SOFM) or Self-Organizing Map (SOM) networks have been successfully applied as a classification tool to various problem domains, including speech recognition, image data compression, image or character recognition, robot control and medical diagnosis, its potential as a robust substitute for clustering analysis remains relatively unresearched. SOM networks combine competitive learning with dimensionality reduction by smoothing the clusters with respect to an a priori grid and provide a powerful tool for data visualization. In this paper, SOM is used for creating a toroidal mapping of two-dimensional lattice to perform cluster analysis on results of a chemical analysis of wines produced in the same region in Italy but derived from three different cultivators, referred to as the “wine recognition data" located in the University of California-Irvine database. The results are encouraging and it is believed that SOM would make an appealing and powerful decision-support system tool for clustering tasks and for data visualization.
Abstract: The avian phytohaemagglutinin skin test is being
proved as an in vivo system for the evaluation an avian in vivo T cell
mitogenicity. The test system was one week old Gallus domesticus
broiler Chickens. Five replicates were done for each of the whole,
1:10 dilutions of each of 0.05 IU tuberculin, tetanus immunoglobulin
and DPT vaccine as test materials. The evaluation parameters were
the skin indurations and lymphoblast percentages in bone marrow
lymphocytes.
Tuberculin indurations were 2.06 and 1.26mm for 0.05 IU
respectively while lymphoblast percent were 0.234 and 0.1
accordingly.
The skin indurations of 135mg/ml and 1.35mg/ml tetanus
immunoglobulin were 4.86 and 3.96mm while lymphoblast
percentages were 0.3 and 0.14 respectively.
The whole DPT and 1:10 concentration were with 4.5 and 3.2mm
while their lymphoblast percentages were 0.28 and 0.12 accordingly.
Thus the mitogenicity of the test materials was of dependant type.
Abstract: In this paper a new robust and efficient algorithm to automatic text extraction from colored book and journal cover sheets is proposed. First, we perform wavelet transform. Next for edge detecting from detail wavelet coefficient, we use dynamic threshold. By blurring approximate coefficients with alternative heuristic thresholding, achieve effective edge,. Afterward, with ROI technique get binary image. Finally text boxes would be extracted with new projection profile.
Abstract: The enthusiasm for gluten avoidance in a growing
market is met by improvements in sensitive detection methods for
analysing gluten content. Paradoxically, manufacturers employ no
such systems in the production process but continue to market their
product as gluten free, a significant risk posed to an undetermined
coeliac population. This paper resonates with an immunological
response that causes gastrointestinal scarring and villous atrophy with
the conventional description of personal injury. This thesis divulges
into evaluating potential inadequacies of gluten labelling laws which
not only present a diagnostic challenge for general practitioners in the
UK but it also exposes a less than adequate form of available legal
protection to those who suffer adverse reactions as a result of gluten
digestion. Central to this discussion is whether a claim brought in
misrepresentation, negligence and/or under the Consumer Protection
Act 1987 could be sustained. An interesting comparison is then made
with the legal regimes of neighboring jurisdictions furthering the
theme of a legally un-catered for gluten kingdom.
Abstract: This manuscript presents, palmprint recognition by
combining different texture extraction approaches with high accuracy.
The Region of Interest (ROI) is decomposed into different frequencytime
sub-bands by wavelet transform up-to two levels and only the
approximate image of two levels is selected, which is known as
Approximate Image ROI (AIROI). This AIROI has information of
principal lines of the palm. The Competitive Index is used as the
features of the palmprint, in which six Gabor filters of different
orientations convolve with the palmprint image to extract the orientation
information from the image. The winner-take-all strategy
is used to select dominant orientation for each pixel, which is
known as Competitive Index. Further, PCA is applied to select highly
uncorrelated Competitive Index features, to reduce the dimensions of
the feature vector, and to project the features on Eigen space. The
similarity of two palmprints is measured by the Euclidean distance
metrics. The algorithm is tested on Hong Kong PolyU palmprint
database. Different AIROI of different wavelet filter families are also
tested with the Competitive Index and PCA. AIROI of db7 wavelet
filter achievs Equal Error Rate (EER) of 0.0152% and Genuine
Acceptance Rate (GAR) of 99.67% on the palm database of Hong
Kong PolyU.
Abstract: This paper suggests ranking alternatives under fuzzy
MCDM (multiple criteria decision making) via an centroid based
ranking approach, where criteria are classified to benefit qualitative,
benefit quantitative and cost quantitative ones. The ratings of
alternatives versus qualitative criteria and the importance weights of
all criteria are assessed in linguistic values represented by fuzzy
numbers. The membership function for the final fuzzy evaluation
value of each alternative can be developed through α-cuts and
interval arithmetic of fuzzy numbers. The distance between the
original point and the relative centroid is applied to defuzzify the
final fuzzy evaluation values in order to rank alternatives. Finally a
numerical example demonstrates the computation procedure of the
proposed model.
Abstract: A Ground Control System (GCS), which controls Unmanned Aerial Vehicles (UAVs) and monitors their missionrelated data, is one of the major components of UAVs. In fact, some traditional GCSs were built on an expensive, complicated hardware infrastructure with workstations and PCs. In contrast, a GCS on a portable device – such as an Android phone or tablet – takes advantage of its light-weight hardware and the rich User Interface supported by the Android Operating System. We implemented that kind of GCS and called it Ground System Software (GSS) in this paper. In operation, our GSS communicates with UAVs or other GSS via TCP/IP connection to get mission-related data, visualizes it on the device-s screen, and saves the data in its own database. Our study showed that this kind of system will become a potential instrument in UAV-related systems and this kind of topic will appear in many research studies in the near future.
Abstract: The city of Suceava, one of the most important
medieval capital of Moldova, owes its urban genesis to the power
center established in its territory at the turn of the thirteenth and
fourteenth centuries. Freed from the effective control exercised by
the Emir Nogai through Alanians, the local center of power evolved
as the main representative of the interests of indigenous people in
relation to the Hungarian Angevin dinasty and to their
representatives from Maramures. From this perspective, the political
and military role of the settlement of Suceava was archeologically
proved by the discovery of extensive fortifications, unrivaled in the
first half of the XIVth century-s Moldavia. At the end of that century,
voivod Peter I decides to move the capital of the state from Siret to
Suceava. That option stimulated the development of the settlement
on specific urban coordinates.
Abstract: In this paper, we propose a Perceptually Optimized Foveation based Embedded ZeroTree Image Coder (POEFIC) that introduces a perceptual weighting to wavelet coefficients prior to control SPIHT encoding algorithm in order to reach a targeted bit rate with a perceptual quality improvement with respect to a given bit rate a fixation point which determines the region of interest ROI. The paper also, introduces a new objective quality metric based on a Psychovisual model that integrates the properties of the HVS that plays an important role in our POEFIC quality assessment. Our POEFIC coder is based on a vision model that incorporates various masking effects of human visual system HVS perception. Thus, our coder weights the wavelet coefficients based on that model and attempts to increase the perceptual quality for a given bit rate and observation distance. The perceptual weights for all wavelet subbands are computed based on 1) foveation masking to remove or reduce considerable high frequencies from peripheral regions 2) luminance and Contrast masking, 3) the contrast sensitivity function CSF to achieve the perceptual decomposition weighting. The new perceptually optimized codec has the same complexity as the original SPIHT techniques. However, the experiments results show that our coder demonstrates very good performance in terms of quality measurement.
Abstract: In an assessment of the extractability of metals in
green liquor dregs from the chemical recovery circuit of semichemical
pulp mill, extractable concentrations of heavy metals in
artificial gastric fluid were between 10 (Ni) and 717 (Zn) times
higher than those in artificial sweat fluid. Only Al (6.7 mg/kg; d.w.),
Ni (1.2 mg/kg; d.w.) and Zn (1.8 mg/kg; d.w.) showed extractability
in the artificial sweat fluid, whereas Al (730 mg/kg; d.w.), Ba (770
mg/kg; d.w.) and Zn (1290 mg/kg; d.w.) showed clear extractability
in the artificial gastric fluid. As certain heavy metals were clearly
soluble in the artificial gastric fluid, the careful handling of this
residue is recommended in order to prevent the penetration of green
liquor dregs across the human gastrointestinal tract.
Abstract: Digital watermarking in medical images can ensure
the authenticity and integrity of the image. This design paper reviews
some existing watermarking schemes and proposes a reversible
tamper detection and recovery watermarking scheme. Watermark
data from ROI (Region Of Interest) are stored in RONI (Region Of
Non Interest). The embedded watermark allows tampering detection
and tampered image recovery. The watermark is also reversible and
data compression technique was used to allow higher embedding
capacity.
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: In this paper, we present a new and effective image indexing technique that extracts features directly from DCT domain. Our proposed approach is an object-based image indexing. For each block of size 8*8 in DCT domain a feature vector is extracted. Then, feature vectors of all blocks of image using a k-means algorithm is clustered into groups. Each cluster represents a special object of the image. Then we select some clusters that have largest members after clustering. The centroids of the selected clusters are taken as image feature vectors and indexed into the database. Also, we propose an approach for using of proposed image indexing method in automatic image classification. Experimental results on a database of 800 images from 8 semantic groups in automatic image classification are reported.
Abstract: In this paper, Differential Evolution (DE) algorithm, a new promising evolutionary algorithm, is proposed to train Radial Basis Function (RBF) network related to automatic configuration of network architecture. Classification tasks on data sets: Iris, Wine, New-thyroid, and Glass are conducted to measure the performance of neural networks. Compared with a standard RBF training algorithm in Matlab neural network toolbox, DE achieves more rational architecture for RBF networks. The resulting networks hence obtain strong generalization abilities.
Abstract: Medical images require special safety and confidentiality because critical judgment is done on the information provided by medical images. Transmission of medical image via internet or mobile phones demands strong security and copyright protection in telemedicine applications. Here, highly secured and robust watermarking technique is proposed for transmission of image data via internet and mobile phones. The Region of Interest (ROI) and Non Region of Interest (RONI) of medical image are separated. Only RONI is used for watermark embedding. This technique results in exact recovery of watermark with standard medical database images of size 512x512, giving 'correlation factor' equals to 1. The correlation factor for different attacks like noise addition, filtering, rotation and compression ranges from 0.90 to 0.95. The PSNR with weighting factor 0.02 is up to 48.53 dBs. The presented scheme is non blind and embeds hospital logo of 64x64 size.
Abstract: Content-based Image Retrieval (CBIR) aims at searching image databases for specific images that are similar to a given query image based on matching of features derived from the image content. This paper focuses on a low-dimensional color based indexing technique for achieving efficient and effective retrieval performance. In our approach, the color features are extracted using the mean shift algorithm, a robust clustering technique. Then the cluster (region) mode is used as representative of the image in 3-D color space. The feature descriptor consists of the representative color of a region and is indexed using a spatial indexing method that uses *R -tree thus avoiding the high-dimensional indexing problems associated with the traditional color histogram. Alternatively, the images in the database are clustered based on region feature similarity using Euclidian distance. Only representative (centroids) features of these clusters are indexed using *R -tree thus improving the efficiency. For similarity retrieval, each representative color in the query image or region is used independently to find regions containing that color. The results of these methods are compared. A JAVA based query engine supporting query-by- example is built to retrieve images by color.
Abstract: The present study is concerned with the absorption
center of photophoresis within a micro-sized and spheroidal particle in
a gaseous medium. A particle subjected to an intense light beam can
absorb electromagnetic energy within the particle unevenly, which
results in photophoretic force to drive the particle in motion. By
evaluating the energy distribution systematically at various conditions,
the study focuses on the effects of governing parameters, such as
particle aspect ratio, size parameter, refractivity, and absorptivity, on
the heat source function within the particle and their potential
influences to the photophoresis.
Abstract: To unveil the mechanism of fast autooxidation of fish
myoglobins, the effect of temperature on the structural change of tuna
myoglobin was investigated. Purified myoglobin was subjected to
preincubation at 5, 20, 50 and 40oC. Overall helical structural decay
through thermal treatment up to 95oC was monitored by circular
dichroism spectrometry, while the structural changes around the heme
pocket was measured by ultraviolet/visible absorption spectrophotometry.
As a result, no essential structural change of myoglobin
was observed under 30oC, roughly equivalent to their body
temperature, but the structure was clearly damaged at 40oC. The Soret
band absorption hardly differed irrespective of preincubation
temperature, suggesting that the structure around the heme pocket was
not perturbed even after thermal treatment.
Abstract: Wireless Sensor Networks (WSNs) are used to monitor/observe vast inaccessible regions through deployment of large number of sensor nodes in the sensing area. For majority of WSN applications, the collected data needs to be combined with geographic information of its origin to make it useful for the user; information received from remote Sensor Nodes (SNs) that are several hops away from base station/sink is meaningless without knowledge of its source. In addition to this, location information of SNs can also be used to propose/develop new network protocols for WSNs to improve their energy efficiency and lifetime. In this paper, range free localization protocols for WSNs have been proposed. The proposed protocols are based on weighted centroid localization technique, where the edge weights of SNs are decided by utilizing fuzzy logic inference for received signal strength and link quality between the nodes. The fuzzification is carried out using (i) Mamdani, (ii) Sugeno, and (iii) Combined Mamdani Sugeno fuzzy logic inference. Simulation results demonstrate that proposed protocols provide better accuracy in node localization compared to conventional centroid based localization protocols despite presence of unintentional radio frequency interference from radio frequency (RF) sources operating in same frequency band.
Abstract: Visualizing sound and noise often help us to determine
an appropriate control over the source localization. Near-field acoustic
holography (NAH) is a powerful tool for the ill-posed problem.
However, in practice, due to the small finite aperture size, the discrete
Fourier transform, FFT based NAH couldn-t predict the activeregion-
of-interest (AROI) over the edges of the plane. Theoretically
few approaches were proposed for solving finite aperture problem.
However most of these methods are not quite compatible for the
practical implementation, especially near the edge of the source. In
this paper, a zip-stuffing extrapolation approach has suggested with
2D Kaiser window. It is operated on wavenumber complex space
to localize the predicted sources. We numerically form a practice
environment with touch impact databases to test the localization of
sound source. It is observed that zip-stuffing aperture extrapolation
and 2D window with evanescent components provide more accuracy
especially in the small aperture and its derivatives.