Abstract: In this study, a three-dimensional haptotaxis model to simulate the migration of a population of cancer cells has been proposed. The invasion of cancer cells is related with the hapto-attractant and the effect of the interface energies between the cells and the ECM. The diffuse interface model, which incorporates the haptotaxis mechanism and interface energies, is employed. The semi-implicit Fourier spectral scheme is adopted for efficient evaluation of the simulation. The simulation results thoroughly reveal the dynamics of cancer-cell migration.
Abstract: The heart tissue is an excitable media. A Cellular
Automata is a type of model that can be used to model cardiac action
potential propagation. One of the advantages of this approach against
the methods based on differential equations is its high speed in large
scale simulations. Recent cellular automata models are not able to
avoid flat edges in the result patterns or have large neighborhoods. In
this paper, we present a new model to eliminate flat edges by
minimum number of neighbors.
Abstract: This paper reports a new pattern recognition approach for face recognition. The biological model of light receptors - cones and rods in human eyes and the way they are associated with pattern vision in human vision forms the basis of this approach. The functional model is simulated using CWD and WPD. The paper also discusses the experiments performed for face recognition using the features extracted from images in the AT & T face database. Artificial Neural Network and k- Nearest Neighbour classifier algorithms are employed for the recognition purpose. A feature vector is formed for each of the face images in the database and recognition accuracies are computed and compared using the classifiers. Simulation results show that the proposed method outperforms traditional way of feature extraction methods prevailing for pattern recognition in terms of recognition accuracy for face images with pose and illumination variations.
Abstract: the reliability analysis of the medical equipments can
help to increase the availability and the efficiency of the systems. In
this manuscript we present a simple method of decomposition that
could be easily applied on the complex medical systems. Using this
method we can easily calculate the effect of the subsystems or
components on the reliability of the overall system. Furthermore, to
investigate the effect of subsystems or components on system
performance, we perform a numerical study varying every time the
worst reliability of subsystem or component with another which has
higher reliability. It can also be useful to engineers and designers of
medical equipment, who wishes to optimize the complex systems.
Abstract: In this paper, the vessel inscribed trigonometry (VITM) for the vessel progression orientation (VPO) is proposed in the two-dimensional fundus image. The VPO is a major factor in the optic disc (OD) detection which is a basic process in the retina analysis. To measure the VPO, skeletons of vessel are used. First, the vessels are classified into three classes as vessel end, vessel branch and vessel stem. And the chain code maps of VS are generated. Next, two farthest neighborhoods of each point on VS are searched by the proposed angle restriction. Lastly, a gradient of the straight line between two farthest neighborhoods is estimated to measure the VPO. VITM is validated by comparing with manual results and 2D Gaussian templates. It is confirmed that VPO of the proposed mensuration is correct enough to detect OD from the results of experiment which applied VITM to detect OD in fundus images.
Abstract: Early detection of breast cancer is considered as a
major public health issue. Breast cancer screening is not generalized
to the entire population due to a lack of resources, staff and
appropriate tools. Systematic screening can result in a volume of data
which can not be managed by present computer architecture, either in
terms of storage capabilities or in terms of exploitation tools. We
propose in this paper to design and develop a data warehouse system
in radiology-senology (DWRS). The aim of such a system is on one
hand, to support this important volume of information providing from
multiple sources of data and images and for the other hand, to help
assist breast cancer screening in diagnosis, education and research.
Abstract: Segmentation of Magnetic Resonance Imaging (MRI) images is the most challenging problems in medical imaging. This paper compares the performances of Seed-Based Region Growing (SBRG), Adaptive Network-Based Fuzzy Inference System (ANFIS) and Fuzzy c-Means (FCM) in brain abnormalities segmentation. Controlled experimental data is used, which designed in such a way that prior knowledge of the size of the abnormalities are known. This is done by cutting various sizes of abnormalities and pasting it onto normal brain tissues. The normal tissues or the background are divided into three different categories. The segmentation is done with fifty seven data of each category. The knowledge of the size of the abnormalities by the number of pixels are then compared with segmentation results of three techniques proposed. It was proven that the ANFIS returns the best segmentation performances in light abnormalities, whereas the SBRG on the other hand performed well in dark abnormalities segmentation.
Abstract: It has been shown that pH 7,3 and 37 0C are the optimal condition for the growth of E. coli “ASAP". The cells grow well on Glucose, Lactose, D-Mannitol, D-Sorbitol, (+)-Xylose, L- (+)-Arabinose and Dulcitol. No growth has been observed on Sucrose, Inositol, Phenylalanine, and Tryptophan. The strain is sensitive to a range of antibiotics. The present study has demonstrated that E. coli “ASAP" inhibit the growth of S. enterica ATCC #700931 in vitro. The studies on conjugating activity has revealed no conjugant of E. coli “ASAP" with plasmid strains E. coli G35#59 and S. enterica ATCC #700931. On the other hand, the conjugants with low frequencies were obtained from E. coli “ASAP" with E. coli G35#61, and E. coli “ASAP" with randomly chosen isolate from healthy human gut microflora: E. coli E6. The results of present study have demonstrated improvements in gut microflora condition of patients with different diseases after the administration of “ASAP"
Abstract: Nosocomial (i.e., hospital-acquired) infections
(NI) is a major cause of morbidity and mortality in hospitals. NI
rate is higher in intensive care units (ICU) than in the general
ward due to patients with severe symptoms, poor immunity,
and accepted many invasive therapies. Contact behaviors
between health caregivers and patients is one of the infect
factors. It is difficult to obtain complete contact records by
traditional method of retrospective analysis of medical records.
This paper establishes a contact history inferential model
(CHIM) intended to extend the use of Proximity Sensing of
rapid frequency identification (RFID) technology to
transferring all proximity events between health caregivers and
patients into clinical events (close-in events, contact events and
invasive events).The results of the study indicated that the
CHIM can infer proximity care activities into close-in events
and contact events.
The infection control team could redesign and build optimal
workflow in the ICU according to the patient-specific contact
history which provided by our automatic tracing system.
Abstract: In this paper, a novel method for a biometric system based on the ECG signal is proposed, using spectral coefficients computed through linear predictive coding (LPC). ECG biometric systems have traditionally incorporated characteristics of fiducial points of the ECG signal as the feature set. These systems have been shown to contain loopholes and thus a non-fiducial system allows for tighter security. In the proposed system, incorporating non-fiducial features from the LPC spectrum produced a segment and subject recognition rate of 99.52% and 100% respectively. The recognition rates outperformed the biometric system that is based on the wavelet packet decomposition (WPD) algorithm in terms of recognition rates and computation time. This allows for LPC to be used in a practical ECG biometric system that requires fast, stringent and accurate recognition.
Abstract: Heart sound is an acoustic signal and many techniques
used nowadays for human recognition tasks borrow speech recognition
techniques. One popular choice for feature extraction of accoustic
signals is the Mel Frequency Cepstral Coefficients (MFCC) which
maps the signal onto a non-linear Mel-Scale that mimics the human
hearing. However the Mel-Scale is almost linear in the frequency
region of heart sounds and thus should produce similar results with
the standard cepstral coefficients (CC). In this paper, MFCC is
investigated to see if it produces superior results for PCG based
human identification system compared to CC. Results show that the
MFCC system is still superior to CC despite linear filter-banks in
the lower frequency range, giving up to 95% correct recognition rate
for MFCC and 90% for CC. Further experiments show that the high
recognition rate is due to the implementation of filter-banks and not
from Mel-Scaling.
Abstract: The purpose of this work is measurement of the
system presampling MTF of a variable resolution x-ray (VRX) CT
scanner. In this paper, we used the parameters of an actual VRX CT
scanner for simulation and study of effect of different focal spot sizes
on system presampling MTF by Monte Carlo method (GATE
simulation software). Focal spot size of 0.6 mm limited the spatial
resolution of the system to 5.5 cy/mm at incident angles of below 17º
for cell#1. By focal spot size of 0.3 mm the spatial resolution
increased up to 11 cy/mm and the limiting effect of focal spot size
appeared at incident angles of below 9º. The focal spot size of 0.3
mm could improve the spatial resolution to some extent but because
of magnification non-uniformity, there is a 10 cy/mm difference
between spatial resolution of cell#1 and cell#256. The focal spot size
of 0.1 mm acted as an ideal point source for this system. The spatial
resolution increased to more than 35 cy/mm and at all incident angles
the spatial resolution was a function of incident angle. By the way
focal spot size of 0.1 mm minimized the effect of magnification nonuniformity.
Abstract: Antibacterial activity of Plumeria alba (Frangipani)
petals methanolic extracts were evaluated against Escherichia coli,
Proteus vulgaris,Staphylococcus aureus, Klebsiella pneumoniae,
Pseudomonas aeruginosa, Staphylococcus saprophyticus,
Enterococcus faecalis and Serratia marcescens by using disk
diffusion method. Concentration extracts (80 %) showed the highest
inhibition zone towards Escherichia coli (14.3 mm). Frangipani
extract also showed high antibacterial activity against
Staphylococcus saprophyticus, Proteus vulgaris and Serratia
marcescens, but not more than the zones of the positive control used.
Comparison between two broad specrum antibiotics to frangipani
extracts showed that the 80 % concentration extracts produce the
same zone of inhibition as Streptomycin. Frangipani extracts showed
no bacterial activity towards Klebsiella pneumoniae, Pseudomonas
aeruginosa and Enterococcus faecalis. There are differences in the
sensitivity of different bacteria to frangipani extracts, suggesting that
frangipani-s potency varies between these bacteria. The present
results indicate that frangipani showed significant antibacterial
activity especially to Escherichia coli.
Abstract: Various sounds generated in the chest are included in
auscultation sound. Adaptive Noise Canceller (ANC) is one of the
useful techniques for biomedical signal. But the ANC is not suitable
for auscultation sound. Because the ANC needs two input channels as
a primary signal and a reference signals, but a stethoscope can
provide just one input sound. Therefore, in this paper, it was
proposed the Single Input ANC (SIANC) for suppression of breath
sound in a cardiac auscultation sound. For the SIANC, it was
proposed that the reference generation system which included Heart
Sound Detector, Control and Reference Generator. By experiment
and comparison, it was confirmed that the proposed SIANC was
efficient for heart sound enhancement and it was independent of
variations of a heartbeat.
Abstract: This paper discusses the effectiveness of the EEG signal
for human identification using four or less of channels of two different
types of EEG recordings. Studies have shown that the EEG signal
has biometric potential because signal varies from person to person
and impossible to replicate and steal. Data were collected from 10
male subjects while resting with eyes open and eyes closed in 5
separate sessions conducted over a course of two weeks. Features
were extracted using the wavelet packet decomposition and analyzed
to obtain the feature vectors. Subsequently, the neural networks
algorithm was used to classify the feature vectors. Results show that,
whether or not the subjects- eyes were open are insignificant for a 4–
channel biometrics system with a classification rate of 81%. However,
for a 2–channel system, the P4 channel should not be included if data
is acquired with the subjects- eyes open. It was observed that for 2–
channel system using only the C3 and C4 channels, a classification
rate of 71% was achieved.
Abstract: Many high-risk pathogens that cause disease in
humans are transmitted through various food items. Food-borne
disease constitutes a major public health problem. Assessment of the
quality and safety of foods is important in human health. Rapid and
easy detection of pathogenic organisms will facilitate precautionary
measures to maintain healthy food. The Polymerase Chain Reaction
(PCR) is a handy tool for rapid detection of low numbers of bacteria.
We have designed gene specific primers for most common food
borne pathogens such as Staphylococci, Salmonella and E.coli.
Bacteria were isolated from food samples of various food outlets and
identified using gene specific PCRs. We identified Staphylococci,
Salmonella and E.coli O157 using gene specific primers by rapid and
direct PCR technique in various food samples. This study helps us in
getting a complete picture of the various pathogens that threaten to
cause and spread food borne diseases and it would also enable
establishment of a routine procedure and methodology for rapid
identification of food borne bacteria using the rapid technique of
direct PCR. This study will also enable us to judge the efficiency of
present food safety steps taken by food manufacturers and exporters.
Abstract: Researchers of drug-drug interaction alert systems
have often suggested that there were high overridden rate for alerts and
also too false alerts. However, research about decreasing false alerts is
scant. Therefore, the aim of this article attempts to proactive
identification of false alert for drug-drug interaction and provide
solution to decrease false alerts. This research involved retrospective
analysis prescribing database and calculated false alert rate by using
MYSQL and JAVA. Results of this study showed 17% of false alerts
and the false alert rate in the hospitals (37%) was more than in the
clinics. To conclude, this study described the importance that
drug-drug interaction alert system should not only detect drug name
but also detect frequency or route, as well as in providing solution to
decrease false alerts.