Abstract: Detecting changes in multiple images of the same
scene has recently seen increased interest due to the many
contemporary applications including smart security systems, smart
homes, remote sensing, surveillance, medical diagnosis, weather
forecasting, speed and distance measurement, post-disaster forensics
and much more. These applications differ in the scale, nature, and
speed of change. This paper presents an application of image
processing techniques to implement a real-time change detection
system. Change is identified by comparing the RGB representation of
two consecutive frames captured in real-time. The detection threshold
can be controlled to account for various luminance levels. The
comparison result is passed through a filter before decision making to
reduce false positives, especially at lower luminance conditions. The
system is implemented with a MATLAB Graphical User interface
with several controls to manage its operation and performance.
Abstract: An early diagnosis of bone metastasis is very
important for making a right decision on a subsequent therapy. One
of the most important steps to be taken initially, for developing a new
radiopharmaceutical is the measurement of organ radiation exposure
dose. In this study, the dosimetric studies of a novel agent for
SPECT-imaging of the bone metastasis, 111In-(4-
{[(bis(phosphonomethyl))carbamoyl]methyl}7,10bis(carboxymethyl)
-1,4,7,10-tetraazacyclododec-1-yl) acetic acid (111In-BPAMD)
complex, have been carried out to estimate the dose in human organs
based on the data derived from mice. The radiolabeled complex was
prepared with high radiochemical purity in the optimal conditions.
Biodistribution studies of the complex was investigated in the male
Syrian mice at the selected times after injection (2, 4, 24 and 48 h).
The human absorbed dose estimation of the complex was made based
on data derived from the mice by the radiation absorbed dose
assessment resource (RADAR) method. 111In-BPAMD complex was prepared with high radiochemical
purity >95% (ITLC) and specific activities of 2.85 TBq/mmol. Total
body effective absorbed dose for 111In-BPAMD was 0.205
mSv/MBq. This value is comparable to the other 111In clinically used
complexes. The results show that the dose with respect to the critical
organs is satisfactory within the acceptable range for diagnostic
nuclear medicine procedures. Generally, 111In-BPAMD has
interesting characteristics and it can be considered as a viable agent
for SPECT-imaging of the bone metastasis in the near future.
Abstract: Myocardial infarction is one of the leading causes of
death in the world. Some of these deaths occur even before the
patient reaches the hospital. Myocardial infarction occurs as a result
of impaired blood supply. Because the most of these deaths are due to
coronary artery disease, hence the awareness of the warning signs of
a heart attack is essential. Some heart attacks are sudden and intense,
but most of them start slowly, with mild pain or discomfort, then
early detection and successful treatment of these symptoms is vital to
save them. Therefore, importance and usefulness of a system
designing to assist physicians in early diagnosis of the acute heart
attacks is obvious. The main purpose of this study would be to enable patients to
become better informed about their condition and to encourage them
to seek professional care at an earlier stage in the appropriate
situations. For this purpose, the data were collected on 711 heart
patients in Iran hospitals. 28 attributes of clinical factors can be
reported by patients; were studied. Three logistic regression models
were made on the basis of the 28 features to predict the risk of heart
attacks. The best logistic regression model in terms of performance
had a C-index of 0.955 and with an accuracy of 94.9%. The variables,
severe chest pain, back pain, cold sweats, shortness of breath, nausea
and vomiting, were selected as the main features.
Abstract: Cortisol is essential to the regulation of the immune
system and pathological yawning is a symptom of multiple sclerosis
(MS). Electromyography activity (EMG) in the jaw muscles typically
rises when the muscles are moved – extended or flexed; and yawning
has been shown to be highly correlated with cortisol levels in healthy
people as shown in the Thompson Cortisol Hypothesis. It is likely
that these elevated cortisol levels are also seen in people with MS.
The possible link between EMG in the jaw muscles and rises in saliva
cortisol levels during yawning were investigated in a randomized
controlled trial of 60 volunteers aged 18-69 years who were exposed
to conditions that were designed to elicit the yawning response.
Saliva samples were collected at the start and after yawning, or at the
end of the presentation of yawning-provoking stimuli, in the absence
of a yawn, and EMG data was additionally collected during rest and
yawning phases. Hospital Anxiety and Depression Scale, Yawning
Susceptibility Scale, General Health Questionnaire, demographic,
and health details were collected and the following exclusion criteria
were adopted: chronic fatigue, diabetes, fibromyalgia, heart
condition, high blood pressure, hormone replacement therapy,
multiple sclerosis, and stroke. Significant differences were found
between the saliva cortisol samples for the yawners, t (23) = -4.263, p
= 0.000, as compared with the non-yawners between rest and poststimuli,
which was non-significant. There were also significant
differences between yawners and non-yawners for the EMG
potentials with the yawners having higher rest and post-yawning
potentials. Significant evidence was found to support the Thompson
Cortisol Hypothesis suggesting that rises in cortisol levels are
associated with the yawning response. Further research is underway
to explore the use of cortisol as a potential diagnostic tool as an assist
to the early diagnosis of symptoms related to neurological disorders.
Bournemouth University Research & Ethics approval granted:
JC28/1/13-KA6/9/13. Professional code of conduct, confidentiality,
and safety issues have been addressed and approved in the Ethics
submission. Trials identification number: ISRCTN61942768.
http://www.controlled-trials.com/isrctn/
Abstract: Lots of motors have been being used in industry.
Therefore many researchers have studied about the failure diagnosis of
motors. In this paper, the effect of measuring environment for
diagnosis of gear fault connected to a motor shaft is studied. The fault
diagnosis is executed through the comparison of normal gear and
abnormal gear. The measured FFT data are compared with the normal
data and analyzed for q-axis current, noise and vibration. For bad and
good environment, the diagnosis results are compared. From these, it
is shown that the bad measuring environment may not be able to detect
exactly the motor gear fault. Therefore it is emphasized that the
measuring environment should be carefully prepared.
Abstract: Measuring the Electrocardiogram (ECG) signal is an
essential process for the diagnosis of the heart diseases. The ECG
signal has the information of the degree of how much the heart
performs its functions. In medical diagnosis and treatment systems,
Decision Support Systems processing the ECG signal are being
developed for the use of clinicians while medical examination. In this
study, a modular wireless ECG (WECG) measuring and recording
system using a single board computer and e-Health sensor platform
is developed. In this designed modular system, after the ECG signal
is taken from the body surface by the electrodes first, it is filtered and
converted to digital form. Then, it is recorded to the health database
using Wi-Fi communication technology. The real time access of the
ECG data is provided through the internet utilizing the developed
web interface.
Abstract: Objective: Sharing devastating news with patients is
often considered the most difficult task of doctors. This study aimed
to explore patients’ perceptions of receiving bad news including
which features improve the experience and which areas need refining. Methods: A questionnaire was written based on the steps of the
SPIKES model for breaking bad new. 20 patients receiving treatment
for a hematological malignancy completed the questionnaire. Results: Overall, the results are promising as most patients praised
their consultation. ‘Poor’ was more commonly rated by women and
participants aged 45-64. The main differences between the ‘excellent’
and ‘poor’ consultations include the doctor’s sensitivity and checking
the patients’ understanding. Only 35% of patients were asked their
existing knowledge and 85% of consultations failed to discuss the
impact of the diagnosis on daily life. Conclusion: This study agreed with the consensus of existing
literature. The commended aspects include consultation set-up and
information given. Areas patients felt needed improvement include
doctors determining the patient’s existing knowledge and checking
new information has been understood. Doctors should also explore
how the diagnosis will affect the patient’s life. With a poorer
prognosis, doctors should work on conveying appropriate hope. The
study was limited by a small sample size and potential recall bias.
Abstract: Cole-Cole parameters of 40 post-menopausal women
are compared with their DEXA bone mineral density measurements.
Impedance characteristics of four extremities are compared; left and
right extremities are statistically same, but lower extremities are
statistically different than upper ones due to their different fat
content. The correlation of Cole-Cole impedance parameters to bone
mineral density (BMD) is observed to be higher for dominant arm.
With the post-menopausal population, ANOVA tests of the dominant
arm characteristic frequency, as a predictor for DEXA classified
osteopenic and osteoporic population around lumbar spine, is
statistically very significant. When used for total lumbar spine
osteoporosis diagnosis, the area under the Receiver Operating Curve
of the characteristic frequency is 0.830, suggesting that the Cole-Cole
plot characteristic frequency could be a useful diagnostic parameter
when integrated into standard screening methods for osteoporosis.
Moreover, the characteristic frequency can be directly measured by
monitoring frequency driven angular behavior of the dominant arm
without performing any complex calculation.
Abstract: Computer aided diagnosis systems provide vital
opinion to radiologists in the detection of early signs of breast cancer
from mammogram images. Architectural distortions, masses and
microcalcifications are the major abnormalities. In this paper, a
computer aided diagnosis system has been proposed for
distinguishing abnormal mammograms with architectural distortion
from normal mammogram. Four types of texture features GLCM
texture, GLRLM texture, fractal texture and spectral texture features
for the regions of suspicion are extracted. Support vector machine
has been used as classifier in this study. The proposed system yielded
an overall sensitivity of 96.47% and an accuracy of 96% for
mammogram images collected from digital database for screening
mammography database.
Abstract: Socio-economic development, which is seen around
the world today, has contributed to the emergence of new problems
of a social nature. Different political, historical, geographical or
economic conditions cause that, in addition to global issues of social
policy such as an aging population, unemployment, migration,
countries, regions, there are also specific new problems that require
diagnosis, individualized approach and efficient, planned solutions.
These should include, among others, digital addiction, peer violence,
obesity among children, the problem of ‘legal highs’, stress,
depression, diseases associated with environmental pollution etc. The
central authorities, selected most often with the tools specific to
representative democracy, that is, the general election, for many
reasons, inter alia, organizational, communication, are not able to
effectively diagnose their intensity, territorial distribution, and thus to
effectively fight them. This article aims to show how in Poland,
citizens influence solving problems related to the broader social
policy implemented at the local government level and indicates the
possibilities of improving those solutions. The conclusions of
theoretical analysis have been supported by empirical studies, which
tested the use of instruments of participatory democracy in the
planning and creation of communal strategies for solving social
problems in one of the Polish voivodeships.
Abstract: Early diagnosis of infection like Hep-B virus in blood
is important for low cost medical treatment. For this purpose, it is
desirable to develop a point of care device which should be able to
detect trace quantities of the target molecule in blood. In this paper,
we report a nanoporous silicon oxide sensor which is capable of
detecting down to 1fM concentration of Hep-B surface antigen in
blood without the requirement of any centrifuge or pre-concentration.
This has been made possible by the presence of resonant peak in the
sensitivity characteristics. This peak is observed to be dependent only
on the concentration of the specific antigen and not on the interfering
species in blood serum. The occurrence of opposite impedance
change within the pores and at the bottom of the pore is responsible
for this effect. An electronic interface has also been designed to
provide a display of the virus concentration.
Abstract: Testability modeling is a commonly used method in
testability design and analysis of system. A dependency matrix will be
obtained from testability modeling, and we will give a quantitative
evaluation about fault detection and isolation.
Based on the dependency matrix, we can obtain the diagnosis tree.
The tree provides the procedures of the fault detection and isolation.
But the dependency matrix usually includes built-in test (BIT) and
manual test in fact. BIT runs the test automatically and is not limited
by the procedures. The method above cannot give a more efficient
diagnosis and use the advantages of the BIT.
A Comprehensive method of fault detection and isolation is
proposed. This method combines the advantages of the BIT and
Manual test by splitting the matrix. The result of the case study shows
that the method is effective.
Abstract: Taiwan is a hyper endemic area for the Hepatitis B
virus (HBV). The estimated total number of HBsAg carriers in the
general population who are more than 20 years old is more than 3
million. Therefore, a case record review is conducted from January
2003 to June 2007 for all patients with a diagnosis of acute hepatitis
who were admitted to the Emergency Department (ED) of a
well-known teaching hospital. The cost for the use of medical
resources is defined as the total medical fee. In this study, principal
component analysis (PCA) is firstly employed to reduce the number of
dimensions. Support vector regression (SVR) and artificial neural
network (ANN) are then used to develop the forecasting model. A total
of 117 patients meet the inclusion criteria. 61% patients involved in
this study are hepatitis B related. The computational result shows that
the proposed PCA-SVR model has superior performance than other
compared algorithms. In conclusion, the Child-Pugh score and
echogram can both be used to predict the cost of medical resources for
patients with acute hepatitis in the ED.
Abstract: This paper presents a novel integrated hybrid
approach for fault diagnosis (FD) of nonlinear systems. Unlike most
FD techniques, the proposed solution simultaneously accomplishes
fault detection, isolation, and identification (FDII) within a unified
diagnostic module. At the core of this solution is a bank of adaptive
neural parameter estimators (NPE) associated with a set of singleparameter
fault models. The NPEs continuously estimate unknown
fault parameters (FP) that are indicators of faults in the system. Two
NPE structures including series-parallel and parallel are developed
with their exclusive set of desirable attributes. The parallel scheme is
extremely robust to measurement noise and possesses a simpler, yet
more solid, fault isolation logic. On the contrary, the series-parallel
scheme displays short FD delays and is robust to closed-loop system
transients due to changes in control commands. Finally, a fault
tolerant observer (FTO) is designed to extend the capability of the
NPEs to systems with partial-state measurement.
Abstract: The mechanisms underlying the association between
obesity and asthma may be related to a decreased immunological
tolerance induced by a defective function of regulatory T cells
(Tregs). The aim of this study is to establish the potential link
between these diseases and CD4+, CD25+ FoxP3+ Tregs as well as T
helper cells (Ths) in children. This is a prospective case control
study. Obese (n:40), asthmatic (n:40), asthmatic obese (n:40) and
healthy children (n:40), who don't have any acute or chronic diseases,
were included in this study. Obese children were evaluated according
to WHO criteria. Asthmatic patients were chosen based on GINA
criteria. Parents were asked to fill up the questionnaire. Informed
consent forms were taken. Blood samples were marked with CD4+,
CD25+ and FoxP3+ in order to determine Tregs and Ths by flow
cytometric method. Statistical analyses were performed. p≤0.05 was
chosen as meaningful threshold. Tregs exhibiting anti-inflammatory
nature were significantly lower in obese (0,16%; p≤0,001), asthmatic
(0,25%; p≤0,01) and asthmatic obese (0,29%; p≤0,05) groups than
the control group (0,38%). Ths were counted higher in asthma group
than the control (p≤0,01) and obese (p≤0,001) groups. T cell
immunity plays important roles in obesity and asthma pathogeneses.
Decreased numbers of Tregs found in obese, asthmatic and asthmatic
obese children may help to elucidate some questions in
pathophysiology of these diseases. For HOMA-IR levels, any
significant difference was not noted between control and obese
groups, but statistically higher values were found for obese
asthmatics. The values obtained in all groups were found to be below
the critical cut off points. This finding has made the statistically
significant difference observed between Tregs of obese, asthmatic,
obese asthmatic and control groups much more valuable. These
findings will be useful in diagnosis and treatment of these disorders
and future studies are needed. The production and propagation of
Tregs may be promising in alternative asthma and obesity treatments.
Abstract: Image segmentation plays an important role in
medical imaging applications. Therefore, accurate methods are
needed for the successful segmentation of medical images for
diagnosis and detection of various diseases. In this paper, we have
used maximum entropy to achieve image segmentation. Maximum
entropy has been calculated using Shannon, Renyi and Tsallis
entropies. This work has novelty based on the detection of skin lesion
caused by the bite of a parasite called Sand Fly causing the disease is
called Cutaneous Leishmaniasis.
Abstract: In medical investigations, uncertainty is a major
challenging problem in making decision for doctors/experts to
identify the diseases with a common set of symptoms and also has
been extensively increasing in medical diagnosis problems. The
theory of cross entropy for intuitionistic fuzzy sets (IFS) is an
effective approach in coping uncertainty in decision making for
medical diagnosis problem. The main focus of this paper is to
propose a new intuitionistic fuzzy cross entropy measure (IFCEM),
which aid in reducing the uncertainty and doctors/experts will take
their decision easily in context of patient’s disease. It is shown that
the proposed measure has some elegant properties, which
demonstrates its potency. Further, it is also exemplified in detail the
efficiency and utility of the proposed measure by using a real life
case study of diagnosis the disease in medical science.
Abstract: Wireless Sensor Networks (WSNs) have wide variety
of applications and provide limitless future potentials. Nodes in
WSNs are prone to failure due to energy depletion, hardware failure,
communication link errors, malicious attacks, and so on. Therefore,
fault tolerance is one of the critical issues in WSNs. We study how
fault tolerance is addressed in different applications of WSNs. Fault
tolerant routing is a critical task for sensor networks operating in
dynamic environments. Many routing, power management, and data
dissemination protocols have been specifically designed for WSNs
where energy awareness is an essential design issue. The focus,
however, has been given to the routing protocols which might differ
depending on the application and network architecture.
Abstract: The effects of hypertension are often lethal thus its
early detection and prevention is very important for everybody. In
this paper, a neural network (NN) model was developed and trained
based on a dataset of hypertension causative parameters in order to
forecast the likelihood of occurrence of hypertension in patients. Our
research goal was to analyze the potential of the presented NN to
predict, for a period of time, the risk of hypertension or the risk of
developing this disease for patients that are or not currently
hypertensive. The results of the analysis for a given patient can
support doctors in taking pro-active measures for averting the
occurrence of hypertension such as recommendations regarding the
patient behavior in order to lower his hypertension risk. Moreover,
the paper envisages a set of three example scenarios in order to
determine the age when the patient becomes hypertensive, i.e.
determine the threshold for hypertensive age, to analyze what
happens if the threshold hypertensive age is set to a certain age and
the weight of the patient if being varied, and, to set the ideal weight
for the patient and analyze what happens with the threshold of
hypertensive age.
Abstract: Pulmonary Function Tests are important non-invasive
diagnostic tests to assess respiratory impairments and provides
quantifiable measures of lung function. Spirometry is the most
frequently used measure of lung function and plays an essential role
in the diagnosis and management of pulmonary diseases. However,
the test requires considerable patient effort and cooperation,
markedly related to the age of patients resulting in incomplete data
sets. This paper presents, a nonlinear model built using Multivariate
adaptive regression splines and Random forest regression model to
predict the missing spirometric features. Random forest based feature
selection is used to enhance both the generalization capability and the
model interpretability. In the present study, flow-volume data are
recorded for N= 198 subjects. The ranked order of feature importance
index calculated by the random forests model shows that the
spirometric features FVC, FEF25, PEF, FEF25-75, FEF50 and the
demographic parameter height are the important descriptors. A
comparison of performance assessment of both models prove that, the
prediction ability of MARS with the `top two ranked features namely
the FVC and FEF25 is higher, yielding a model fit of R2= 0.96 and
R2= 0.99 for normal and abnormal subjects. The Root Mean Square
Error analysis of the RF model and the MARS model also shows that
the latter is capable of predicting the missing values of FEV1 with a
notably lower error value of 0.0191 (normal subjects) and 0.0106
(abnormal subjects) with the aforementioned input features. It is
concluded that combining feature selection with a prediction model
provides a minimum subset of predominant features to train the
model, as well as yielding better prediction performance. This
analysis can assist clinicians with a intelligence support system in the
medical diagnosis and improvement of clinical care.