Abstract: Hepatitis B and hepatitis C are among the most
significant hepatic infections all around the world that may lead to
hepatocellular carcinoma. This study is first time performed at the
blood transfussion centre of Omar hospital, Lahore. It aims to
determine the sero-prevalence of these diseases by screening the
apparently healthy blood donors who might be the carriers of HBV or
HCV and pose a high risk in the transmission. It also aims the
comparison between the sensitivity of two diagnostic tests;
chromatographic immunoassay – one step test device and Enzyme
Linked Immuno Sorbant Assay (ELISA). Blood serum of 855
apparently healthy blood donors was screened for Hepatitis B surface
antigen (HBsAg) and for anti HCV antibodies. SPSS version 12.0
and X2 (Chi-square) test were used for statistical analysis. The seroprevalence
of HCV was 8.07% by the device method and by ELISA
9.12% and that of HBV was 5.6% by the device and 6.43% by
ELISA. The unavailability of vaccination against HCV makes it more
prevalent. Comparing the two diagnostic methods, ELISA proved to
be more sensitive.
Abstract: This paper used a fuzzy kohonen neural network for medical image segmentation. Image segmentation plays a important role in the many of medical imaging applications by automating or facilitating the diagnostic. The paper analyses the tumor by extraction of the features of (area, entropy, means and standard deviation).These measurements gives a description for a tumor.
Abstract: The level of visual abilities, language, memory
processes and intellectual functioning development affects the quality
of a written text. The following analysis will present the results of
diagnostic tests indicating the most common criterion for a group and
stating whether a person has been diagnosed with having cognitive
developmental level below the group-s average or not.The study-s
aim is to determine whether there are specific patterns of cognitive
deficits, which can be distinguished among the group of young
people with spelling disorders.
Abstract: In this study, we present a new and fast algorithm for lung segmentation using CTA images. This process is quite important especially at lung vessel segmentation, detection of pulmonary emboly, finding nodules or segmentation of airways. Applied method has been carried out at four steps. At first step, images have been applied optimal threshold. At the second one, the subsegment vessels, which have a place in lung region and which are in small dimension, have been removed. At the third one, identifying and segmentation of lungs and airway edges have been carried out. Lastly, by throwing away the airway, lung segmentation has been presented.
Abstract: Sonogram images of normal and lymphocyte thyroid tissues have considerable overlap which makes it difficult to interpret and distinguish. Classification from sonogram images of thyroid gland is tackled in semiautomatic way. While making manual diagnosis from images, some relevant information need not to be recognized by human visual system. Quantitative image analysis could be helpful to manual diagnostic process so far done by physician. Two classes are considered: normal tissue and chronic lymphocyte thyroid (Hashimoto's Thyroid). Data structure is analyzed using K-nearest-neighbors classification. This paper is mentioned that unlike the wavelet sub bands' energy, histograms and Haralick features are not appropriate to distinguish between normal tissue and Hashimoto's thyroid.
Abstract: Occurrence of a multiple-points fault in machine operations could result in exhibiting complex fault signatures, which could result in lowering fault diagnosis accuracy. In this study, a multiple-points defect model (MPDM) is proposed which can simulate fault signature-s dynamics for n-points bearing faults. Furthermore, this study identifies that in case of multiple-points fault in the rotary machine, the location of the dominant component of defect frequency shifts depending upon the relative location of the fault points which could mislead the fault diagnostic model to inaccurate detections. Analytical and experimental results are presented to characterize and validate the variation in the dominant component of defect frequency. Based on envelop detection analysis, a modification is recommended in the existing fault diagnostic models to consider the multiples of defect frequency rather than only considering the frequency spectrum at the defect frequency in order to incorporate the impact of multiple points fault.
Abstract: Laser Doppler flowmetry is a modern method of noninvasive
microcirculation investigation. The aim of our study was to
use this method in the examination of patients with secondary
lymphedema of the lower extremities and obliterating atherosclerosis
of lower extremities. In the analysis of the amplitude-frequency
spectrum of secondary lymphedema patients we have identified
remarkable changes. To describe the changes we used a special
amplitude rate. In both of patients groups this rate was significally
(p
Abstract: Two optimized strategies were successfully established
to develop biomolecule-based magnetic nanoassemblies.
Streptavidin-coated and amine-coated magnetic nanoparticles were
chosen as model scaffolds onto which double-stranded DNA and
human immunoglobulin G were specifically conjugated in succession,
using biotin-streptavidin interaction or covalent cross-linkers. The
success of this study opens the prospect of developing selective and
sensitive nanoparticle-based structures for diagnostics or drug
delivery.
Abstract: Ultrafast doped zinc oxide crystal promised us a good
opportunity to build new instruments for ICF fusion neutron
measurement. Two pulsed neutron detectors based on ZnO crystal
wafer have been conceptually designed, the superfast ZnO timing
detector and the scintillation recoil proton neutron detection system.
The structure of these detectors was presented, and some characters
were studied as well. The new detectors could be much faster than
existing systems, and would be more competent for ICF neutron
diagnostics.
Abstract: With the advance of multimedia and diagnostic
images technologies, the number of radiographic images is increasing
constantly. The medical field demands sophisticated systems for
search and retrieval of the produced multimedia document. This
paper presents an ongoing research that focuses on the semantic
content of radiographic image documents to facilitate semantic-based
radiographic image indexing and a retrieval system. The proposed
model would divide a radiographic image document, based on its
semantic content, and would be converted into a logical structure or
a semantic structure. The logical structure represents the overall
organization of information. The semantic structure, which is bound
to logical structure, is composed of semantic objects with
interrelationships in the various spaces in the radiographic image.
Abstract: Until recently, researchers have developed various
tools and methodologies for effective clinical decision-making.
Among those decisions, chest pain diseases have been one of
important diagnostic issues especially in an emergency department. To
improve the ability of physicians in diagnosis, many researchers have
developed diagnosis intelligence by using machine learning and data
mining. However, most of the conventional methodologies have been
generally based on a single classifier for disease classification and
prediction, which shows moderate performance. This study utilizes an
ensemble strategy to combine multiple different classifiers to help
physicians diagnose chest pain diseases more accurately than ever.
Specifically the ensemble strategy is applied by using the integration
of decision trees, neural networks, and support vector machines. The
ensemble models are applied to real-world emergency data. This study
shows that the performance of the ensemble models is superior to each
of single classifiers.
Abstract: The objective of this work is to explicit knowledge on the interactions between the chlorophyll-a and nine meroplankton larvae of epibenthonic fauna. The studied case is the Arraial do Cabo upwelling system, Southeastern of Brazil, which provides different environmental conditions. To assess this information a network approach based in probability estimative was used. Comparisons among the generated graphs are made in the light of different water masses, application of Shannon biodiversity index, and the closeness and betweenness centralities measurements. Our results show the main pattern among different water masses and how the core organisms belonging to the network skeleton are correlated to the main environmental variable. We conclude that the approach of complex networks is a promising tool for environmental diagnostic.
Abstract: Both prognostic and diagnostic modes of a 3D baroclinic
model in hydrodynamic and sediment transport models of
the Princeton Ocean Model (POM) were conducted to separate
prognose and diagnose effects of different hydrodynamic factors on
transport of suspended sediment discharged from the rivers to the
Gulf of Thailand (GoT). Both transport modes of suspended sediment
distribution in the GoT were numerically simulated. It could be
concluded that the suspended sediment discharged from the rivers
around the GoT. Most of sediments in estuaries and coastal areas are
deposited outside the GoT under the condition of wind-driven current,
and very small amount of the sediments of them are transported
faraway. On the basis of wind forcing, sediments from the lower
GoT to the upper GoT are mainly transported south-northwestward
and also continuously moved north-southwestward. An obvious 3D
characteristic of suspended sediment transport is produced in the
wind-driven current residual circulation condition. In this study, the
transport patterns at the third layer are generally consistent with
the typhoon-induced strong currents in two case studies of Typhoon
Linda 1997. The case studies presented the prognostic and diagnostic
modes during 00UTC28OCT1997 to 12UTC06NOV1997 in a short
period with the current condition for pre-operation of the suspended
sediment transport model in estuaries and coastal areas.
Abstract: Diabetes Mellitus is a chronic metabolic disorder, where the improper management of the blood glucose level in the diabetic patients will lead to the risk of heart attack, kidney disease and renal failure. This paper attempts to enhance the diagnostic accuracy of the advancing blood glucose levels of the diabetic patients, by combining principal component analysis and wavelet neural network. The proposed system makes separate blood glucose prediction in the morning, afternoon, evening and night intervals, using dataset from one patient covering a period of 77 days. Comparisons of the diagnostic accuracy with other neural network models, which use the same dataset are made. The comparison results showed overall improved accuracy, which indicates the effectiveness of this proposed system.
Abstract: The object of this work is the probabilistic performance evaluation of safety instrumented systems (SIS), i.e. the average probability of dangerous failure on demand (PFDavg) and the average frequency of failure (PFH), taking into account the uncertainties related to the different parameters that come into play: failure rate (λ), common cause failure proportion (β), diagnostic coverage (DC)... This leads to an accurate and safe assessment of the safety integrity level (SIL) inherent to the safety function performed by such systems. This aim is in keeping with the requirement of the IEC 61508 standard with respect to handling uncertainty. To do this, we propose an approach that combines (1) Monte Carlo simulation and (2) fuzzy sets. Indeed, the first method is appropriate where representative statistical data are available (using pdf of the relating parameters), while the latter applies in the case characterized by vague and subjective information (using membership function). The proposed approach is fully supported with a suitable computer code.
Abstract: Functional gastrointestinal disorders affect millions of people spread all age regardless of race and sex. There are, however, rare diagnostic methods for the functional gastrointestinal disorders because functional disorders show no evidence of organic and physical causes. Our research group identified recently that the gastrointestinal tract well in the patients with the functional gastrointestinal disorders becomes more rigid than healthy people when palpating the abdominal regions overlaying the gastrointestinal tract. Aim of this study is, therefore, to develop a diagnostic system for the functional gastrointestinal disorders based on ultrasound technique, which can quantify the characteristic above related to the rigidity of the gastrointestinal tract well. Ultrasound system was designed. The system consisted of transmitter, ultrasonic transducer, receiver, TGC, and CPLD, and verified via a phantom test. For the phantom test, ten soft-tissue specimens were harvested from porcine. Five of them were then treated chemically to mimic a rigid condition of gastrointestinal tract well, which was induced by functional gastrointestinal disorders. Additionally, the specimens were tested mechanically to identify if the mimic was reasonable. The customized ultrasound system was finally verified through application to human subjects with/without functional gastrointestinal disorders (Normal and Patient Groups). It was identified from the mechanical test that the chemically treated specimens were more rigid than normal specimen. This finding was favorably compared with the result obtained from the phantom test. The phantom test also showed that ultrasound system well described the specimen geometric characteristics and detected an alteration in the specimens. The maximum amplitude of the ultrasonic reflective signal in the rigid specimens (0.2±0.1Vp-p) at the interface between the fat and muscle layers was explicitly higher than that in the normal specimens (0.1±0.0Vp-p). Clinical tests using our customized ultrasound system for human subject showed that the maximum amplitudes of the ultrasonic reflective signals near to the gastrointestinal tract well for the patient group (2.6±0.3Vp-p) were generally higher than those in normal group (0.1±0.2Vp-p). Here, maximum reflective signals was appeared at 20mm depth approximately from abdominal skin for all human subjects, corresponding to the location of the boundary layer close to gastrointestinal tract well. These results suggest that newly designed diagnostic system based on ultrasound technique may diagnose enough the functional gastrointestinal disorders.
Abstract: Diagnostic goal of transformers in service is to detect the winding or the core in fault. Transformers are valuable equipment which makes a major contribution to the supply security of a power system. Consequently, it is of great importance to minimize the frequency and duration of unwanted outages of power transformers. So, Frequency Response Analysis (FRA) is found to be a useful tool for reliable detection of incipient mechanical fault in a transformer, by finding winding or core defects. The authors propose as first part of this article, the coupled circuits method, because, it gives most possible exhaustive modelling of transformers. And as second part of this work, the application of FRA in low frequency in order to improve and simplify the response reading. This study can be useful as a base data for the other transformers of the same categories intended for distribution grid.
Abstract: Many contemporary telemedical applications rely on
regular consultations over the phone or video conferencing which
consumes valuable resources such as the time of the doctors. Some
applications or treatments allow automated diagnostics on the patient
side which only notifies the doctors in case a significant worsening
of patient’s condition is measured.
Such programs can save valuable resources but an important
implementation issue is how to ensure effective and cheap diagnostics
on the patient side. First, specific diagnostic devices on patient side
are expensive and second, they need to be user-˜friendly to encourage
patient’s cooperation and reduce errors in usage which may cause
noise in diagnostic data.
This article proposes the use of modern smartphones and various
build-in or attachable sensors as universal diagnostic devices applicable
in a wider range of telemedical programs and demonstrates their
application on a case-study – a program for schizophrenic relapse
prevention.
Abstract: This paper presents an approach for early breast
cancer diagnostic by employing combination of artificial neural
networks (ANN) and multiwaveletpacket based subband image
decomposition. The microcalcifications correspond to high-frequency
components of the image spectrum, detection of microcalcifications
is achieved by decomposing the mammograms into different
frequency subbands,, reconstructing the mammograms from the
subbands containing only high frequencies. For this approach we
employed different types of multiwaveletpacket. We used the result
as an input of neural network for classification. The proposed
methodology is tested using the Nijmegen and the Mammographic
Image Analysis Society (MIAS) mammographic databases and
images collected from local hospitals. Results are presented as the
receiver operating characteristic (ROC) performance and are
quantified by the area under the ROC curve.
Abstract: Large metal and concrete structures suffer by various kinds of deterioration, and accurate prediction of the remaining life is important. This paper informs about two methods for its assessment. One method, suitable for steel bridges and other constructions exposed to fatigue, monitors the loads and damage accumulation using information systems for the operation and the finite element model of the construction. In addition to the operation load, the dead weight of the construction and thermal stresses can be included into the model. The second method is suitable for concrete bridges and other structures, which suffer by carbonatation and other degradation processes, driven by diffusion. The diffusion constant, important for the prediction of future development, can be determined from the depth-profile of pH, obtained by pH measurement at various depths. Comparison with measurements on real objects illustrates the suitability of both methods.