Abstract: Since prestressed concrete members rely on the tensile
strength of the prestressing strands to resist loads, loss of even few
them could result catastrophic. Therefore, it is important to measure
present residual prestress force. Although there are some techniques
for obtaining present prestress force, some problems still remain. One
method is to install load cell in front of anchor head but this may
increase cost. Load cell is a transducer using the elastic material
property. Anchor head is also an elastic material and this might result
in monitoring monitor present prestress force. Features of fiber optic
sensor such as small size, great sensitivity, high durability can assign
sensing function to anchor head. This paper presents the concept of
smart anchor head which acts as load cell and experiment for the
applicability of it. Test results showed the smart anchor head worked
good and strong linear relationship between load and response.
Abstract: The article deals with technical support of intracranial single unit activity measurement. The parameters of the whole measuring set were tested in order to assure the optimal conditions of extracellular single-unit recording. Metal microelectrodes for measuring the single-unit were tested during animal experiments. From signals recorded during these experiments, requirements for the measuring set parameters were defined. The impedance parameters of the metal microelectrodes were measured. The frequency-gain and autonomous noise properties of preamplifier and amplifier were verified. The measurement and the description of the extracellular single unit activity could help in prognoses of brain tissue damage recovery.
Abstract: Fracture process in mechanically loaded steel fiber
reinforced high-strength (SFRHSC) concrete is characterized by
fibers bridging the crack providing resistance to its opening.
Structural SFRHSC fracture model was created; material fracture
process was modeled, based on single fiber pull-out laws, which were
determined experimentally (for straight fibers, fibers with end hooks
(Dramix), and corrugated fibers (Tabix)) as well as obtained
numerically ( using FEM simulations). For this purpose experimental
program was realized and pull-out force versus pull-out fiber length
was obtained (for fibers embedded into concrete at different depth
and under different angle). Model predictions were validated by
15x15x60cm prisms 4 point bending tests. Fracture surfaces analysis
was realized for broken prisms with the goal to improve elaborated
model assumptions. Optimal SFRHSC structures were recognized.
Abstract: Optimization study of the diesters biolubricant oleyl 9(12)-hydroxy-10(13)-oleioxy-12(9)-octadecanoate (OLHYOOT) was synthesized in the presence of sulfuric acid (SA) as catalyst has been done. Optimum conditions of the experiment to obtain high yield% of OLHYOOT were predicted at ratio of OL/HYOOA of 1:1 g/g, ratio of SA/HYOOA of 0.20:1 g/g, reaction temperature 110 °C and 4.5 h of reaction time. At this condition, the Yield% of OLHYOOT was 88.7. Disappearance of carboxylic acid (C=O) peak has observed by FTIR with appearance ester (C=O) at 1738 cm-1. 1H NMR spectra analyses confirmed the result of OLHYOOT with appearance ester (-CHOCOR) at 4.05ppm and also the 13C-NMR confirmed the result with appearance ester (C=O) peak at 173.93ppm.
Abstract: Availability of high dimensional biological datasets such as from gene expression, proteomic, and metabolic experiments can be leveraged for the diagnosis and prognosis of diseases. Many classification methods in this area have been studied to predict disease states and separate between predefined classes such as patients with a special disease versus healthy controls. However, most of the existing research only focuses on a specific dataset. There is a lack of generic comparison between classifiers, which might provide a guideline for biologists or bioinformaticians to select the proper algorithm for new datasets. In this study, we compare the performance of popular classifiers, which are Support Vector Machine (SVM), Logistic Regression, k-Nearest Neighbor (k-NN), Naive Bayes, Decision Tree, and Random Forest based on mock datasets. We mimic common biological scenarios simulating various proportions of real discriminating biomarkers and different effect sizes thereof. The result shows that SVM performs quite stable and reaches a higher AUC compared to other methods. This may be explained due to the ability of SVM to minimize the probability of error. Moreover, Decision Tree with its good applicability for diagnosis and prognosis shows good performance in our experimental setup. Logistic Regression and Random Forest, however, strongly depend on the ratio of discriminators and perform better when having a higher number of discriminators.
Abstract: Prostate cancer is one of the most frequent cancers in men and is a major cause of mortality in the most of countries. In many diagnostic and treatment procedures for prostate disease accurate detection of prostate boundaries in transrectal ultrasound (TRUS) images is required. This is a challenging and difficult task due to weak prostate boundaries, speckle noise and the short range of gray levels. In this paper a novel method for automatic prostate segmentation in TRUS images is presented. This method involves preprocessing (edge preserving noise reduction and smoothing) and prostate segmentation. The speckle reduction has been achieved by using stick filter and top-hat transform has been implemented for smoothing. A feed forward neural network and local binary pattern together have been use to find a point inside prostate object. Finally the boundary of prostate is extracted by the inside point and an active contour algorithm. A numbers of experiments are conducted to validate this method and results showed that this new algorithm extracted the prostate boundary with MSE less than 4.6% relative to boundary provided manually by physicians.
Abstract: Considering non-ideal behavior of fluids and its effects on hydrodynamic and mass transfer in multiphase flow is very essential. Simulations were performed that takes into account the effects of mass transfer and mixture non-ideality on hydrodynamics reported by Irani et al. In this paper, by assuming the density of phases to be constant and Raullt-s law instead of using EOS and fugacity coefficient definition, respectively for both the liquid and gas phases, the importance of non-ideality effects on mass transfer and hydrodynamic behavior was studied. The results for a system of octane/propane (T=323 K, P =445 kpa) also indicated that the assumption of constant density in simulation had major role to diverse from experimental data. Furthermore, comparison between obtained results and the previous report indicated significant differences between experimental data and simulation results with more ideal assumptions.
Abstract: A novel path planning approach is presented to solve
optimal path in stochastic, time-varying networks under priori traffic
information. Most existing studies make use of dynamic programming
to find optimal path. However, those methods are proved to
be unable to obtain global optimal value, moreover, how to design
efficient algorithms is also another challenge.
This paper employs a decision theoretic framework for defining
optimal path: for a given source S and destination D in urban transit
network, we seek an S - D path of lowest expected travel time
where its link travel times are discrete random variables. To solve
deficiency caused by the methods of dynamic programming, such as
curse of dimensionality and violation of optimal principle, an integer
programming model is built to realize assignment of discrete travel
time variables to arcs. Simultaneously, pruning techniques are also
applied to reduce computation complexity in the algorithm. The final
experiments show the feasibility of the novel approach.
Abstract: This paper presents an algorithm for the recognition
and tracking of moving objects, 1/10 scale model car is used to verify
performance of the algorithm. Presented algorithm for the recognition
and tracking of moving objects in the paper is as follows. SURF
algorithm is merged with Lucas-Kanade algorithm. SURF algorithm
has strong performance on contrast, size, rotation changes and it
recognizes objects but it is slow due to many computational
complexities. Processing speed of Lucas-Kanade algorithm is fast but
the recognition of objects is impossible. Its optical flow compares the
previous and current frames so that can track the movement of a pixel.
The fusion algorithm is created in order to solve problems which
occurred using the Kalman Filter to estimate the position and the
accumulated error compensation algorithm was implemented. Kalman
filter is used to create presented algorithm to complement problems
that is occurred when fusion two algorithms. Kalman filter is used to
estimate next location, compensate for the accumulated error. The
resolution of the camera (Vision Sensor) is fixed to be 640x480. To
verify the performance of the fusion algorithm, test is compared to
SURF algorithm under three situations, driving straight, curve, and
recognizing cars behind the obstacles. Situation similar to the actual is
possible using a model vehicle. Proposed fusion algorithm showed
superior performance and accuracy than the existing object
recognition and tracking algorithms. We will improve the performance
of the algorithm, so that you can experiment with the images of the
actual road environment.
Abstract: The most important parameter in transformers life
expectancy is the hot-spot temperature level which accelerates the
rate of aging of the insulation. The aim of this paper is to present
thermal models for transformers loaded at prefabricated MV/LV
transformer substations and outdoor situations. The hot-spot
temperature of transformers is studied using their top-oil temperature
rise models. The thermal models proposed for hot-spot and top-oil
temperatures of different operating situations are compared. Since the
thermal transfer is different for indoor and outdoor transformers
considering their operating conditions, their hot-spot thermal models
differ from each other. The proposed thermal models are verified by
the results obtained from the experiments carried out on a typical
1600 kVA, 30 /0.4 kV, ONAN transformer for both indoor and
outdoor situations.
Abstract: The Muslim faith requires individuals to fast between
the hours of sunrise and sunset during the month of Ramadan. Our
recent work has concentrated on some of the changes that take place
during the daytime when fasting. A questionnaire was developed to
assess subjective estimates of physical, mental and social activities,
and fatigue. Four days were studied: in the weeks before and after
Ramadan (control days) and during the first and last weeks of
Ramadan (experimental days). On each of these four days, this
questionnaire was given several times during the daytime and once
after the fast had been broken and just before individuals retired at
night.
During Ramadan, daytime mental, physical and social activities
all decreased below control values but then increased to abovecontrol
values in the evening. The desires to perform physical and
mental activities showed very similar patterns. That is, individuals
tried to conserve energy during the daytime in preparation for the
evenings when they ate and drank, often with friends. During
Ramadan also, individuals were more fatigued in the daytime and
napped more often than on control days. This extra fatigue probably
reflected decreased sleep, individuals often having risen earlier
(before sunrise, to prepare for fasting) and retired later (to enable
recovery from the fast).
Some physiological measures and objective measures of
performance (including the response to a bout of exercise) have also
been investigated. Urine osmolality fell during the daytime on
control days as subjects drank, but rose in Ramadan to reach values
at sunset indicative of dehydration. Exercise performance was also
compromised, particularly late in the afternoon when the fast had
lasted several hours. Self-chosen exercise work-rates fell and a set
amount of exercise felt more arduous. There were also changes in
heart rate and lactate accumulation in the blood, indicative of greater
cardiovascular and metabolic stress caused by the exercise in
subjects who had been fasting. Daytime fasting in Ramadan produces
widespread effects which probably reflect combined effects of sleep
loss and restrictions to intakes of water and food.
Abstract: Subsurface erosion in river banks and its details, in
spite of its occurrence in various parts of the world has rarely been
paid attention by researchers. In this paper, quantitative concept of
the subsurface bank erosion has been investigated for vertical banks.
Vertical banks were simulated experimentally by considering a sandy
erodible layer overlaid by clayey one under uniformly distributed
constant overhead pressure. Results of the experiments are indicated
that rate of sandy layer erosion is decreased by an increase in
overburden; likewise, substituting 20% of coarse (3.5 mm) sand layer
bed material by fine material (1.4 mm) may lead to a decrease in
erosion rate by one-third. This signifies the importance of the bed
material composition effect on sandy layers erosion due to subsurface
erosion in river banks.
Abstract: Performance of millimeter-wave (mm-wave) multiband
orthogonal frequency division multiplexing (MB-OFDM) ultrawideband
(UWB) signal generation using frequency quadrupling
technique and transmission over fiber is experimentally investigated.
The frequency quadrupling is achived by using only one Mach-
Zehnder modulator (MZM) that is biased at maximum transmission
(MATB) point. At the output, a frequency quadrupling signal is
obtained then sent to a second MZM. This MZM is used for MBOFDM
UWB signal modulation. In this work, we demonstrate 30-
GHz mm-wave wireless that carries three-bands OFDM UWB
signals, and error vector magnitude (EVM) is used to analyze the
transmission quality. It is found that our proposed technique leads to
an improvement of 3.5 dB in EVM at 40% of local oscillator (LO)
modulation with comparison to the technique using two cascaded
MZMs biased at minimum transmission (MITB) point.
Abstract: Intravitreal injection (IVI) is the most common treatment for eye posterior segment diseases such as endopthalmitis, retinitis, age-related macular degeneration, diabetic retinopathy, uveitis, and retinal detachment. Most of the drugs used to treat vitreoretinal diseases, have a narrow concentration range in which they are effective, and may be toxic at higher concentrations. Therefore, it is critical to know the drug distribution within the eye following intravitreal injection. Having knowledge of drug distribution, ophthalmologists can decide on drug injection frequency while minimizing damage to tissues. The goal of this study was to develop a computer model to predict intraocular concentrations and pharmacokinetics of intravitreally injected drugs. A finite volume model was created to predict distribution of two drugs with different physiochemical properties in the rabbit eye. The model parameters were obtained from literature review. To validate this numeric model, the in vivo data of spatial concentration profile from the lens to the retina were compared with the numeric data. The difference was less than 5% between the numerical and experimental data. This validation provides strong support for the numerical methodology and associated assumptions of the current study.
Abstract: We propose a fast and robust hierarchical face detection system which finds and localizes face images with a cascade of classifiers. Three modules contribute to the efficiency of our detector. First, heterogeneous feature descriptors are exploited to enrich feature types and feature numbers for face representation. Second, a PSO-Adaboost algorithm is proposed to efficiently select discriminative features from a large pool of available features and reinforce them into the final ensemble classifier. Compared with the standard exhaustive Adaboost for feature selection, the new PSOAdaboost algorithm reduces the training time up to 20 times. Finally, a three-stage hierarchical classifier framework is developed for rapid background removal. In particular, candidate face regions are detected more quickly by using a large size window in the first stage. Nonlinear SVM classifiers are used instead of decision stump functions in the last stage to remove those remaining complex nonface patterns that can not be rejected in the previous two stages. Experimental results show our detector achieves superior performance on the CMU+MIT frontal face dataset.
Abstract: In this paper, we propose a new approach to query-by-humming, focusing on MP3 songs database. Since MP3 songs are much more difficult in melody representation than symbolic performance data, we adopt to extract feature descriptors from the vocal sounds part of the songs. Our approach is based on signal filtering, sub-band spectral processing, MDCT coefficients analysis and peak energy detection by ignorance of the background music as much as possible. Finally, we apply dual dynamic programming algorithm for feature similarity matching. Experiments will show us its online performance in precision and efficiency.
Abstract: This paper presents the source extraction system which can extract only target signals with constraints on source localization in on-line systems. The proposed system is a kind of methods for enhancing a target signal and suppressing other interference signals. But, the performance of proposed system is superior to any other methods and the extraction of target source is comparatively complete. The method has a beamforming concept and uses an improved time-frequency (TF) mask-based BSS algorithm to separate a target signal from multiple noise sources. The target sources are assumed to be in front and test data was recorded in a reverberant room. The experimental results of the proposed method was evaluated by the PESQ score of real-recording sentences and showed a noticeable speech enhancement.
Abstract: Deformable active contours are widely used in
computer vision and image processing applications for image
segmentation, especially in biomedical image analysis. The active
contour or “snake" deforms towards a target object by controlling the
internal, image and constraint forces. However, if the contour
initialized with a lesser number of control points, there is a high
probability of surpassing the sharp corners of the object during
deformation of the contour. In this paper, a new technique is
proposed to construct the initial contour by incorporating prior
knowledge of significant corners of the object detected using the
Harris operator. This new reconstructed contour begins to deform, by
attracting the snake towards the targeted object, without missing the
corners. Experimental results with several synthetic images show the
ability of the new technique to deal with sharp corners with a high
accuracy than traditional methods.
Abstract: Undoubtedly, chassis is one of the most important
parts of a vehicle. Chassis that today are produced for vehicles are
made up of four parts. These parts are jointed together by screwing.
Transverse parts are called cross member.
This study reviews the stress generated by cyclic laboratory loads
in front cross member of Peugeot 405. In this paper the finite element
method is used to simulate the welding process and to determine the
physical response of the spot-welded joints. Analysis is done by the
Abaqus software.
The Stresses generated in cross member structure are generally
classified into two groups: The stresses remained in form of residual
stresses after welding process and the mechanical stress generated by
cyclic load. Accordingly the total stress must be obtained by
determining residual stress and mechanical stress separately and then
sum them according to the superposition principle.
In order to improve accuracy, material properties including
physical, thermal and mechanical properties were supposed to be
temperature-dependent. Simulation shows that maximum Von Misses
stresses are located at special points. The model results are then
compared to the experimental results which are reported by
producing factory and good agreement is observed.
Abstract: The fundamental defect inherent to the thermoforming
technology is wall-thickness variation of the products due to
inadequate thermal processing during production of polymer. A
nonlinear viscoelastic rheological model is implemented for
developing the process model. This model describes deformation
process of a sheet in thermoforming process. Because of relaxation
pause after plug-assist stage and also implementation of two stage
thermoforming process have minor wall-thickness variation and
consequently better mechanical properties of polymeric articles. For
model validation, a comparative analysis of the theoretical and
experimental data is presented.