Abstract: The existing two-dimensional micro-Doppler features extraction ignores the correlation information between the spatial and temporal dimension features. For the range-Doppler map, the time dimension is introduced, and a frequency modulation continuous wave (FMCW) radar human fall detection algorithm based on time-varying range-Doppler features is proposed. Firstly, the range-Doppler sequence maps are generated from the echo signals of the continuous motion of the human body collected by the radar. Then the three-dimensional data cube composed of multiple frames of range-Doppler maps is input into the three-dimensional Convolutional Neural Network (3D CNN). The spatial and temporal features of time-varying range-Doppler are extracted by the convolution layer and pool layer at the same time. Finally, the extracted spatial and temporal features are input into the fully connected layer for classification. The experimental results show that the proposed fall detection algorithm has a detection accuracy of 95.66%.
Abstract: Classification of high resolution polarimetric Synthetic Aperture Radar (PolSAR) images plays an important role in land cover and land use management. Recently, classification algorithms based on Bag of Visual Words (BOVW) model have attracted significant interest among scholars and researchers in and out of the field of remote sensing. In this paper, BOVW model with pixel based low-level features has been implemented to classify a subset of San Francisco bay PolSAR image, acquired by RADARSAR 2 in C-band. We have used segment-based decision-making strategy and compared the result with the result of traditional Support Vector Machine (SVM) classifier. 90.95% overall accuracy of the classification with the proposed algorithm has shown that the proposed algorithm is comparable with the state-of-the-art methods. In addition to increase in the classification accuracy, the proposed method has decreased undesirable speckle effect of SAR images.
Abstract: Ground Penetrating Radar (GPR) is one of the most effective electromagnetic techniques for non-destructive non-invasive subsurface features investigation. Water leak from pipelines is the most common undesirable reason of potable water losses. Rapid detection of such losses is going to enhance the use of the Water Distribution Networks (WDN) and decrease threatens associated with water mains leaks. In this study, GPR approach was developed to detect leaks by implementing an appropriate imaging analyzing strategy based on image refinement, reflection polarity and reflection amplitude that would ease the process of interpreting the collected raw radargram image.
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: Abstract—[Tris (1,10-phenanthroline) lanthanum(III)]
trithiocyanate is a new compound that has shown high ability for
stopping the synthesis of DNA and also acting as a photosensitizer.
Nowadays, the radiation dose assessment resource (RADAR) method
is known as the most common method for absorbed dose calculation.
177Lu was produced by (n, gamma) reaction in a research reactor.
177Lu-PL3 was prepared in the optimized condition. The
radiochemical yield was checked by ITLC method. The
biodistribution of the complex was investigated by intravenously
injection to wild-type rats via their tail veins. In this study, the
absorbed dose of 177Lu-PL3 to human organs was estimated by
RADAR method. 177Lu was prepared with a specific activity of 2.6-3
GBq.mg-1 and radionuclide purity of 99.98 %. Final preparation of
the radiolabelled complex showed high radiochemical purity of >
99%. The results show that liver and spleen have received the highest
absorbed dose of 1.051 and 0.441 mSv/MBq, respectively. The
absorbed dose values for these two dose-limiting tissues suggest
more biological studies special in tumor-bearing animals.
Abstract: The measurement of organ radiation exposure dose is
one of the most important steps to be taken initially, for developing a
new radiopharmaceutical. In this study, the dosimetric studies of a
novel agent for SPECT-imaging of the bone metastasis, 111In-
1,4,7,10-tetraazacyclododecane-1,4,7,10 tetraethylene phosphonic
acid (111In-DOTMP) complex, have been carried out to estimate the
dose in human organs based on the data derived from rats. The
radiolabeled complex was prepared with high radiochemical purity in
the optimal conditions. Biodistribution studies of the complex was
investigated in the male Syrian rats at 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 rats by the
radiation absorbed dose assessment resource (RADAR) method.
111In-DOTMP complex was prepared with high radiochemical purity
of >99% (ITLC). Total body effective absorbed dose for 111In-
DOTMP was 0.061 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-
DOTMP has interesting characteristics and can be considered as a
viable agent for SPECT-imaging of the bone metastasis in the near
future.
Abstract: The conventional rectangular horn has been used for microwave antenna a long time. Its gain can be increased by enlarging the construction of horn to flare exponentially. This paper presents a study of the shaped woodpile Electromagnetic Band Gap (EBG) to improve its gain for conventional horn without construction enlargement. The gain enhancement synthesis method for shaped woodpile EBG that has to transfer the electromagnetic fields from aperture of a horn antenna through woodpile EBG is presented by using the variety of shaped woodpile EBGs such as planar, triangular, quadratic, circular, gaussian, cosine, and squared cosine structures. The proposed technique has the advantages of low profile, low cost for fabrication and light weight. The antenna characteristics such as reflection coefficient (S11), radiation patterns and gain are simulated by utilized A Computer Simulation Technology (CST) software. With the proposed concept, an antenna prototype was fabricated and experimented. The S11 and radiation patterns obtained from measurements show a good impedance matching and a gain enhancement of the proposed antenna. The gain at dominant frequency of 10 GHz is 25.6 dB, application for X- and Ku-Band Radar, that higher than the gain of the basic rectangular horn antenna around 8 dB with adding only one appropriated EBG structures.
Abstract: Design and implementation of a novel B-ACOSD CFAR algorithm is presented in this paper. It is proposed for detecting radar target in log-normal distribution environment. The BACOSD detector is capable to detect automatically the number interference target in the reference cells and detect the real target by an adaptive threshold. The detector is implemented as a System on Chip on FPGA Altera Stratix II using parallelism and pipelining technique. For a reference window of length 16 cells, the experimental results showed that the processor works properly with a processing speed up to 115.13MHz and processing time0.29 ┬Ás, thus meets real-time requirement for a typical radar system.
Abstract: Support Vector Machine (SVM) is a statistical
learning tool that was initially developed by Vapnik in 1979 and later
developed to a more complex concept of structural risk minimization
(SRM). SVM is playing an increasing role in applications to
detection problems in various engineering problems, notably in
statistical signal processing, pattern recognition, image analysis, and
communication systems. In this paper, SVM was applied to the
detection of SAR (synthetic aperture radar) images in the presence of
partially developed speckle noise. The simulation was done for single
look and multi-look speckle models to give a complete overlook and
insight to the new proposed model of the SVM-based detector. The
structure of the SVM was derived and applied to real SAR images
and its performance in terms of the mean square error (MSE) metric
was calculated. We showed that the SVM-detected SAR images have
a very low MSE and are of good quality. The quality of the
processed speckled images improved for the multi-look model.
Furthermore, the contrast of the SVM detected images was higher
than that of the original non-noisy images, indicating that the SVM
approach increased the distance between the pixel reflectivity levels
(the detection hypotheses) in the original images.
Abstract: This work deals with unsupervised image deblurring.
We present a new deblurring procedure on images provided by lowresolution
synthetic aperture radar (SAR) or simply by multimedia in
presence of multiplicative (speckle) or additive noise, respectively.
The method we propose is defined as a two-step process. First, we
use an original technique for noise reduction in wavelet domain.
Then, the learning of a Kohonen self-organizing map (SOM) is
performed directly on the denoised image to take out it the blur. This
technique has been successfully applied to real SAR images, and the
simulation results are presented to demonstrate the effectiveness of
the proposed algorithms.
Abstract: There are many automotive accidents due to blind spots and driver inattentiveness. Blind spot is the area that is invisible to the driver's viewpoint without head rotation. Several methods are available for assisting the drivers. Simplest methods are — rear mirrors and wide-angle lenses. But, these methods have a disadvantage of the requirement for human assistance. So, the accuracy of these devices depends on driver. Another approach called an automated approach that makes use of sensors such as sonar or radar. These sensors are used to gather range information. The range information will be processed and used for detecting the collision. The disadvantage of this system is — low angular resolution and limited sensing volumes. This paper is a panoramic sensor based automotive vehicle monitoring..