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Oil pollution on the ocean has been highlighted in the past 40 years by several tanker accidents in Europe, like those of Exxon Valdez, Erika or Prestige. But these oil tanker accidents only account for a few percent of the total oil pollution worldwide and hide the regular pollution in important traffic zones like the Mediterranean and other oceans caused by oil drillings or illegal discharges. Due...
Automatic identification of specific osseous landmarks on the spinal radiograph can be used to automate calculations for correcting ligament instability and injury, which affect 75% of patients injured in motor vehicle accidents. In this work, we propose to use deep learning based object detection method as the first step towards identifying landmark points in lateral lumbar X-ray images. The significant...
In this paper, we propose a novel lattice reduction (LR) algorithm for the low-complexity multiple-input multiple-output (MIMO) detection with near-maximum-likelihood (ML) performance. The proposed LR algorithm is designed considering both the hardware complexity and the power consumption. First, a modified column traverse strategy is proposed to reduce the worst-case complexity (hardware complexity)...
C.L.E.O. (Cleaner of Lower Earth Orbit) is a space architecture concept that aims at removing debris, ranged between 1 to 10 cm and even larger in diameter. The module consists of two systems; the capturing mechanism and module stabilization. The oncoming debris will be identified using MWIR sensors. Due to the rotatory tendency of the debris, algorithms are used which will find the size, shape and...
As wireless technologies continue to advance the radio spectrum has become more congested. Spectrum utilization can be enhanced considerably by allowing a secondary user to use a licensed band when the primary user (PU) is not present. Cognitive radio (CR) promotes the efficient use of the spectrum. Cyclostationary detection is a method for detecting primary user transmissions by taking advantage...
This paper presents a design of particle detection system based on optical transmission and scattering method. In this setup, a laser with emitting wavelength of 671 nm is employed. The sample particles are 3.03 um and 7.07 um polystyrene microspheres. Based on Mie scattering theory and Beer-Lambert law, the particle size and particle number concentrations against the scattered light intensity and...
By exploiting the communication infrastructure among the sensors, actuators and control systems, attackers can compromise the security of the power systems with unknown cyber attack. In this paper, Luenberger observer-based algorithm is proposed to detect and isolate the cyber attack in smart power systems. Firstly, a simple classical linearized version of swing model is considered, where the smart...
To implement on-board detection and matching of feature points on satellite, a FPGA-based hardware architecture of prototype was proposed in this paper. The SURF detector and the BRIEF descriptor are implemented on the selected FPGA (Xilinx K7 XC7K325T-1ffg900). Experiment results indicated that the detection speed of one frame with size of 256 × 256 was 1.5 ms under the clock frequency was 100MHz...
Aiming at the problem of traffic flow detection, a method of detecting traffic flow by GNSS-R is proposed for the first time. Using the dielectric constant difference between the vehicle and the ground, it is possible to judge whether the vehicle is present in the detection area. After receiving the reflection signal in the detection area, and calculating the signal-to-noise ratio and the related...
An RFI processor breadboard has been designed and developed for future spaceborne microwave radiometer systems. RFI detection is based on the anomalous amplitude, kurtosis, and cross-frequency algorithms. These are implemented in VHDL code in an FPGA. Thus algorithm performance can be assessed by proper code simulation. The breadboard has been integrated with a Ku band radiometer subjected to RFI-like...
In this work, the problem of developing algorithms that automatically infer information about small-scale solar photovoltaic (PV) arrays in high resolution aerial imagery is considered. Such algorithms potentially offer a faster and cheaper solution to collecting small-scale PV information, such as their location and capacity. Existing work on this topic has focused on the automatic identification...
In this work, we consider the problem of detecting target objects in remote sensing imagery; such as detecting rooftops, trees, or cars in color/hyperspectral imagery. Many detection algorithms for this problem work by assigning a decision statistic (or “confidence”) to all, or a subset, of spatial locations in the data. A threshold is then applied to the statistics to identify detections. The detection...
Radio-Frequency Interference (RFI) is a growing problem for applications based on the Global Navigation Satellite Systems (GNSS), including Earth observation using GNSS — Reflectometry (GNSS-R). Nowadays, many efforts are being concentrated to develop RFI signal detectors with high sensitivity, which can help to control the proliferation of RFI generators or jammers. This work aims at designing and...
Wireless Sensor Networks (WSNs) are collection of large number of sensor nodes that are used for essential monitoring purposes. They include many applications such as military and security applications, elementary monitoring, seismic monitoring, industrialized automation, wellness and robust monitoring etc. Due to its distributed nature and interconnected network approach, they are considered common...
The article shows the methods of vehicle recognition on the image sequence and its trajectory registration. As a recognition algorithm authors used Viola-Jones method with optical flow filter and the deep convolutional neural network in combination with sliding window technique for vehicle detection task. Also authors analyze approaches to registration of detected vehicle trajectories on image sequence...
Action recognition from well-segmented 3D skeleton video has been intensively studied. However, due to the difficulty in representing the 3D skeleton video and the lack of training data, action detection from streaming 3D skeleton video still lags far behind its recognition counterpart and image-based object detection. In this paper, we propose a novel approach for this problem, which leverages both...
An infrastructure to record, detect and label the behavioral patterns of children with Autism Spectrum Disorder (ASD) has been developed. The system incorporates 2 different sensor platforms which are wearable and static. The wearable system is based on accelerometer which detects behavioral patterns of a subject, while the static sensors are microphones and cameras which captures the sounds, images...
Cataract is the most common cause of global blindness. Early detection and grading of cataract helps reduce the vision loss. Clinical grading of cataract is subjective and time consuming process but it has a vital role in treatment planning for cataract patients. Automatic detection and grading of cataract greatly improved the health care services for the cataract patients. A number of medical imaging...
Unmanned underwater vehicles (UUVs) are a kind of marine power multipliers, with extensive and important applications for scientific research. It is out of question that UUVs will play an irreplaceable role in marine detection. In this paper, the issue of model design for UUVs with the purpose of marine detection is studied. A well designed architecture for UUV model is proposed first, which includes...
Wireless sensor networks (WSNs) should collect accurate readings to reliably capture an environment's state. However, readings may become erroneous because of sensor hardware failures or degradation. In remote deployments, centrally detecting those reading errors can result in many message transmissions, which in turn dramatically decreases sensor battery life. In this paper, we address this issue...
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