Search

In this work, a fast and new sub-diffraction resolution-marker-free optical imaging method has been proposed to reconstruct the refractive index variation profile capable of quick capturing without mechanical sweeping, neither using fluorescent marker nor a high-vacuum requirement nor a quenching beam. To explain the main idea of the proposed method, one- and two-dimensional approaches are developed in this paper. The superposition of optical signals with a controlled phase array is used to create a tunable lens for refractive index reconstruction of an arbitrary target point on the test sample. By tuning the phase and using a harmonic generator (fifth harmonic in this work), it is possible to enhance the resolution of the proposed imaging system below the sub-diffraction limit (170 nm image resolution for 1000 nm wavelength). Utilizing High Harmonic Generation (HHG) may improve the imaging resolution tremendously down to a few tens of nanometers. The proposed method is numerically evaluated, and the resolution dependency of the imaging method on system parameters has been analyzed. [ABSTRACT FROM AUTHOR]

The channel mismatches, particularly the gain and the timing skew errors degrade significantly the performance of high-speed Time-Interleaved Analog-to-Digital converters (TIADCs). The error correction using blind calibration methods is difficult because of the correlation between the input signal and the noise signal caused by these channel mismatch errors. In this paper, a new fast convergent algorithm is proposed to correct the gain mismatch and timing skew errors. This new algorithm is based on oversampling and guarantees the independence of the signal and the noise. To estimate noise produced by gain mismatch and timing skew error, a new structure based on modulation concept is developed. The proposed adaptive compensation structure has fast convergence speed using an accurate estimated error signal and a simple cost function. The proposed structure unlike other oversampling-based algorithms is applicable in narrow-band signals by selecting the optimum oversampling ratio. The proposed algorithm is simulated using a four-channel TIADC with 10-bit resolution. Theoretical analysis and simulation results verified the fast convergence speed and the good performance of the proposed algorithm for both narrow-band and wide-band signals. [ABSTRACT FROM AUTHOR]

Over the last few years, deep learning on irregular 3D data given its wide range of applications has become one of the active topics in the field. While field programmable gate array (FPGA)-based acceleration of deep learning models has been proved to produce power-efficient designs in comparison with other platforms such as CPUs and GPUs, only a few studies have been conducted regarding the models that consume point clouds as their input. Although tailoring the hardware designs to specific networks could lead to better optimization opportunities, it is also important to keep the reusability of the design in mind, especially for a new and evolving topic like learning on point clouds. In this work, we have aimed to achieve reusability by keeping the hardware isolated from the computational graph. Considering the numerous types of layers used in dynamic graph convolutional neural network (DGCNN) and its popularity, our proposed design aims for the thorough acceleration of DGCNN. The challenges including 18 types of tensor operations, achieving burst transfers, dealing with kernel complexities, external memory banks, in-order and out-of-order execution modes, and approaches with multiple processing elements have been explained in details throughout the paper. Our experiments on a single FPGA with a single bitstream, DDR4 memory subsystem, and Float32 data type demonstrated speedups of 2.73 × to 8.4 × compared to a sequential single-threaded implantation on an Intel Core i7 6700HQ. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles are becoming an important part of the modern life. Despite some recent advances in GPS-aided navigation of quadrotors, the concern of crash and collision still overshadows their reliability and safety, especially in GPS-denied environments. Therefore, the necessity for developing fully automatic methods for safe, accurate, and independent landing of drones increases over time. This paper investigates the autolanding process by focusing on an accurate and continuous position estimation of the drone using a monocular vision system and the fusion with the inertial measurement unit and ultrasonic sensors' data. An ARUCO marker is used as the landing pad, and the information is processed in the ground station through a real-time Wi-Fi link. In order to overcome the closed loop instability caused by the communication and localization delays, we propose a method called "movement slicing method". This method divides the moves around the marker into moving and waiting slices and makes the landing process not only more accurate but also faster. Experimental results show a successful landing of the UAV on a predefined location, while it is accurately aligned with the marker using the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: This article aims to provide a new and fast method for differentiation of inks on a questioned document. The data acquisition was carried out by designing specific image analysis software for evaluating thin layer chromatograms (TLC-IA). The ink spot was extracted from the document using methanol and separated by TLC using plastic sheet silica gel 60 without fluorescent indicator, and a mixture of ethyl acetate, ethanol, and water (70:35:30, v/v/v) as mobile phase. To discriminate between different pen inks, new software was designed on the basis of intensity profile of red, green, and blue (RGB) characteristic. In practice, after development of chromatogram, the chromatograms were scanned by ordinary office scanner, intensity profiles of RGB characteristics on the development straight of each sample were produced and compared with the mentioned software. RGB profiles of ballpoint inks from various manufacturers showed that the patterns in most cases were distinctly different from each other. This new method allowed discriminating among different pen inks with a high reliability and the discriminating power of 92.8%. Blue ballpoint pen inks of 41 different samples available on the local market were successfully analyzed and discriminated. [Copyright &y& Elsevier]

Resolution enhancement of a high-speed fiber-optic spectrometer is investigated in this article. The operation of these types spectrometers is based on conversion of the spectral-domain signal into the time domain by a dispersive element. A photonic crystal fiber is used as a dispersive fiber in this spectrometer. Resolution enhancement of considered spectrometer with photonic crystal fibers is studied. The fiber loss and length minimization in this spectrometer are obtained. Simulation results show that an increase in resolution will cause a decrease in the speed of the spectrometer. Trade offs between resolution and speed are studied. [ABSTRACT FROM AUTHOR]