Solid-state Lidar with wide steering angle using counter-propagating beams.

In a solid-state photonics-based Lidar, all essential components can be integrated into a silicon chip. It is simple and effective to use a tunable laser source to implement Lidar's beam steering. However, how to effectively increase the steering angle in a small wavelength tuning range is usually a key challenge due to the limited material and waveguide dispersion.

Least squares reverse time migration imaging with illumination preconditioned based on improved PRP conjugate gradients.

Least squares reverse time migration (LSRTM) imaging is the one of the most accurate methods for migration imaging at present, and Polak-Ribiere-Polyak conjugate gradient (PRPCG) for LSRTM has the good numerical performance but weak convergence, so we construct an optimization factor to improve the iteration direction of the gradient, which can automatically generate a sufficient descent direction. The improved PRPCG (IPRPCG) can reduce the data residual values and speed up the iteration. And the illumination preconditioned (IP) operator is employed to IPRPCG-LSRTM which solves the problem of low resolution due to the insufficient iterative gradient information.

An integrated network based on 2D/3D feature correlations for benign-malignant tumor classification and uncertainty estimation in digital breast tomosynthesis.

Classification of benign and malignant tumors is important for the early diagnosis of breast cancer. Over the last decade, digital breast tomosynthesis (DBT) has gradually become an effective imaging modality for breast cancer diagnosis due to its ability to generate three-dimensional (3D) visualizations. However, computer-aided diagnosis (CAD) systems based on 3D images require high computational costs and time.

The investigation of a portable solar telescope with a high gain metamaterial antenna for F10.7 radio flux measurement.

A high gain and high aperture efficiency metamaterial (MTM) antenna is applied to a solar telescope in this paper. First, a portable solar telescope including the MTM antenna and a receiving system is presented. Next, the theory of the MTM antenna is proposed and analyzed based on the ray-tracing model.

A semi-independent policies training method with shared representation for heterogeneous multi-agents reinforcement learning.

Humans do not learn everything from the scratch but can connect and associate the upcoming information with the exchanged experience and known knowledge. Such an idea can be extended to cooperated multi-reinforcement learning and has achieved its success on homogeneous agents by means of parameter sharing. However, it is difficult to straightforwardly apply parameter sharing when dealing with heterogeneous agents thanks to their individual forms of input/output and their diverse functions and targets.

Water level prediction using soft computing techniques: A case study in the Malwathu Oya, Sri Lanka.

Hydrologic models to simulate river flows are computationally costly. In addition to the precipitation and other meteorological time series, catchment characteristics, including soil data, land use, land cover, and roughness, are essential in most hydrologic models. The unavailability of these data series challenged the accuracy of simulations.

Parabolic-Index Ring-Core Fiber Supporting High-Purity Orbital Angular Momentum Modes.

We design a graded-index ring-core fiber with a GeO-doped silica ring core and SiO cladding. This fiber structure can inhibit the effect of spin-orbit coupling to mitigate the power transfer among different modes and eventually enhance the orbital angular momentum (OAM) mode purity. By changing the high-index ring core from the step-index to parabolic graded-index profile, the purity of the OAM mode can be improved from 86.

The HIE-FDTD Method for Simulating Dispersion Media Represented by Drude, Debye, and Lorentz Models.

The hybrid implicit-explicit finite-difference time-domain (HIE-FDTD) method is a weakly conditionally stable finite-difference time-domain (FDTD) method that has attracted much attention in recent years. However due to the dispersion media such as water, soil, plasma, biological tissue, optical materials, etc., the application of the HIE-FDTD method is still relatively limited.

Delay-Aware and Link-Quality-Aware Geographical Routing Protocol for UANET via Dueling Deep Q-Network.

In an unmanned aerial vehicles ad hoc network (UANET), UAVs communicate with each other to accomplish intricate tasks collaboratively and cooperatively. However, the high mobility of UAVs, the variable link quality, and heavy traffic loads can lead to difficulties in finding an optimal communication path. We proposed a delay-aware and link-quality-aware geographical routing protocol for a UANET via the dueling deep Q-network (DLGR-2DQ) to address these problems.

Age Classification of Rice Seeds in Japan Using Gradient-Boosting and ANFIS Algorithms.

The rapidly changing climate affects an extensive spectrum of human-centered environments. The food industry is one of the affected industries due to rapid climate change. Rice is a staple food and an important cultural key point for Japanese people.

Editorial: Special Issue "Optical Signal Processing Technologies for Communication, Computing, and Sensing Applications".

Optical technology is one of the key technologies that have been widely used for communication, computing and sensing [...

Predicting effectiveness of anti-VEGF injection through self-supervised learning in OCT images.

Anti-vascular endothelial growth factor (Anti-VEGF) therapy has become a standard way for choroidal neovascularization (CNV) and cystoid macular edema (CME) treatment. However, anti-VEGF injection is a long-term therapy with expensive cost and may be not effective for some patients. Therefore, predicting the effectiveness of anti-VEGF injection before the therapy is necessary.

Face Mask Identification Using Spatial and Frequency Features in Depth Image from Time-of-Flight Camera.

Face masks can effectively prevent the spread of viruses. It is necessary to determine the wearing condition of masks in various locations, such as traffic stations, hospitals, and other places with a risk of infection. Therefore, achieving fast and accurate identification in different application scenarios is an urgent problem to be solved.

Recent Advances in Reconfigurable Metasurfaces: Principle and Applications.

Metasurfaces have shown their great capability to manipulate electromagnetic waves. As a new concept, reconfigurable metasurfaces attract researchers' attention. There are many kinds of reconfigurable components, devices and materials that can be loaded on metasurfaces.

A high -factor dual-band terahertz metamaterial absorber and its sensing characteristics.

In this paper, a dual-band metamaterial absorber in the terahertz frequencies is proposed and its refractive index sensing characteristics is analyzed. The metamaterial structure is designed using a square metal ring with four T-shaped strips loaded outside of the ring, where the metal periodic array is on top of a silicon wafer backed with a metal ground plane. The resonant frequencies of the absorber are at 0.

A Dual-Path Cross-Modal Network for Video-Music Retrieval.

In recent years, with the development of the internet, video has become more and more widely used in life. Adding harmonious music to a video is gradually becoming an artistic task. However, artificially adding music takes a lot of time and effort, so we propose a method to recommend background music for videos.

Brain Activity Associated with the Planning Process during the Long-Time Learning of the Tower of Hanoi (ToH) Task: A Pilot Study.

Planning and decision-making are critical managerial functions involving the brain's executive functions. However, little is known about the effect of cerebral activity during long-time learning while planning and decision-making. This study investigated the impact of planning and decision-making processes in long-time learning, focusing on a cerebral activity before and after learning.

Intelligent Reflecting Surface Assisted Secure Transmission in UAV-MIMO Communication Systems.

This paper studies the intelligent reflecting surface (IRS) assisted secure transmission in unmanned aerial vehicle (UAV) communication systems, where the UAV base station, the legitimate receiver, and the malicious eavesdropper in the system are all equipped with multiple antennas. By deploying an IRS on the facade of a building, the UAV base station can be assisted to realize the secure transmission in this multiple-input multiple-output (MIMO) system. In order to maximize the secrecy rate (SR), the transmit precoding (TPC) matrix, artificial noise (AN) matrix, IRS phase shift matrix, and UAV position are jointly optimized subject to the constraints of transmit power limit, unit modulus of IRS phase shift, and maximum moving distance of UAV.

Microwave Polarization Sensing for Dielectric Materials Based on a Twisted Dual-Layer Meta-Surface.

A microwave sensor is proposed based on a chiral twisted dual-layer meta-surface. Elliptical angle and polarization rotation angle are used to characterize the different dielectric constants of materials. The dielectric films consisting of polydimethylsiloxane and barium titanate with volume fractions 0%, 10%, 15%, 20% are prepared and tested for a proof of concept.

Expectation-Maximization-Based Simultaneous Localization and Mapping for Millimeter-Wave Communication Systems.

In this paper, we proposed a novel expectation-maximization-based simultaneous localization and mapping (SLAM) algorithm for millimeter-wave (mmW) communication systems. By fully exploiting the geometric relationship among the access point (AP) positions, the angle difference of arrival (ADOA) from the APs and the mobile terminal (MT) position, and regarding the MT positions as the latent variable of the AP positions, the proposed algorithm first reformulates the SLAM problem as the maximum likelihood joint estimation over both the AP positions and the MT positions in a latent variable model. Then, it employs a feasible stochastic approximation expectation-maximization (EM) method to estimate the AP positions.

Over-Two-Octave Supercontinuum Generation of Light-Carrying Orbital Angular Momentum in Germania-Doped Ring-Core Fiber.

In this paper, we design a silica-cladded Germania-doped ring-core fiber (RCF) that supports orbital angular momentum (OAM) modes. By optimizing the fiber structure parameters, the RCF possesses a near-zero flat dispersion with a total variation of <±30 ps/nm/km over 1770 nm bandwidth from 1040 to 2810 nm for the OAM1,1 mode. A beyond-two-octave supercontinuum spectrum of the OAM1,1 mode is generated numerically by launching a 40 fs 120 kW pulse train centered at 1400 nm into a 12 cm long designed 50 mol% Ge-doped fiber, which covers 2130 nm bandwidth from 630 nm to 2760 nm at −40 dB of power level.

W-Band 4th Order Waveguide Filter Based on Double Layer SU8 Microfabrication.

This paper investigates the fabrication accuracy of the W-band SU-8 photoresist micromachined 4th order waveguide bandpass filters (BPF). The designed filter based on cylindrical resonators is excited in TM mode. It is ideally suitable for the layered SU-8 micromachining process as the height of the resonator is much smaller than one wavelength, the electromagnetic fields remain unchanged in the thickness direction.

DDQN with Prioritized Experience Replay-Based Optimized Geographical Routing Protocol of Considering Link Stability and Energy Prediction for UANET.

Unmanned aerial vehicles (UAVs) are important equipment for efficiently executing search and rescue missions in disaster or air-crash scenarios. Each node can communicate with the others by a routing protocol in UAV ad hoc networks (UANETs). However, UAV routing protocols are faced with the challenges of high mobility and limited node energy, which hugely lead to unstable link and sparse network topology due to premature node death.

Federated Deep Reinforcement Learning-Based Task Offloading and Resource Allocation for Smart Cities in a Mobile Edge Network.

Mobile edge computing (MEC) has become an indispensable part of the era of the intelligent manufacturing industry 4.0. In the smart city, computation-intensive tasks can be offloaded to the MEC server or the central cloud server for execution.

An Efficient Automatic Fruit-360 Image Identification and Recognition Using a Novel Modified Cascaded-ANFIS Algorithm.

Automated fruit identification is always challenging due to its complex nature. Usually, the fruit types and sub-types are location-dependent; thus, manual fruit categorization is also still a challenging problem. Literature showcases several recent studies incorporating the Convolutional Neural Network-based algorithms (VGG16, Inception V3, MobileNet, and ResNet18) to classify the Fruit-360 dataset.