Backward Direction Research Articles

Janus Device Based on Liquid Crystal Regulation with a Large Incidence Angle: Analogous Quantum Optical Effect and Absorption

AbstractIn this paper, a Janus metastructure device (JMD) is proposed. The JMD design introduces asymmetric structures, which leads to the generation of analogous quantum optical effects when light is incident at large angles. Specifically, forward electromagnetic‐induced transparency (EIT) and backward narrowband absorption (NA) are achieved when light is incident along different directions, displaying Janus characteristics in the forward and backward directions. Additionally, the operating frequency of JMD can be controlled through the use of liquid crystal. Such features hold promising potential for various applications in photonic and optoelectronic fields. When the axial direction of the liquid crystal is oriented along the x‐direction, the JMD achieves a transparent window over 90% within 0.46–0.51 THz at forward incidence, and an absorption peak of 84.1% appears at 0.331 THz at backward incidence. When the axial direction is oriented along the y‐direction, the JMD achieves EIT in the range of 0.51–0.575 THz at forward incidence, and a backward absorption peak of 93.3% occurs at 0.305 THz. In addition, the performance changes at different polarization and incidence angles are presented. The mechanism of absorption generation, the method of suppressing excess absorption, and the parametric inversion of the electromagnetic characteristics of JMD are also discussed.

Spectral Efficiency Improvement Using Bi-Deep Learning Model for IRS-Assisted MU-MISO Communication System.

The intelligent reflecting surface (IRS) is a two-dimensional (2D) surface with a programmable structure and is composed of many arrays. The arrays are used to supervise electromagnetic wave propagation by altering the electric and magnetic properties of the 2D surface. IRS can influentially convert wireless channels to very effectively enhance spectral efficiency (SE) and communication performance in wireless systems. However, proper channel information is necessary to realize the IRS anticipated gains. The conventional technique has been taken into consideration in recent attempts to fix this issue, which is straightforward but not ideal. A deep learning model which is called the long short-term memory (Bi-LSTM) model can tackle this issue due to its good learning capability and it plays a vital role in enhancing SE. Bi-LSTM can collect data from both forward and backward directions simultaneously to provide improved prediction accuracy. Because of the tremendous benefits of the Bi-LSTM model, in this paper, an IRS-assisted Bi-LSTM model-based multi-user multiple input single output downlink system is proposed for SE improvement. A Wiener filter is used to determine the optimal phase of each IRS element. In the simulation results, the proposed system is compared with other DL models and methods for the SE performance evaluation. The model exhibits satisfactory SE performance with a different signal-to-noise ratio compared to other schemes in the online phase.

Broadband composite nonreciprocal polarization wave plates and optical isolators

We theoretically study a technique for a broadband nonreciprocal wave retarder whose quarter-wave plate phase retardation is the same in forward and backward directions. The system is built using a number of sequential nonreciprocal wave plates. The proposed device can also be utilized to create a broadband optical diode, which consists of two achromatic quarter-wave plates, one reciprocal and the other non-reciprocal, that are sandwiched between two polarizers aligned in parallel.

Accelerate Safety Model Checking Based on Complementary Approximate Reachability

Model checking is an automatic formal verification method that is widely applied to hardware verification. Safety properties are the mainly verified properties in practice that can be falsified within finite steps if they do not hold for systems. However, state-of-the-art safety model checking algorithms cannot meet the performance requirement driven by the industry as the sizes of (hardware) systems to be verified increase rapidly. Therefore, more efficient techniques are still eagerly in demand. Recently, a new safety model checking technique Complementary Approximate Reachability (CAR) was presented and received considerable concerns from the community. CAR has shown its advantages in unsafe checking (bug finding), but cannot be as competitive as other state-of-the-art techniques, e.g., IC3/PDR, on safe checking (proving correctness). In this paper, we propose four kinds of heuristics, two inspired by IC3/PDR and another two dedicated to CAR, to improve the performance of CAR. We integrate the heuristics into the opensource model checker SimpleCAR and compare the performance to the original CAR and IC3/PDR on 748 instances from the hardware model-checking competitions. Our results show that by fixing the time and memory resources, CAR can solve 124 more instances with the four proposed heuristics, i.e., 53.4% more instances can be solved comparing to the original CAR. Furthermore, CAR in both forward and backward directions can solve 10 more instances than IC3/PDR in corresponding directions, and uniquely solve 44 more instances that IC3/PDR in corresponding directions cannot solve, which increases the capability of the current model-checking portfolio.

High sensitivity D-shaped fiber decorated with self-assembly Ag nanoparticles for Raman enhancement via collecting backward and vertical direction scattering signals

High sensitivity D-shaped fiber decorated with self-assembly Ag nanoparticles for Raman enhancement via collecting backward and vertical direction scattering signals

Packet Loss Compensation for VoIP through Bone‐Conducted Speech Using Modified Linear Prediction

In this paper, we compare air‐conducted (AC) speech with bone‐conducted (BC) speech for the purpose of utilizing them in packet loss concealment (PLC) for speech quality of voice over internet protocol (VoIP). Instead of the autocorrelation method of linear prediction (LP), which was utilized in the conventional PLC techniques, we employ the modified covariance (MC) method. The MC method provides accurate LP estimation from short input data samples and avoids the numerical problem the autocorrelation method suffers from. The lost frame is compensated from both forward and backward directions in which linear gain and weighting are applied. When BC speech is used as the input speech data for PLC in the case where the speech sender is in noisy environments, BC speech behaves more accurately than the corresponding AC speech, resulting in an excellent performance of the LP‐based PLC technique. This unveils a useful use of BC speech in speech information systems. Experiments show that in severe noise environments of AC speech‐to‐noise ratio being less than 10 dB, BC speech is superior to AC speech for PLC. It is also shown that the transmitted BC speech is more accurately reconstructed for PLC than transmitted AC speech is done. © 2023 The Authors. IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

(Invited) Advanced Carbon Nanotube Fluorescence Spectrometry for Novel Applications

Instrumental advances in near-IR fluorescence spectroscopy are enabling new types of measurements involving single-wall carbon nanotubes (SWCNTs). Two unique systems will be described. The first is a two-dimensional fluorescence-detected circular dichroism (FDCD) spectrometer. In this, SWCNT samples are excited by a spectrally selected supercontinuum laser beam that is switched between left- and right-circular polarization in an electro-optic modulator. Near-infrared sample fluorescence emitted in the backward direction is captured and directed to a scanning monochromator with a cooled InGaAs single-channel detector. After amplification and high precision digitization, the modulated signal component is extracted by computer-based phase sensitive detection. The system can measure a sample’s E22 circular dichroism in four spectral modes: 1) conventional FDCD, with scanned visible excitation wavelength and spectrally integrated (zero-order grating) emission detection; 2) Emission-specific FDCD, with scanned visible excitation wavelengths and selected emission wavelength; 3) Emission-scanned FDCD, with selected visible excitation wavelength and scanned emission wavelengths; 4) Excitation-Emission FDCD, with excitation and emission wavelengths both scanned to give two-dimensional data sets. This instrument can spectroscopically resolve enantiomer signals from a single (n,m) species in a racemic SWCNT sample.In a parallel project, developments in SWCNT fluorescence spectrometry are advancing nanotube-based strain measurement technology toward commercialization. Because SWCNT emission wavelengths vary systematically with axial strain, nanotubes in a thin coating on a specimen can serve as optically interrogated strain gauges. We apply this effect to measure strain maps through hyperspectral imaging of SWCNT fluorescence. A rotated band pass filter is used to capture a set of images in multiple spectral slices, from which a custom computer program deduces strain at each of ~105 image pixels and compiles strain maps. We will describe how this apparatus has evolved from a lab prototype into a compact portable system that can make measurements in industrial settings.

A high-gain dual-beam folded transmit-reflect-array antenna based on phase-shifting surface

Abstract In this paper, a high-gain dual-beam folded transmit-reflect-array antenna is designed based on the shared aperture method. It consists of the top transmit-reflect-array, the bottom transmitarray, and the feed horn located at the center of the bottom transmitarray. A phase-shifting surface is proposed as the transmission unit cell capable of transmitting incident waves while providing adequate transmission phase shift. The designed transmission unit cell is improved into the transmit-reflect unit cell by adding polarization grids to realize the reflection function. The bottom transmitarray is constructed by transmission unit cells. The top transmit-reflect-array is composed of transmit-reflect unit cells and polarization grids vertical to the unit cell. The x-polarized wave transmits through the top transmit-reflect-array and forms a pencil beam in the forward direction. In addition, the y-polarized wave is reflected by the top transmit-reflect-array and transmits through the bottom transmitarray to form a pencil beam in the backward direction. The tested realized gains of the transmitted beam and reflected beam at 10 GHz are 19.87 dBi with an aperture efficiency of 48.27 % and 23.95 dBi with an aperture efficiency of 30.88 %, respectively. With its low profile and ease of manufacture, it has great prospects for navigation and radar communication.

A compact metasurface-based circularly polarized antenna with high gain and high front-to-back ratio for RFID readers.

Developing a compact circularly polarized (CP) antenna with good radiation characteristics for handheld radio frequency identification (RFID) readers is a very challenging task. Many compact CP antennas have been reported in the open literature, but most suffer from critical drawbacks of low gain and/or high back radiation. This paper presents a metasurface (MS) based CP antenna with compact size, high gain, and high front-to-back ratio characteristics. The compact size of the proposed design is achieved by using a 2 × 2 unit-cell MS, while the CP realization is accomplished through a coupling between the MS and a Y-shaped patch as a primary CP source. The final antenna has compact overall dimensions of 0.45λ × 0.45λ × 0.02λ, where λ is the guided wavelength at the center frequency. The operating bandwidth is about 2.0% (2.43-2.48 GHz) and the broadside gain is about 6.3 dBi. Besides, the front-to-back ratio (FBR) defined by the difference gain levels between the forward and backward directions is about 18 dB. Compared with the related compact CP antennas in the literature, the proposed design has the advantages of high gain and high FBR, making it suitable for compact RFID readers.

The Subsea Micro-Drilling Vehicle’s Dynamic Analysis during Landing

Whether the subsea micro-drilling vehicle (SMDV) can perform its subsequent operations safely depends on the quality of the landing procedure. RecurDyn creates the SMDV dynamic model for this study. A model of the interaction between the SMDV and deep-sea sediment is built, and a simulation of the SMDV falling on the sea’s sediment substrate is developed. The water resistance is applied to the model by equivalent height replacement, and the in-situ soil data is measured with a triaxial undrained unconsolidated (UU) compression test and a load-sinkage experiment. When the landing surface is a flat sediment substrate, the release height is 5 m, the sinkage amount is 347 mm, and the center of mass’s impact acceleration is less than seven gravitational accelerations. Three states can occur when the vehicle lands on a sloped surface: stability, slip, and overturning. The risk of slipping and overturning is the least when the vehicle is landing on the ground in the forward direction, and the risk is equal when it lands on the ground in the backward and sideways directions. The ultimate overturning angle drops, and the final slip angle remains relatively constant as the vehicle’s release height increases. Our findings offer a theoretical foundation for the SMDV’s safe landing and the scientific formulation of rational release intervals.

Designing and Analysis of an Architecture of Motion Control for a Mobile Robot Using Simulation

In recent decades, the control of motion and navigation of mobile robots has received the eminent attention of researchers. Motion control is an important technique that allows a mobile robot (MR) to move adaptively and precisely. The main aim of this research work is to design and analyze the architecture of the navigation and motion control systems for a mobile robot by using Simulink modeling. An encoder sensor is used to analyze the motion control. Experimental and simulation techniques are used to prove the application of the encoder sensor and dead reckoning approach to control MR motion. The modeling of the Simulink model for a motion control system for an MR through MATLAB 2022a software has been presented in this article. The main objective of this research work is to control the motion of the robot in forward and backward directions. The presented model in this paper has been verified through real-time simulation, and it shows the performance of the control system in the predefined optimal time range standard. Finally, this article provides a comprehensive survey of future research trends for the control system of MR.

A Jeap-BiLSTM Neural Network for Action Recognition

Human action recognition in videos is an important task in computer vision with applications in fields such as surveillance, human–computer interaction, and sports analysis. However, it is a challenging task due to the complex background changes and redundancy of long-term video information. In this paper, we propose a novel bi-directional long short-term memory method with attention pooling based on joint motion and difference entropy (JEAP-BiLSTM) to address these challenges. To obtain discriminative features, we introduce a joint entropy map that measures both the entropy of motion and the entropy of change. The Bi-LSTM method is then applied to capture visual and temporal associations in both forward and backward directions, enabling efficient capture of long-term temporal correlation. Furthermore, attention pooling is used to highlight the region of interest and to mitigate the effects of background changes in video information. Experiments on the UCF101 and HMDB51 datasets demonstrate that the proposed JEAP-BiLSTM method achieves recognition rates of 96.4% and 75.2%, respectively, outperforming existing methods. Our proposed method makes significant contributions to the field of human action recognition by effectively capturing both spatial and temporal patterns in videos, addressing background changes, and achieving state-of-the-art performance.

Nonreciprocal topological mode conversion by encircling an exceptional point in dynamic waveguides.

The topology of exceptional points (EPs) has been revealed by taking stationary or dynamical encircling around them, which induces eigenstate exchange or chiral mode conversion. However, the conversions are usually reciprocal obeying restricted transmittances. Here we propose the concept of nonreciprocal encircling of EPs in a dynamic waveguide under complex modulation. The waveguide allows direction-dependent EPs in their quasienergy spectra due to different phase-matching conditions for opposite propagation direction. We design a closed loop that will encircle the EP in the backward direction but not in the forward direction. In this way, a nonreciprocal topological conversion is achieved as the forward transmittance from the even to odd mode significantly exceeds the backward transmittance from the odd to even mode. As a result, the forward propagation produces two modes with equal strength while the backward propagation leads to a specific mode regardless of the input. The structure is promising for making robust optical isolators.

Backscatter amplification in a turbulent atmosphere and the law of conservation of energy.

We demonstrate how energy is redistributed and the law of conservation of energy is fulfilled when optical radiation is reflected in a turbulent atmosphere. It is found that the mean intensity of a laser beam, scattered by a point reflector or an ensemble of point reflectors in a turbulent atmosphere, increases in a strictly backward direction as compared to the intensity of the beam scattered in a homogeneous medium without turbulence-the backscatter amplification (BSA) effect-at the expense of overflow of the energy of the scattered beam from the side directions covering a huge area of several orders of magnitude exceeding the BSA effect localization area.

Directionally duplexed all-dielectric metalens for multifunctional structured light generation.

Directionally duplexed metalenses manipulated by the geometric phase of a silicon nano-bar are theoretically designed to generate multifunctional structured light. It is numerically demonstrated that incident light with different linear and circular polarization states, along forward and backward propagation directions, can be differentially converted into multiple focusing structured beams of arbitrary topological charges, either of vector light with azimuthally variant polarizations or of vortex light with helical phases. Due to the all-silicon and nonresonant metastructural design, the resultant high working efficiencies of our proposed metalens are promising for applications such as optical communication, nanoparticle manipulation, and other direction-duplexed multifunctional optical meta-devices.

3D passive microfluidic valves in silicon and glass using grayscale lithography and reactive ion etching transfer

A fabrication strategy for high-efficiency passive three-dimensional microfluidic valves with no mechanical parts fabricated in silicon and glass substrates is presented. 3D diffuser-nozzle valve structures were produced and characterized in their added value in comparison to conventional diffuser-nozzle valve designs with rectangular cross sections. A grayscale lithography approach for 3D photoresist structuring combined with a proportional transfer by reactive ion etching allowed to transfer 3D resist valve designs with high precision into the targeted substrate material. The efficiency with respect to the rectification characteristics or so-called diodicity of the studied valve designs is defined as the ratio of the pressure drops in backward and forward flow directions. The studied valve designs were characterized experimentally as well as numerically based on finite element simulations with overall matching results that demonstrate a significantly improved flow rectification of the 3D valves compared to the corresponding conventional structure. Our novel 3D valve structures show, for instance, even without systematic optimization a measured diodicity of up to 1.5 at low flow rates of only about 10 μl/s.

Yoga Posture Recognition by Learning Spatial-Temporal Feature with Deep Learning Techniques

Yoga posture recognition remains a difficult issue because of crowded backgrounds, varied settings, occlusions, viewpoint alterations, and camera motions, despite recent promising advances in deep learning. In this paper, the method for accurately detecting various yoga poses using DL (Deep Learning) algorithms is provided. Using a standard RGB camera, six yoga poses — Sukhasana, Kakasana, Naukasana, Dhanurasana, Tadasana, and Vrikshasana — were captured on ten people, five men and five women. In this study, a brand-new DL model is presented for representing the spatio-temporal (ST) variation of skeleton-based yoga poses in movies. It is advised to use a variety of representation learners to pry video-level temporal recordings, which combine spatio-temporal sampling with long-range time mastering to produce a successful and effective training approach. A novel feature extraction method using Open Pose is described, together with a DenceBi-directional LSTM network to represent spatial-temporal links in both the forward and backward directions. This will increase the efficacy and consistency of modeling long-range action detection. To improve temporal pattern modeling capability, they are stacked and combined with dense skip connections. To improve performance, two modalities from look and motion are fused with a fusion module and compared to other deep learning models are LSTMs including LSTM, Bi-LSTM, Res-LSTM, and Res-BiLSTM. Studies on real-time datasets of yoga poses show that the suggested DenseBi-LSTM model performs better and yields better results than state-of-the-art techniques for yoga pose detection.

Subjective evaluation of facial asymmetry with three-dimensional simulated images among the orthodontists and laypersons: a cross-sectional study

ObjectivesWe used three-dimensional (3D) virtual images to undertake a subjective evaluation of how different factors affect the perception of facial asymmetry among orthodontists and laypersons with the aim of providing a quantitative reference for clinics.Materials and methodsA 3D virtual symmetrical facial image was acquired using FaceGen Modeller software. The left chin, mandible, lip and cheek of the virtual face were simulated in the horizontal (interior/exterior), vertical (up/down), or sagittal (forward or backward) direction in 3, 5, and 7 mm respectively with Maya software to increase asymmetry for the further subjective evaluation. A pilot study was performed among ten volunteers and 30 subjects of each group were expected to be included based on 80% sensitivity in this study. The sample size was increased by 60% to exclude incomplete and unqualified questionnaires. Eventually, a total of 48 orthodontists and 40 laypersons evaluated these images with a 10-point visual analog scale (VAS). The images were presented in random order. Each image would stop for 30 s for observers with a two-second interval between images. Asymmetry ratings and recognition accuracy for asymmetric virtual faces were analyzed to explore how different factors affect the subjective evaluation of facial asymmetry. Multivariate linear regression and multivariate logistic regression models were used for statistical data analysis.ResultsOrthodontists were found to be more critical of asymmetry than laypersons. Our results showed that observers progressively decreased ratings by 1.219 on the VAS scale and increased recognition rates by 2.301-fold as the degree of asymmetry increased by 2 mm; asymmetry in the sagittal direction was the least noticeable compared with the horizontal and vertical directions; and chin asymmetry turned out to be the most sensitive part among the four parts we simulated. Mandible asymmetry was easily confused with cheek asymmetry in the horizontal direction.ConclusionsThe degree, types and parts of asymmetry can affect ratings for facial deformity as well as the accuracy rate of identifying the asymmetrical part. Although orthodontists have higher accuracy in diagnosing asymmetrical faces than laypersons, they fail to correctly distinguish some specific asymmetrical areas.

Ubiquitous Superconducting Diode Effect in Superconductor Thin Films.

The macroscopic coherence in superconductors supports dissipationless supercurrents that could play a central role in emerging quantum technologies. Accomplishing unequal supercurrents in the forward and backward directions would enable unprecedented functionalities. This nonreciprocity of critical supercurrents is called the superconducting (SC) diode effect. We demonstrate the strong SC diode effect in conventional SC thin films, such as niobium and vanadium, employing external magnetic fields as small as 1Oe. Interfacing the SC layer with a ferromagnetic semiconductor EuS, we further accomplish the nonvolatile SC diode effect reaching a giant efficiency of 65%. By careful control experiments and theoretical modeling, we demonstrate that the critical supercurrent nonreciprocity in SC thin films could be easily accomplished with asymmetrical vortex edge and surface barriers and the universal Meissner screening current governing the critical currents. Our engineering of the SC diode effect in simple systems opens the door for novel technologies while revealing the ubiquity of the Meissner screening effect induced SC diode effect in superconducting films, and it should be eliminated with great care in the search for exotic superconducting states harboring finite-momentum Cooper pairing.

Feature tracking and matching for wide-baseline images with closed-loop sequence

Variations in wide-baseline images occur depending on the viewing angle in a three-dimensional reconstruction of oblique photography, leading to instability in interest-point extraction. Traditional methods, however, invalidate wide-baseline images. In this study, a feature-tracking and matching algorithm based on the analysis of closed-loop images is proposed for wide-baseline images. First, the points of interest in each image were extracted using the SuperPoint algorithm. Continuous pairwise matching was then performed using the SuperGlue algorithm. The matching results were used for feature tracking in both the forward and backward directions, and the feature tracking results were combined. Finally, the algorithm filters the points to obtain an optimal matching result. Comparative experiments demonstrated that this method significantly outperforms the existing conventional methods. The proposed method is robust, obtains matching points more uniformly, and performs better than traditional methods for wide-baseline images.