Inverse design and realization of an optical cavity-based displacement transducer with arbitrary responses

Optical cavity has long been critical for a variety of applications ranging from precise measurement to spectral analysis.A number of theories and methods have been successful in describing the optical response of a stratified optical cavity,while the inverse problem,especially the inverse design of a displacement sensitive cavity,remains a significant challenge due to the cost of computation and comprehensive performance requirements.This paper reports a novel inverse design methodology combining the characteristic matrix method,mixed-discrete variables optimization algorithm,and Monte Carlo method-based tolerance analysis.The material characteristics are indexed to enable the mixed-discrete variables optimization,which yields considerable speed and efficiency improvements.This method allows arbitrary response adjustment with technical feasibility and gives a glimpse into the analytical characterization of the optical response.Two entirely different light-displacement responses,including an asymmetric sawtooth-like response and a highly symmetric response,are dug out and experimentally achieved,which fully confirms the validity of the method.The compact Fabry-Perot cavities have a good balance between performance and feasibility,making them promising candidates for displacement transducers.More importantly,the proposed inverse design paves the way for a universal design of optical cavities,or even nanophotonic devices.

Comparison of Machine Learning Methods for Satellite Image Classification: A Case Study of Casablanca Using Landsat Imagery and Google Earth Engine

Satellite image classification is crucial in various applications such as urban planning,environmental monitoring,and land use analysis.In this study,the authors present a comparative analysis of different supervised and unsupervised learning methods for satellite image classification,focusing on a case study in Casablanca using Landsat 8 imagery.This research aims to identify the most effective machine-learning approach for accurately classifying land cover in an urban environment.The methodology used consists of the pre-processing of Landsat imagery data from Casablanca city,the authors extract relevant features and partition them into training and test sets,and then use random forest(RF),SVM(support vector machine),classification,and regression tree(CART),gradient tree boost(GTB),decision tree(DT),and minimum distance(MD)algorithms.Through a series of experiments,the authors evaluate the performance of each machine learning method in terms of accuracy,and Kappa coefficient.This work shows that random forest is the best-performing algorithm,with an accuracy of 95.42%and 0.94 Kappa coefficient.The authors discuss the factors of their performance,including data characteristics,accurate selection,and model influencing.

Universal FRFT-based algorithm for parameter estimation of chirp signals

The realization of the parameter estimation of chirp signals using the fractional Fourier transform （FRFT） is based on the assumption that the sampling duration of practical observed signals would be equal to the time duration of chirp signals contained in the former. However, in many actual circumstances, this assumption seems unreasonable. On the basis of analyzing the practical signal form, this paper derives the estimation error of the existing parameter estimation method and then proposes a novel and universal parameter estimation algorithm. Furthermore, the proposed algorithm is developed which allows the estimation of the practical observed Gaussian windowed chirp signal. Simulation results show that the new algorithm works well.

Review of micromachined optical accelerometers:from mg to sub-μg

Micro-Opto-Electro-Mechanical Systems(MOEMS)accelerometer is a new type of accelerometer which combines the merits of optical measurement and Micro-Electro-Mechanical Systems(MEMS)to enable high precision,small volume and anti-electromagnetic disturbance measurement of acceleration.In recent years,with the in-depth research and development of MOEMS accelerometers,the community is flourishing with the possible applications in seismic monitoring,inertial navigation,aerospace and other industrial and military fields.There have been a variety of schemes of MOEMS accelerometers,whereas the performances differ greatly due to different measurement principles and corresponding application requirements.This paper aims to address the pressing issue of the current lack of systematic review of MOEMS accelerometers.According to the optical measurement principle,we divide the MOEMS accelerometers into three categories:the geometric optics based,the wave optics based,and the new optomechanical accelerometers.Regarding the most widely studied category,the wave optics based accelerometers are further divided into four sub-categories,which is based on grating interferometric cavity,Fiber Bragg Grating(FBG),Fabry-Perot cavity,and photonic crystal,respectively.Following a brief introduction to the measurement principles,the typical performances,advantages and disadvantages as well as the potential application scenarios of all kinds of MOEMS accelerometers are discussed on the basis of typical demonstrations.This paper also presents the status and development tendency of MOEMS accelerometers to meet the ever-increasing demand for high-precision acceleration measurement.

Modeling of deformation processes in rock massif in the vicinity of underground goafs considering the formation of discontinuity zones

The construction of mechanical-mathematical model and numerical method for the deformation processes of rock massifs with goafs and underground structures is very complex and also important task in modern rock mechanics.In this study,the mechanical-mathematical model is developed for rock massif in vicinity of underground goafs considering the internal block-layered structure of the rock massif.A new constitutive model is introduced in this study to describe the negative Poisson’s ratio for the lock-layered structure.Two types of defining equations systems for studying the state of a rock massif taking into account the block-layered structure are described.Finally,several examples are given using the present mechanical-mathematical model.

M-ary information processing via an optimal nonlinear detector

This paper presents a novel approach of M-ary baseband pulse amplitude modulated signal processing via a parameter-optimized nonlinear dynamic system. This nonlinear system usually shows the phenomenon of stochastic resonance by adding noise. To thoroughly discuss the signal processing performance of the nonlinear system, we tune the system parameters to obtain a nonlinear detector with optimal performance. For characterizing the output of the nonlinear system, the derivation of the probability of detection error is given by the system response speed and the probability density function of the nonlinear system output. By varying the noise intensity with fixed system parameters, the phenomenon of stochastic resonance is shown and by tuning the system parameters with fixed noise, the probability of detection error is minimized and the nonlinear system is optimized. The detection performance of the two cases is compared with the theoretical probability of detection error, which is validated by numerical simulation.

Effects of error feedback on a nonlinear bistable system with stochastic resonance

In this paper, we discuss the effects of error feedback on the output of a nonlinear bistable system with stochastic resonance. The bit error rate is employed to quantify the performance of the system. The theoretical analysis and the numerical simulation are presented. By investigating the performances of the nonlinear systems with different strengths of error feedback, we argue that the presented system may provide guidance for practical nonlinear signal processing.

An Indoor Localization Approach Based on Fingerprint and Time-Difference of Arrival Fusion

In this paper,an effective target locating approach based on the fingerprint fusion posi-tioning(FFP)method is proposed which integrates the time-difference of arrival(TDOA)and the received signal strength according to the statistical variance of target position in the stationary 3D scenarios.The FFP method fuses the pedestrian dead reckoning(PDR)estimation to solve the moving target localization problem.We also introduce auxiliary parameters to estimate the target motion state.Subsequently,we can locate the static pedestrians and track the the moving target.For the case study,eight access stationary points are placed on a bookshelf and hypermarket;one target node is moving inside hypermarkets in 2D and 3D scenarios or stationary on the bookshelf.We compare the performance of our proposed method with existing localization algorithms such as k-nearest neighbor,weighted k-nearest neighbor,pure TDOA and fingerprinting combining Bayesian frameworks including the extended Kalman filter,unscented Kalman filter and particle fil-ter(PF).The proposed approach outperforms obviously the counterpart methodologies in terms of the root mean square error and the cumulative distribution function of localization errors,espe-cially in the 3D scenarios.Simulation results corroborate the effectiveness of our proposed approach.

Effects of potential functions on stochastic resonance

In this paper, the effects of a bistable potential function U（x） = -ax2/2＋b｜x＋｜2y/（2y） on stochastic resonance （SR） is discussed. We investigate the effects of index y on the performance of the SR system with fixed parameters a and b, and with fixed potential barriers, respectively. To measure the performance of the SR system in the presence of an aperiodic input, the bit error rate is employed, as is commonly used in binary communications. The numerical simulations strongly support the theoretical results. The goal of this investigation is to explore the effects of the shape of potential functions on SR and give a guidance of nonlinear systems in the application of information processing.

Architecture and Implementation of 3D Engine Based on WebGL

As the progress of 3D rendering technology and the changes of market demand, the 3D application has been widely used and reached as far as education, entertainment, medical treatment, city planning, military training and so on. Its trend is gradually changed from client to web, and so many people start to research the 3D graphics engine technology on the web. WebGL and HTML5 rise in recent years and WebGL solves two problems of interactive 3D application on the web perfectly. Firstly, it implements the interactive 3D web application by JavaScript without any browser plug-in components. Secondly, it makes graphics rendering using the underlying graphics hardware, which is united, standard and cross-platform OpenGL interface. However, it is very difficult for 3D application web programmer to understand multifarious details. Therefore, a 3D engine based on WebGL comes into being. The paper consults the existing 3D engine design idea, architecture and implementation experience, and designs a 3D graphics engine based on WebGL and Typescript.

A New HARQ Scheme for 5G Systems via Interleaved Superposition Retransmission

Within the framework of the 5G new radio(NR),we propose a new hybrid automatic repeat request(HARQ)scheme to improve the throughput performance.The difference between the proposed scheme and the conventional one lies in the first retransmission,where the erroneous coded block group is interleaved and superimposed(XORed)onto a fresh coded block group.At the receiver,an iterative message-passing decoding algorithm can be employed to recover the target erroneous code block group(CBG).Only when the superposed retransmission fails,the conventional incremental redundancy(IR)or repetition redundancy(RR)retransmission is initiated.In any case,since the first retransmission is along with but has negligible effect on the fresh CBG,it costs neither transmitted power nor bandwidth.Monte-Carlo simulation results reveal that the presented HARQ schemes can achieve throughput improvements up to 10%over block fading channels and up to 50%over fast fading channels in comparison with the original 5G CBG-level HARQ scheme but without excessively increasing the implementation complexity.

Strong anharmonicity-assisted low lattice thermal conductivities and high thermoelectric performance in double-anion Mo_(2)AB_(2)(A=S,Se,Te;B=Cl,Br,I)semiconductors

The thermoelectric properties of layered Mo_(2)AB_(2)(A=S,Se,Te;B=Cl,Br,I)materials are systematically investigated by first-principles approach.Soft transverse acoustic modes and direct Mo d–Mo d couplings give rise to strong anharmonicities and low lattice thermal conductivities.The double anions with distinctly different electronegativities of Mo_(2)AB_(2)monolayers can reduce the correlation between electron transport and phonon scattering,and further benefit much to their good thermoelectric properties.Thermoelectric properties of these Mo_(2)AB_(2)monolayers exhibit obvious anisotropies due to the direction-dependent chemical bondings and transport properties.Furthermore,their thermoelectric properties strongly depend on carrier type(n-type or p-type),carrier concentration and temperature.It is found that n-type Mo_(2)AB_(2)monolayers can be excellent thermoelectric materials with high electric conductivity,σ,and figures of merit,ZT.Choosing the types of A and B anions of Mo_(2)AB_(2)is an effective strategy to optimize their thermoelectric performance.These results provide rigorous understanding on thermoelectric properties of double-anions compounds and important guidance for achieving high thermoelectric performance in multi-anion compounds.

Specialty optical fibers for advanced sensing applications

Optical fiber technology has changed the world by enabling extraordinary growth in world-wide communications and sensing.The rapid development and wide deployment of optical fiber sensors are driven by their excellent sensing performance with outstanding flexibility,functionality,and versatility.Notably,the research on specialty optical fibers is playing a critical role in enabling and proliferating the optical fiber sensing applications.This paper overviews recent developments in specialty optical fibers and their sensing applications.The specialty optical fibers are reviewed based on their innovations in special structures,special materials,and technologies to realize lab in/on a fiber.An overview of sensing applications in various fields is presented.The prospects and emerging research areas of specialty optical fibers are also discussed.

Mode-dependent dynamic gain of all-fiber FM-EDFA under various pump manipulation

The dynamic gain of a few-mode erbium-doped fiber amplifier(FM-EDFA)is vital for the long-haul mode division multiplexing(MDM)transmission.Here,we investigate the mode-dependent dynamic gain of an FM-EDFA under various manipulations of the pump mode.First,we numerically calculate the gain variation with respect to the input signal power,where a modedependent saturation input power occurs under different pump modes.Even under the fixed intensity profile of the pump laser,the saturation input power of each spatial mode is different.Moreover,high-order mode pumping leads to a compression of the linear amplification region,even though it is beneficial for the mitigation of the differential modal gain(DMG)arising in all guided modes.Then,we develop an all-fiber 3-mode EDFA,where the fundamental mode of the pump laser can be efficiently converted to the LP_(11)mode using the all-fiber mode-selective coupler(MSC).In comparison with the traditional LP_(01)pumping scheme,the DMG at 1550 nm can be mitigated from 1.61 dB to 0.97 dB under the LP_(11)mode pumping,while both an average gain of 19.93 dB and a DMG of less than 1 dB can be achieved from 1530 nm to 1560 nm.However,the corresponding signal input saturation powers are reduced by 0.3 dB for the LP_(01)mode and 1.6 dB for the LP_(11)mode,respectively.Both theoretical and experimental results indicate that a trade-off occurs between the DMG mitigation and the extension of the linear amplification range when the intensity profile of pump laser is manipulated.

Reputation-Based Hierarchically Cooperative Spectrum Sensing Scheme in Cognitive Radio Networks

Cooperative spectrum sensing in cognitive radio is investigated to improve the detection performance of Primary User(PU).Meanwhile,cluster-based hierarchical cooperation is introduced for reducing the overhead as well as maintaining a certain level of sensing performance.However,in existing hierarchically cooperative spectrum sensing algorithms,the robustness problem of the system is seldom considered.In this paper,we propose a reputation-based hierarchically cooperative spectrum sensing scheme in Cognitive Radio Networks(CRNs).Before spectrum sensing,clusters are grouped based on the location correlation coefficients of Secondary Users(SUs).In the proposed scheme,there are two levels of cooperation,the first one is perfonned within a cluster and the second one is carried out among clusters.With the reputation mechanism and modified MAJORITY rule in the second level cooperation,the proposed scheme can not only relieve the influence of the shadowing,but also eliminate the impact of the PU emulation attack on a relatively large scale.Simulation results show that,in the scenarios with deep-shadowing or multiple attacked SUs,our proposed scheme achieves a better tradeoff between the system robustness and the energy saving compared with those conventionally cooperative sensing schemes.

Vision based terrain reconstruction for planet rover using a special binocular bundle adjustment

This paper presents a pure vision based technique for 3D reconstruction of planet terrain. The reconstruction accuracy depends ultimately on an optimization technique known as 'bundle adjustment'. In vision techniques, the translation is only known up to a scale factor, and a single scale factor is assumed for the whole sequence of images if only one camera is used. If an extra camera is available, stereo vision based reconstruction can be obtained by binocular views. If the baseline of the stereo setup is known, the scale factor problem is solved. We found that direct application of classical bundle adjustment on the constraints inherent between the binocular views has not been tested. Our method incorporated this constraint into the conventional bundle adjustment method. This special binocular bundle adjustment has been performed on image sequences similar to planet terrain circumstances. Experimental results show that our special method enhances not only the localization accuracy, but also the terrain mapping quality.

A 3-kHz Er:YAG single-frequency laser with a‘triple-reflection’configuration on a piezoelectric actuator

A novel Er:YAG laser system operating at 1645 nm with high pulse-repetition-frequency(PRF)of kHz level is demonstrated.A ring cavity with double gain medium end-pumped by two fiber lasers is utilized to obtain high pulse energy.A novel‘triple-reflection’configuration on a piezoelectric actuator(PZT)is adopted to achieve high-repetition-rate at 3-kHz operation with the ramp-fire locking method.Single frequency pulses with maximum average power of 18.3 W at 3 kHz are obtained,and the pulse duration time is 318 ns.The full line width at half maximum(FWHM)of the pulses measured by the heterodyne technique is 1.71 MHz at 3 kHz.To the best of our knowledge,this is the highest PRF single-frequency laser pulses achieved based Er:YAG gain medium.

A HEVC Video Steganalysis Algorithm Based on PU Partition Modes

Steganalysis is a technique used for detecting the existence of secret information embedded into cover media such as images and videos.Currently,with the higher speed of the Internet,videos have become a kind of main methods for transferring information.The latest video coding standard High Efficiency Video Coding(HEVC)shows better coding performance compared with the H.264/AVC standard published in the previous time.Therefore,since the HEVC was published,HEVC videos have been widely used as carriers of hidden information.In this paper,a steganalysis algorithm is proposed to detect the latest HEVC video steganography method which is based on the modification of Prediction Units(PU)partition modes.To detect the embedded data,All the PU partition modes are extracted from P pictures,and the probability of each PU partition mode in cover videos and stego videos is adopted as the classification feature.Furthermore,feature optimization is applied,that the 25-dimensional steganalysis feature has been reduced to the 3-dimensional feature.Then the Support Vector Machine(SVM)is used to identify stego videos.It is demonstrated in experimental results that the proposed steganalysis algorithm can effectively detect the stego videos,and much higher classification accuracy has been achieved compared with state-of-the-art work.

Modified virtual internal bond model based on deformable Voronoi particles

In last time,the series of virtual internal bond model was proposed for solving rock mechanics problems.In these models,the rock continuum is considered as a structure of discrete particles connected by normal and shear springs(bonds).It is well announced that the normal springs structure corresponds to a linear elastic solid with a fixed Poisson ratio,namely,0.25 for threedimensional cases.So the shear springs used to represent the diversity of the Poisson ratio.However,the shearing force calculation is not rotationally invariant and it produce difficulties in application of these models for rock mechanics problems with sufficient displacements.In this letter,we proposed the approach to support the diversity of the Poisson ratio that based on usage of deformable Voronoi cells as set of particles.The edges of dual Delaunay tetrahedralization are considered as structure of normal springs(bonds).The movements of particle’s centers lead to deformation of tetrahedrals and as result to deformation of Voronoi cells.For each bond,there are the corresponded dual face of some Voronoi cell.We can consider the normal bond as some beam and in this case,the appropriate face of Voronoi cell will be a cross section of this beam.If during deformation the Voronoi face was expand,then,according Poisson effect,the length of bond should be decrees.The above mechanism was numerically investigated and we shown that it is acceptable for simulation of elastic behavior in 0.1–0.3 interval of Poisson ratio.Unexpected surprise is that proposed approach give possibility to simulate auxetic materials with negative Poisson’s ratio in interval from–0.5 to–0.1.

An adaptive pipelining scheme for H.264/AVC CABAC decoder

An adaptive pipelining scheme for H.264/AVC context-based adaptive binary arithmetic coding(CABAC) decoder for high definition(HD) applications is proposed to solve data hazard problems coming from the data dependencies in CABAC decoding process.An efficiency model of CABAC decoding pipeline is derived according to the analysis of a common pipeline.Based on that,several adaptive strategies are provided.The pipelining scheme with these strategies can be adaptive to different types of syntax elements(SEs) and the pipeline will not stall during decoding process when these strategies are adopted.In addition,the decoder proposed can fully support H.264/AVC high4:2:2 profile and the experimental results show that the efficiency of decoder is much higher than other architectures with one engine.Taking both performance and cost into consideration,our design makes a good tradeoff compared with other work and it is sufficient for HD real-time decoding.