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Despite the resistance-type gas sensors attracting intensive research interest, the vulnerability to the interference of humidity is a great challenge for their large-scale productions and applications. Herein, a convenient "gas-sensitized sensing material + adhesive" approach for the fabrication of superhydrophobic interface has been proposed to settle the problem. The multiwalled carbon nanotubes (MWCNTs)/styrene-ethylene/butylene-styrene block copolymer (SEBS) layer formed by spraying the cyclohexane suspension of MWCNTs and SEBS with micro/nanostructure endows the sensor with outstanding superhydrophobic property, presenting that the apparent contact angles (CA) are up to 179.6∘. The superhydrophobic paper sensor exhibited high sensing performance for acetone vapor and most importantly exceptional anti-humidity. The response of as-prepared sensor for other gaseous chemicals was consistent with that of MWCNTs, which indicated that the "gas-sensitized sensing material + adhesive " approach did not change the MWCNTs gas-sensitive characteristics. The approach builds an efficient bridge between gas-sensitive particles and flexible, superhydrophobic systems, inspiring a new simple way to the development of gas sensor with high immunity to humidity. A convenient "gas sensitized sensing material + adhesive" approach was proposed to form superhydrophobic paper sensor, which not only has outstanding superhydrophobic property, presenting that the apparent contact angle is up to 179.6∘, but also preserves the gas sensitized sensing material origin gas-sensitive characteristics. [ABSTRACT FROM AUTHOR]

In this paper, an analysis of the precision of range sensors is presented. Light Detection and Ranging (LIDAR) data from three different sensors (HLS-LFCD-LDS, SICK TIM561, and Kinect V2), stereo data from the Realsense D435, and structured light data from both Kinect V1 for Xbox and the Xtion PRO Live were analyzed regarding the influence of range, incident angle to the surface, and surface material. In addition, a comparison with standard deviation models based on vendor-provided specifications was performed. We found that the vendor specifications are in general not specific enough to facilitate accurate sensor simulations. Therefore, we developed a data-driven model for range precision. Our model can be used to create realistic sensor simulations and to develop robot navigation algorithms weighing sensor range readings based on the precision. [ABSTRACT FROM AUTHOR]

With the use of Convolutional Neural Network (CNN) in the application of sensor signal processing system, it usually faces the urgent requirements of system integration, high throughput, hardware resource and energy efficiency. This paper introduces a resource efficient accelerator with general two-dimensional multiply-add array operator to focus on the characteristic of sensor signal processing, which can be applied to standard CNN, depth-wise CNN, Fully Connected (FC) layer for varied networks. Meanwhile, resource estimation model is also constructed to provide the exploration of parallel parameters for computing efficiency. Finally, a board-level verification is implemented to demonstrate the efficiency of proposed accelerator with common scene of LeNet and complex scene of MobileNetV1. Experimental results show that the Inferences Per Second (IPS) of 332225 and 1498 is realized with 100 MHz frequency. The corresponding efficiency is 88.84% and 61.09%, which outperforms other related works about CNN accelerator design in terms of signal processing. This paper is also applicable and scalable to other fields about effective acceleration research. [ABSTRACT FROM AUTHOR]

Localization-loss and classification-loss are optimized at the same time to train the one-stage object detectors. Because of the large number of anchors, the severe foreground–background class disproportion causes significant classification-loss. This paper discusses using a ranking module instead of the classification module to mitigate this difficulty and also Average-Precision loss (AP-loss) is utilized on the ranking module. An optimization algorithm is used to make the AP-loss as effective as possible. Optimization algorithm blends the error-driven updating method of perceptron learning and the deep network backpropagation technique. This optimization algorithm handles the foreground–background class disproportion issues. One-stage detector with AP-loss and backbone with ResNet-152 attains improvement in the detection performance compared to the classification-losses-based detectors. [ABSTRACT FROM AUTHOR]

A linear acceleration sensor integrated into an inertial measurement unit and its signal processing technology are presented in this paper. Based on the characteristics of the acceleration sensor, before analog-to-digital conversion, a design method for optimizing and conditioning the output signal in levels of frequency with the high-order anti-aliasing Cauer filter is proposed. Compared with the previously published papers, here we not only focus on the anti-aliasing filtering effect under a single channel, but also pay more attention to the anti-aliasing filtering effect with more data to the same type of channels with the same cut-off frequency and different types of channels with different cut-off frequencies. Similar to other kinds of filters, this paper points out that the high-order anti-aliasing Cauer filter also has its inherent delay characteristic. And this paper also reveals the qualitative relationship between frequency and time delay in different testing environments by using various delay test data. Compared with the previously published papers, through the simple solution processing with the true attitude data, this paper further estimates the error of simple attitude signal processing. [ABSTRACT FROM AUTHOR]

In ultraviolet (UV) astronomical observations, photons from the sources are very few compared to the visible or infrared (IR) wavelength ranges. Detectors operating in the UV usually employ a photon-counting mode of operation. These detectors usually have an image intensifier sensitive to UV photons and a readout mechanism that employs photon counting. The development of readouts for these detectors is resource-intensive and expensive. In this paper, we describe the development of a low-cost UV photon-counting detector processing unit that employs a Raspberry Pi (RPi) with its built-in readout to perform the photon-counting operation. Our system can operate in both 3 × 3 and 5 × 5 window modes at 30 frames per second (fps). The system can be built quickly from readily available custom-off-the-shelf (COTS) components and is thus used in inexpensive CubeSats or small satellite missions. [ABSTRACT FROM AUTHOR]

In this paper, in view of the insufficiency of the CenterNet detector's inability to achieve high real-time performance with high accuracy when performing object detection, we designed a new detector called A_CenterNet. In the detector, we use our newly designed lightweight Hourglass-256 model, and we also use the feature map fusion method we designed, as well as our improved attention mechanism. Through the experimental results on multiple datasets, it can be known that the A_CenterNet proposed in this paper has a competitive advantage compared with some existing classic detectors. A_CenterNet achieves the best speed-accuracy trade-off on the MS COCO dataset, with 44.6 AP at 36 FPS. Compared with CenterNet, A_CenterNet greatly improves the detection speed without loss of detection accuracy. [ABSTRACT FROM AUTHOR]

In this paper, a novel nanosensor comprising the metal–insulator–metal (MIM) plasmonics waveguide with a semi-elliptical and rectangular ring resonant cavity is designed. In near-infrared waveband, the propagation properties of electromagnetic waves in the structure are studied using the finite-difference time-domain (FDTD) method. The results show that, based on the coupling between the semi-elliptical and the rectangular ring resonant cavity, the transmission spectrum of the structure exhibits a sharp Fano resonance shape. Next, the influence of the refractive index and sensor structure parameters on performance is systematically investigated. The simulation results show that the sensor structure has the best sensitivity of 1384 nm/RIU (refractive index unit), and the figure of merit (FOM) is 28.4. The simple MIM structure could be applied to sensitive plasmonic sensors. [ABSTRACT FROM AUTHOR]

Piezoelectric energy harvesters are used to extract and generate electrical energy from ambient vibration sources. Under low excitation, the efficiency of the rectifier plays an important role in determining the efficiency of energy harvesters. Asymmetric Synchronous Electric Charge Extraction (ASECE) has higher efficiency compared to other conventional rectifiers. In this paper, the subcircuits of ASECE, i.e., peak detector and zero crossing detector, are designed. The proposed detectors can operate even at minimum frequency of 10 Hz and in the temperature range of 0–125∘C. The proposed peak detector has shown detection in subthreshold region also. The performance of these detectors at different temperatures, supply voltages and frequencies has been reported in this paper. The detectors are designed using Tanner (2019.2) EDA tool at 180 nm CMOS technology. Piezoelectric energy harvesters are used to extract and generate electrical energy from the ambient vibration sources. Under low excitation, the efficiency of rectifier plays an important role in determining the efficiency of energy harvesters. ASECE (Asymmetric Synchronous Electric Charge Extraction) has higher efficiency compared to other conventional rectifiers. In this paper, the sub circuits of ASECE, i.e., peak detector and zero crossing detector are designed. The proposed detectors can operate even at minimum frequency of 10 Hz and in the temperature range of 0∘C to 125∘C. The proposed peak detector has shown detection in sub threshold region also. The performance of these detectors at different temperature, supply voltage and frequency have been reported. The detectors are designed using Tanner (2019.2) EDA tool at 180 nm CMOS technology. [ABSTRACT FROM AUTHOR]

A double U-shaped PCF-SPR sensor is proposed for the detection of analytes with low refractive indexes (RI). The U-shaped structure facilitates the penetration of analytes. Compared with a single formant sensor, the sensor exhibits double formant characteristics. Therefore, the analytes to be measured can be identified more accurately. This study employs the finite element method (FEM) to analyze the sensor. The findings suggest that the sensor is capable of detecting analytes with low RI ranging from 1.15 to 1.33 over an ultra-wide wavelength range of 800–6400nm. The maximum wavelength sensitivities of the first and second peaks of the sensor are 54,300nm/RIU and 60,000nm/RIU, respectively. In addition, this paper introduces double peak shift sensitivity (DPSS), the highest DPSS value is 55,700nm/RIU. Owing to these distinct characteristics, the sensor has great application prospects in the field of biosensing, especially in drug detection. [ABSTRACT FROM AUTHOR]

The detection of subtle strain on the human body by flexible sensors suffers from the inferior sensitivity. In general, poor sensitivity derives from the intact structural integrity of building blocks of electric material. Inspired by the rolling friction in daily life, a three-dimensional (3D) nanohybrid of gold@carbonaceous nanoballs (Au@CBs) is developed. Compared with the pure Au nanostructure, the CBs increase the defect sites of conductivity and deformation sensitivity between Au nanostructures. The Flexible Stress Sensor (FSS) based on the 3D nanohybrid of Au@CBs is fabricated, and due to the enough displacement variation of 3D nanohybrid of Au@CBs, the change of resistance could be triggered by the tiny stress. The as-prepared sensor has high sensitivity at wide working range (S = 0. 1 2 KPa − 1 , 0.1–10 KPa and S = 0. 0 8 5 KPa − 1 , 10–100 KPa) and good cyclic stability (5000 cycles). Finally, the FSS based on the 3D nanohybrid of Au@CBs is employed for the detection of subtle vibration and movement of the human body, such as pulse and joint bending, which exerts great potential as wearable electronics. The flexible stress sensor based on the 3D nanohybrid of gold@carbonaceous nanoballs (Au@CBs) was fabricated, due to the sandwich structure based on the 3D nanohybrid of Au@CBs. Enough displacement and resistance variation of 3D nanohybrid of Au@CBs could be triggered by the tiny stress. The Au@CBs sensor features high sensitivity at wide working range, which exerts great potential as wearable electronics. [ABSTRACT FROM AUTHOR]

The quantum adder is a vital arithmetic operation for quantum algorithms. However, the existing quantum floating-point adders only considered the case of two normal numbers. In this paper, we propose an enhanced quantum floating-point adder based on IEEE 754 standard. First, we divide quantum floating-point adders into four cases: the normal case, subnormal case, mixed case, and special case. Then, we propose a result-sign and mantissa-sign determining unit to avoid conversion from sign-magnitude to two complements. Moreover, we design a new quantum leading zero detector with the optimized T-depth and T-count. Comparison results reveal that the proposed floating-point adder has lower circuit width, T-depth, and T-count than the current works. [ABSTRACT FROM AUTHOR]

This paper proposes LHFNet, an improved object detection method based on CenterNet, which achieves a better speed-accuracy trade-off. The main contributions of this paper are as follows: We design a lightweight Hourglass network to reduce the number of parameters and computations of CenterNet, thus improving the detection speed. We introduce an intermediate feature map fusion module to enhance the feature extraction capability of Hourglass, which compensates for the possible performance degradation caused by the network simplification. We apply an attention module to the final heat map to improve the image feature representation. We design and optimize a series of loss functions to train LHFNet effectively. Through the research in this paper, we demonstrate that the feature map fusion and the attention module greatly improve the performance of LHFNet. We evaluate our method on the COCO dataset and achieve a high accuracy at a fast speed (Tesla V100), which outperforms other object detection methods in terms of both accuracy and efficiency. [ABSTRACT FROM AUTHOR]

In this paper, we propose a hierarchical attention-based sensor fusion strategy for depth estimation under various weather conditions. Multiple-sensor fusion is proven as a promising solution for predicting accurate depth maps in diverse weather conditions, especially for extreme weather conditions. However, most of the current studies simply fuse the information from different sensors without jointly considering the difference in their performance at the sensor level and feature level. To fill this gap, our hierarchical attention-based fusion strategy uses two attention mask-generation modules that weigh sensor data from branches (i.e. different sensors) and features. With the cooperation of these two masks, our system is able to determine the adaptive contribution of each sensor as well as the individual contribution of each feature in the sensor regarding their performance in different weather. We compare the proposed methods with the baseline, i.e. the late fusion Sparse-to-Dense model, and two extended models individually with the branch-wise-only and feature-wise-only masks. The results show a robust and superior performance of our methods even in clear environments where the baseline already performs well enough. Moreover, we investigate the performance of RGB camera, radar, and LiDAR in foggy environments comprehensively by visualizing the generated mask. Our results show a significantly increased importance of radar sensors in extreme weather conditions, e.g. dense fog. [ABSTRACT FROM AUTHOR]

In this paper, a TMDC-based surface plasmon resonance (SPR) sensor for detecting fat concentration milk, incorporating an Ag-Pt (bimetallic) layer, is presented. The Pt (Platinum) layer provides chemical stability and increases sensitivity with the TMDC layer. Compared to the conventional SPR sensor, the maximum sensitivity, detection accuracy (DA), and figure of merit (FoM) of 314∘/RIU, 0.142/degree, and FoM 44.05/RIU are achieved with the WS2 layer. The sensor's increased sensitivity is due to the increased field intensity and depth of penetration into the sensor layer, resulting in a larger interaction volume. The presence of the WS2 layer, with its significant imaginary part of the dielectric constant, helps improve sensitivity and broadens the SPR curves. This broadening SPR curve ultimately affects the DA and FoM of the sensor. The capability of the proposed sensor to detect various biological analytes with a refractive index (1.3452–1.3657) can be demonstrated. [ABSTRACT FROM AUTHOR]

With the development of industrial technology, acceleration sensors have a wide range of applications. The application environment has strict requirements on acceleration sensor, which needs it to get accurate input and output response in complexity. According to the Hammerstein model, this paper studies the dynamic nonlinear relationship between the output voltage and the input acceleration of the acceleration sensor that can be divided into static nonlinear component and dynamic linear component. We combine the least square method with adaptive neural network to calculate the parameters of static nonlinear and dynamic linear components. The least square method is used to improve the training performance of the network and avoid the network falling into the local minimum of the traditional neural network. Experimental results show that compared with other methods, the proposed method has the advantages of less training steps and strong approximation ability, and the algorithm is less affected by external noise. This method can realize nonlinear system identification of acceleration sensor and provide reliable basis for compensation. [ABSTRACT FROM AUTHOR]

An extended Neyman–Pearson detector based on the combination of a traditional matched and wavelet filter in pulsed monostatic radar was proposed in this paper. Its properties were compared with properties of the cell average constant false alarm radar detector in the presence of white noise. The properties of detectors were examined in the receiver operating characteristic curves, parameter space. It consisted of false detection rate and the rate of true positive detected targets. In order to investigate the influence of temperature, the new parameter space was constructed: the temperature versus the rate of true positive detected targets. The traditional Neyman–Pearson detector based on a matched filter was fully operational and superior in the temperature range between 290 K and 350 K. Below this temperature range, its performance is completely degraded. It has been shown that by adding a wavelet filter, it can extend this temperature range between 260 K and 350 K. In the temperature range, where all detectors are fully operational, extended and classic Neyman–Pearson detectors had better performance than constant false alarm radar detector in the receiver operating characteristic curves' parameter space. [ABSTRACT FROM AUTHOR]

The LIGO-India project to build and operate an advanced LIGO (aLIGO) gravitational wave (GW) detector in India in collaboration with LIGO-USA was initiated as an Indian national mega-science project in 2011. The project relied on the advantage of a head start and cost saving due to the ready availability of most of the aLIGO interferometer components from LIGO-USA, approved by the National Science Foundation. A suitable site was selected and the provisional governmental approval for project was obtained in 2016, immediately following the first direct detection of gravitational waves with the aLIGO detectors. I had discussed the scope and the science case of the project, as well as the plans for its realization by 2022 in a paper [C. S. Unnikrishnan, Int. J. Mod. Phys. D 22 (2013) 1341010, arXiv:1510.06059]. With the KAGRA GW detector in Japan being tuned to be part of the GW detector network, it is now the occasion to assess the progress of the LIGO-India project, and evaluate its relevance and scope for GW science and astronomy. Various key factors in the implementation of the project are reassessed in the backdrop of the projected evolution of the global GW detector sensitivity. In my realistic estimate, it will take more than a decade, beyond 2034, and nearly thrice the original budget to commission and operate the detector with a good fraction of the projected design sensitivity. My decadal assessment points to the eroded scientific relevance of the LIGO-India detector in the GW detector network of the next decade. I argue that the only solution to regain its scientific relevance is to re-plan and relaunch the LIGO-India detector in an upgraded A # version, similar to the projected post-O5 upgrade of the LIGO-USA detectors beyond 2029. [ABSTRACT FROM AUTHOR]

Nowadays, developing the radio frequency (RF)-photonic sensors suitable for several Defence and civil applications is emerging due to its various unique advantages. In today's scientific world, the involvement of low radar cross-section (RCS) airspace targets, such as unman aerial vehicles, drones, mini-helicopters, ornithopters, bionic birds, etc., is more for the purpose of airspace traffic management/guidance, materials delivery, legal/illegal surveillance and Defence/offense applications. The detection and recognition of such targets using the conventional RF sensors (which process only the main Doppler) is almost impossible. Therefore, extracting the distinctive micro-Doppler (m-D) signatures of these low-RCS targets and using them to image/differentiate/recognize their postures become significant which is the main contribution in this paper. A C-band continuous wave RF-photonic sensor is developed and different low-RCS targets: 2/3 blades rotating propeller system (drones), cone like structure (warhead) and a bionic-bird (spy-bird); are operated in front of it. The different nonlinear postures, of these targets, covered in our experimental measurements are m-D extraction of a slowly moving propeller system, detection of back-and-forth movements of a rotational propeller system, discerning the moving and static rotational propeller systems, simultaneous extraction of m-D signatures of a rotational and moving targets and recognition of flapping/gliding motions of bionic-bird. The analysis and recognition of all these postures using the experimentally generated m-D signatures are described. [ABSTRACT FROM AUTHOR]

A closed-loop controlled system usually consists of the main structure, sensors, and actuators. In this paper, asymptotic stability of trivial solutions of a controlled nonlinear stochastic system considering the dynamics of sensors and actuators is investigated. Considering the inherent and intentional nonlinearities and random loadings, the coupled dynamic equations of the controlled system with sensors and actuators are given, which are further formulated by a controlled, randomly excited, dissipated Hamiltonian system. The Hamiltonian of the controlled system is introduced, and, based on the stochastic averaging method, the original high-dimensional system is reduced to a one-dimensional averaged system. The analytical expression of Lyapunov exponent of the averaged system is derived, which gives the approximately necessary and sufficient condition of the asymptotic stability of trivial solutions of the original high-dimensional system. The validation of the proposed method is demonstrated by a four-degree-of-freedom controlled system under pure stochastically parametric excitations in detail. A comparative analysis, which is related to the stochastic asymptotic stability of the system with and without considering the dynamics of sensors and actuators, is carried out to investigate the effect of their dynamics on the motion of the controlled system. Results show that ignoring the dynamics of sensors and actuators will get a shrink stable region of the controlled system. [ABSTRACT FROM AUTHOR]

In this paper, a Quantum-Dot Cellular Automata (QCA)-based D -flip flop is designed with low quantum cost to propose a 3-bit sequence detector which detects a bit pattern 101 in both overlapping and non-overlapping forms. Initially, a level to edge-triggered clock converter is proposed to convert clock signal levels into edge defining signals. Later, D -flip flops of both level and edge triggered clock inputs are developed. Compared with the recently reported designs in the literature, it is observed that the quantum cost of the proposed D -flip flops is decreased by more than 28% with a cell count of 34, which in turn defines the low area too. Also, latency of the same is reduced by one-fourth with a value of 1. 2 5 × 1 0 − 1 2 s. As far as the sequence detector is concerned, it is smaller in size at 0.16 μ m2 than the existing sequential circuits with a reduction in area and quantum cost by 30%. Further, from the bit stream it detects, the proposed sequence detector can also be used as negative pulse detector and interrupt handler circuit in the future QCA-based digital systems to detect the external interrupts. [ABSTRACT FROM AUTHOR]

This paper presents a novel strategy for indirectly identifying the natural frequency of a bridge via multiple sensors on an ordinary vehicle. It does not require specifically designed cars or multiple cars as the excitation sources, as many earlier studies have used, but only one normal vehicle, providing practicability. A signal processing method incorporating cross-spectrum estimation can extract the bridge frequency among complex and varied frequency components in the vehicle spectrogram. The bridge natural frequency as a common vibration component among different sensor responses is identified as a clear peak that occurs in the cross-spectrum. The methodology is validated by an experimental study using a steel beam and a scale truck model with an engine to construct the vehicle–bridge interaction system. With this approach, the first mode frequency of the bridge is successfully identified under various bridge conditions. In addition, the performance of the proposed strategy in bridges with and without road roughness is discussed, and the influence of vehicle weight on the success rates of frequency identification is also confirmed. [ABSTRACT FROM AUTHOR]

Electrocardiogram (ECG) is considered as the important diagnostic tests in medical field for detecting the cardiac anomalies. But, the ECG signals are polluted with numerous noise from power line intrusion, muscle noise, baseline wander, motion artifacts, low frequency noise signals, high frequency noise signals and T-wave, which automatically affects the QRS profile. The existing method provides the result in lesser accuracy with higher rate of error detection. To overcome these issues, QRS detector using modified maximum mean minimum (MoMaMeMi) filter optimized with mayfly optimization algorithm (QRS-MoMaMeMi-MOA) is proposed in this paper for less computational cost along with resource requirements. The proposed filter design consists of two phases for detecting QRS detector, such as filtering process associated to the enhancement and detection phase. Initially, the ECG data are taken from MIT/BIH arrhythmia dataset (MIT-AD). For eradicating the baseline wander in ECG data, MaMeMi filter is used. For expanding the performance of the modified MaMeMi filter, filter parameters, such as σ and Δ are optimized by MOA to accomplish the best values and measure the performance of the whole QRS detector. For high frequency noise suppression in ECG data, the range function, noise subtractors, modified triangular detector are used. Then, heart beat detection can be done with the help of adaptive thresholding technique. The proposed filter design is carried out in MATLAB and implemented on field programmable gate arrays (FPGAs). The proposed QRS-MoMaMeMi-MOA filter design had 0.93%, 0.12% and 0.19% higher accuracy and 89.32%, 50% and 62% low detection error rate, compared to the existing filters, like Kalman filtering based adaptive threshold algorithm for QRS complex detection (QRS-KF-ATA), QRS detection of ECG signal utilizing hybrid derivative with MaMeMi filter by efficiently removing the baseline wander (QRS-HD-MaMeMi), and knowledge-based QRS detection operated by cascade of moving average filters (QRS-CAF). Then, the device utilization of the proposed FPGA implementation of the QRS-MoMaMeMi-MOA filter provides 95.556% and 71.428% lower power usage compared with the existing algorithms, like Kalman filtering based adaptive threshold algorithm for QRS complex detection in FPGA (FPGA-QRS-KF-ATA), and efficient architecture for QRS detection in FPGA utilizing integer Haar wavelet transform (FPGA-QRS-IHWT). [ABSTRACT FROM AUTHOR]

Neutron detection using gadolinium (Gd) and its prompt gamma-rays is vital because of the high cross-section of Gd on thermal neutrons, thereby leading to significant interest in neutron detection with Gd-converted or Gd-loaded detector. However, simultaneous detection of neutron and gamma-rays with a Gd-loaded scintillator has been given less attention. In this study, we explored the feasibility of the GdI3:Ce detector for simultaneous detection with Monte Carlo N-Particle transport extended simulation. Furthermore, we examined the physical properties of Gd for application in the radiation field mixed with neutron and gamma-rays. Similarly, we simulated the geometry of the GdI3:Ce scintillator and its spectra obtained under various conditions. The results showed that GdI3:Ce with a thickness of 1 cm is enough to absorb 90 % of photons with energy under 81 keV. A shorter source-to-detector distance and larger detector size were superior to detecting prompt gamma-rays emitted from neutron capture, not only the gamma-rays from isomeric transition (named as general gamma-ray in this paper). Ultimately, spectra taken with the Gd3:Ce scintillator under the radiation field mixed with neutrons and gamma-ray showed gamma-ray peaks from both radio-isotopes and Gd (n γ) Gd reaction, indicating the feasibility of the application of simultaneous detection. [ABSTRACT FROM AUTHOR]

This paper constructs a low-resolution model for face recognition and sports training actions based on wireless sensors. The model obtains the distribution of the information size in the face image by calculating the image entropy value, and assigns different weights according to the size of the information to perform face recognition calculation, so that the original module-based algorithm is simply based on image segmentation into one based on entropy. The size of the value is divided into blocks, which solves the problem of computational quantification of category information. In the test stage, the traditional orthogonal matching pursuit algorithm is used to solve the coding coefficients, and the excellent classification and recognition results are obtained by calculating the intra-class matrix of the face image and the inter-class matrix of the sports training action image. Methods that perform well on classification problems further improve face recognition rates. The specific processing process is to add Gaussian noise, salt and pepper noise to the input face image and reduce the size of the face image in the input image, so that the improved algorithms are improved. The experimental results show that the high-efficiency resolution sensing technology is used to learn the sports training actions corresponding to the two modalities, and the matrix coefficient between the obtained high-resolution modal and low-resolution modal images reaches 0.971, and the iteration rate is improved by 71.5%, effectively promoting the high recognition rate of faces and actions. [ABSTRACT FROM AUTHOR]

The photonic crystal fiber (PCF) sensor based on surface plasmon resonance (SPR) technology has flexibility in birefringence, negative dispersion, effective area and nonlinearity and has become a widely studied new fiber. However, there are many problems in the practical application of the sensor, such as complex structure design, not easy to prepare, the low sensitivity of sensing detection, narrow range of refractive index detection of analytes, which greatly limits the application range and functions of PCF sensors. To solve the above problems, this paper adopts a structure with a longer vertical distance between the D-shaped large air hole channel and the core. The energy of the core conduction mode is better limited by the cladding to transmit in the core, and the plasma mode is enhanced, which can effectively increase the wavelength sensitivity. In this paper, the hexagonal double-clad air hole structure and the D-type structure are combined to ensure a simple structure and facilitate manufacturing and production, while the wavelength sensitivity is also greatly improved. The wavelength sensitivity of the dual sample channel can reach up to 16200 nm/RIU and 15800 nm/RIU, which has broad application prospects in the field of high-sensitivity detection. [ABSTRACT FROM AUTHOR]

This paper proposes a dual-channel high sensitivity photonic crystal fiber sensor with rectangular air holes, which can detect the refractive index of a single sample or detect the refractive index of two samples simultaneously, to increase the detection efficiency and wavelength sensitivity of the sample refractive index. The sensor can reduce the times of filling, emptying and cleaning of the sample to be tested and save labor and time costs. The finite element method is used to thoroughly analyze the proposed structure's sensing properties. The results show that when the sensor detects a single sample, the maximum wavelength sensitivity is 67,300 nm/RIU, and the highest figure of merit (FOM) is 547 RIU − 1 . When the sensor detects two samples synchronously, the maximum wavelength sensitivity is 64,100 nm/RIU, which is the highest level among the known sensors of the same kind. It has good application prospect in the field of high sensitivity refractive index detection. [ABSTRACT FROM AUTHOR]

In this paper, we perform a search for the vector-like leptons (VLLs) in W ν τ channel at the future TeV e + e − colliders such as the International Linear Collider (ILC) with 1 TeV and Compact Linear Collider (CLIC) with 1.5 TeV. We divide the signal into two decay channels, that is the pure leptonic channel and the fully hadronic channel. Through a detailed detector simulation, we display the excluding and discovering capability of VLLs at the ILC and CLIC. Compared to the pure leptonic channel, we find that it is more promising to detect the VLLs in the fully hadronic channel. [ABSTRACT FROM AUTHOR]

In this paper, we present the instrumental characterization and performance of the 4 k × 4 k CCD detector mounted on a 104-cm Sampurnanand telescope located at ARIES, Manora Peak Nainital, India. A detailed description of the filter wheel and its motion is presented. We measured the gain and read-out noise along with the linearity of the detector. Gain estimates are 5–10% higher than manufacturer values. The estimated read-out noise values do not fall within the manufacturer's range. It is expected that experimentally derived values will be more precise than designed values. It is suggested that the current derived values will be used rather than the designed values. The response to the incident light on the detector is linear to 99% level. To study the performance of a 4 k × 4 k CCD camera, we observe an open cluster Czernik 43. The fundamental parameters, i.e. log(age), distance and reddening E (B − V) are estimated as 7.9, 2.5 kpc and 0.65 mag, respectively. The estimated parameters of the cluster are comparable to the values derived in the literature within the error. Our detailed analysis illustrates that the detector is precise enough to carry out routine astronomical observations. [ABSTRACT FROM AUTHOR]

TIRCAM2 is the facility near-infrared Imager at the Devasthal 3.6-m telescope in northern India, equipped with an Aladdin III InSb array detector. We have pioneered the use of TIRCAM2 for very fast photometry, with the aim of recording Lunar Occultations (LO). This mode is now operational and publicly offered. In this paper, we describe the relevant instrumental details, provide references to the LO method and the underlying data analysis procedures, and list the LO events recorded so far. Among the results, we highlight a few which have led to the measurement of one small-separation binary star and of two stellar angular diameters. We conclude with a brief outlook on further possible instrumental developments and an estimate of the scientific return. In particular, we find that the LO technique can detect sources down to K ≈ 9 mag with SNR = 1 on the Devasthal Optical Telescope telescope. Angular diameters larger than ≈ 1 milliarcsecond (mas) could be measured with SNR above 10, or K ≈ 6 mag. These numbers are only an indication and will depend strongly on observing conditions such as lunar phase and rate of lunar limb motion. Based on statistics alone, there are several thousands LO events observable in principle with the given telescope and instrument every year. [ABSTRACT FROM AUTHOR]

Feature detection is one of the basic research topics in the fields of image processing and corner that has been widely applied on vehicle detection, UAV image matching, camera calibration and so on. Particularly, a fast corner detector is of much benefit to many real-time tasks. A novel discrete curvature estimation method for corner detection based on the ratio of center distances of symmetric contour (RCDSC) is proposed in this paper. Benefiting from calculating the Euclidean distance twice only to estimate the discrete curvature at each point on a contour, RCDSC is much fast compared with other corner detectors. In addition, by choosing a relatively large radius of region of support and employing relative distance instead of absolute distance for constructing corner response function, RCDSC is also much robust to noises and local variations of contour. Extensive experiments exhibit the effectiveness and the efficiency of RCDSC in terms of average repeatability (AR), accuracy (ACU) and localization error (LE). [ABSTRACT FROM AUTHOR]

In this paper, we prepared a fluorescent sensor based on carbon quantum dots (CDs) and molecularly imprinted technology (MIT) that was successfully synthesized and applied to the detection of aspirin (Asp) residues in biological and pharmaceutical samples. The molecularly imprinted fluorescence sensor had the high sensitivity of quantum dots and the high selectivity of molecularly imprinted polymers (MIPs). Nitrogen-doped carbon quantum dots (N-CDs) with high fluorescence intensity were prepared and then was coated with silicon by the reverse microemulsion method. Finally, 3-aminopropyltriethoxysilane (APTES) was used as the functional monomer and Asp as the template molecule, molecularly imprinted layers were formed around the N-CDs. Under the best experimental conditions, the detection limit of the sensor was 0.198 mg L − 1 . Between 0.9–9.0 mg L − 1 , this fluorescence sensor had a good linear relationship with the concentration of Asp. To test the practicability of the sensor, we used this fluorescent sensor to detect Asp in human urine and saliva. Satisfied recovery rate between 101.1–105.1% and 102.1–106.0% were obtained, respectively. In this paper, a molecularly imprinted fluorescence sensor was prepared by the inverse microemulsion method. Fluorescence quenching method based on molecularly imprinted fluorescence sensor was used to determine the content of Asp. When Asp combined with N-CDs@SiO2@MIPs, the fluorescence of N-CDs was quenched. The experimental results showed that the molecularly imprinted fluorescent sensor could quickly and accurately detect Asp residues in human urine and saliva. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) reconstruction of a human head with high precision has promising applications in scientific research, product design and other fields. However, it still faces resistance from two factors. One is inaccurate registration caused by symmetrical distribution of head feature points, and the other is economic burden due to high-accuracy sensors. Research on 3D reconstruction with portable consumer RGB-D sensors such as the Microsoft Kinect has been highlighted in recent years. Based on our multi-Kinect system, a precise and low-cost three-dimensional modeling method and its system implementation are introduced in this paper. A registration method for multi-source point clouds is provided, which can reduce the fusion differences and reconstruct the head model accurately. In addition, a template-based texture generation algorithm is presented to generate a fine texture. The comparison and analysis of our experiments show that our method can reconstruct a head model in an acceptable time with less memory and better effect. [ABSTRACT FROM AUTHOR]

The semi-quantum key distribution protocol based on the hyperentanglement Bell state of polarization-spatial mode is presented in this paper. This protocol is utilized to share the session keys and construct key hierarchy of security systems in high capacity between the legitimate users securely. Different from the previous protocols, two quantum non-demolition detectors are constructed with cross-Kerr nonlinearities and different phase shifts for distinguishing the Bell states in spatial mode degree of freedom. Meanwhile, this protocol can improve the capacity and efficiency when the legitimate users share the session keys. And the technology of the hyperentanglement purification and hyperentanglement concentration can enhance the robustness and stability of this protocol. At last, this protocol proposed in this paper can withstand several kinds of attacks. [ABSTRACT FROM AUTHOR]

In this 21th century, the demand for glucose sensors in monitoring diabetes reaches a year-on-year peak due to the unhealthy lifestyle of society. Therefore, it is the utmost important task for scientists and researchers to develop a highly efficient and effective glucose sensor. However, conventional enzymatic glucose sensors have showed some drawbacks and the underlying issues faced by enzymatic glucose sensors are outlined in this paper. With the tremendous advancement of science and technology, the field of diabetes monitoring has evolved from enzymatic to nonenzymatic glucose sensor that heavily emphasized on the usage of nanomaterial. This transformation is supported by various justifications such as a better stability of nonenzymatic sensors towards the surrounding, higher sensitivity and ease of fabrication. Numerous materials including graphene, noble metals, (transition) metal oxides and composites have been explored for its potential in the development and performance improvement of nonenzymatic glucose sensors. This paper reviewed nonenzymatic glucose sensors, their mechanism of glucose oxidation and various promising graphene-based nanocomposite systems as well as the challenges and future perspectives of glucose biosensors. In this review, the basic operation principle of enzymatic glucose sensor and the issues it faced are reported. Besides, the general oxidation mechanism of non-enzymatic glucose sensor has also been reviewed. A variety of different graphene-based nanocomposites that have been developed in recent years as enzymeless glucose sensor, as well as its oxidation mechanisms are also dissected in detailed. Finally, the challenges and future perspectives are discussed, to provide a more comprehensive view for glucose sensor. [ABSTRACT FROM AUTHOR]

Virtual simulation and 3D interaction have shown great potentials in a variety of domains for our future life. For a virtual fish swarm simulation system, the simulation of cohesion behaviors of fish swarm and the interaction between human and fish swarm are two key components to create immersive interactive experiences. However, it is a huge challenge to create a realistic fish swarm simulation system while providing a natural and comfortable interaction. In this paper, we propose a method for immersive virtual fish swarm simulation based on infrared sensors. Based on dynamic weight constraints, we propose a particle swarm optimization method for fish swarm cohesion simulation, which separates a particle swarm by the state of each particle and dynamically controls the particle swarm, making the movement behavior of virtual fish more realistic. In addition, an interactive fast skinning method is proposed for cartoon fishes, which leverages image segmentation, Optical Character Recognition (OCR) and bone skinning are used to generate cartoon fishes based on user-created colors. With infrared sensors, we propose a method for virtual fish swarm interaction, where the positions of human skeleton are processed by an action analyzer, achieving real-time user interactions with fish swarms. With all the proposed techniques integrated in a system, the experimental results show that our method is feasible and effective. [ABSTRACT FROM AUTHOR]

To study the nonlinear characteristics simulation and experiment of multimode driving of intelligent vehicle, an improved neural network PID controller is proposed to realize the safe and active braking requirements of cruise vehicles, according to the study of vehicle dynamics of different active braking forms and the joint simulation of road condition, driving condition, and braking mechanical structure. On the basis of the current research, the four-layer neural network combined with PID control is proposed in this paper, which can better control the braking compared with the traditional PID controller and BP neural network, safety, efficiency and stability have been improved in the following cars. According to the animation simulation demonstration of CAR SIM software, it can be determined that the improved neural network PID controller in the mechanical system can realize the safety and active braking requirements of cruise vehicle, and it is more accurate and efficient than the traditional BP neural network PID controller. Relevant parameters of the existing millimeter-wave radars are set by the radar sensors, and the long-distance horizontal detection range is plus or minus 10 degrees. The radar is installed on the longitudinal axis of the front bumper and has a height of 442 mm. According to Car SIM's preset radar sensor module parameters, the sensors can independently collect and transmit relevant data, it is also possible to cooperate with other sensors for the same variable parameter to increase the accuracy and avoid abnormal errors caused by the failure of a certain sensor. Compared with the traditional PID controller and BP neural network, the combination of four-layer neural network and PID control can carry out better braking control and improve the safety, efficiency, and stability of the following cars. [ABSTRACT FROM AUTHOR]

Smart contracts are programs running on blockchain. In recent years, due to the persistent occurrence of security-related accidents in smart contracts, the effective detection of vulnerabilities in smart contracts has received extensive attention from researchers and engineers. Machine learning-based vulnerability detection techniques have the advantage that they do not need expert rules for determining vulnerabilities. However, existing approaches cannot identify vulnerabilities when the versions of smart contract compilers are updated. In this paper, we propose OC-Detector (Opcode Clustering Detector), a smart contract vulnerability detection approach based on clustering opcode instructions. OC-Detector learns the characteristics of opcode instructions to cluster them and replaces opcode instructions belonging to the same cluster with the ID of the cluster. After that, the similarity between the contract under analysis and contracts in the vulnerability database is calculated to identify vulnerabilities. The experimental results demonstrate that OC-Detector improves the F1 value of detecting vulnerabilities from 0.04 to 0.40 compared to DC-Hunter, Securify, SmartCheck and Osiris. Additionally, compared to DC-Hunter, the F1 value is improved by 0.27 when detecting vulnerabilities in smart contracts compiled by different versions of compilers. [ABSTRACT FROM AUTHOR]

This paper presents a simple, fast, and inexpensive method for the large-scale fabrication of polymer-based humidity sensors on glass substrates. The nanoparticles were synthesized using laser ablation, this is an environmentally friendly method for fabricating metal nanoparticles and provides a unique tool for nanofabrication. In this work, humidity sensing material, poly(3,4 ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) along with different kinds of nanoparticles, Au and Ag, are employed to enhance the stability and sensitivity to humidity sensing. Based on the experimental results, the TEM images show the crystallinity of the nanoparticles, indicating alloying of the nanoparticles. Based on XRD, this result indicates that the amorphous structure of PEDOT:PSS is only slightly affected by mixing with nanoparticles. According to FE-SEM analysis, the formation of interconnected crystallites facilitates the charge transport mechanism in the polymer chains due to improved conduction paths. Has been Characterization of humidity sensors Using (LCR), study the effect of humidity on capacitance at different frequencies (100 Hz, 1 kHz, 10 kHz, and 100 kHz), and the response and recovery time characteristics. The results show excellent linear and active behavior of the capacitive humidity response. Ag, PEDOT, and Au NPs have a synergistic effect, exhibiting a more extended sensing range and better stability. This work shows a high-sensitivity and low-cost sensing material for different humidity sensor applications. [ABSTRACT FROM AUTHOR]

In this paper, Cu2O/ZnO/GaN hierarchical nanoarchitectonics was synthesized using a solution process. The hierarchical nanoarchitectonics was assembled from in situ etching and growth Cu2O nanostructures on random distributed ZnO nanotubes/GaN film by hydrothermal process. The device demonstrated multiple wavelength photodetection. It demonstrates that the detector based on Cu2O/ZnO/GaN hierarchical nanoarchitectonics can be used as a low-cost multiple band detection areas. Cu2O/ZnO/GaN hierarchical nanoarchitectonics was synthesized using a solution process. The hierarchical nanoarchitectonics was assembled from in-situ etching and the growth Cu2O nanostructures on random distributed ZnO nanotubes/GaN film by hydrothermal process. The device demonstrated multiple wavelength photodetection. [ABSTRACT FROM AUTHOR]

Sensitivity analysis plays an important part in the validation of a sensor layout for the identification of the dynamic response of a system. Although sensitivity analysis has been implemented for this purpose in several civil engineering structures, there are still uncertainties in the case of more complex, nonlinear systems, such as guyed masts, where small changes in mass or stiffness can result in large variations of the general dynamic behavior. This paper describes the influence of antenna masses and initial guy tension variation in the total number and position of sensors required to assess the dynamic response of tall guyed mast telecommunication towers. For the study, the computational models of four different guyed masts were generated and a sensor layout was obtained for each model using a sensitivity analysis. Then, the proposed sensor layouts were verified for different initial guy tensions and total antenna mass of the system, by means of the Modal Assurance Criterion. The principal finding is that initial guy tension presents the highest influence on the variation of correspondence values between mode shapes, with modifications of these values in up to 9 8 %. This finding suggests that a preliminary sensor layout based on information provided by a computational model or structural drawings of a guyed mast may be rendered inefficient if there is variation in guy tension due to construction errors or relaxation of cables. [ABSTRACT FROM AUTHOR]

This paper designs a three-axis closed-loop fluxgate system for geophysical prospecting, which contains excitation, induction, and feedback circuits. By analyzing and comparing the noise levels before and after the system operation, it is concluded that the main factor affecting the fluxgate performance is the excitation circuit noise. By analyzing the principle of fluxgate, the noise on the induction signal and feedback signal can reduce the accuracy of fluxgate and even lead to system instability in serious cases. In this paper, a passive filter circuit is designed to reduce the noise associated with the fundamental frequency from the source to ensure stable operation and improved performance of the system. Simulation and experimental data show that after using the filter circuit, the secondary frequency noise level of the induction signal and the feedback signal noise level are reduced by 10 times, and the trend capturing capability under external magnetic field is greatly improved. [ABSTRACT FROM AUTHOR]

This paper proposes a high-performance framework for accurate multi-stage object detection in low-altitude based UAV images. The proposed system employs a cascade style architecture with increasing thresholds for achieving accurate detection. The framework makes use of highly efficient Feature Pyramid Networks (FPNs) to detect objects of small sizes, and various scales which are the main challenge in low-altitude aerial images. FPNs aim to resolve scale variation problems in object detection by combining features of multiple levels. The experiments have been performed on a complex low-altitude aerial dataset VisDrone which has multiple categories of classes. The FPN-Cascade detector has been supported by slicing the data horizontally and vertically that resulted in an advancement of 8% mAP when compared with the base detector. The experiments compare the FPN-Cascade performance on the standard as well as augmented VisDrone dataset. A concrete methodology about the training process, hyperparameter tuning, and performance evaluation methods for Cascade RCNN on the VisDrone dataset is highlighted. The proposed framework achieves state of the art 30.04% mAP value on the VisDrone dataset. [ABSTRACT FROM AUTHOR]

Efficiency of the piezoelectric chemisensors may be considerably enhanced by use of zinc oxide nanorods as sensing elements. ZnO nanorod arrays being good piezoelectric materials possess large surface area, which provides extra benefits for chemisorption and photodetection. Highly oriented nanorod arrays are typically prepared onto highly crystalline substrates, whereas the nanorods growth onto metal contacts meets significant technological difficulties. In this paper, we report on carbothermal, electrochemical, and hydrothermal techniques of ZnO nanorod arrays synthesis on metal contacts. The optical and structural properties of the obtained nanorods were studied using scanning electron microscopy, X-ray diffraction (XRD), Raman spectroscopy, and luminescence spectroscopy. A reliable technique was developed for obtaining ohmic contact with the grown nanorods. I–U curves of prepared contact were studied. Carbothermal synthesis made it possible to obtain the most crystallinely perfect, homogeneous, and dense arrays of nanorods and control the concentration of point defects by changing the synthesis parameters over a wide range. The electrochemical synthesis demonstrated excellent results for synthesis of ZnO nanorods on the surface of resonator electrodes. [ABSTRACT FROM AUTHOR]

The lifetime of battery-operated sensor platforms (i.e., sensor nodes) is a critical issue. The replacement of their batteries is quite a challenging task if these platforms are deployed for detecting events in inaccessible geographical areas (e.g., forest). This paper describes an optimized RF energy harvester/scavenger (consisting of an antenna, impedance matching circuit and rectifier) for energizing low-power sensor platforms (electronic systems). Few nonmatched rectifiers (using HSMS-285X Schottky diodes) are fabricated to characterize the input impedance for different sets of parameters. After characterization a proper impedance matching circuit is integrated for the maximum power transfer from antenna to rectifier. It is shown that a single stage of RF rectifier is enough to produce output voltage of 1.8 V. Very few realizations of RF energy harvester are reported in the literature under 2.4 GHz ISM band category. Furthermore, high-gain microstrip patch array antennas are fabricated to capture the maximum power from the surroundings. The maximum harvesting range of 0.92 m is obtained at 27 dBm transmitting power level. [ABSTRACT FROM AUTHOR]

In this paper, a four layer neuro-fuzzy architecture of multi-sensor fusion is developed for a fault diagnosis system which is applied to an industrial fish cutting machine. An important characteristic of the fault diagnosis approach developed in this paper is to make an accurate decision of the machine condition by fusing information acquired from three types of sensors: Accelerometer, microphone and charge-coupled device (CCD) camera. Feature vectors for vibration and sound signals from their fast Fourier transform (FFT) frequency spectra are defined and extracted from the acquired information. A feature-based vision method is applied for object tracking in the machine, to detect and track the fish moving on the conveyor. A four-layer neural network including a fuzzy hidden layer is developed in the paper to analyze and diagnose existing faults. Feature vectors of vibration, sound and vision are provided as inputs to the neuro-fuzzy network for fault detection and diagnosis. By proper training of the neural network using data samples for typical faults, six crucial faults in the fish cutting machine are detected with high reliability and robustness. On this basis, not only the condition of the machine can be determined for possible retuning and maintenance, but also alarms to warn about impending faults may be generated during the machine operation. [ABSTRACT FROM AUTHOR]

This paper studies a method for estimating the motion parameters { V , D , f 0 , t c } using the instantaneous frequency estimates of the acoustical signal emitted from a moving target in the air and received by an acoustic sensor placed on the ground. Here, V is the target's travel speed, D is the closest point of approach slant range, f 0 is the source acoustical frequency, and t c is the time at the target get to the closest point of approach to the sensor. A novel relationship formula between the instantaneous frequency and motion parameters is derived and an algorithm for estimating the motion parameters based on the solution of quadratic nonlinear optimization from the instantaneous frequency estimates is proposed. The instantaneous frequency is estimated by searching the peak of a polynomial Wigner–Ville distribution. An approach for calculating the optimal window width in a polynomial Wigner–Ville distribution is proposed. Numerical examples are provided for validating our theoretic claims. [ABSTRACT FROM AUTHOR]

Small infrared (IR) target detection is an important and challenging issue in IR target tracking system. In this paper, a patch ordering-based method is proposed for small IR target detection in an image with complicated background. Inspired by the contrast mechanism of human vision system, a patch ordering-based contrast measure (POCM) is designed to deal with the input image, which cannot only suppress the background noise and clutter but also enhance the targets significantly. In this way, POCM can increase the contrast ratio between target and background. This leads to higher Signal Clutter Ratio (SCR). Then the true target can be detected by applying simple adaptive thresholding method. The experimental results on two sequences show that the proposed method can efficiently detect small IR target from heavy clutter. [ABSTRACT FROM AUTHOR]

This paper presents a complete framework (estimation, identification and control) for the implementation of joint-torque control on the humanoid robot HRP-2. While torque control has already been implemented on a few humanoid robots, this is one of the first implementations of torque control on a robot that was originally built to be position controlled (iCub [F. Nori, S. Traversaro, J. Eljaik, F. Romano, A. Del Prete and D. Pucci, iCub whole-body control through force regulation on rigid non-coplanar contacts, Frontiers in Robotics and AI 2 (2015).] and Asimo [O. Khatib, P. Thaulad and J. Park, Torque-position transformer for task control of position controlled robots, 2008 IEEE Int. Conf. Robotics and Automation, May 2008, pp. 1729-1734.] being the first two, to the best of our knowledge). The challenge comes from both the hardware, which does not include joint-torque sensors and presents large friction due to the high-ratio gear boxes, and the software interface, which only accepts desired joint-angle commands (no motor current/voltage control). The contribution of the paper is to provide a complete methodology that is very likely to be reproduced as most robots are designed to provide only position control capabilities. Additionally, the method is validated by exhaustive experiments on one leg of the robot, including a comparison with the original position controller. We tested the torque controller in both motion control and cartesian force control. The torque control can track better a reference trajectory while using lower values for the feedback gains (up to 25%). Moreover, we verified the quality of the identified motor models by analyzing the contribution of the feedforward terms of our torque controller, which dominate the feedback terms. [ABSTRACT FROM AUTHOR]

Since the growth of single layer of Si has emerged, silicene became a potential candidate material to make up the disadvantage of graphene. In this paper, the complex surface conductivity is applied to characterize the properties of silicene and we investigate the optical characterization of silicene-dielectric interfaces from IR to far UV range. The silicene-Si and silicene-Ge interfaces along both parallel and perpendicular polarization directions of electromagnetic field with normal incidence are considered in this work. The optical properties of the silicene-dielectric systems proposed in this paper lay a foundation for the performance of complex silicene-based optoelectronic devices such as sensors, detectors, filters, UV absorbers and so on. [ABSTRACT FROM AUTHOR]