Large Interference Research Articles

Discrete interferences optimum beamformer in correlated signal and interfering noise

This paper introduces a significant special situation where the noise is a collection of D-plane interference signals and the correlated noise of D+1 is less than the number of array components. An optimal beamforming processor based on the minimum variance distortionless response (MVDR) generates and combines appropriate statistics for the D+1 model. Instead of the original space of the N-dimensional problem, the interference signal subspace is reduced to D+1. Typical antenna arrays in many modern communication networks absorb waves generated from multiple point sources. An analytical formula was derived to improve the signal to interference and noise ratio (SINR) obtained from the steering errors of the two beamformers. The proposed MVDR processor-based beamforming does not enforce general constraints. Therefore, it can also be used in systems where the steering vector is compromised by gain. Simulation results show that the output of the proposed beamformer based on the MVDR processor is usually close to the ideal state within a wide range of signal-to-noise ratio and signal-to-interference ratio. The MVDR processor-based beamformer has been experimentally evaluated. The proposed processor-based MVDR system significantly improves performance for large interference white noise ratio (INR) in the sidelobe region and provide an appropriate beam pattern.

Monitoring Respiratory Motion during VMAT Treatment Delivery Using Ultra-Wideband Radar.

The goal of this paper is to evaluate the potential of a low-cost, ultra-wideband radar system for detecting and monitoring respiratory motion during radiation therapy treatment delivery. Radar signals from breathing motion patterns simulated using a respiratory motion phantom were captured during volumetric modulated arc therapy (VMAT) delivery. Gantry motion causes strong interference affecting the quality of the extracted respiration motion signal. We developed an artificial neural network (ANN) model for recovering the breathing motion patterns. Next, automated classification into four classes of breathing amplitudes is performed, including no breathing, breath hold, free breathing and deep inspiration. Breathing motion patterns extracted from the radar signal are in excellent agreement with the reference data recorded by the respiratory motion phantom. The classification accuracy of simulated deep inspiration breath hold breathing was 94% under the worst case interference from gantry motion and linac operation. Ultra-wideband radar systems can achieve accurate breathing rate estimation in real-time during dynamic radiation delivery. This technology serves as a viable alternative to motion detection and respiratory gating systems based on surface detection, and is well-suited to dynamic radiation treatment techniques. Novelties of this work include detection of the breathing signal using radar during strong interference from simultaneous gantry motion, and using ANN to perform adaptive signal processing to recover breathing signal from large interference signals in real time.

Study of green surface-enhanced Raman spectroscopy determination of methanol in alcoholic beverages

There are two main challenges in completing surface-enhanced Raman spectroscopy (SERS) detection. One is the small Raman scattering cross-section of methanol, and the other is the derivatization strategy. They were solved by coupling the catalytic strategy with a thermal purge separation and enrichment device. In this study, quantitative analysis of methanol in alcoholic beverages was performed as methanol was catalyzed to formaldehyde. For detecting methanol in low-alcohol beverages, the acetaldehyde derivatives generated by the interaction of ethanol-catalyzed oxide acetaldehyde with 3-methyl 2-benzothiazolinone hydrazone hydrochloride hydrate (MBTH) during the catalytic process will not cause large interference with the SERS signal of formaldehyde. In this case, MBTH with higher sensitivity is selected for the derivatization operation. In the analysis of methanol in high-alcohol beverages, acetylacetonate derivatization without interaction with acetaldehyde was used to avoid the interference of the acetaldehyde generated from ethanol. Based on the detection of formaldehyde in methanol standard solutions, methanol was detected in wine and sake as well as in high-alcohol beverages. Thus, a convenient and rapid method was achieved for the detection of methanol in alcoholic beverages.

True differential superconducting on-chip output amplifier *

The true-differential superconductor on-chip amplifier has complementary outputs that float with respect to chip ground. This improves signal integrity and compatibility with the receiving semiconductor stage. Both source-terminated and non-source-terminated designs producing 4 mV demonstrated rejection of a large common mode interference in the package. Measured margins are ±8.5% on the output bias, and ±28% on AC clock amplitude. Waveforms and eye diagrams are taken at 2.9–10 Gb . Direct measurement of bit-error rates are better than the resolution limit of at 2.9 Gb , and better than at 10 Gb .

Modeling and Performance Analysis in UAV-Assisted Cellular Networks with Clustered Edge Users

A UAV-assisted cellular network can provide ubiquitous links to everything and it is considered to be one of the key technologies for 6G wireless networks. In this paper, we consider an uplink wireless network with a macrobase station (MBS) and cellular users. However, the coverage equality of edge users cannot be guaranteed in scenarios where data service is dense. Specifically, a novel topology of the UAV-assisted wireless network is considered. UAVs are deployed upon the cell edge to serve edge users with poor communication quality. To avoid larger interference caused by users and UAVs in the overlapping area, the locations of these UAVs are modeled as a homogeneous Poisson point process (HPPP) under the Poisson cluster distance constraint (PCDC). In addition, we assume that edge users cluster around each UAV and model their locations as Poisson cluster processes (PCPs). Initially, the Laplace transforms of intra-cluster interference, inter-cluster interference, and other interference are derived. Subsequently, coverage probability and area spectrum efficiency are derived for UAVs and MBS using tools from stochastic geometry. Moreover, the energy efficiency of the system is obtained. Simulation results are examined to validate the accuracy of theoretical analysis and provide insights into the effects of the system parameters as well as useful guidelines for practical system design.

Highly efficient fingerprint detection from cation-anion doping Sr3-xBaxAlO4F1-zClz: yTb3+ anti-perovskite phosphor

Latent fingerprint (LFP) detection has become an essential component of criminal investigation because fingerprint has the characteristics of great difference and invariability. Nowadays, powder dusting method is favored to visualize LFP due to its environmental friendliness. However, serious shortcomings, such as low resolution, low sensitivity, and large background interference, of this method immensely limit its applications. To address these issues, we proposed a cation-anion units co-doping strategy from Sr3-xBaxAlO4F1-zClz: yTb3+ anti-perovskite phosphors with the emission of ∼555 nm under ultraviolet C (UVC, 265 nm) excitation by the high-temperature solid-state method. Besides, the corresponding structural phase, luminescent properties, decay curves, and resistance of color shift under various temperatures are systematically investigated. The result indicates that cation-anion modulation can significantly improve the photoluminescence (PL) intensity under UVC excitation, and then contribute to obvious suppression of background interference of substrate for fingerprint detection. Surprisingly, the optimized Sr2.6Ba0.4AlO4F0.9Cl0.1:3%Tb3+ phosphor shows a very high color shift resistance from 300 to 420 K. Because of the foregoing, Sr2.6Ba0.4AlO4F0.9Cl0.1:3%Tb3+ phosphor overcomes the above-mentioned shortcomings and exhibits good potential for high resolution and high sensitivity LFP detection.

Quantitative Evaluation for Magnetoelectric Sensor Systems in Biomagnetic Diagnostics.

Dedicated research is currently being conducted on novel thin film magnetoelectric (ME) sensor concepts for medical applications. These concepts enable a contactless magnetic signal acquisition in the presence of large interference fields such as the magnetic field of the Earth and are operational at room temperature. As more and more different ME sensor concepts are accessible to medical applications, the need for comparative quality metrics significantly arises. For a medical application, both the specification of the sensor itself and the specification of the readout scheme must be considered. Therefore, from a medical user’s perspective, a system consideration is better suited to specific quantitative measures that consider the sensor readout scheme as well. The corresponding sensor system evaluation should be performed in reproducible measurement conditions (e.g., magnetically, electrically and acoustically shielded environment). Within this contribution, an ME sensor system evaluation scheme will be described and discussed. The quantitative measures will be determined exemplarily for two ME sensors: a resonant ME sensor and an electrically modulated ME sensor. In addition, an application-related signal evaluation scheme will be introduced and exemplified for cardiovascular application. The utilized prototype signal is based on a magnetocardiogram (MCG), which was recorded with a superconducting quantum-interference device. As a potential figure of merit for a quantitative signal assessment, an application specific capacity (ASC) is introduced. In conclusion, this contribution highlights metrics for the quantitative characterization of ME sensor systems and their resulting output signals in biomagnetism. Finally, different ASC values and signal-to-noise ratios (SNRs) could be clearly presented for the resonant ME sensor (SNR: dB, ASC: dB Hz) and also the electrically modulated ME sensor (SNR: dB, ASC: 23 dB Hz), showing that the electrically modulated ME sensor is better suited for a possible MCG application under ideal conditions. The presented approach is transferable to other magnetic sensors and applications.

Joint Waveform and Discrete Phase Shift Design for RIS-Assisted Integrated Sensing and Communication System Under Cramer-Rao Bound Constraint

Integrated sensing and communication (ISAC) technique has been viewed as a promising component in future network. A major challenge for ISAC systems is that the constraint introduced by sensing functionality will constrain the degrees of freedom in waveform design and results in large multi-user interference (MUI), thus degrading the communication performance. In this paper, we study the employment of RIS in mitigating MUI in ISAC systems. For practical consideration, we investigate joint constant-modulus waveform and discrete RIS phase shift design, with the aim of minimizing MUI under the Cramer-Rao bound (CRB) constraint for direction of arrival (DOA) estimation. An alternating optimization algorithm is proposed to solve the formulated problem, and two schemes are proposed to deal with the discrete RIS phase shifts. Simulation results show that the proposed algorithm can dramatically improve the sum rate, and the performance under moderate phase shift quantization level is close to that under continuous phase shifts.

ЗАЗЕМЛЕНИЕ КАК МЕТОД СНИЖЕНИЯ ЭЛЕКТРОМАГНИТНЫХ ПОМЕХ В ПОЛЕВЫХ МОБИЛЬНЫХ КОМПЛЕКСАХ

The article considers grounding as one of the design and technological methods for reducing the electromagnetic compatibility of radio engineering devices in field mobile HF communication complexes, lists interference that can be minimized by grounding, and describes measures that allow organizing an effective grounding system. By grounding, it is possible to provide a constant level of potentials, minimize parasitic connections, divert large interference currents into the ground, and improving the electromagnetic environment of the field mobile complex as a whole.

Research on the integrated manipulator of point cloud measurement and precise cutting for waste nuclear tank

PurposeNuclear waste tanks need to be cut into pieces before they can be safely disposed of, but the cutting process produces a large amount of aerosols with radiation, which is very harmful to the health of the operator. The purpose of this paper is to establish an intelligent strategy for an integrated robot designed for measurement and cutting, which can accurately identify and cut unknown nuclear waste tanks and realize autonomous precise processing.Design/methodology/approachA robot system integrating point cloud measurement and plasma cutting is designed in this paper. First, accurate calibration methods for the robot, tool and hand-eye system are established. Second, for eliminating the extremely scattered point cloud caused by metal surface refraction, an omnidirectional octree data structure with 26 vectors is proposed to extract the point cloud model more accurately. Then, a minimum bounding box is calculated for limiting the local area to be cut, the local three-dimensional shape of the nuclear tank is fitted within the bounding box, in which the cutting trajectories and normal vectors are planned accurately.FindingsThe cutting precision is verified by changing the tool into a dial indicator in the simulation and the experiment process. The octree data structure with omnidirectional pointing vectors can effectively improve the filtering accuracy of the scattered point cloud. The point cloud filter algorithm combined with the structure calibration methods for the integrated measurement and processing system can ensure the final machining accuracy of the robot.Originality/valueAiming at the problems of large measurement noise interference, complex transformations between coordinate systems and difficult accuracy guarantee, this paper proposes structure calibration, point cloud filtering and point cloud-based planning algorithm, which can greatly improve the reliability and accuracy of the system. Simulation and experiment verify the final cutting accuracy of the whole system.

Combinational Fusion and Global Attention of the Single-Shot Method for Synthetic Aperture Radar Ship Detection

Synthetic Aperture Radar (SAR), an active remote sensing imaging radar technology, has certain surface penetration ability and can work all day and in all weather conditions. It is widely applied in ship detection to quickly collect ship information on the ocean surface from SAR images. However, the ship SAR images are often blurred, have large noise interference, and contain more small targets, which pose challenges to popular one-stage detectors, such as the single-shot multi-box detector (SSD). We designed a novel network structure, a combinational fusion SSD (CF-SSD), based on the framework of the original SSD, to solve these problems. It mainly includes three blocks, namely a combinational fusion (CF) block, a global attention module (GAM), and a mixed loss function block, to significantly improve the detection accuracy of SAR images and remote sensing images and maintain a fast inference speed. The CF block equips every feature map with the ability to detect objects of all sizes at different levels and forms a consistent and powerful detection structure to learn more useful information for SAR features. The GAM block produces attention weights and considers the channel attention information of various scale feature information or cross-layer maps so that it can obtain better feature representations from the global perspective. The mixed loss function block can better learn the positions of the truth anchor boxes by considering corner and center coordinates simultaneously. CF-SSD can effectively extract and fuse the features, avoid the loss of small or blurred object information, and precisely locate the object position from SAR images. We conducted experiments on the SAR ship dataset SSDD, and achieved a 90.3% mAP and fast inference speed close to that of the original SSD. We also tested our model on the remote sensing dataset NWPU VHR-10 and the common dataset VOC2007. The experimental results indicate that our proposed model simultaneously achieves excellent detection performance and high efficiency.

It is not always positive: emotional bias in young and older adults.

Healthy ageing has been associated with a bias toward positive information and greater psychological well-being. However, to what extent this positivity bias also applies to prioritizing positive information under emotional competition is unclear. Old and young adults performed a word-face interference task, in which they responded to the valence of positive and negative target-words while ignoring happy or angry distractor-faces that could be affectively congruent or incongruent. A control condition with scrambled neutral distractor-faces was also used. Findings showed small facilitation effects with faster responses when targets and distractors were affectively congruent and large interference effects with slower responses when targets and distractors were affectively incongruent compared to the control condition. Importantly, whereas for younger adults there was a similar pattern of interference from happy and angry distractor-faces, for older adults there was greater interference from angry distractor-faces. The present findings are discussed in the context of emotional bias literature.

Causes, the impact of stress and ways of dealing with the stress of subject teachers in primary school and the role of professional associate pedagogue

The paper deals with the problem of teacher stress and teachers' attitudes towards stress exposure. The aim of the research was to examine the sources of stress in primary school teachers, the ways in which they deal with stress, and how stress affects them. Also, this research aimed to reveal the opinion of the respondents about the professional associate - pedagogue and how he/she can help them in some segments of work. The research was conducted on a sample of 346 subject teachers in primary school. The results were processed using the SPSS program using descriptive and inferential statistics procedures (t-test for independent samples and correlation analysis). The results of the research shows that teachers believe that underestimation in society is the biggest source of stress (AS = 4.1). They also point out to a large extent political interference (AS = 3.88), injustice in employment (AS = 3.76), and insufficient rewarding of excellence (AS = 3.74). Research has also shown that stress has the greatest impact on teacher health (AS = 3.03). As for coping techniques, they answered that they do not blame themselves for everything that happens at school (AS = 3.73) and that they set a time for rest (AS = 3.55). When it comes to issues related to the professional associate - pedagogue, most respondents believe that the pedagogue should deal more with students and less with administration (AS = 4.2). T-test for independent samples revealed statistically significant differences in student disobedience and classroom discipline (p <0.001) and parents' treatment of teachers (p <0.01) with respect to age. The results of the research show that many factors affect teachers' stress, from society, parents to classroom work, and such a situation significantly affects teachers. Emphasis on the care and satisfaction of workers should be an imperative of every job, including teaching, and it should go from the school level, where it would be more dedicated to cooperation and respect, to external associates who would help teachers to the state that would change its approach to education.

A 32-Channel Time-Multiplexed Artifact-Aware Neural Recording System.

This paper presents a low-power, low-noise microsystem for the recording of neural local field potentials or intracranial electroencephalographic signals. It features 32 time-multiplexed channels at the electrode interface and offers the possibility to spatially delta encode data to take advantage of the large correlation of signals captured from nearby channels. The circuit also implements a mixed-signal voltage-triggered auto-ranging algorithm which allows to attenuate large interferers in digital domain while preserving neural information. This effectively increases the system dynamic range and avoids the onset of saturation. A prototype, fabricated in a standard 180 nm CMOS process, has been experimentally verified in-vitro with cellular cultures of primary cortical neurons from mice. The system shows an integrated input-referred noise in the 0.5-200 Hz band of 1.4 μVrms for a spot noise of about 85 nV /√{Hz}. The system draws 1.5 μW per channel from 1.2 V supply and obtains 71 dB + 26 dB dynamic range when the artifact-aware auto-ranging mechanism is enabled, without penalising other critical specifications such as crosstalk between channels or common-mode and power supply rejection ratios.

Development of a Portable Chronic Non-specific Low Back Pain Measurement System

We developed a portable non-specific low back pain measurement system EasiLBP and evaluated its performance in collecting EMG signals:during the wearer's movement without the assistance of a doctor, the collection of EMG signals by portable devices met problems such as large noise interference, difficulty in accurately calibrating the start and end points of the action interval, and imbalanced samples for feature recognition, et al. To challenge these problems, we proposed a small group-based noise removal method, a dynamic dual-threshold automatic method for identifying the start and end points of the motion interval, and a sampling method to balance group samples, respectively. Portable device and a medical EMG acquisition equipment Thought Technology FlexComp Infiniti 10 were used to perform EMG measurements on 15 patients with non-specific low back pain and 15 normal people. Clinical experiments and statistical analysis show that the portable EMG acquisition system has significant differences in EMG signal characteristics between normal people and non-specific low back pain patients, and it has good measurement consistency and accuracy with the medical EMG acquisition equipment.

VitaSi: A real-time contactless vital signs estimation system

The non-contact monitoring of vital signs, especially the Heart Rate (HR) and Breathing Rate (BR), using facial video is becoming increasingly important. Although, researchers have made considerable progress in the past few years, there are still some limitations to the technology, such as the lack of challenging datasets, the time consuming nature of the estimation process, and non-portability of the system. In this paper, we proposed a new framework for estimating HRs and BRs by combining a Convolutional Neural Network (CNN) with the Phase-based Video Motion Processing (PVMP) algorithm. The experimental results show that our approach achieves better performance. Meanwhile, we introduce a new challenging dataset with fewer constraints, such as large movements, facial expressions and light interference. In addition, we developed a new Android application, which works in real time and offline, based on a CNN for HR and BR estimations.

Hybrid active contour model driven by optimized local pre-fitting image energy for fast image segmentation

In this paper, the hybrid active contour model driven by optimized local pre-fitting image (OLPFI) energy was proposed for fast image segmentation. Since the proposed model combines the local pre-fitted image (LPFI) function with region-based characteristic and the optimized edge indicator function with edge-based characteristic, the proposed model can not only correctly segment images with intensity inhomogeneity or weak boundaries, but also can deal with images whose target has large noise interference inside. The two pre-fitting functions are computed before curve evolution, so the computational cost of the proposed model reduces greatly. Furthermore, the evolution curve can adaptively select the motion direction according to image information because of energy sign function. Regularized function used in the proposed model can accelerate the segmentation speed of the proposed model. Moreover, the addition of the regularization term and length term helps to improve segmentation efficiency of the proposed model and eliminate the effect of sensitive parameters in traditional penalty and length terms. Experimental results show that the proposed model has great efficiency in segmenting images and great robustness on initialization and parameters.

Trajectory tracking control of quadrotor under variable payloads with model-free controller and sliding mode control technology

Purpose This study aims to deal with the problem of trajectory tracking control for the quadrotor under external environmental disturbance and variable payloads. Design/methodology/approach In the field of unmanned aerial vehicle (UAV) control, external environmental disturbance and internal variable payloads as two major interference factors lead to control performance degradation or even instability, thus a trajectory tracking controller which innovatively combines sliding mode control technology and model-free control technique is proposed. The proposed controller is constructed with a learning rate-based sliding mode controller and an ultra-local model. Based on the proposed controller, the nonlinear system model of variable load quadrotor is locally estimated and the system’s uncertainties and disturbances can be compensated. Findings The simulation and actual test results demonstrate the satisfactory control performance and the robustness of the proposed controller compared with the PID and Backstepping controller under external environmental disturbance and variable payloads. Moreover, the proposed controller solves the trajectory tracking control problem not only when payloads change at the center of gravity but also when the position of load variation deviates from the center of gravity. Practical implications In both military and civilian domains, the quadrotor may encounter such situations that the payloads change, such as transporting goods, aerial refueling and so on. As a large internal interference factor, variable load tends to lead to unstable control. The research results provide theoretical guidance and technical support for trajectory tracking control of quadrotor under variable payloads. Originality/value The proposed controller combines learning rate-based sliding mode controller and model-free control technique to achieve a more efficient and accurate trajectory control of the quadrotor when considering system uncertainties and the load variation that happens in the unknown location.

850-nm VCSEL-Based Single-Lane 200-Gbps PAM-4 Transmission for Datacenter Intra-Connections

A demonstration of an 850-nm vertical cavity surface emitting laser (VCSEL) based 200-Gb/s PAM-4 transmission over 100-m OM4 multimode fiber (MMF) is presented. To overcome the large Inter-symbol Interference (ISI) caused by bandwidth limitation and to compensate the non-linearity caused by optics, we propose to combine noise cancellation algorithm, partial response signaling and simplified Volterra nonlinear equalizer (NLE) in the digital signal processing (DSP). A power margin about 4 dB for 50-m MMF transmission and 3 dB for 100-m MMF transmission is observed. Different DSP configurations are also experimentally evaluated. The use of the simplified Volterra NLE enables the BER to be improved from 2×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">- 2</sup> to 1.1×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">- 3</sup> . A 2.5 dB power margin improvement is also achieved by employing the noise cancellation module.

Single production of vector-like quarks: the effects of large width, interference and NLO corrections

We provide a comprehensive discussion, together with a complete setup for simulations, relevant for the production of a single vector-like quark at hadron colliders. Our predictions include finite width effects, signal-background interference effects and next-to-leading order QCD corrections. We explicitly apply the framework to study the single production of a vector-like quark T with charge 2/3, but the same procedure can be used to analyse the single production of vector-like quarks with charge −4/3, −1/3, 2/3 and 5/3, when the vector-like quark interacts with the Standard Model quarks and electroweak bosons. Moreover, this procedure can be straightforwardly extended to include additional interactions with exotic particles. We provide quantitative results for representative benchmark scenarios characterised by the T mass and width, and we determine the role of the interference terms for a range of masses and widths of phenomenological significance. We additionally describe in detail, both analytically and numerically, a striking feature in the invariant mass distribution appearing only in the T → th channel.