Unwanted Signals Research Articles

Robust Chipless RFID Detection Using Complex Natural Frequency Along With the k-Nearest Neighbor Algorithm

This paper proposes a detection technique for the chipless RFID system. In the proposed technique, the experiments for measuring the scattering responses of all possible tags were conducted first in a free-space anechoic chamber in order to avoid the effect of unwanted signals due to the environment. The responses of all possible tags were exploited in order to extract poles, including natural frequencies and damping factors, by using the short-time matrix pencil method. All extracted poles successively chosen from the late-time portions were exploited to create the decision boundary by using the k- nearest neighbor algorithm. In order to validate the robustness of the proposed detection technique, experiments with the chipless RFID system with tags attached to containers, i.e. parcel and plastic boxes, were conducted. Poles extracted from the response of the tag attached to a container were fed to the decision boundary for ID detection. The poles that had fallen into the region labeled as logic “1” were detected as logic “1,” and vice versa . The experiment results showed that the attachment of the tags to the containers caused a change in the poles. The conventional technique using only natural frequencies has exhibited poor performance regarding tag ID detection. On the other hand, the proposed detection technique achieved a 100% detection rate, although the extracted poles used to detect the bit logic were disturbed by the container. The experimental results confirm the superiority of the proposed system over conventional chipless RFID detection. Moreover, the proposed technique can be considered a robust detection technique.

Elliptically Bended Hybrid Ring Coupler

In this paper, a size reduced elliptically bended hybrid ring coupler is proposed with better directivity, isolation factor, coupling factor, better impedance matching and undesired signal suppression for wideband applications. The proposed elliptically bended compact hybrid coupler is desired to operate at 1.8 GHz providing wide bandwidth, better return loss, and isolation with less insertion loss where a novel gradual impedance bending technique is implemented to suppress unwanted signals.

Wavefront shaping with a tunable metasurface: Creating cold spots and coherent perfect absorption at arbitrary frequencies

Modern electronic systems operate in complex electromagnetic environments and must handle noise and unwanted coupling. The capability to isolate or reject unwanted signals for mitigating vulnerabilities is critical in any practical application. In this work, we describe the use of a binary programmable metasurface to (i) control the spatial degrees of freedom for waves propagating inside an electromagnetic cavity and demonstrate the ability to create nulls in the transmission coefficient between selected ports; and (ii) create the conditions for coherent perfect absorption. Both objectives are performed at arbitrary frequencies. In the first case a novel and effective optimization algorithm is presented that selectively generates coldspots over a single frequency band or simultaneously over multiple frequency bands. We show that this algorithm is successful with multiple input port configurations and varying optimization bandwidths. In the second case we establish how this technique can be used to establish a multi-port coherent perfect absorption state for the cavity.

Time-resolved polarization lock-in filtering for background suppression in Raman spectroscopy of biomass pyrolysis

Laser-based Raman spectroscopy is a powerful technique for non-intrusive measurements of chemical composition in gas, liquid, and solids. However, weak signals make it challenging to employ the technique for diagnostics under harsh conditions with various background interferences. To overcome such limitations, we have devised a method, polarization lock-in filtering (PLF) based on temporal modulation of the excitation laser polarization, to filter out polarization-independent signals from acquired data. The PLF method applied for continuous Raman spectroscopy measurements of a biomass pyrolysis process showed promising filtering abilities for unwanted background fluorescence signals. A broadband fluorescence background interference was suppressed by up to a factor of 50. Therefore, released species during the biomass pyrolysis process were readily identified with their Raman spectrum signatures and their amounts quantified. In addition, the PLF method provided Raman spectra of low background, from which a gradual change in hydrocarbons released at different stages during the pyrolysis could be observed. Altogether, the efficient background suppression method increases the general applicability of Raman spectroscopy under conditions where interfering signals present a challenge and a limiting factor.

Event-driven tool condition monitoring methodology considering tool life prediction based on industrial internet

Tool condition monitoring (TCM) and remaining useful life (RUL) prediction is of great practical significance for any machining process to ensure machining quality and reduce the machine tool downtime. At the standpoint of workshop management, the current TCM has two drawbacks. (i) Continuously acquiring data without distinguishing the working states of the machine tool and the machining tasks will inevitably bring a large volume of unwanted signals, making difficulty for tool RUL prediction. (ii) The tool condition is independent of machining task, thus cannot provide further decision-making support for workshop scheduling and machining parameters optimization. Therefore, it is an important issue to consider various random events under the right machining tasks to trigger “monitoring” and RUL prediction just in time. This paper proposes an event-driven tool condition monitoring (EDTCM) methodology. The structure of EDTCM is designed based on the architecture of the Industrial Internet. Multi-source events are collected under the architecture, including MES events, machine tool events based on the OPC-UA (OPC Unified Architecture) standard, smart mobile terminal events, etc. The event-driven mode is designed to process these events such that the “monitoring” is triggered just in time. Then the Tool RUL is predicted online with the monitored sensor data based on the Bayesian method. A prototype system of EDTCM is developed and a case study is implemented to verify the feasibility of the proposed methodology. Our work promotes that the theories of TCM and tool RUL prediction deeply integrate with the real industrial practical applications.

Modified tamarind kernel polysaccharide-based matrix alters neuro-keratinocyte cross-talk and serves as a suitable scaffold for skin tissue engineering

Advanced technologies like skin tissue engineering are requisite of various disorders where artificially synthesized materials need to be used as a scaffold in vivo, which in turn can allow the formation of functional skin and epidermal layer with all biological sensory functions. In this work, we present a set of hydrogels which have been synthesized by the method utilizing radical polymerization of a natural polymer extracted from kernel of Tamarindus indica, commonly known as Tamarind Kernel Powder (TKP) modified by utilizing the monomer acrylic acid (AA) in different mole ratios. These materials are termed as TKP: AA hydrogels and characterized by Atomic Force Microscopy (AFM), surface charge, and particle size distribution using Dynamic Light Scattering measurements. These materials are biocompatible with mouse dermal fibroblasts (NIH- 3T3) and human skin keratinocytes (HaCaT), as confirmed by MTT and biocompatibility assays. These TKP: AA hydrogels do not induce unwanted ROS signaling as confirmed by mitochondrial functionality determined by DCFDA staining, Mitosox imaging, and measuring the ATP levels. We demonstrate that in the co-culture system, TKP: AA allows the establishment of proper neuro-keratinocyte contact formation, suggesting that this hydrogel can be suitable for developing skin with sensory functions. Skin corrosion analysis on SD rats confirms that TKP: AA is appropriate for in vivo applications as well. This is further confirmed by in vivo compatibility and toxicity studies, including hemocompatibility and histopathology of liver and kidney upon direct introduction of hydrogel into the body. We propose that TKP: AA (1: 5) offers a suitable surface for skin tissue engineering with sensory functions applicable in vitro, in vivo, and ex vivo. These findings may have broad biomedical and clinical importance.

Methods for removal of artifacts from EEG signal: A review

Electroencephalogram (EEG)is the record of cerebral activity, the electric potential of cerebral activity is of low amplitude, and less frequency ranges between 4 to 60 Hz, which can easily mix up different non-cerebral signals and other environmental noise signals. The extraction of actual cerebral signals from the contaminated EEG signal is the major challenge in medical analysis. Somehow, during the recording of the EEG signal, contamination of other signals takes place, which increases complexity in analyzing the accurate EEG signal. This leads to inaccurate information signals in the analysis. Accordingly, the process to eliminate the unwanted signals in the pre-processing level is mandatory in brain signal analysis. The unwanted signals from various sources are together termed as artifacts; the researchers have implemented various techniques to reduce the undesired signals. However, still, there is no standard technique in detecting and eliminating the artifacts, and hence, the research became most challenging.

Improving classification performance of four class FNIRS-BCI using Mel Frequency Cepstral Coefficients (MFCC)

Experimentation and analysis of Functional near-infrared spectroscopy (fNIRS) in Brain-Computer Interface (BCI) has increasingly been studied as a communication possibility for patients who are severely paralyzed. This study has applied this technique to distinguish brain activities during four different mental tasks. These tasks include Mental Arithmetic (MA), Motor Imagery of Left-Hand (LHMI) and Right-Hand (RHMI) and Rest. fNIRS data used is from an open access dataset of 29 individuals which was collected by Continuous-wave imaging system (NIR Scout). In this research Data integration is performed before the data is preprocessed. Usual preprocessing is done using Butterworth filter to minimize or eliminate any unwanted signal distortion. After that an extensive signal analysis is done in which six different statistical features (Signal Mean (SM), Skewness (SK), Kurtosis (KR), Standard Deviation (SD), Signal Peak (SP), and Signal Variance (SV)) are obtained in the time domain and 13 Mel Frequency Cepstral Coefficients (MFCC) features are obtained from the frequency domain. As per literature review, MFCC has never been used as feature towards classification of fNIRS signal, which is a novel contribution towards this study. Separate Classification analysis is performed on each domain features. We were able to compare, differentiate and distinguish the brain signal activities captured while performing four different tasks using three different classifiers i.e. Linear Discriminant Analysis (LDA), Support Vector Machine (SVM) and K Nearest Neighbor (KNN). The average classification accuracy of 90.54% is achieved from K Nearest Neighbors (KNN) using the time domain features and accuracy achieved from Support Vector Machine (SVM) using the frequency domain features is 95.7%. Comparison with benchmark study shows the efficiency of MFCC as suitable features for improved classification accuracy.

1-Tx/5-Rx Through-Wall UWB Switched-Antenna-Array Radar for Detecting Stationary Humans.

This research proposes a through-wall S-band ultra-wideband (UWB) switched-antenna-array radar scheme for detection of stationary human subjects from respiration. The proposed antenna-array radar consists of one transmitting (Tx) and five receiving antennas (Rx). The Tx and Rx antennas are of Vivaldi type with high antenna gain (10 dBi) and narrow-angle directivity. The S-band frequency (2–4 GHz) is capable of penetrating non-metal solid objects and detecting human respiration behind a solid wall. Under the proposed radar scheme, the reflected signals are algorithmically preprocessed and filtered to remove unwanted signals, and 3D signal array is converted into 2D array using statistical variance. The images are reconstructed using back-projection algorithm prior to Sinc-filtered refinement. To validate the detection performance of the through-wall UWB radar scheme, simulations are carried out and experiments performed with single and multiple real stationary human subjects and a mannequin behind the concrete wall. Although the proposed method is an odd concept, the interest of this paper is applying the 1-Tx/5-Rx UWB switched-antenna array radar with the proposed method that is capable of distinguishing between the human subjects and the mannequin behind the concrete wall.

Pulse-shaped chopping: Eliminating and characterizing heat effects in ultrafast infrared spectroscopy.

The infrared pulses used to generate nonlinear signals from a vibrational probe can cause heating via solvent absorption. Solvent absorption followed by rapid vibrational relaxation produces unwanted heat signals by creating spectral shifts of the solvent and probe absorptions. The signals are often isolated by "chopping," i.e., alternately blocking one of the incident pulses. This method is standard in pump-probe transient absorption experiments. As less heat is deposited into the sample when an incident pulse is blocked, the heat-induced spectral shifts give rise to artificial signals. Here, we demonstrate a new method that eliminates heat induced signals using pulse shaping to control pulse spectra. This method is useful if the absorption spectrum of the vibrational probe is narrow compared to the laser bandwidth. By using a pulse shaper to selectively eliminate only frequencies of light resonant with the probe absorption during the "off" shot, part of the pulse energy, and the resulting heat, is delivered to the solvent without generating the nonlinear signal. This partial heating reduces the difference heat signal between the on and off shots. The remaining solvent heat signal can be eliminated by reducing the wings of the on shot spectrum while still resonantly exciting the probe; the heat deposition from the on shot can be matched with that from the off shot, eliminating the solvent heat contribution to the signal. Modification of the pulse sequence makes it possible to measure only the heat signal, permitting the kinetics of heating to be studied.

A review on recent near infrared spectroscopic measurement setups and their challenges

Despite near infrared spectroscopy (NIRS) has been studied as an alternative measurement approach in various applications, NIRS measurement setup that used in most of studies is ambiguous. Thus, this study aims to review the measurement setup of different near infrared spectroscopic (NIRS) acquisition modes with respect to different types of instrumentation and samples, and to classify them systematically. The relationship among different reported acquisition modes was analysed. Different reported acquisition modes were classified based on the position of instruments in acquiring near infrared signals. A detailed analysis is provided to highlight the distinction of different NIRS acquisition modes. The challenges of existing measurement setups have been discussed. Interaction and diffuse reflection are the same because both measure diffuse signals that reflected from the inner parts of a sample. Finding shows that future NIRS investigation should address the concerns that related to the acquisition modes, unwanted signals, and measurement parameters.

A Noise Suppression Filter for Molecular Communication via Diffusion

Molecular communication via diffusion (MCvD) is one of the most feasible communication paradigms for nanonetworks, especially for bio-nanonetworks in water-rich biological environments. Noise is an unwanted signal that severely limits the receiver’s ability to detect the wanted signal. The dominant noise in MCvD is counting noise, which is much different from traditional communication paradigms. However, noise suppression in MCvD has not been explicitly investigated. Therefore, it is necessary to propose a practical noise-suppression approach to diminish the impact of noise in MCvD. In this letter, we propose a simple but effective noise-suppression filter for MCvD, the I-filter. Moreover, the proposed noise-suppression filter has low computational complexity. Our work shows that the proposed filter performs much better than current noise-suppression approaches, the moving average algorithm, in the state-of-the-art detection schemes in terms of bit error rate (BER) performance in the severe noise scenarios.

Controlling the Effects of External Perturbations on a Gene Regulatory Network Using Proportional-Integral-Derivative Controller.

Gene regulatory networks are biologically robust, which imparts resilience to living systems against most external perturbations affecting them. However, there is a limit to this and disturbances beyond this limit can impart unwanted signalling on one or more master regulators in a network. Certain disturbances may affect the functioning of other constituent genes of the same network. In most cases, this phenomenon can have some effect on the functioning of the living organism. In this investigation, we have proposed a methodology to mitigate the effects of external perturbations on a genetic network using a proportional-integral-derivative controller. The proposed controller has been used to perturb one or more of the other unaffected master regulators such that the most affected gene/s of the network revert to their normal state. The only required condition of such type of manoeuvring is that there should be multiple master regulators in a network. The proposed technique has been experimented on a 10-gene DREAM4 benchmark network and also on a larger 20-gene network, where only downregulation has been considered due to data constraints. Simulation results indicate that the most vulnerable genes can be reverted to their normal expression levels in 10 out of the 16 simulations performed.

Classification and analysis of cardiac arrhythmia based on incremental support vector regression on IOT platform

The electrocardiogram (ECG) is a diagnostic device capable of monitoring normal or irregular heart function. The entire ECG beat can be categorized into five different forms of beat arrhythmias (N, S, V, F, U). Quick and precise diagnosis of forms of arrhythmia is critical for identifying the heart problem and provides the proper treatment to the patient. In this paper, Discrete Wavelet Transform and Higher Order Statistics techniques has been used for analyzing and determining the ECG signals and implement it on an IOT-based platform. This system is based on three categories: The first approach involves inputting the ECG data; the second approach involves extracting the ECG beats with their respective amplitude from the base line. Wavelet transform function, and higher order statistics are used to eliminate noise and unwanted signal components and thus to extract ECG features. The third approach is to classify the ECG beats based on the Incremental Support vector regression classifier. After classification ECG beat is transmitted to the controller section for signal processing are given to controller section (Arduino Uno). The process can be implemented by employing the statistical feature for the feature extraction from the ECG signal. Compared to other approaches, the method provided by Incremental Support vector regression to identify the ECG beats and predict arrhythmia can provide successful detection of arrhythmias. The basic concept of the proposed system is to provide patients with reliable health care by using cloud data compliance to allow doctors to use this information and to provide a fast and feasible service. The findings show that the proposed algorithm is successful in predicting cardiac arrhythmias, with a 98% that is higher than other approaches.

Beamforming and combining for multi‐user large MIMO communication system

A beamforming and combining method for a multi-user large multiple-input multiple-output (MIMO) system is proposed, in this study. A transmitter is equipped with a very large number of antennas to serve many users. At the transmitter, a group of antennas is allocated to each user. For a particular group of antennas, a specific beamforming vector is employed at the transmitter for transmission of a signal of a specific user. At the user end, a distinct combining vector is utilised for detecting the transmitted signal. In the proposed scheme, first, the interference due to unwanted signals of undesired users is nullified by using the concept of null space. Then the method of maximum ratio transmission is used to calculate the beamforming vector. The calculation of combining vector depends upon the maximum eigenvalue criterion. The analytical performance of the proposed method is discussed in terms of symbol error rate (SER). An expression of SER is derived by using the moment generating function approach. It is shown by simulations and analysis that the proposed scheme performs better if more antennas are equipped either at the transmitter or users.

Electrically compensated, tattoo-like electrodes for epidermal electrophysiology at scale.

Epidermal electrophysiology is widely carried out for disease diagnosis, performance monitoring, human-machine interaction, etc. Compared with thick, stiff, and irritating gel electrodes, emerging tattoo-like epidermal electrodes offer much better wearability and versatility. However, state-of-the-art tattoo-like electrodes are limited in size (e.g., centimeters) to perform electrophysiology at scale due to challenges including large-area fabrication, skin lamination, and electrical interference from long interconnects. Therefore, we report large-area, soft, breathable, substrate- and encapsulation-free electrodes designed into transformable filamentary serpentines that can be rapidly fabricated by cut-and-paste method. We propose a Cartan curve-inspired transfer process to minimize strain in the electrodes when laminated on nondevelopable skin surfaces. Unwanted signals picked up by the unencapsulated interconnects can be eliminated through a previously unexplored electrical compensation strategy. These tattoo-like electrodes can comfortably cover the whole chest, forearm, or neck for applications such as multichannel electrocardiography, sign language recognition, prosthetic control or mapping of neck activities.

High performance hardware design of compressor adder in DA based FIR filters for hearing aids

Hearing aid is an acoustic device which is worn by hearing loss people. To compensate the different types of hearing loss, it is necessary to selectively amplify sounds at required frequencies. The main aim of the hearing aid is to selectively remove the noise signal such that the processed sound matches ones audiogram. To achieve this, the decimation filter in hearing aids can be design using multiplier less architecture which should be able to adjust sound levels at arbitrary frequencies within a given spectrum. In hearing aids, decimation filter plays a key role. This paper presents a low complexity design of a digital finite impulse response (FIR) filter for digital hearing aid application. This paper proposed approximate 4:2 compressor adders in memory less DA based FIR filter architecture. In DA architecture the area of the ROM increases gradually when filter order is increased. Memory less DA is designed using compressor adders is a solution to decrease the power consumption and area of the FIR filters and makes the area and power reduction for hearing aid application. The proposed DA based FIR filter architecture is synthesized on 90 nm technology using Synapsis Application Specific Integrated circuit design compiler. The proposed architecture has 45% reduction in area delay product when distinguish with systolic architecture and 10% less ADP when compare with OBC DA architecture. The proposed design is also implemented Field Programmable Gate Array and the results shows that the proposed architecture has less slices than best existing designs. The proposed architecture is used in decimation filter of hearing aids applications using matlab simulink, which removes the unwanted signal.

Dielectric antenna effects in integrating line piezoelectric sensors for optoacoustic imaging

This work studies the adverse effects, as regards noise, of immersing in water an integrating line piezoelectric detector devoted to optoacoustic imaging. We found that the sensor, in conjunction with the acoustic coupling medium (water), behaves as a resonant dielectric antenna. This phenomenon limits the performance of the system because it efficiently captures unwanted electromagnetic signals. The requirement of good acoustic coupling between the water and the sensor precluded the use of a standard metallic shielding enclosure. Therefore, we resorted to a silver-paint-based electrical shield deposited on the detector. This easy-to-implement and low-cost solution significantly increases the signal to noise ratio and does not degrade the acoustic performance. The noise reduction allows the use of a better transimpedance amplifier with higher gain and bandwidth; thus achieving a very sensitive, low-noise detection system.

Multi-domain functional metasurface with selectivity of polarization in operation frequency and time

In this paper, we propose the design of a multi-domain functional metasurface (MDFM) that can achieve selectivity of polarization in operation frequency and time. The MDFM consists of a wire grating as the front layer, a frequency selective surface as the middle layer and an active orthogonal wire grating loaded with positive-intrinsic-negative (PIN) diodes as the back layer. The front wire grating serves as a polarization selective surface that only passes electromagnetic (EM) waves polarized perpendicular to the wire, whereas the middle frequency selective surfaces exerts a pass-band in the frequency-domain. To further obtain selectivity in the time-domain, another orthogonal wire grating loaded with PIN diodes is adopted to switch on/off the pass-band. Three functional layers are combined to integrate the three selective functions. To verify this design idea, a MDFM operating at 3.19 GHz was designed, with a total thickness about λ/11. A prototype was fabricated and measured to validate the design. The experimental results are in satisfactory agreement with the simulated ones. Due to multi-fold selectivity, the MDFM can achieve high rejection for unwanted signals and may find wide applications in areas such as wireless communication, EM compatibility and stealthy radomes.

Pencegahan Kesalahan Alarm dalam Sistem Pendeteksi Dini Kebakan dan Pemadaman Berbasis Internet of Things


 
 
 
 False alarm in fire detection can cause a huge loss. False alarm is generated by unwanted signal of smoke detector such as outdoor smoke or smoking. Therefore, it is designed a system that can reduce false alarm. The purposed system is built based on three components, those are sensors, actuators and data communication. Sensors are smoke, flame and camera sensor. Smoke sensor is used as the first thing to sense a signal from the system that warns the system there is a fire. Flame sensor and camera are used to confirm that a signal of fire whether false alarm or not. Internet of Things (IoT) is applied to control the system. The result show that the system is applicable.