Many domains, including communication, signal processing, and image processing, use the Fourier Transform as a mathematical tool for signal analysis.Although it can analyze signals with steady and transitory properties, it has limits.The Wavelet Packet Decomposition (WPD) is a novel technique that we suggest in this study as a way to improve the Fourier Transform and get beyond these drawbacks.In this experiment, we specifically considered the utilization of Daubechies level 4 for the wavelet transformation.The choice of Daubechies level 4 was motivated by several reasons.Daubechies wavelets are known for their compact support, orthogonality, and good time-frequency localization.By choosing Daubechies level 4, we aimed to strike a balance between preserving important transient information and avoiding excessive noise or oversmoothing in the transformed signal.Then we compared the outcomes of our suggested approach to the conventional Fourier Transform using a non-stationary signal.The findings demonstrated that the suggested method offered a more accurate representation of nonstationary and transient signals in the frequency domain.Our method precisely showed a 12% reduction in MSE and a 3% rise in PSNR for the standard Fourier transform, as well as a 35% decrease in MSE and an 8% increase in PSNR for voice signals when compared to the traditional wavelet packet decomposition method.
To address the difficulties in fusing multi-mode sensor data for complex industrial machinery, an adaptive deep coupling convolutional auto-encoder (ADCCAE) fusion method was proposed. First, the multi-mode features extracted synchronously by the CCAE were stacked and fed to the multi-channel convolution layers for fusion. Then, the fused data was passed to all connection layers for compression and fed to the Softmax module for classification. Finally, the coupling loss function coefficients and the network parameters were optimized through an adaptive approach using the gray wolf optimization (GWO) algorithm. Experimental comparisons showed that the proposed ADCCAE fusion model was superior to existing models for multi-mode data fusion.
The observation, in the past, that a thunderstorm perturbed the transmissions of an old vacuum tubes radio with noise discharges in correspondence with lightnings, suggested the possibility of radio-acoustic study of thunderstorms. The noise discharges appeared to convey not only information about lightnings, but also about any other thunderstorm electromagnetic phenomena generating noise discharges. The low-cost instrumentation involved in the radio-acoustic study, comprised a radio Telefunken mod. T33B, a 15 m long indoor wire antenna, a mobile telephone Samsung Galaxy S20 FE 5G provided with the recorder App Enregistreur vocal, a computer HP Pavillion dv5-1254eg and the s/w audio analyser Audacity. A first thunderstorm on 20 June 2023 and a second thunderstorm on 22 June 2023, both above Munich, were radio-acoustic studied. The second thunderstorm was more active than the first and released much more energy.
The massive growth of wireless traffic goes hand in hand with the deployment of advanced radio interfaces as well as network densification. This growth has a direct impact on the radio access architecture, which today is moving from centralized to distributed deployments through the use of a large number of access points (APs). This paper verifies the feasibility of deploying multiple APs in series on a single line in a ring topology in a cell-less network. On the one hand, this technique will further improve the communication capacity and flexibility of a Radio-over-Fiber (RoF) based mobile communication system and will reduce its construction cost. And on the other hand, this deployment topology is a solution to achieve a massive cell-free Multiple-Input Multiple-Output (MIMO) architecture and a cost-effective fronthaul solution. First, a passive optical add/drop multiplexer (OADM) is used to extract and add downlink and uplink signals from the remote access points of one kilometer. Then, a deployment model is developed with version 17 Optisystem software. The results obtained showed that the quadrature amplitude modulation (QAM) does not adapt to this multi-carrier transmission to deploy several AP in series on a single line. Thus, the performance degradation increases when the number of APs integrated on the line increases.
Exposure to toxins can lead to a wide range of adverse health effects, including respiratory problems, neurological disorders, cancer, and reproductive issues. Toxins can come from various sources, such as industrial waste, agricultural runoff, and household chemicals. Therefore, detecting and monitoring toxins in the environment is crucial for protecting human health and the environment. This study aimed to evaluate the performance of Hememics biosensor system in detecting environmental toxins such as Ricin and Staphylococcal enterotoxin B (SEB) in mixed matrixes. When Ricin and SEB are spiked into soil, chopped lettuce, tap water, milk and serum, the biosensor was able to detect these toxins, without sample processing, at a level of detection comparable to lab testing with high sensitivity and specificity. Furthermore, Hememics biosensor system is designed to be network-enabled, which means that results can be transmitted to relevant agencies for quick decisions. This feature is crucial in cases where quick action is needed to prevent further contamination or exposure to harmful toxins.
To address the intermittent positioning and drift of personnel positioning RTK in the high-frequency signal interference environment of substations, we propose to use IMU as the positioning compensation module of RTK and adopt the joint RTK/PDR positioning method to solve the positioning results. The heading angle is easily scattered in the pedestrian heading projection (PDR) process and the heading angles calculated from the output data of the gyroscope, accelerometer and magnetometer after denoising are input into the complementary filter for fusion. To improve the accuracy of step estimation in the PDR process, an improved step estimation model is used. For RTK/PDR data fusion, the extended Kalman filter (EKF) method is used, which helps to achieve outdoor full-scene high-accuracy positioning. The final simulation results show that RTK can be effectively compensated by PDR under the interference of high-frequency signals, and the positioning accuracy reaches 0.02 m.
Pedestrian inertial positioning is an effective means when satellites fail. Heading accuracy determines the performance of pedestrian inertial positioning. To realize an accurate positioning, a heading drift correction method was proposed. An in-situ active rotation is performed before autonomous positioning, and the error compensation coefficient of biaxial geomagnetic measurement is obtained by using the ellipse fitting correction method to achieve effective suppression of external environmental geomagnetic interference. The corrected biaxial geomagnetic measurement information is used to directly calculate the heading information and combine it with the peak stride detection method and linear step estimation model to achieve autonomous positioning of pedestrians. To verify the effectiveness and stability of the algorithm, several sets of experiments on the autonomous positioning of pedestrians are carried out in an outdoor environment. The experimental results show that the average deviation between the starting point and the endpoint of the proposed algorithm’s positioning trajectory accounts for 0.95% of the total travel in the 150 m positioning experiments.
Refractometric fiber optic sensors have a number of applications in industry due to advantages like remote sensing ability, compact size, easy to fit, etc. A refractometric sensor contains a pair of parallel fibers and a gap between the sensor probe and reflector, wherein the liquid whose refractive index is to be measured is filled. This paper describes the importance of mathematical modeling of this sensor. Ray tracing approach is used to model the sensor mathematically. This mathematical model is generalized for any scenario which is useful to avoid tedious trial and error techniques to design the sensor prototype. Mathematical modelling is a useful tool to optimize the gap distance for a detection of refractive index of liquid. The model is developed and analyzed rigorously considering adulteration of diesel by kerosene where refractive index varies from 1.44 to 1.46. Simulation experiments are carried out to optimize the gap distance which is found to be 6.8 mm using both models. Experiments are carried out where sensor probe is fabricated and results are analyzed. It is observed that for suggested gap distance sensor output varies almost linear over the entire range.
Surface plasmon resonance (SPR) sensors have grown in popularity owing to their sensitivity, precision, and capacity for a variety of applications, including detection, monitoring, and sensing, among others. Sensitivity and resolution are two areas where this technology has room for development. A plasmonic biosensor based on an asymmetric slotted PCF structure with extremely high sensitivity has been described and theoretically investigated. This high performance sensor is constructed and completely characterized using finite element method in COMSOL Multiphysics software environment. Sensitivity and resolution are analyzed as performance parameters for the proposed sensor. Numerical simulation exhibits the maximum wavelength-sensitivity of 1100 nm/RIU with 9.09 × 10-6 RIU resolution in the broad measurement range of refractive index from 1.30 to 1.44. A polarization controller can be used to fine-tune this extremely sensitive and wide-ranging refractive index sensor to fulfil a variety of practical needs. This is performed with the consideration of the variation in the refractive index (RI) of the analyte channels. In comparison with earlier PCF-based sensors, the fiber design structure is basic, symmetrical, simple to produce, and cost-effective. Because of the asymmetric air holes and higher sensitivities of the refractive index detector, it is possible to identify biomolecules, biochemicals and other analytes.
A simple electrochemical sensor for dopamine detection, is based on molecularly imprinted and electropolymerized over-oxidized polypyrrole (OPPy). The MIP-based electrode is obtained by electrocopolymerization of pyrrole (0.1 M) in the presence of the template molecular (dopamine, DA) (10-3 M). The square wave voltammetry (SWV) is used for the detection of dopamine in buffer solution. The current peak obtained at the MIP electrode was proportional to the logarithm of the DA concentration in the range of 10-11 to 5 × 10-8 M with a detection limit of 10-11 M. The proposed sensor was used for the detection of DA in spiked blood serum, satisfactory results were obtained.
In the last few decades, several monitoring systems integrated with water level detection have been the major research focus. Production boost and its sustainability depend mainly on sustainable water supply, measuring water level, and avoiding waste of water is an essential task for all stakeholders. There-fore, the aim of this paper is to design and implement a mobile phone-based remote control. This will be applied to control the operation of a submersible motor in a water tank. The water level in the tank is detected and the device remotely turns the motor pump on/off. The design process is accomplished by developing an android application that works on GSM technology to man-age the filling of water tank. An AT89C51 microcontroller is used for the desired programming. At the transmitting end, sensor is used for level detection and GSM module is used to send the information to user. According to this information, user controls the on/off operation of the pump. A SIM card is required for its operation and it works on attention (AT) commands. After the design and implementation of the device, the test results showed that all features of the device worked properly, and the device functions exactly as expected. More significantly, the paper has shown that ultrasonic sensors can be used to determine the level of water in a water tank and a GSM module can be used to control a submersible pump. The design and implementation of this device can help to reduce waste of time and power. Ultimately, it avoids water wastage thereby ensuring availability, conservation, and sustainability of water supply.
The high tech industrial revolution in the last fifty years depleted and ruined the planet natural resources. Energy harvesting is the main challenge in the research in green technologies. Compact wideband efficient antennas are crucial for energy harvesting portable sensors and systems. Small antennas have low efficiency. The efficiency of 5G, IoT communication and energy harvesting systems may be improved by using wideband efficient passive and active antennas. The system dynamic range may be improved by connecting amplifiers to the small antenna feed line. Ultra-wideband portable harvesting systems are presented in this paper. This paper presents new Ultra-Wideband energy harvesting system and antennas in frequencies ranging from 0.15 GHz to 18 GHz. Three wideband antennas cover the frequency range from 0.15 GHz to 18 GHz. A wideband metamaterial antenna with metallic strips covers the frequency range from 0.15 GHz to 0.42 GHz. The antenna bandwidth is around 75% for VSWR better than 2.3:1. A wideband slot antenna covers the frequency range from 0.4 GHz to 6.4 GHz. A wideband fractal notch antenna covers the frequency range from 6 GHz to 18 GHz. Printed passive and active notch and slot antennas are compact, low cost and have low volume. The active antennas may be employed in energy harvesting portable systems. The antennas and the harvesting system components may be assembled on the same, printed board. The printed notch and slot antennas bandwidth are from 75% to 100% for VSWR better than 3:1. The slot and notch antenna gain is around 3 dBi with efficiency higher than 90%. The antennas electrical parameters were computed in free space and near the human body. There is a good agreement between computed and measured results.
