Adaptive Vibrarthographic Signal Denoising via Ant Colony Optimization Using Dynamic Denoising Filter Parameters

This study proposes an ant colony optimization (ACO) denoising method with dynamic filter parameters. The proposed method is developed based on ensemble empirical mode decomposition (EEMD), and aims to improve the quality of vibrarthographic (VAG) signals. It mixes the original VAG signals with different white noise amplitudes, and adopts a hybrid technology that combines EEMD with a Savitzky-Golay (SG) filter containing the dynamic parameters optimized by ACO. The results show that the proposed method provides a higher peak signal-to-noise ratio (PSNR) and a smaller root-mean-square difference than the regular methods. The SNR improvement for the VAG signals of normal knees can reach 13 dB while maintaining the original signal structure, and the SNR improvement for the VAG signals of abnormal knees can reach 20 dB. The method proposed in this study can improve the quality of nonstationary VAG signals.

Electronically Tunable TISO Voltage-Mode Universal Filter Using Two LT1228s

This study aims to design an electronically tunable voltage-mode (VM) universal filter utilizing commercially available LT1228 integrated circuits (ICs) with three-input and single-output (TISO) configuration. With the procedure based on two integrator loop filtering structures, the proposed filter consists of two LT1228s, four resistors, and two grounded capacitors. It realizes five filter output responses: low-pass, all-pass, band-reject, band-pass, and high-pass functions. By selecting input voltage signals, each output responses can be achieved without changing the circuit architecture. The natural angular frequency can be controlled electronically. The input voltage nodes Vin1 and Vin3 possess high impedance. The output node has low impedance, so it can be cascaded to other circuits. The performance of the proposed filter is corroborated by PSpice simulation and hardware implementation which support the theoretical assumptions. The result shows that the range of total harmonic distortion (THD) is lower than 1%, and that the higher the temperature is, the lower the natural angular frequency is.

Ultrasonic Measurement for the Experimental Investigation of Velocity Distribution in Vapor-Liquid Boiling Bubbly Flow

This study proposes an ultrasonic velocity profiler (UVP) with a single ultrasonic gas-liquid two-phase separation (SUTS) technique to measure the velocity distribution of vapor-liquid boiling bubbly flow. The proposed technique is capable of measuring the velocity of the vapor bubble and liquid separately in boiling conditions. To confirm the viability of the measurement technique, the experiment is conducted on vertical pipe flow apparatus. The ultrasonic transmission and effect of ultrasonic refraction through the pipe wall and water are investigated at ambient temperature until subcooled boiling temperature is reached. The velocity profile in the water at elevated temperature is measured to verify the ability of the technique in this application. The bubbly flow velocity distribution measurement in boiling conditions is then demonstrated. The results show that the proposed technique can effectively investigate the velocity of both phases under various fluid conditions in boiling bubbly flow.

Development of Solar Desalination Units Using Solar Concentrators or/and Internal Reflectors

Solar distillation is one of the oldest and simplest technologies for desalination of salty water using renewable energy, namely solar energy, and the main problem of solar distillers is the low freshwater yield in contrast to the amount of energy input from the sun. To overcome the problem, this study develops three solar desalination units by using solar concentrators or/and internal reflectors, and compares the performance of three developed systems with the one of a conventional solar distiller under the climatic conditions of the Rabat region of Morocco. The three systems are: the solar distiller with a solar concentrator, the solar distiller with internal reflectors, and the solar distiller with a solar concentrator and internal reflectors. The energy balance equations of the systems are numerically resolved to utilize MATLAB software. The findings indicate that the utilization of the internal reflectors, the solar concentrator, and the solar concentrator and internal reflectors give better performance compared to the conventional solar distiller.

Laboratory Model Tests on Stone Column and Pervious Concrete Columns: A Comparative Study

This study aims to perform laboratory model tests to investigate the load-deformation behavior of stone columns (SCs), pervious concrete columns (PCCs), and composite columns (CCs). Here, CC refers to the column which has the upper portion made of PCC and the lower portion made of SC. The parameters investigated in this study include column diameters, column lengths, and installation methods (pre-cast and cast-in-situ methods). The results of the model tests reveal that the axial load-carrying capacity of PCC is nearly 8 times more than that of SC with the same diameter. Moreover, it is also observed that at the top portion of SC, with the PCC length which is about 3.75 to 5 times the column diameter, the load-carrying capacity can significantly increase. It is concluded that the installation methods have marginal influence on the load-deformation behavior of PCC.

A Hybrid Simulation of Converter-Interfaced Generation as the Part of a Large-Scale Power System Model

This study aims to propose an alternative hybrid approach to model renewable energy sources (RESs), which provide the most reliable results in comparison with the existing simulating tools. Within the framework of this approach, a specialized hybrid processor for modeling converter-interfaced generation (CIG) is developed. This study describes its structure and validation in the test system by comparing the results with commercial modeling tools, and also presents experimental studies of its operation as parts of the practical power system. The results obtained confirm the adequacy of the developed tools.

A Review on Advances in Automated Plant Disease Detection

Plant diseases cause major yield and economic losses. To detect plant disease at early stages, selecting appropriate techniques is imperative as it affects the cost, diagnosis time, and accuracy. This research gives a comprehensive review of various plant disease detection methods based on the images used and processing algorithms applied. It systematically analyzes various traditional machine learning and deep learning algorithms used for processing visible and spectral range images, and comparatively evaluates the work done in literature in terms of datasets used, various image processing techniques employed, models utilized, and efficiency achieved. The study discusses the benefits and restrictions of each method along with the challenges to be addressed for rapid and accurate plant disease detection. Results show that for plant disease detection, deep learning outperforms traditional machine learning algorithms while visible range images are more widely used compared to spectral images.

Planar EBG Loaded UWB Monopole Antenna with Triple Notch Characteristics

A triple band-notched ultra-wideband (UWB) monopole antenna using a planar electromagnetic bandgap (EBG) design is proposed. The EBG unit cell composed by an Archimedean spiral and inter-digital capacitance demonstrates the notch frequencies. The antenna with EBG cells near the feed line occupies only 30 × 36 mm2 with triple band-rejection characteristics. The three notched bands at 4.2 GHz, 5.2 GHz, and 9.1 GHz can be used in C-band satellite downlink, wireless local area network (WLAN), and X-band radio location for naval radar or military required applications. In addition, the proposed design is flexible to tune different notched bands by altering the EBG dimensions. The parametric analysis is studied in details after placing the EBG unit cells near the feed line to show the coupling effect. The input impedance and surface current distribution analysis are also analyzed to understand the effect of EBG at notch frequencies. The proposed design prototype is fabricated and characterized. A fairly considerable agreement is observed between simulated and measured results.

Using Deep Learning Technology to Realize the Automatic Control Program of Robot Arm Based on Hand Gesture Recognition

In this study, the robot arm control, computer vision, and deep learning technologies are combined to realize an automatic control program. There are three functional modules in this program, i.e., the hand gesture recognition module, the robot arm control module, and the communication module. The hand gesture recognition module records the user’s hand gesture images to recognize the gestures’ features using the YOLOv4 algorithm. The recognition results are transmitted to the robot arm control module by the communication module. Finally, the received hand gesture commands are analyzed and executed by the robot arm control module. With the proposed program, engineers can interact with the robot arm through hand gestures, teach the robot arm to record the trajectory by simple hand movements, and call different scripts to satisfy robot motion requirements in the actual production environment.

Finite Element Based Comparative Analysis of Positive Streamers in Multi Dispersed Nanoparticle Based Transformer Oil

The dispersion of dissimilar nanoparticles (NPs) in transformer oil (TO) has a major impact on fast propagating positive streamers. This work investigates the positive streamer dynamics in TO modified by dispersing both Fe3O4 and Al2O3 NPs at a homogenous concentration. The hydrodynamic drift diffusion model of positive streamer evolution and propagation are solved using the commercial software package COMSOL Multiphysics. The impact of multiple NPs (MNPs) has been analysed for streamer propagation, electric field intensity, electron density, and space charge density of modified TO. MNPs successfully reduce streamer propagation velocity by 50%, 17%, and 37.5% comparing to pure oil, Fe3O4 based nanodielectric fluids (NDFs), and Al2O3 based NDFs, respectively. The spatial distribution of electron density reveals the loss of electrons from the ionization region until the saturation of NPs. A comparative study demonstrates that MNPs significantly alter the streamer dynamics and augment the dielectric strength of TO compared to individual NPs.