Musaddak Maher Abdul Zahra

Small-scale Darrieus wind turbines have a wide scope in areas that are isolated from the power grid for such small-scale household applications. Applications of wind turbines on house roofs are one potential way to generate electricity from wind energy harvesting in low-wind urban locations. This work studies the aerodynamic behavior of a vertical axis wind turbine based on a MATLAB programming mathematical model. The NACA0021 airfoil profile blade was used in this present research investigation. The turbine was fabricated with dimensions such as chord length, c = 95 mm, blade height, h = 600 mm, and turbine diameter, D = 600 mm. The experimental results of the turbine for air velocity from 1 to 12 ms−1 were used in this paper and compared with analytical results. It has been observed that the fixed-pitch turbine does not start by itself at a low air velocity of 1 to 5 m/s due to a minimum and negative torque.

The powder mixed electrical discharge machining (PMEDM) process was simulated via finite element analysis in the current study to assess heat behavior and material removal rate. The goal of this paper is to conduct a thorough experimental and thermal examination of electrical discharge machining (EDM) in order to forecast its cutting characteristics and subsequently optimize the output variables using a response surface methodology for simulations and choosing the most suitable set of process variables related to the PMEDM process. This study’s objective is to design a 2D axisymmetrical transient thermal model that might also describe the physics of material removal in a single spark PMEDM operation on a Titanium Zirconium Molybdenum (TZM) superalloy. ANSYS (version 9.1) software is used to perform transient heat transfer simulations to determine the temperature profile with the amount of material removal at different current, pulse on and off times, gap voltages, and fraction of heat that enters the specimen. The PMEDM process produced craters with a lower diameter and depth, which increased the material removal rate and enhanced the surfacing quality. Compared to the conventional EDM process, the inclusion of powder raised the heat flux given to the work material by 10%–12%. It has been determined that with the single spark modeling technique, the temperature significantly dropped in both the radial and depth directions. The computational results are compared with experimental observations for similar machining conditions, and both results agree satisfactorily.

The random forest algorithm under the MapReduce framework has too many redundant and irrelevant features, low training feature information, and low parallelization efficiency when dealing with multihoming big data network problems, so parallelism is based on information theory, and norms is proposed for random forest algorithm (PRFITN). In this paper, the technique used first builds a hybrid dimensional reduction approach (DRIGFN) focused on information gain and the Frobenius norm, successfully reducing the number of redundant and irrelevant features; then, an information theory feature is offered. This results in the dimensionality-reduced dataset. Finally, a technique is suggested in the Reduce stage. The features are grouped in the FGSIT strategy, and the stratified sampling approach is employed to assure the information quantity of the training features in the building of the decision tree in the random forest. When datasets are provided as key/value pairs, it is common to want to aggregate statistics across all objects with the same key. To acquire global classification results and achieve a rapid and equal distribution of key-value pairs, a key-value pair redistribution method (RSKP) is used, which improves the cluster’s parallel efficiency. The approach provides a superior classification impact in multihoming large data networks, particularly for datasets with numerous characteristics, according to the experimental findings. We can utilize feature selection and feature extraction together. In addition to minimizing overfitting and redundancy, lowering dimensionality contributes to improved human interpretation and cheaper computing costs through model simplicity.

The Internet of Things (IoTs) has accelerated with the introduction of powerful biomedical sensors, telemedicine services and population ageing are concerns that can be solved by smart healthcare systems. However, the security of medical signal data that collected from sensors of IoTs technology, while it is being transmitted over public channels has grown to be a serious problem that has limited the adoption of intelligent healthcare systems. This suggests using the technology of blockchain to create a safe and reliable heart sound signal (PCG) that can communicate with wireless body area networks. The security plan offers a totally dependable and safe environment for every data flowing from the back end to front-end. Also in this paper, to classify heart sound signals, we suggested a one-dimensional convolutional neural network (1D-CNN) model. The denoising autoencoder extracted the heart sounds' deep features as an input feature of 1D-CNN. To extract the detailed characteristics from the PCG signals, a Data Denoising Auto Encoder (DDAE) was used instead of the standard MFCC, the suggested model shows significant improvement. The system's benefits include a less difficult encryption algorithm and a more capable and effective blockchain-based data transfer and storage system.

Because network of sensors gives a more accurate representation of remotely sensed environments, a network of wirelessly connected sensors is essential. Data packets must be routed to the base station hop by hop, which causes conventional network data collecting to use a lot of power. Unmanned aerial vehicles (UAV) were employed for hovering over the detected environment and gather data to solve this issue. The paper also aims to provide an automatic alignment for UAV antennas for tracking by utilising computer vision technologies. A directional antenna with high gain is used by a ground station that can operate by a pan-tilt to point towards the low-gain omnidirectional antenna carried by the UAV. To center the UAV's antenna's image in the frame, the antenna is equipped with a camera, and a computer detects the video and controls the pan-tilt. The antennas are aligned if there are no more than a few pixels between the UAV image center and the image center. The proposed imaging system exhibits fast data collection, thus attaining a high packet delivery rate and the minimum use of energy. With the suggested antenna auto-alignment approach, the antennas can be accurately aligned with an angle error of under one. UAVs must take the smoothest and shortest pathways possible to accommodate their motion and time constraints. As a result, the Traveling Sales Problem (TSP) is utilized to determine the shortest route, and Bezier curves are then employed to turn paths into a flyable path.

American scientific publishing group

The bending behavior of beams with a square cross-section containing holes under a three-point bending load was investigated in the present study. As aluminum alloys are lighter than steel and there are many automobile companies that use this material, 6063 aluminum alloy was chosen for this study. The present research was carried out both experimentally and numerically. In the numerical section, aluminum beams were simulated with the finite element software LS-DYNA. These beams contained holes with a diameter of 21 mm, which were placed at different distances on the length of the beam. In this research, 36 perforated beams were simulated in three thicknesses: 1, 1.5, and 2, and the holes were placed at 0, 3.5, 7, 10.5, 14, 17.5, 21, 24.5, 28, 35, 42, and 49 mm in relation to the middle of the beam. In addition, a beam without holes was studied for each thickness. Numerical simulations were validated with experiments and good results were observed. The obtained results showed that as the hole moves from the center to the sides, the absorption of energy and maximum force increases. In the final section, the most optimal beams were determined in terms of thickness and hole location, and based on these a car bumper was proposed.

Population growth and urbanization cause developing-country cities to create energy-intensive buildings. Building energy efficiency can be improved through active and passive solar design to reduce energy consumption, increase equipment efficiency, and utilize renewable energy, converting renewable energy into thermal energy or electricity. In this study, passive architecture was evaluated for both urban block and building energy usage. When reliable information and analysis of signs and parameters impacting energy consumption are available, designers and architects can evaluate and passively design a building with higher precision and an accurate picture of its energy consumption in the early stages of the design process. This article compares the location of Baku’s building mass to six climate-related scenarios. Three methodologies are used to determine how much solar energy the models utilize and the difference between annual heating and cooling energy consumption. The structure’s rotation has little effect on the energy utilized in most forms. Only east-west linear designs employ 6 to 4 kWh/m² of area and are common. Most important is the building’s increased energy consumption, which can take several forms. The building’s westward rotation may be its most important feature. Any westward revolution requires more energy. Building collections together offers many benefits, including the attention designers and investors provide to all places. Having an integrated collection and a sense of community affects inhabitants’ later connections. Dictionary and encyclopedia entries include typology discoveries. These findings will inform future research and investigations. An architect must know a variety of qualities and organizations to define and segregate the environment because architecture relies heavily on the environment. This research involves analyzing the current situation to gain knowledge for future estimations. The present will determine the future.

In the era of information technology, users had to send millions of images back and forth daily. It's crucial to secure these photos. It is important to secure image content using digital image encryption. Using secret keys, digital images are transformed into noisy images in image encryption techniques, and the same keys are needed to restore the images to their original form. The majority of image encryption methods rely on two processes: confusion and diffusion. However, previous studies didn’t compare recent techniques in the image encryption field.This research presents an evaluation of three types of image encryption algorithms includinga Fibonacci Q-matrix in hyperchaotic, Secure Internet of Things (SIT), and AES techniques. The Fibonacci Q-matrix in the hyperchaotic technique makes use of a six-dimension hyperchaotic system's randomly generated numbers and confuses the original image to dilute the permuted image. The objectives here areto analyze the image encryption process for the Fibonacci Q-matrix in hyperchaotic, Secure Internet of Things (SIT), and Advanced Encryption Standard (AES), and compare their encryption robustness. The discussed image encryption techniques were examined through histograms, entropy, Unified Average Changing Intensity (UACI), Number of Pixels Change Rate (NPCR), and correlation coefficients. Since the values of the Chi-squared test were less than (293) for the Hyperchaotic System & Fibonacci Q-matrix method, this indicates that this technique has a uniform distribution and is more efficient. The obtained results provide important confirmation that the image encryption using Fibonacci Q-matrix in hyperchaotic algorithm performed better than both the AES and SIT based on the image values of UACI and NPCR.

In the era of the Internet of Things (IoT) and the Industrial Internet of Things (IIoT), elements along the supply chain can be connected to one another to offer tracking capabilities. The information obtained from an always connected and working supply chain is then incorporated into the simulations of the virtual world (digital twin). This allows for an instantaneous simulation of the environment at any point in time and better, more optimized, and quicker decisions are made based on the results. This translates into more performance and a stronger competitive advantage. This paper will examine the main concepts surrounding the supply chain from the perspective of digitalization. In this paper, we will take a closer look at the main concepts related to the supply chain in light of digitalization.