One of the most significant challenges of medical care is the infection of postoperative wounds, and conventional visual examination often fails to detect it early. This research proposes the design of an innovative, passive wireless telemetry system for non-intrusive monitoring of the wound-healing process. The system integrates a biocompatible resonance circuit (LC) with a high-sensitivity piezoresistive sensor based on MXene (Ti3C2Tx). It operates within the standard industrial and medical (ISM) band at 13.56 MHz.The detection mechanism in the system is based on the principle of "impedance modulation" (Impedance Modulation), which arises from changes in the sensor's resistance under physiological tissue pressure. The system was modeled and simulated using the Proteus environment to evaluate its frequency response. The results showed a high dynamic range, as the system recorded a stable output voltage of 863 mV (-1.28 dB) during the recovery phase (Rs≈10KΩ), against a sharp decrease to 15 mV (-36.5 dB) during the inflammation phase (Rs≈100Ω), which effectively indicates the phenomenon of "signal breakdown." In addition, sensitivity analysis emphasized the importance of component compatibility, as an amplitude mismatch caused the resonance frequency to shift to 11.9 MHz. The proposed system can accurately distinguish between healthy and inflamed tissues.
Magneto-rheological (MR) valve is one of the devices generally used to control the speed of Hydraulic actuator of MR fluid. The performance of valve depends on the magnetic circuit design. Present study deals with a new design of MR valve. A mathematical model for the MR valve is developed and the simulation is carried out to evaluate the newly developed MR valve. The design of the magnetic circuit is accomplished by magnetic finite element software such as Finite Element Method Magnetic (FEMMR). The model dimensions of MR valve, material properties are taken into account. The results of analysis are presented in terms of magnetic strength H and magnetic flux density B. The simulation results based on the proposed model indicate that the ef
... Show MoreThe current research sheds light on an important aspect of the great and rapid development in the field of science and technology and modern manufacturing methods as a result of the scientific revolution resulting from the accelerated cognitive development, which prompted designers in general and interior design in particular to exploit and invest in digital technology and the development of digital control in the process of designing the industrial product for the purpose of creativity and innovation through these digital programs Digital models achieve the requirements and desires of the interior designer according to the creative skill using modern software with high efficiency And extreme accuracy that is consistent with the requirem
... Show MoreThe electrode in the microbial fuel cell has a significant effect on cell performance. The treatment of the electrode is a crucial step to make the electrode surface more habitable for bacteria growth, thus, increases the power production as well as waste treatment. In the current study, two graphite electrodes were treated by a microwave. The first electrode was treated with 100W microwave energy, while the second one was treated with 600W microwave energy. There is a significant enhancement in the surface of the graphite anode after the pretreatment process. The results show an increase in the power density from 10 mW/m2 to 15 mW/m2 with 100w treatment and to 13.47 mW/m2 with 600w treatment. An organic
... Show MoreThe rapid development of Internet of Things (IoT) devices and their increasing numbers have caused a tremendous increase in network traffic and a wider range of cyber-attacks. This growing trend has complicated the detection process for traditional intrusion detection systems and heightened the challenges faced by these devices, such as imbalanced and large training data. This study presents a cohesive methodology of a series of intelligent techniques to prepare clean and balanced data for training the first (core) layer of a robust hierarchical intrusion detection system. The methodology was built by cleaning and compressing the data using an Autoencoder and preparing a strong latent space for balancing using a hybrid method that combines
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