No abstract

Body area network (BAN) connects sensors and actuators to the human body in order to collect patient’s information and transmitting it to doctors in a confined space with limited users. wireless body area network (WBAN) is derived from wireless sensor networks (WSN) and enables to transfer of the patient's information with a wide range of communication due to the limitations of the wired body area network. It plays a vital role in healthcare monitoring, healthcare systems, medical field, sports field, and multimedia communication. Sensors and actuators lead to high energy consumption due to their tiny size. WBAN facilitates in securely storing patient information and transmitting it to the doctor without data loss at a specific time. This review examines and summarizes methodological approaches in WBAN relating to security, safety, reliability, and the fastest transmission. Flying body area networks (FBAN) utilizing unmanned aerial vehicles for data transmission are recommended to promote rapid and secure communication in WBAN. FBAN improve the security, scalability, and speed in order to transmit patient’s information to the doctor due to high mobility.

No abstract

There are a slew of elements at work in the composites sector, from people and markets to technology and innovation, that are continually reshaping the industry's structure. For now, composite materials' winning combination of high strength-to-weight ratio continues to propel them into new areas, but other attributes are just as crucial. These properties, which may be customized for unique purposes, result in a completed product requiring fewer raw materials and fewer joints and fasteners, as well as reduced assembly times, thanks to composite materials. To lower product lifespan costs, composites also have demonstrated resilience in industrial applications to temperature extremes as well as corrosion and wear. Polymers, ceramics, and metals can all be used as matrices. Thermoplastic (TP) resin is the second most prevalent matrix type, and it is becoming increasingly popular among composite makers. By melting or softening and then chilling the material, thermoplastic linear polymer chains are generated and may be reformed into shaped solids. It is common for thermoplastics to be offered in sheet or panel form, which may be treated using in situ consolidation processes, such as pressing, to manufacture durable, near-net-shape components without the need for an autoclave or vacuum bag cure. Correcting abnormalities or fixing harm done in service is possible with reformability.

Modeling and controller design for an aeropendulum system is important because it enables to control the pendulum action by controlling the voltage given such as the stability, dead time,rise time, overshoot etc. This concept of pendulum system is very useful and can be applied in day to day life. There are different kinds of applications of pendulum systems such as measurement applications, Schuler tuning methods, coupled pendulum applications, entertainment purposes, etc. By equation of motion, the open loop transfer function can be obtained and simulation is done accordingly.Aeropendulum is a suspended pendulum, which has a propeller at the end of the stick which is motorized,It can be controlled by controlling the voltage given to dc electric motor.Designing of Proportional Integral Derivative (PID),Linear Quadratic Regulator (LQR),PID based LQR controllers are used for nonlinear pendulum dynamic system in this project. The promising performance of the proposed controllers investigates in simulation.The effectiveness and the comparisons of the controller methods for Nonlinear Aeropendulum Dynamical System are delivered in this project.

Flying Ad Hoc Network is derived from the mobile ad hoc network and it consists of unmanned aerial vehicles (UAV) for high-speed communication. Flying Ad Hoc Network has high mobility, and the users can communicate without the help of human intervention. Due to high mobility in FANET, network performance is to be concentrated more. Designing a routing protocol is the most important metric for continuous monitoring, analyzing the network performance, and improve efficient network communication. Design of routing protocol should fulfill the important criteria like neighbor nodes selection, shortest path, traffic control, high scalability, high reliability, high data delivery, low drop rate, lesser delay, and high throughput. Due to the high speed in FANET, routing protocols are to be focused on the improvement of network performance and quality of services. This research work studies the detailed review of suitable routing protocols for Flying Ad hoc Networks and discussed the possible outcomes of the different routing strategies such as source-initiated data-centric, table-driven, hybrid, multipath, location-aware, multicast, geographical multicast, power-aware, and energy-aware. This research study suggested the important metrics be concentrated on designing the efficient routing protocol for Flying Ad Hoc Networks and on improving the quality of services.

Obstructive Sleep Apnea is a respiratory disorder that impairs sleep quality by causing respiratory arrest. An irregular breath delay or decrease of airflow during sleep is the hallmark of the apnea syndrome. According to the literature, approximately 2% of middle-aged women and 4% of middle-aged men are affected. The disease is diagnosed by the physician in two steps. In the first stage, the physician reviews the medical records obtained using the polysomnography system. The disease is diagnosed in two stages by the physician, who examines the patient records taken with the polysomnography system in the first stage. New diagnostic processes and equipment are required as a result of the negative aspects of this procedure. The heart rate variable (HRV) and electrocardiography (ECG) signals are used, and ECG records from the patient and control groups are obtained. The optical filter was used to clean ECG signals and heart rate variables (HRV) from patient and control classes. After that, the ECG signal was used to calculate the HRV parameter. The HRV and ECG signals were then used to extract functionality. Reduced machine learning techniques, such as random forest, SVM, and the kNN feature selection process, were used to classify the extracted features. To evaluate the classifiers’ efficiency, the sensitivity and specificity values, as well as the accuracy rates for each class in the test set, were computed, and a receiver operating characteristic curve was developed. The method can be realized with Random forest, Support Vector Machine, and KNN, which have the best accuracy of 82.5 percent, 97 percent, and 89 percent, respectively, using 11 ECG and HRV features, according to the results. The system will work with these success rates. It is possible to implement a realistic sleep/awake detection method when all of these factors are taken into account. This means that using machine learning and signal processing methods, the ECG signal can be used to diagnose obstructive sleep apnea.

No abstract