The Internet-of-things (IoT) has been gradually paving the way for the pervasive connectivity of wireless networks. Due to the ability to connect a number of devices to the Internet, many applications of IoT networks have recently been proposed. Though these applications range from industrial automation to smart homes, healthcare applications are the most critical. Providing reliable connectivity among wearables and other monitoring devices is one of the major tasks of such healthcare networks. The main source of power for such low-powered IoT devices is the batteries, which have a limited lifetime and need to be replaced or recharged periodically. In order to improve their lifecycle, one of the most promising proposals is to harvest energy from the ambient resources in the environment. For this purpose, we designed an energy harvesting protocol that harvests energy from two ambient energy sources, namely radio frequency (RF) at 2.4 GHz and thermal energy. A rectenna is used to harvest RF energy, while the thermoelectric generator (TEG) is employed to harvest human thermal energy. To verify the proposed design, extensive simulations are performed in Green Castalia, which is a framework that is used with the Castalia simulator in OMNeT++. The results show significant improvements in terms of the harvested energy and lifecycle improvement of IoT devices.

In hostile and remote environments, such as mountains, forests or suburban areas, traditional communications may not be available, especially after a disaster, such as a flood, a forest fire or an earthquake. In these situations, the wireless networks may become congested or completely disrupted and may not be adequate to support the traffic generated by rescuers. It is also considered as the key tool in Corona Virus (COVID-19) battle. Moreover, the conventional approaches with fixed gateways may not work either, and this might lead to decoding errors due to the large distance between mobile nodes and the gateway. To avoid the decoding errors and improve the reliability of the messages, we propose to use intermediate Unmanned Aerial Vehicles (UAVs) to transfer messages from ground-based Long Range (LoRa) nodes to the remote base station (BS). Specifically, this UAV-enabled LoRa architecture is based on the ad hoc WiFi network, wherein, UAVs act as relays for the traffic generated between LoRa nodes and BS. To make the architecture more efficient, a distributed topology control algorithm is also proposed for UAVs. The algorithm is based on virtual spring forces and movement prediction technique that periodically updates the UAV topology to adapt to the movement of the ground-based LoRa nodes that move on the surface. The simulation results show the feasibility of the proposed approach for packet reception rate and average delay quality of service (QoS) metrics. It is observed that the mechanisms implemented in a UAV-enabled LoRa network effectively help to improve the packet reception rate with nominal buffer delays.

Non-orthogonal multiple access (NOMA) has become the key technology in the future 5G wireless networks. It can achieve multi-user multiplexing in the transmit power domain by allocating different power, which can effectively improve the system capacity and spectral efficiency. Aiming at the problem of high computational complexity and improving system capacity in non-orthogonal multiple access (NOMA) based on orthogonal frequency division multiple access (OFDMA) for 5G wireless cellular networks, this paper proposes an improved low complexity radio resource allocation algorithm for user grouping and power allocation optimization. The optimization model is established with the goal of maximizing system capacity. Through the step-by-step optimization idea, the complex non-convex optimization problem is decomposed into two sub-problems to be solved separately. Firstly, all users are grouped based on the greedy method, and then the power allocation is performed on the sub-carriers of the fixed group. Simulation results show that the proposed algorithm has better system capacity than the existing state-of-the-art algorithms and reduced complexity performance.

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Abstract-This project concerns the application of haptic feedback to a virtual reality laparoscopic surgery simulator. Haptic attributes such as mass, friction, stiction, elasticity, roughness and viscosity are individually modeled, validated and applied to the existing visual simulation created by researchers at Monash University.Validation studies has shown that refinements to our mechanical interface improves the accuracy of localisation by 25%. Using our mechanical interface, the JND (Just Noticeable Difference) for instantaneous change of magnitude of haptic attributes is approximately 12%. This suggests the mechanical interface is suitable to use for surgery based studies.There are times in surgery when the view from the camera cannot be depended upon. When visual feedback is impeded, haptic feedback must be relied upon more by the surgeon. A realistic simulator should include some sort of visual impedance. Results from a simple tissue holding task suggested the inclusion of haptic feedback in a simulator aids the user when visual feedback is impeded.Haptic force feedback modeling, systems implementation, threshold and level perception, and validation studies form the principal areas of new work associated with this project.

Abstract-Hysteroscopy is an extensively popular option in evaluating and treating women with infertility. The procedure utilizes an endoscope, inserted through the vagina and cervix to examine the intra-uterine cavity via a monitor. The difficulty of hysteroscopy from the surgeon's perspective is the visual spatial perception of interpreting 3D images on a 2D monitor, and the associated psychomotor skills in overcoming the fulcrum-effect. Despite the widespread use of this procedure, current qualified hysteroscopy surgeons have not been trained the fundamentals through an organized curriculum.The emergence of virtual reality as an educational tool for this procedure, and for other endoscopic procedures, has undoubtedly raised interests. The ultimate objective is for the inclusion of virtual reality training as a mandatory component for gynecological endoscopic training. Part of this process involves the design of a simulator, encompassing the technical difficulties and complications associated with the procedure. The proposed research examines fundamental hysteroscopic factors as well as current training and accreditation norms, and proposes a hysteroscopic simulator design that is suitable for educating and training.

Abstract-Hysteroscopy is an extensively popular option in evaluating and treating women with infertility. The procedure utilizes an endoscope, inserted through the vagina and cervix to examine the intra-uterine cavity via a monitor. The difficulty of hysteroscopy from the surgeon's perspective is the visual spatial perception of interpreting 3D images on a 2D monitor, and the associated psychomotor skills in overcoming the fulcrum-effect. Despite the widespread use of this procedure, current qualified hysteroscopy surgeons have not been trained the fundamentals through an organized curriculum.The emergence of virtual reality as an educational tool for this procedure, and for other endoscopic procedures, has undoubtedly raised interests. The ultimate objective is for the inclusion of virtual reality training as a mandatory component for gynecological endoscopic training. Part of this process involves the design of a simulator, encompassing the technical difficulties and complications associated with the procedure. The proposed research examines fundamental hysteroscopic factors as well as current training and accreditation norms, and proposes a hysteroscopic simulator design that is suitable for educating and training.

Abstract-A virtual reality based laparoscopic surgery simulator is an important training option for laparoscopic surgeons. It has significant advantages over other training methods. Instruments-anatomy interactions are one of the main features of these simulators. In this paper we present the deformation of the uterine tube using three dimensional finite element methods with finite element software. The work examines the feasibility of incorporating the finite element (FE) model within the visual graphic model to achieve high degree of realism of instrument-tissue interactions.