Compact Real-Time Control System for Autonomous Vehicle

Due to global warming, there is an increase in the number of natural disasters occurring around the world. With more disasters happening, post disaster search and rescue personnel are putting their life on the line more often in scouting out the post disaster site and sending in first aid supplies while waiting for rescue vehicles like fire trucks and ambulance to arrive. In Malaysia alone, the use of compact autonomous landed vehicle (ALV) for this purpose is limited. There are many compact ALV that are being developed with microcontrollers and microprocessors such as Arduino and Raspberry Pi as the central control system, but they are fragile and can be damaged easily when used in harsh environments. In addition, multiple microcontrollers and microprocessors are needed for the ALV as parallel processing and limited gates are some of the common problems with microprocessors and microcontrollers. In this paper, a central control system using an FPGA is proposed together with the design of a prototype for the ALV. The ALV consists of three systems: Propulsion System, Sensor System, and Remote-Control System. These systems are integrated together with the Altera DE-115 board as the central control unit of the ALV. Verilog Hardware Description language (Verilog HDL) is used for designing the control system for the ALV. The proposed system is stable, low cost, allows parallel processing and the compact size of the ALV allows smooth manoeuvring through small areas of post disaster sites to scout out the area and send in first aid supplies to the victims

A HOLISTIC APPROACH TO DEVELOP ENGINEERING PROGRAMME OUTCOMES: A CASE STUDY OF TAYLOR'S UNIVERSITY

Part fulfilment of providing an engineering programme which implements outcome based education includes various outcomes that are tied to what the graduate should achieve after, during and before graduation. The programme outcomes are specifically crafted to encapsulate attributes that must be attained by a student upon graduation. The following paper details the principles used to craft the programme outcomes of an engineering undergraduate degree programme. The principles used were chosen based its importance and innovative content as well as being aligned to the purpose of the university which is running the degree programme. Upon crafting the prescribed outcomes, the paper will also detail how stakeholders were engaged and how their opinion was accounted for in the final crafting of the new set of programme outcomes. The paper also highlights how a gap analysis was performed to capture areas which were not covered by the previous programme outcomes

An Improved DC-DC Boost Converter for Energy Harvesting

A novel dual-input DC-DC boost converter that can perform the integration of harvested energy from solar and vibrational input energy sources is proposed. Firstly, the background of a hybrid energy system that relates to multi-input DC-DC converters is discussed, and the limitations of the current designs of power converter ICs are highlighted. A detailed design analysis of the proposed converter was done to justify its performance. A current and voltage stress analysis has been performed to ensure suitable switching devices are selected for the converter. Two different power control strategies are proposed for the DIDCB converter to manage output voltage during source and load-side disturbances. Performance analysis of the circuit is carried out using MATLAB Simulink software. Different duty ratios for power switches in the converter were tested to determine the maximum boost ratio and the highest efficiency that can be achieved by the converter. To demonstrate the feasibility of the proposed converter, the performance of the converter is compared with existing converter topologies. The proposed converter achieved a high efficiency of 99.4%, had less fluctuation in the output voltage, and had reduced overshoot. In addition, the proposed converter demonstrated a simpler configuration and required fewer component counts, which helped reduce the cost and size of the system

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Hardware prototyping of Iris recognition system: A neural network approach

Iris recognition, a relatively new biometric technology, possesses great advantages, such as variability, stability and security, making it to be the most promising method for high security environments. A novel hardware-based iris recognition system is proposed in this paper, which consists of two main parts: image processing and recognition. Image processing involves histogram stress, thresholding, cropping, transformation and normalizing that is performed by using Matlab. Multilayer perceptron architecture with backpropagation algorithm is employed to recognize iris pattern. The entire architecture was modeled using VHDL, a hardware description language. The approach obtained a recognition accuracy of 98.5%. The design was successfully implemented, tested and validated on Altera Mercury EP1M120F484C5 FPGA utilizing 4157 logic cells and achieved a maximum frequency of 121.87 MHz. This novel and efficient method in hardware, based on FPGA technology showed improved performance over existing approaches for iris recognitio

Novel Hybrid Metaheuristics And Algorithm Extensions For Optimization Of Engineering Applications

NP-hard optimization problems that are found in many engineering domains pose great challenges to traditional algorithmic solutions. The search space normally encompasses a huge number of local optimal and the computational effort to achieve a global optimum can be very huge for practical use. In this thesis, the design, analysis. improvement and application of metaheuristics for hard CO problems is presented. The research is motivated by four engineering applications that covers high-level synthesis, multiprocessor scheduling, flexible manufacturing systems and hybrid flow shop scheduling

Hardware Realization Of Fuzzy Wavelets Neural Network To Power Quality Analysis

This thesis presents a new approach aimed at automating the analysis of power quality disturbances. The approach focuses on the application of discrete wavelet transform technique to extract features from disturbance waveforms and their classification using a powerful combination of neural network and fuzzy logic. As there exists uncertainty in the training set and in the subsequent pattern recognition, fuzzy logic is used to determine the final output rather than taking the output of the neural network as the final classification, improving robustness in the system. The disturbances of interest include sag, swell, transient, fluctuation, interruption and normal waveform. Each power quality disturbance has unique deviations from the pure sinusoidal wave form and this is adopted to provide a reliable classification of disturbance

Advances in Signal Processing and Artificial Intelligence Technologies in the Classification of Power Quality Events: A Survey

Power quality monitoring has advanced from strictly problem solving to ongoing monitoring of system performance. The increased amount of data being collected requires more advanced analysis tools. New intelligent system technologies using expert systems and artificial neural networks provide some unique advantages regarding fault analysis. The purpose of this article is to review and discuss various tools and methodologies aimed at providing more flexible and efficient ways of assessing power quality. Advances in signal processing and artificial intelligence tools will be examined for their role in the detection and classification of events, the application of various mathematical transforms and the implementation of rules-based expert systems. We focus further on the review on several implementation methodologies, and a performance comparison of existing implementations are presented. Recommendations for future study are also outlined. This review opens the path for researchers to future comparative studies between different architectures, and as a reference point for developing more powerful and flexible structures

VHDL modeling of the IEEE802.11b DCF MAC

The wireless communication is highly deployed due to it convenience of mobility. The wireless local area network, WLAN is dominated by EEEE802.11 standard. All the new notebooks are equipped with the IEEE802.11 b WLAN. It becomes one of the main focuses of the WLAN research. Most of the researches are simulation based due to high cost required for the hardware implementation. The IEEE802.11b standard contains two major operations, the Distribution Coordination Function (DCF) and Point Coordination Function (PCF). The main core of the IEEE802.11b, the CSMA/CA and the EEEE802.11b Physical and MAC are modeled in this paper using VHDL. The VHDL is defined in IEEE as a tool of creation of electronics system because it supports the development, verification, synthesis and testing of hardware design, the communication of hardware design data and the maintenance, modification and procurement of hardware[2]. The CSMA/CA is modeled to 3 major blocks in VHDL, the CSMACA, Random Generator and counter. The CSMA/CA is successfully modeled with a total of 58 pins and it used 15% of the total logic elements of the APEX (TM) 20KE FPGA. The CSMA/CA can support the operation frequency up to 50MHz