Immune-Inspired Error Detection for Multiple Faulty Robots in Swarm Robotics

Error detection and recovery are important issues in swarm robotics research, as they are a means by which fault tolerance can be achieved. Our previous work has looked at error detection for single failures in a swarm robotics scenario with the Receptor Density Algorithm. Three modes of failure to the wheels of individual robots was investigated and comparable performance to other statistical methods was achieved. In this paper, we investigate the potential of extending this approach to a robot swarm with multiple faulty robots. Two experiements have been conducted: A swarm of ten robots with 1 to 8 faulty robots, and a swarm of 10 to 20 robots with varying number of faulty robots. Results from the experiments showed that the proposed approach is able to detect errors in multiple faulty robots. The results also suggest the need to further investigate other aspects of the robot swarm that can potentially affect the performance of detection such as the communication range.</p

Development of a license plate recognition system for a non-ideal environment

A new algorithm for license plate character recognition system is proposed on the basis of Signature analysis properties and features extraction. Signature analysis has been used to locate license plate region and its properties can be further utilised in supporting and affirming the license plate character recognition. This paper presents the implementation of Signature Analysis combined with Features Extraction to form feature vector for each character with a length of 56. Implementation of these two methods is used in tracking of vehicle’s automatic license plate recognition system (ALPR). The developed ALPR comprises of three phase. The recognition stage utilised the vector to be trained in a simple multi-layer feed-forward back-propagation Neural Network with 56 inputs and 34 neurons in its output layer. The network is trained with both ideal and noisy characters. The results obtained show that the proposed system is capable to recognise both ideal and non-ideal license plate characters. The system also capable to tackle the common character misclassification problems due to similarity in characters

Entropic Interactions in Suspensions of Semi-Flexible Rods: Short-Range Effects of Flexibility

We compute the entropic interactions between two colloidal spheres immersed in a dilute suspension of semi-flexible rods. Our model treats the semi-flexible rod as a bent rod at fixed angle, set by the rod contour and persistence lengths. The entropic forces arising from this additional rotational degree of freedom are captured quantitatively by the model, and account for observations at short range in a recent experiment. Global fits to the interaction potential data suggest the persistence length of fd-virus is about two to three times smaller than the commonly used value of $2.2 \mu {m}$.Comment: 4 pages, 5 figures, submitted to PRE rapid communication

Crossover-first differential evolution for improved global optimization in non-uniform search landscapes

The differential evolution (DE) algorithm is currently one of the most widely used evolutionary-based optimizers for global optimization due to its simplicity, robustness and efficiency. The DE algorithm generates new candidate solutions by first conducting the mutation operation which is then followed by the crossover operation. This order of genetic operation contrasts with other evolutionary algorithms where crossover typically precedes mutation. In this study, we investigate the effects of conducting crossover first and then followed by mutation in DE which we named as crossover-first differential evolution (XDE). In order to test this simple and straightforward modification to the DE algorithm, we compared its performance against the original DE algorithm using the CEC2005 global optimization’s set of 25 continuous optimization test problems. The statistical results indicate that the average performance of XDE is better than the original DE and three other well-known global optimizers. This straightforward reversal in the order of the genetic operations in DE can indeed improve its performance, in particular when attempting to solve complex search spaces with highly non-uniform landscapes

Beacon-integrated Attendance App

Taking attendance in class is still practised in many institutions of higher learning. With the advent of technologies, the conventional practice with pen-and-paper is deemed inefficient and time consuming. On top of the possible human-error in taking the attendance and also the ease of tampering with the data, manually taking attendance is very time-consuming. There are many apps developed to tackle these issues. However, many of these apps merely transform the practice from physical pen-and-paper to electronic touch-and-click in which the attendance is still taken by the instructor. In this paper, we propose the use of a beacon device to verify the attendance and it can be configured for automatic attendance taking. On top of that, other functionalities such as attendance report, submission of letter of absent, assign demonstrator/tutor to take attendance, manual attendance for those without smartphones are also included

Exploring Edge-Based Segmentation Towards Automated Skin Lesion Diagnosis

Automated medical diagnosis has many potentials and benefits to support healthcare. Therefore, there is growing number of research on this topic. There are many challenges before automated medical diagnosis is accepted by the healthcare industry and the public as a tool to facilitate healthcare professionals. In this paper, initial work on exploring edge-based segmentation algorithms to identify areas on an image that form the skin lesion is presented. Four edge-segmentation operators namely Canny, Prewitt, Sobel, and Roberts were tested using images from online image database. Experiments show results with mixed accuracy depending on the quality of image as well as the pattern of the skin lesions

Error Detection in Swarm Robotics: A Focus on Adaptivity to Dynamic Environments

This thesis examines the problem of adaptive error detection in swarm robotics. As part of the challenges for the transition of current swarm robotics research into the real world implementation, the ability to differentiate between changes to the behaviour due to faulty components and environmental is important. This is a requirement to ensure that robot swarms deployed are fault-tolerant to internal faults as well as external perturbations. Previous work has investigated this issue from a perspective of a single robot but has largely ignored the aspect of adaptivity to environmental changes. By contrast, this work approaches the problem from a perspective of a collective and explicitly addresses the issue of adaptive detection. A collective self-detection scheme called the CoDe scheme is proposed and developed. This scheme is demonstrated to work in detecting errors in dynamic environments with the use of various classifiers. This approach has potential to be applied for other domains that share similar characteristics to swarm robotics in which adaptivity to dynamic environments is crucial. Motivated by the potential resource limitations in swarm robotic systems, this thesis also investigates other aspects related to minimising resource usage such as reducing the number of false positives and communication overhead

Sustainable Campus: Innovating Attendance Taking with The Use of Beacon-integrated Mobile App

Many institutions of higher learning (IHL) are moving towards the establishment of a sustainable campus. In addition, budget cuts in IHL demand innovative ways of transforming business processes for efficiency and savings. Attendance taking is one of the many routine processes in many settings ranging from seminars, trainings, meetings, workshops, and classes. Although it may seem insignificant, it actually uses huge amount of resources due to its frequency of practice. In any IHL, there can be up to a total of hundreds of meetings, classes, trainings, workshops, and seminars. In addition to the resources for printing, many pen and papers are used. Therefore, re-engineering of this practice can offer cost and time savings. With the advancement of technologies and the ubiquitous of mobile devices, this paper proposes an innovative way of taking attendance with the integration of beacon devices with mobile technologies. A beacon is a device that uses Bluetooth Low Energy to broadcast its universally unique identifier. This new technology offers advantages in terms of cost and indoor positioning over other technogies such as Global Positioning System, QR code, and Radio Frequency Identification