A Framework for Controlling Wheelchair Motion by using Gaze Information

Users with severe motor ability are unable to control their wheelchair using standard joystick and hence an alternative control input is preferred. In this paper a method on how to enable the severe impairment user to control a wheelchair via gaze information is proposed. Since when using such an input, the navigation burden for the user is significantly increased, an assistive navigation platform is also proposed to reduce the user burden. Initially, user information is inferred using a camera and a bite-like switch. Then information from the environment is obtained using combination of laser and Kinect sensors. Eventually, both information from the environment and the user is analyzed to decide the final control operation that according to the user intention and safe from collision. Experimental results demonstrate the feasibility of the proposed approach

Robot creativity: humanlike behaviour in the robot-robot interaction

Artificial Intelligence development is mainly directed toward imitat­ing human reasoning and performing different tasks. For that purpose, related software and program solution where artificial intelligence is used have mostly thinking abilities. However, there are many questions to answer in ongoing AI research, especially when we come to the point which is addressing humanlike behaviour and reasoning triggered by emotions. In this paper, we are presenting an interactive installation Botorikko: Machine Create State, which is part of the Syntropic Counterpoints art/research project. We are exposing AI cyber clones to some of the fundamental questions for humankind and challenge their creativity. The robots are trained by using the publications Machiavelli and Sun Tzu and confronted to the crucial questions related to moral, ethic, strategy, politics, diplo­macy, war etc. We are using a recurrent neural network (RNN) and robot-robot interaction to trigger unsupervised robot creativity and humanlike behaviour on generated machine-made content

Development of Human Fall Detection System using Joint Height, Joint Velocity, and Joint Position from Depth Maps

Human falls are a major health concern in many communities in today’s aging population. There are different approaches used in developing fall detection system such as some sort of wearable, ambient sensor and vision based systems. This paper proposes a vision based human fall detection system using Kinect for Windows. The generated depth stream from the sensor is used in the proposed algorithm to differentiate human fall from other activities based on human Joint height, joint velocity and joint positions. From the experimental results our system was able to achieve an average accuracy of 96.55% with a sensitivity of 100% and specificity of 95

Implementation of Robot Operating System in Beaglebone Black based Mobile Robot for Obstacle Avoidance Application

The Robot Operating System (ROS) is a collection of tools, libraries, and conventions that focus on simplifying the task of creating a complex and advanced robotics system. Its standard framework can be shared with another robotics system that has a similar platform and suitable for being introduced as an educational tool in robotics. However, the problems found out in the current robot platform available in the market are expensive and encapsulated. The development of an open source robot platform is encouraged. Therefore, this research is carried out to design and develop an ROS based obstacle avoidance system for existing differential-wheeled mobile robot. The ROS was installed under Ubuntu 14.04 on a Beaglebone Black embedded computer system. Then, the ROS was implemented together with the obstacle avoidance system to establish the communication between program nodes. The mobile robot was then designed and developed to examine the obstacle avoidance application. The debugging process was carried out to check the obstacle avoidance system application based on the communication between nodes. This process is important in examining the message publishing and subscribing from all nodes. The obstacle avoidance mobile robot has been successfully tested where the communication between nodes was running without any problem

Deep transfer learning application for automated ischemic classification in posterior fossa CT images

Abstract—Computed Tomography (CT) imaging is one of the conventional tools used to diagnose ischemic in Posterior Fossa (PF). Radiologist commonly diagnoses ischemic in PF through CT imaging manually. However, such a procedure could be strenuous and time consuming for large scale images, depending on the expertise and ischemic visibility. With the rapid development of computer technology, automatic image classification based on Machine Learning (ML) is widely been developed as a second opinion to the ischemic diagnosis. The practical performance of ML is challenged by the emergence of deep learning applications in healthcare. In this study, we evaluate the performance of deep transfer learning models of Convolutional Neural Network (CNN); VGG-16, GoogleNet and ResNet-50 to classify the normal and abnormal (ischemic) brain CT images of PF. This is the first study that intensively studies the application of deep transfer learning for automated ischemic classification in the posterior part of brain CT images. The experimental results show that ResNet-50 is capable to achieve the highest accuracy performance in comparison to other proposed models. Overall, this automatic classification provides a convenient and time-saving tool for improving medical diagnosis

Web-based reward and redemption system for smart recyle system

The Recycling rate among developing nation is very low and the number of waste is increasing every day.Although many steps have been taken such as through national campaign, yet the recycle rate remains unchanged especially in Malaysia.Thus, the smart recycle bin is proposed to give a reward to public user who thrown the recyclable waste into the innovated smart recycle bin by giving points (later can be converted to money).This paper discussed the development of reward-based smart recycle system.The system has been implemented in a web-based environment and it supports for public user and waste authority.The system is then to be integrated with the desktop-based applications for waste authority to manage the point and transaction from the innovated recycle bin to the reward system

Design and Simulation Study of Excitation Coil System with Different Array Configurations for Magnetic Particle Imaging Application

Magnetic Particle Imaging (MPI) is a tomographic imaging method has been introduced for three-dimensional (3D) imaging of human body with some potential applications such as magnetic hyperthermia and cancer imaging. It involves three important elements; tracer development using magnetic nanoparticles (MNPs), hardware realization (scanner using excitation and pickup coils), and image reconstruction optimization. Their combination will produce a high-quality image taken from any biological tissue in the human body based on the secondary magnetic field signal from the magnetized MNPs that are injected into human body. A homogeneous and adequate magnetic field strength from an excitation coil is needed to enhance the quality of the secondary signal. However, the complex surface topography of human body and physical properties of an excitation coil influence the strength and the homogeneity of the magnetic field generation at the MNPs. Therefore, this paper presents a new concept of excitation coil configuration to improve the magnetic field strength and the homogeneity to obtain better magnetization of MNPs to be detected in MPI. Two designs will be proposed with variation in physical properties and coil arrangement based on simulation study that will be carried out by using ANSYS Maxwell to generate magnetic field strength and homogeneity towards the targeted distance of 10 mm – 50 mm below the coils. The obtained magnetic field from the simulation was validated by the mathematical calculation using Biot-Savart Law equation. As a result, the new concept of excitation coil configuration proposed can be used to improve the MPI scanner system performance for various medical application

Cross validation analysis of convolutional neural network variants with various white blood cells datasets for the classification task

White Blood Cells (WBCs) analysis is an important procedure to detect diseases is that closely related to human immunity system. Manual WBCs analysis is laborious and hence computer aided system (CAD) is a better option to alleviate the shortcoming. Since conventional segmentation�classification approach is tedious to configure, a Convolutional Neural Network (CNN) become recent trend for WBCs classification. Previously, there are many works proposed for WBCs identification. However, the models that can be generalised to works well among various datasets is remain vague. In this paper, an analysis of various CNN models which are simple Alexnet, embedded friendly Mobilenet, inception based Googlenet, systematic architecture VGG�16 and skip connection based model (Resnet & Densenet), are tested with three major WBCs datasets (Kaggle, LISC and IDB-2). From the rigorous experi�ments, it can be concluded that simple CNN model of Alexnet performs well across all three datasets with 98.08% accuracy on Kaggle, 96.34% accuracy on IDB-2 and 84.52% on LISC. This outcome can be utilise as a basis to improve the CNN classification model that can be generalize to works under various WBCs datasets

GSM-based notification system and location tagging using GPS for smart recycle bin

This paper describe the design and development of a system to detect the level of recyclable waste in a smart recycle bin and then send notification signals including the locations coordinate to assist the authority to collect and empty the bin. At present, the current system does not provide a notification system mechanism to inform the waste authority that the recycle bin is full and need to be collected. Therefore, an automatic notification system is proposed as to reduce and optimize the collection time. This could also assist the waste collector to re-schedule the collection time and place depending on the regularity of the signal received. This could also reduce the manual collection process which require time and cost of labor. The development of the system involved the use of GSM module to enable the SMS text notification system and some software to manage all the notification received from the bin