A brief network analysis of Artificial Intelligence publication

In this paper, we present an illustration to the history of Artificial Intelligence(AI) with a statistical analysis of publish since 1940. We collected and mined through the IEEE publish data base to analysis the geological and chronological variance of the activeness of research in AI. The connections between different institutes are showed. The result shows that the leading community of AI research are mainly in the USA, China, the Europe and Japan. The key institutes, authors and the research hotspots are revealed. It is found that the research institutes in the fields like Data Mining, Computer Vision, Pattern Recognition and some other fields of Machine Learning are quite consistent, implying a strong interaction between the community of each field. It is also showed that the research of Electronic Engineering and Industrial or Commercial applications are very active in California. Japan is also publishing a lot of papers in robotics. Due to the limitation of data source, the result might be overly influenced by the number of published articles, which is to our best improved by applying network keynode analysis on the research community instead of merely count the number of publish.Comment: 18 pages, 7 figure

Proposal of a health care network based on big data analytics for PDs

Health care networks for Parkinson's disease (PD) already exist and have been already proposed in the literature, but most of them are not able to analyse the vast volume of data generated from medical examinations and collected and organised in a pre-defined manner. In this work, the authors propose a novel health care network based on big data analytics for PD. The main goal of the proposed architecture is to support clinicians in the objective assessment of the typical PD motor issues and alterations. The proposed health care network has the ability to retrieve a vast volume of acquired heterogeneous data from a Data warehouse and train an ensemble SVM to classify and rate the motor severity of a PD patient. Once the network is trained, it will be able to analyse the data collected during motor examinations of a PD patient and generate a diagnostic report on the basis of the previously acquired knowledge. Such a diagnostic report represents a tool both to monitor the follow up of the disease for each patient and give robust advice about the severity of the disease to clinicians

Fibre Optic-Based Force Sensor for Bio-Mimetic Robotic Finger

A novel optical-based fingertip force sensor, which is integrated in a bio-mimetic finger for robotic and prosthetic manipulation is presented. This is used to obtain tactile information during grasping and manipulation of objects. Unlike most devices the proposed force sensor is free of any electrical and metal components and as such is immune to electromagnetic fields. The sensor is simple and very compact, has extremely low power consumption and noise levels and requires no additional hardware. It is based on a cantilever design combined with fiber optics and is integrated on the distal phalange of a robotic finger. The unique design of this sensor makes it ideally suited for use in messy or harsh environments that may be prone to electromagnetic fields, granular or liquid intrusion, may include combustible gasses or be subject to radiatio

A Novel Bioinspired PVDF Micro/Nano Hair Receptor for a Robot Sensing System

This paper describes the concept and design of a novel artificial hair receptor for the sensing system of micro intelligent robots such as a cricket-like jumping mini robot. The concept is inspired from the natural hair receptor of animals, also called cilium or filiform hair by different research groups, which is usually used as a vibration receptor or a flow detector by insects, mammals and fishes. The suspended fiber model is firstly built and the influence of scaling down is analyzed theoretically. The design of this artificial hair receptor is based on aligned suspended PVDF (polyvinylidene fluoride) fibers, manufactures with a novel method called thermo-direct drawing technique, and aligned suspended submicron diameter fibers are thus successfully fabricated on a flexible Kapton. In the post process step, some key problems such as separated electrodes deposition along with the fiber drawing direction and poling of micro/nano fibers to impart them with good piezoeffective activity have been presented. The preliminary validation experiments show that the artificial hair receptor has a reliable response with good sensibility to external pressure variation and, medium flow as well as its prospects in the application on sensing system of mini/micro bio-robots

Toward a Memory Model for Autonomous Topological Mapping and Navigation: the Case of Binary Sensors and Discrete Actions

We propose a self-organizing database for per- ceptual experience capable of supporting autonomous goal- directed planning. The main contributions are: (i) a formal demonstration that the database is complex enough in principle to represent the homotopy type of the sensed environment; (ii) some initial steps toward a formal demonstration that the database offers a computationally effective, contractible approximation suitable for motion planning that can be ac- cumulated purely from autonomous sensory experience. The provable properties of an effectively trained data-base exploit certain notions of convexity that have been recently generalized for application to a symbolic (discrete) representation of subset nesting relations. We conclude by introducing a learning scheme that we conjecture (but cannot yet prove) will be capable of achieving the required training, assuming a rich enough exposure to the environment. For more information: Kod*La

Ultrasonic Single Element and Sectorized Array Transducers with Omnidirectional 2D Field Distribution for Non-Contact Human-Machine Interface and Echo-Location

This work discusses the possibilities of some novel applications for the high frequency (200 kHz–500 kHz), high sensitivity (-20 dB– -35 dB) and wide band (> 50 % @ -20 dB) air-coupled transducers that have been used so far for nondestructive testing and materials characterization at CSIC. These applications refer to non-contact human-machine interfaces, gesture recognition and echolocation. Compared with other technologies, the relatively higher frequency and bandwidth permit to achieve better resolution and the higher sensitivity permit to reach longer distances. In addition, this later feature also permits to reduce the number of transducers. This is achieved by using a conical reflector that provides an omnidirectional (2D) acoustic field. Examples of applications and realizations are shown by using single element 250 kHz transducers; and 8-elements 400 kHz sectorized array transducers. This later type of air-coupled array is introduced here for the first time

Intelligent Sensing for Robotic Re-Manufacturing in Aerospace - An Industry 4.0 Design Based Prototype

Emerging through an industry-academia collaboration between the University of Sheffield and VBC Instrument Engineering Ltd, a proposed robotic solution for remanufacturing of jet engine compressor blades is under ongoing development, producing the first tangible results for evaluation. Having successfully overcome concept adaptation, funding mechanisms, design processes, with research and development trials, the stage of concept optimization and end-user application has commenced. A variety of new challenges is emerging, with multiple parameters requiring control and intelligence. An interlinked collaboration between operational controllers, Quality Assurance (QA) and Quality Control (QC) systems, databases, safety and monitoring systems, is creating a complex network, transforming the traditional manual re-manufacturing method to an advanced intelligent modern smart-factory. Incorporating machine vision systems for characterization, inspection and fault detection, alongside advanced real-time sensor data acquisition for monitoring and evaluating the welding process, a huge amount of valuable industrial data is produced. Information regarding each individual blade is combined with data acquired from the system, embedding data analytics and the concept of ìInternet of Thingsî (IoT) into the aerospace re-manufacturing industry. The aim of this paper is to give a first insight into the challenges of the development of an Industry 4.0 prototype system and an evaluation of first results of the operational prototype

Towards a cyber physical system for personalised and automatic OSA treatment

Obstructive sleep apnea (OSA) is a breathing disorder that takes place in the course of the sleep and is produced by a complete or a partial obstruction of the upper airway that manifests itself as frequent breathing stops and starts during the sleep. The real-time evaluation of whether or not a patient is undergoing OSA episode is a very important task in medicine in many scenarios, as for example for making instantaneous pressure adjustments that should take place when Automatic Positive Airway Pressure (APAP) devices are used during the treatment of OSA. In this paper the design of a possible Cyber Physical System (CPS) suited to real-time monitoring of OSA is described, and its software architecture and possible hardware sensing components are detailed. It should be emphasized here that this paper does not deal with a full CPS, rather with a software part of it under a set of assumptions on the environment. The paper also reports some preliminary experiments about the cognitive and learning capabilities of the designed CPS involving its use on a publicly available sleep apnea database

3D Printable Sensorized Soft Gelatin Hydrogel for Multi-Material Soft Structures

The ability to 3D print soft materials with integrated strain sensors enables significant flexibility for the design and fabrication of soft robots. Hydrogels provide an interesting alternative to traditional soft robot materials, allowing for more varied fabrication techniques. In this work, we investigate the 3D printing of a gelatin-glycerol hydrogel, where transglutaminase is used to catalyse the crosslinking of the hydrogel such that its material properties can be controlled for 3D printing. By including electron-conductive elements (aqueous carbon black) in the hydrogel we can create highly flexible and linear soft strain sensors. We present a first investigation into adapting a desktop 3D printer and optimizing its control parameters to fabricate sensorized 2D and 3D structures which can undergo >300% strain and show a response to strain which is highly linear and synchronous. To demonstrate the capabilities of this material and fabrication approach, we produce some example 2D and 3D structures and show their sensing capabilities