TERASENSE: THz device technology laboratory: final summary

The use of THz frequencies, particularly W and G band allows reaching higher resolution and deeper penetration in emerging applications like imaging, sensing, etc. The development of those new applications lays on reliable technologies, background of expertise and know-how. The CDS2008-00068 TERASENSE CONSOLIDER project has given the opportunity to extent upwards in frequency the previous background of the microwaves research group partners. This article summarizes the developments of the TERASENSE work package “THz Device Technology Laboratory”.This work was supported by the Spanish Ministerio de Ciencia e Innovación through the CONSOLIDER-INGENIO 2010 program reference CSD2008-00068 TERASENSE

Novel neural approaches to data topology analysis and telemedicine

1noL'abstract è presente nell'allegato / the abstract is in the attachmentopen676. INGEGNERIA ELETTRICAnoopenRandazzo, Vincenz

Optical image compression and encryption methods

International audienceOver the years extensive studies have been carried out to apply coherent optics methods in real-time communications and image transmission. This is especially true when a large amount of information needs to be processed, e.g., in high-resolution imaging. The recent progress in data-processing networks and communication systems has considerably increased the capacity of information exchange. However, the transmitted data can be intercepted by nonauthorized people. This explains why considerable effort is being devoted at the current time to data encryption and secure transmission. In addition, only a small part of the overall information is really useful for many applications. Consequently, applications can tolerate information compression that requires important processing when the transmission bit rate is taken into account. To enable efficient and secure information exchange, it is often necessary to reduce the amount of transmitted information. In this context, much work has been undertaken using the principle of coherent optics filtering for selecting relevant information and encrypting it. Compression and encryption operations are often carried out separately, although they are strongly related and can influence each other. Optical processing methodologies, based on filtering, are described that are applicable to transmission and/or data storage. Finally, the advantages and limitations of a set of optical compression and encryption methods are discussed

Implementation of Middleware for Internet of Things in Asset Tracking Applications: In-lining Approach

ThesisInternet of Things (IoT) is a concept that involves giving objects a digital identity and limited artificial intelligence, which helps the objects to be interactive, process data, make decisions, communicate and react to events virtually with minimum human intervention. IoT is intensified by advancements in hardware and software engineering and promises to close the gap that exists between the physical and digital worlds. IoT is paving ways to address complex phenomena, through designing and implementation of intelligent systems that can monitor phenomena, perform real-time data interpretation, react to events, and swiftly communicate observations. The primary goal of IoT is ubiquitous computing using wireless sensors and communication protocols such as Bluetooth, Wireless Fidelity (Wi-Fi), ZigBee and General Packet Radio Service (GPRS). Insecurity, of assets and lives, is a problem around the world. One application area of IoT is tracking and monitoring; it could therefore be used to solve asset insecurity. A preliminary investigation revealed that security systems in place at Central University of Technology, Free State (CUT) are disjointed; they do not instantaneously and intelligently conscientize security personnel about security breaches using real time messages. As a result, many assets have been stolen, particularly laptops. The main objective of this research was to prove that a real-life application built over a generic IoT architecture that innovatively and intelligently integrates: (1) wireless sensors; (2) radio frequency identification (RFID) tags and readers; (3) fingerprint readers; and (4) mobile phones, can be used to dispel laptop theft. To achieve this, the researcher developed a system, using the heterogeneous devices mentioned above and a middleware that harnessed their unique capabilities to bring out the full potential of IoT in intelligently curbing laptop theft. The resulting system has the ability to: (1) monitor the presence of a laptop using RFID reader that pro-actively interrogates a passive tag attached to the laptop; (2) detect unauthorized removal of a laptop under monitoring; (3) instantly communicate security violations via cell phones; and (4) use Windows location sensors to track the position of a laptop using Googlemaps. The system also manages administrative tasks such as laptop registration, assignment and withdrawal which used to be handled manually. Experiments conducted using the resulting system prototype proved the hypothesis outlined for this research

Ridge orientation modeling and feature analysis for fingerprint identification

This thesis systematically derives an innovative approach, called FOMFE, for fingerprint ridge orientation modeling based on 2D Fourier expansions, and explores possible applications of FOMFE to various aspects of a fingerprint identification system. Compared with existing proposals, FOMFE does not require prior knowledge of the landmark singular points (SP) at any stage of the modeling process. This salient feature makes it immune from false SP detections and robust in terms of modeling ridge topology patterns from different typological classes. The thesis provides the motivation of this work, thoroughly reviews the relevant literature, and carefully lays out the theoretical basis of the proposed modeling approach. This is followed by a detailed exposition of how FOMFE can benefit fingerprint feature analysis including ridge orientation estimation, singularity analysis, global feature characterization for a wide variety of fingerprint categories, and partial fingerprint identification. The proposed methods are based on the insightful use of theory from areas such as Fourier analysis of nonlinear dynamic systems, analytical operators from differential calculus in vector fields, and fluid dynamics. The thesis has conducted extensive experimental evaluation of the proposed methods on benchmark data sets, and drawn conclusions about strengths and limitations of these new techniques in comparison with state-of-the-art approaches. FOMFE and the resulting model-based methods can significantly improve the computational efficiency and reliability of fingerprint identification systems, which is important for indexing and matching fingerprints at a large scale

Dense light field coding: a survey

Light Field (LF) imaging is a promising solution for providing more immersive and closer to reality multimedia experiences to end-users with unprecedented creative freedom and flexibility for applications in different areas, such as virtual and augmented reality. Due to the recent technological advances in optics, sensor manufacturing and available transmission bandwidth, as well as the investment of many tech giants in this area, it is expected that soon many LF transmission systems will be available to both consumers and professionals. Recognizing this, novel standardization initiatives have recently emerged in both the Joint Photographic Experts Group (JPEG) and the Moving Picture Experts Group (MPEG), triggering the discussion on the deployment of LF coding solutions to efficiently handle the massive amount of data involved in such systems. Since then, the topic of LF content coding has become a booming research area, attracting the attention of many researchers worldwide. In this context, this paper provides a comprehensive survey of the most relevant LF coding solutions proposed in the literature, focusing on angularly dense LFs. Special attention is placed on a thorough description of the different LF coding methods and on the main concepts related to this relevant area. Moreover, comprehensive insights are presented into open research challenges and future research directions for LF coding.info:eu-repo/semantics/publishedVersio

Parkinson’s disease diagnosis using convolutional neural networks and figure-copying tasks

Parkinson’s disease (PD) is a progressive neurodegenerative disorder that causes abnormal movements and an array of other symptoms. An accurate PD diagnosis can be a challenging task as the signs and symptoms, particularly at an early stage, can be similar to other medical conditions or the physiological changes of normal ageing. This work aims to contribute to the PD diagnosis process by using a convolutional neural network, a type of deep neural network architecture, to differentiate between healthy controls and PD patients. Our approach focuses on discovering deviations in patient’s movements with the use of drawing tasks. In addition, this work explores which of two drawing tasks, wire cube or spiral pentagon, are more effective in the discrimination process. With $93.5\%$ accuracy, our convolutional classifier, trained with images of the pentagon drawing task and augmentation techniques, can be used as an objective method to discriminate PD from healthy controls. Our compact model has the potential to be developed into an offline real-time automated single-task diagnostic tool, which can be easily deployed within a clinical setting

Passive low frequency RFID for non-destructive evaluation and monitoring

Ph. D ThesisDespite of immense research over the years, defect monitoring in harsh environmental conditions still presents notable challenges for Non-Destructive Testing and Evaluation (NDT&E) and Structural Health Monitoring (SHM). One of the substantial challenges is the inaccessibility to the metal surface due to the large stand-off distance caused by the insulation layer. The hidden nature of corrosion and defect under thick insulation in harsh environmental conditions may result in it being not noticed and ultimately leading to failures. Generally electromagnetic NDT&E techniques which are used in pipeline industries require the removal of the insulation layer or high powered expensive equipment. Along with these, other limitations in the existing techniques create opportunities for novel systems to solve the challenges caused by Corrosion under Insulation (CUI). Extending from Pulsed Eddy Current (PEC), this research proposes the development and use of passive Low Frequency (LF) RFID hardware system for the detection and monitoring of corrosion and cracks on both ferrous and non-ferrous materials at varying high temperature conditions. The passive, low cost essence of RFID makes it an enchanting technique for long term condition monitoring. The contribution of the research work can be summarised as follows: (1) implementation of novel LF RFID sensor systems and the rig platform, experimental studies validating the detection capabilities of corrosion progression samples using transient feature analysis with respect to permeability and electrical conductivity changes along with enhanced sensitivity demonstration using ferrite sheet attached to the tag; (2) defect detection using swept frequency method to study the multiple frequency behaviour and further temperature suppression using feature fusion technique; (3) inhomogeneity study on ferrous materials at varying temperature and demonstration of the potential of the RFID system; (4) use of RFID tag with ceramic filled Poly-tetra-fluoro-ethyulene (PTFE) substrate for larger applicability of the sensing system in the industry; (5) lift-off independent defect monitoring using passive sweep frequency RFID sensors and feature extraction and fusion for robustness improvement. This research concludes that passive LF RFID system can be used to detect corrosion and crack on both ferrous and non-ferrous materials and then the system can be used to compensate for temperature variation making it useful for a wider range of applications. However, significant challenges such as permanent deployment of the tags for long term monitoring at higher temperatures and much higher standoff distance, still require improvement for real-world applicability.Engineering and Physical Sciences Research Council (EPSRC) CASE, National Nuclear Laboratory (NNL)

Measuring Information Security Awareness Efforts in Social Networking Sites – A Proactive Approach

For Social Network Sites to determine the effectiveness of their Information Security Awareness (ISA) techniques, many measurement and evaluation techniques are now in place to ensure controls are working as intended. While these techniques are inexpensive, they are all incident- driven as they are based on the occurrence of incident(s). Additionally, they do not present a true reflection of ISA since cyber-incidents are hardly reported. They are therefore adjudged to be post-mortem and risk permissive, the limitations that are inacceptable in industries where incident tolerance level is low. This paper aims at employing a non-incident statistic approach to measure ISA efforts. Using an object- oriented programming approach, PhP is employed as the coding language with MySQL database engine at the back-end to develop sOcialistOnline – a Social Network Sites (SNS) fully secured with multiple ISA techniques. Rather than evaluating the effectiveness of ISA efforts by success of attacks or occurrence of an event, password scanning is implemented to proactively measure the effects of ISA techniques in sOcialistOnline. Thus, measurement of ISA efforts is shifted from detective and corrective to preventive and anticipatory paradigms which are the best forms of information security approach