Detection of emerging faults on industrial gas turbines using extended Gaussian mixture models

The paper extends traditional Gaussian Mixture Model (GMM) techniques to provide recognition of operational states and detection of emerging faults for industrial or complex systems. A Variational Bayesian (VB) method allows a GMM to cluster with its Mixture Components (MCs) to facilitate the extraction of steady-state operational behaviour — this is recognised as being a primary factor in reducing the susceptibility of alternative prognostic/diagnostic techniques which can initiate false-alarms resulting from control set-point and load changes. Furthermore, a GMM with an Outlier Component (GMMOC) is discussed and applied for direct fault detection. To demonstrate the efficacy of the proposed techniques, real-time measurements from operational Industrial Gas Turbines (IGTs) show that the resulting VBGMM facilitates the selection of the number of required MCs to cluster the data, and thereby provide essential input for operational signature recognition. Moreover, GMMOC is shown to facilitate the early detection of emerging faults. An advantage of the VBGMM over traditional pre-defined thresholds is the extraction of steady-state data during both full- and part-load cases, and a primary advantage of the GMMOC method is its applicability for novelty detection when there is a lack of prior knowledge of fault patterns. Results based on measurements taken from IGTs operating in the field are therefore also included which show that the techniques provide an integrated pre-processing, benchmarking and novelty/fault detection methodology

SUSIG: an on-line signature database, associated protocols and benchmark results

We present a new online signature database (SUSIG). The database consists of two parts that are collected using different pressure-sensitive tablets ( one with and the other without an LCD display). A total of 100 people contributed to each part, resulting in a database of more than 3,000 genuine signatures and 2,000 skilled forgeries. The genuine signatures in the database are real signatures of the contributors. In collecting skilled forgeries, forgers were shown the signing process on the monitor and were given a chance to practice. Furthermore, for a subset of the forgeries ( highly skilled forgeries), this animation was mapped onto the LCD screen of the tablet so that the forgers could trace over the mapped signature. Forgers in this group were also informed of how close they were to the reference signature, so that they could improve their forgery quality. We describe the signature acquisition process and several verification protocols for this database. We also report the performance of a state-of-the-art signature verification system using the associated protocols. The results show that the highly skilled forgery set is significantly more difficult compared to the skilled forgery set, providing researchers with challenging forgeries. The database is available through http://icproxy.sabanciuniv.edu:215

In-home monitoring system based on WiFi fingerprints for ambient assisted living

This paper presents an in-home monitoring system based on WiFi fingerprints for Ambient Assisted Living. WiFi fingerprints are used to continuously locate a patient at the different rooms in her/his home. The experiments performed provide a correctly location rate of 96% in the best case of all studied scenarios. The behavior obtained by location monitoring allows to detect anomalous behavior such as long stays in rooms out of the common schedule. The main characteristics of the presented system are: a) it is robust enough to work without an own WiFi access point, which in turn means a very affordable solution; b) low obtrusiveness, as it is based on the use of a mobile phone; c) highly interoperable with other wireless connections (bluetooth, RFID) present in current mobile phones; d) alarms are triggered when any anomalous behavior is detected

Source Anonymization of Digital Images: A Counter–Forensic Attack on PRNU based Source Identification Techniques

A lot of photographers and human rights advocates need to hide their identity while sharing their images on the internet. Hence, source–anonymization of digital images has become a critical issue in the present digital age. The current literature contains a number of digital forensic techniques for “source–identification” of digital images, one of the most efficient of them being Photo–Response Non–Uniformity (PRNU) sensor noise pattern based source detection. PRNU noise pattern being unique to every digital camera, such techniques prove to be highly robust way of source–identification. In this paper, we propose a counter–forensic technique to mislead this PRNU sensor noise pattern based source–identification, by using a median filter to suppress PRNU noise in an image, iteratively. Our experimental results prove that the proposed method achieves considerably higher degree of source anonymity, measured as an inverse of Peak–to–Correlation Energy (PCE) ratio, as compared to the state–of–the–art

Providing Databases for Different Indoor Positioning Technologies: Pros and Cons of Magnetic Field and Wi-Fi Based Positioning

Localization is one of the main pillars for indoor services. However, it is still very difficult for the mobile sensing community to compare state-of-the-art indoor positioning systems due to the scarcity of publicly available databases. To make fair and meaningful comparisons between indoor positioning systems, they must be evaluated in the same situation, or in the same sets of situations. In this paper, two databases are introduced for studying the performance of magnetic field and Wi-Fi fingerprinting based positioning systems in the same environment (i.e., indoor area). The “magnetic” database contains more than 40,000 discrete captures (270 continuous samples), whereas the “Wi-Fi” one contains 1,140 ones. The environment and both databases are fully detailed in this paper. A set of experiments is also presented where two simple but effective baselines have been developed to test the suitability of the databases. Finally, the pros and cons of both types of positioning techniques are discussed in detail.The authors gratefully acknowledge funding from the European Union through the GEO-C project (H2020-MSCA-ITN- 2014, Grant Agreement no. 642332, http://www.geo-c.eu/). The authors also gratefully acknowledge funding from the Spanish Ministry of Economy and Competitiveness through the “Metodolog´ıas avanzadas para el diseno, desarrollo, eval- ˜ uacion e integraci ´ on de algoritmos de localizaci ´ on en inte- ´ riores” project (Proyectos I+D Excelencia, codigo TIN2015- ´ 70202-P) and the “Red de Posicionamiento y Navegacion en ´ Interiores” network (Redes de Excelencia, codigo TEC2015- ´ 71426-REDT). The authors would like to thank all the current and past members of the Geospatial Technologies Research Group and Ubik Geospatial Solutions S.L. for their valuable help in creating the SmartUJI platform and providing us with the supporting services that allowed integrating the existing GIS services in the applications developed to create both databases