Encrypted statistical machine learning: new privacy preserving methods

We present two new statistical machine learning methods designed to learn on fully homomorphic encrypted (FHE) data. The introduction of FHE schemes following Gentry (2009) opens up the prospect of privacy preserving statistical machine learning analysis and modelling of encrypted data without compromising security constraints. We propose tailored algorithms for applying extremely random forests, involving a new cryptographic stochastic fraction estimator, and na\"{i}ve Bayes, involving a semi-parametric model for the class decision boundary, and show how they can be used to learn and predict from encrypted data. We demonstrate that these techniques perform competitively on a variety of classification data sets and provide detailed information about the computational practicalities of these and other FHE methods.Comment: 39 page

An analysis of the Afrikaans telephonic descriptors of cardiac arrest in a Western Cape Emergency Control centre

Introduction: Out of Hospital Cardiac Arrest (OHCA) is a time-sensitive emergency which requires prompt identification and emergency care in order to reduce morbidity and mortality. The first step in recognising OHCA is rapid identification by the emergency dispatch centre. Identification of such patients remains challenging in South Africa due to multiple languages and widely differing levels of education. This study aimed to identify the key descriptors (words and phrases) of OHCA used by callers speaking Afrikaans when contacting the emergency dispatch centre of the Western Cape Provincial Emergency Medical Services (WC-EMS). Methodology: Computer-aided dispatch (CAD) data with a corresponding “patient unresponsive” incident type were drawn for a 12 month period (January – December 2018). Corresponding patient care records were extracted to verify OHCA. The original voice recordings between the caller and emergency call taker at the time of the emergency were extracted and transcribed verbatim. Transcriptions were subjected to inductive, qualitative content analysis to the manifest level. Descriptors of OHCA in Afrikaans calls were coded, categorised and quantified. Results: A total of 729 confirmed OHCA cases were identified, of which 36 (5%) were in Afrikaans and eligible for analysis. Following content analysis, 83 distinct codes in six categories were identified. The most prevalent categories were descriptors related to Respiratory Effort (apnoea and difficulty in breathing; 30.1%) (30.1%), Clinical Features (related to the eyes, mouth and body temperature; 20.4%) and Cardiac Activity (pulselessness; 16.8%). Conclusion Afrikaans Callers within the Western Cape province of South Africa use consistent descriptors when requesting and ambulance for OHCA. Future studies should focus on describing descriptors for other languages commonly spoken in the province, and to develop and validate telephonic OHCA recognition algorithms

Connecting knowledge to power: the future of digital democracy in the UK

Since its invention, the internet has been considered a ‘game-changer’ when it comes to democracy, with a worldwide network providing the potential to create a truly participatory democracy. This has yet to happen, but numerous individuals and groups are beginning to ask what can be done to marry the internet with representative democracy, including the Speaker of the House of Commons. Here, Chris Waller and Louis Reynolds discuss an exciting new project which seeks to use a wiki approach to crowdsource a submission to the Speaker’s Commission on Digital Democracy

Predicting memory formation over multiple study episodes

Repeated study typically improves episodic memory performance. Two different types of explanations of this phenomenon have been put forward: 1) reactivating the same representations strengthens and stabilizes memories, or 2) greater encoding variability benefits memory by promoting richer traces. The present experiment directly compared these predictions in a design with multiple repeated study episodes, allowing to dissociate memory for studied items and their context of study. Participants repeatedly encoded names of famous people four times, either in the same task, or in different tasks. During the test phase, an old/new judgement task was used to assess item memory, followed by a source memory judgement about the encoding task. Consistent with predictions from the encoding variability view, encoding stimulus in different contexts resulted in higher item memory. In contrast, consistent with the reactivation view, source memory performance was higher when participants encoded stimuli in the same task repeatedly. Taken together, our findings indicate that encoding variability benefits episodic memory, by increasing the number of items that are recalled. These benefits are however at the expenses of source recollection and memory for details, which are decreased, likely due to interference and generalisation across contexts

Light Field Morphable Models

Statistical shape and texture appearance models are powerful image representations, but previously had been restricted to 2D or simple 3D shapes. In this paper we present a novel 3D morphable model based on image-based rendering techniques, which can represent complex lighting conditions, structures, and surfaces. We describe how to construct a manifold of the multi-view appearance of an object class using light fields and show how to match a 2D image of an object to a point on this manifold. In turn we use the reconstructed light field to render novel views of the object. Our technique overcomes the limitations of polygon based appearance models and uses light fields that are acquired in real-time

Development of PDT/PET theranostics: synthesis and biological evaluation of an ¹⁸F-radiolabeled water soluble porphyrin

Synthesis of the first water-soluble porphyrin radiolabeled with fluorine-18 is described: a new molecular theranostic agent which integrates the therapeutic selectivity of photodynamic therapy (PDT) with the imaging efficacy of positron emission tomography (PET). Generation of the theranostic was carried out through the conjugation of a cationic water-soluble porphyrin bearing an azide functionality to a fluorine-18 radiolabeled prosthetic bearing an alkyne functionality through click conjugation, with excellent yields obtained in both cold and hot synthesis. Biological evaluation of the synthesized structures shows the first example of an 18 F-radiolabeled porphyrin retaining photocytotoxicity following radiolabeling and demonstrable conjugate uptake and potential application as a radiotracer in vivo. The promising results gained from biological evaluation demonstrate the potential of this structure as a clinically relevant theranostic agent, offering exciting possibilities for the simultaneous imaging and photodynamic treatment of tumors

Multiple-Input Multiple-Output Rayleigh Flat Fading Outage Capacity using Channel Estimation

Upper and lower bounds on the outage capacity for a multiple-input multiple-output (MIMO) Rayleigh flat fading wireless baseband communication environment are derived for the case when the channel is completely unknown at the transmitter and the receiver has access to channel state information (CSI) via pilot estimation. The bounds show that the channel estimation error significantly impacts the outage capacity. A change in the outage probability is also shown to have a larger impact on the outage capacity when the channel estimation error is small. To get an idea of how these bounds are affected by a temporally correlated channel, they are calculated when pilot symbol assisted modulation (PSAM) is employed. When the doppler frequency of the channel is increased, the outage capacity deteriorates quicker