Author Correction: Proton range verification with MACACO II Compton camera enhanced by a neural network for event selection (vol 11, 23903, 2021)

The applicability extent of hadron therapy for tumor treatment is currently limited by the lack of reliable online monitoring techniques. An active topic of investigation is the research of monitoring systems based on the detection of secondary radiation produced during treatment. MACACO, a multi-layer Compton camera based on LaBr3 scintillator crystals and SiPMs, is being developed at IFIC-Valencia for this purpose. This work reports the results obtained from measurements of a 150 MeV proton beam impinging on a PMMA target. A neural network trained on Monte Carlo simulations is used for event selection, increasing the signal to background ratio before image reconstruction. Images of the measured prompt gamma distributions are reconstructed by means of a spectral reconstruction code, through which the 4.439 MeV spectral line is resolved. Images of the emission distribution at this energy are reconstructed, allowing calculation of the distal fall-off and identification of target displacements of 3 mm

Laser-Accelerated proton beams as diagnostics for cultural heritage

This paper introduces the first use of laser-generated proton beams as diagnostic for materials of interest in the domain of Cultural Heritage. Using laser-accelerated protons, as generated by interaction of a high-power short-pulse laser with a solid target, we can produce proton-induced X-ray emission spectroscopies (PIXE). By correctly tuning the proton flux on the sample, we are able to perform the PIXE in a single shot without provoking more damage to the sample than conventional methodologies. We verify this by experimentally irradiating materials of interest in the Cultural Heritage with laser-accelerated protons and measuring the PIXE emission. The morphological and chemical analysis of the sample before and after irradiation are compared in order to assess the damage provoked to the artifact. Montecarlo simulations confirm that the temperature in the sample stays safely below the melting point. Compared to conventional diagnostic methodologies, laser-driven PIXE has the advantage of being potentially quicker and more efficien

Search Heuristics, Case-Based Reasoning and Software Project Effort Prediction

This paper reports on the use of search techniques to help optimise a case-based reasoning (CBR) system for predicting software project effort. A major problem, common to ML techniques in general, has been dealing with large numbers of case features, some of which can hinder the prediction process. Unfortunately searching for the optimal feature subset is a combinatorial problem and therefore NP-hard. This paper examines the use of random searching, hill climbing and forward sequential selection (FSS) to tackle this problem. Results from examining a set of real software project data show that even random searching was better than using all available for features (average error 35.6% rather than 50.8%). Hill climbing and FSS both produced results substantially better than the random search (15.3 and 13.1% respectively), but FSS was more computationally efficient. Providing a description of the fitness landscape of a problem along with search results is a step towards the classification of search problems and their assignment to optimum search techniques. This paper attempts to describe the fitness landscape of this problem by combining the results from random searches and hill climbing, as well as using multi-dimensional scaling to aid visualisation. Amongst other findings, the visualisation results suggest that some form of heuristic-based initialisation might prove useful for this problem

Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

A deep, narrow J-band search for proto-galactic Lyman Alpha emission at redshifts z~9

We present a deep, narrow J-band search for proto--galactic Lyman Alpha emission at redshifts z~9. We combine an exceptionally deep image of the Hubble Deep Field South, obtained using a narrow band filter centred on the wavelength 1.187 microns using the VLT/ISAAC facility, with existing deep, broad band images covering optical to near infrared wavelengths. We search for z~9 Lyman Alpha emitting galaxies displaying a significant narrow band excess relative to the Js-band that are undetected at optical wavelengths. We detect no sources consistent with this criterion to the 90% point source flux limit of the NB image, F_{NB} = 3.28 x 10^{-18} ergs/s/cm2. The survey selection function indicates that we have sampled a volume of approximately 340 h^{-3} Mpc^3 to a Lyman Alpha emission luminosity of 10^{43} h^{-2} ergs/s. We conclude by considering the potential implications for the physics of the high--redshift universe.Comment: 11 pages, accepted MNRAS. Please note that the automatic postscript generation may result in a corrupted postscript file. Please use ftp://astroftp.phys.uvic.ca/pub/jwillis/jwillis_zen1.ps.gz to obtain an uncorrupted versio