Projections Onto Convex Sets (POCS) Based Optimization by Lifting

Two new optimization techniques based on projections onto convex space (POCS) framework for solving convex and some non-convex optimization problems are presented. The dimension of the minimization problem is lifted by one and sets corresponding to the cost function are defined. If the cost function is a convex function in R^N the corresponding set is a convex set in R^(N+1). The iterative optimization approach starts with an arbitrary initial estimate in R^(N+1) and an orthogonal projection is performed onto one of the sets in a sequential manner at each step of the optimization problem. The method provides globally optimal solutions in total-variation, filtered variation, l1, and entropic cost functions. It is also experimentally observed that cost functions based on lp, p<1 can be handled by using the supporting hyperplane concept

Content-adaptive color transform for image compression

Cataloged from PDF version of article.In this paper, an adaptive color transform for image compression is introduced. In each block of the image, coefficients of the color transform are determined from the previously compressed neighboring blocks using weighted sums of the RGB pixel values, making the transform block-specific. There is no need to transmit or store the transform coeffi- cients because they are estimated from previous blocks. The compression efficiency of the transform is demonstrated using the JPEG image coding scheme. In general, the suggested transformation results in better peak signal-to-noise ratio (PSNR) values for a given compression level. ( C) 2011 Society of Photo-Optical Instrumentation Engineer

How Do You Like Me in This: User Embodiment Preferences for Companion Agents

We investigate the relationship between the embodiment of an artificial companion and user perception and interaction with it. In a Wizard of Oz study, 42 users interacted with one of two embodiments: a physical robot or a virtual agent on a screen through a role-play of secretarial tasks in an office, with the companion providing essential assistance. Findings showed that participants in both condition groups when given the choice would prefer to interact with the robot companion, mainly for its greater physical or social presence. Subjects also found the robot less annoying and talked to it more naturally. However, this preference for the robotic embodiment is not reflected in the users’ actual rating of the companion or their interaction with it. We reflect on this contradiction and conclude that in a task-based context a user focuses much more on a companion’s behaviour than its embodiment. This underlines the feasibility of our efforts in creating companions that migrate between embodiments while maintaining a consistent identity from the user’s point of view

First Demonstration of a Pixelated Charge Readout for Single-Phase Liquid Argon Time Projection Chambers

Liquid Argon Time Projection Chambers (LArTPCs) have been selected for the future long-baseline Deep Underground Neutrino Experiment (DUNE). To allow LArTPCs to operate in the high-multiplicity near detector environment of DUNE, a new charge readout technology is required. Traditional charge readout technologies introduce intrinsic ambiguities, combined with a slow detector response, these ambiguities have limited the performance of LArTPCs, until now. Here, we present a novel pixelated charge readout that enables the full 3D tracking capabilities of LArTPCs. We characterise the signal to noise ratio of charge readout chain, to be about 14, and demonstrate track reconstruction on 3D space points produced by the pixel readout. This pixelated charge readout makes LArTPCs a viable option for the DUNE near detector complex.Comment: 13 pages, 9 figure

The influence of COMT Val158Met genotype on the character dimension cooperativeness in healthy females

Objectives: Although the Val(158)Met catechol-O-methyltransferase (COMT) gene has been linked with the temperament dimension Novelty Seeking (NS), new insights in this polymorphism might point to a major role for character features as well. Given that individual life experiences may influence Val(158) and Met(158) allele carriers differently it has been suggested that the character trait cooperativeness could be implicated. Case report: A homogeneous group of eighty right-handed Caucasian healthy female university students were assessed with the TCI and genotyped for the COMT Val(158)Met polymorphism (rs4680). Gene determination showed that eighteen were Val(158) homozygotes, forty-four Val/Met(158) heterozygotes, and eighteen were Met(158) homozygotes. All were within the same age range and never documented to have suffered from any neuropsychiatric illness. Bonferroni corrected non-parametric analyses showed that only for the character scale cooperativeness Val(158) homozygotes displayed significant higher scores when compared to Met(158) homozygotes. No significant differences on cooperativeness scores were found between Val(158) and Val/Met(158) carriers or between Met(158) and Val/Met(158) carriers. No differences were observed for the COMT Val(158) Met polymorphism and the other temperament and character scales. Conclusions: Our findings support the assumption that the Val(158)Met single nucleotide polymorphism (SNP) influences character traits and not only temperament. Our results add to the notion that Val(158) homozygotes are considered to be helpful and empathic and it suggest that these cooperativeness character traits are related to the dopaminergic system

Prospect for Charge Current Neutrino Interactions Measurements at the CERN-PS

Tensions in several phenomenological models grew with experimental results on neutrino/antineutrino oscillations at Short-Baseline (SBL) and with the recent, carefully recomputed, antineutrino fluxes from nuclear reactors. At a refurbished SBL CERN-PS facility an experiment aimed to address the open issues has been proposed [1], based on the technology of imaging in ultra-pure cryogenic Liquid Argon (LAr). Motivated by this scenario a detailed study of the physics case was performed. We tackled specific physics models and we optimized the neutrino beam through a full simulation. Experimental aspects not fully covered by the LAr detection, i.e. the measurements of the lepton charge on event-by-event basis and their energy over a wide range, were also investigated. Indeed the muon leptons from Charged Current (CC) (anti-)neutrino interactions play an important role in disentangling different phenomenological scenarios provided their charge state is determined. Also, the study of muon appearance/disappearance can benefit of the large statistics of CC muon events from the primary neutrino beam. Results of our study are reported in detail in this proposal. We aim to design, construct and install two Spectrometers at "NEAR" and "FAR" sites of the SBL CERN-PS, compatible with the already proposed LAr detectors. Profiting of the large mass of the two Spectrometers their stand-alone performances have also been exploited.Comment: 70 pages, 38 figures. Proposal submitted to SPS-C, CER

Prospects for the measurement of muon-neutrino disappearance at the FNAL-Booster

Neutrino physics is nowadays receiving more and more attention as a possible source of information for the long-standing problem of new physics beyond the Standard Model. The recent measurement of the mixing angle $\theta_{13}$ in the standard mixing oscillation scenario encourages us to pursue the still missing results on leptonic CP violation and absolute neutrino masses. However, puzzling measurements exist that deserve an exhaustive evaluation. The NESSiE Collaboration has been setup to undertake conclusive experiments to clarify the muon-neutrino disappearance measurements at small $L/E$, which will be able to put severe constraints to models with more than the three-standard neutrinos, or even to robustly measure the presence of a new kind of neutrino oscillation for the first time. To this aim the use of the current FNAL-Booster neutrino beam for a Short-Baseline experiment has been carefully evaluated. This proposal refers to the use of magnetic spectrometers at two different sites, Near and Far. Their positions have been extensively studied, together with the possible performances of two OPERA-like spectrometers. The proposal is constrained by availability of existing hardware and a time-schedule compatible with the CERN project for a new more performant neutrino beam, which will nicely extend the physics results achievable at the Booster. The possible FNAL experiment will allow to clarify the current $\nu_{\mu}$ disappearance tension with $\nu_e$ appearance and disappearance at the eV mass scale. Instead, a new CERN neutrino beam would allow a further span in the parameter space together with a refined control of systematics and, more relevant, the measurement of the antineutrino sector, by upgrading the spectrometer with detectors currently under R&D study.Comment: 76 pages, 52 figure

ClusterNN: A hybrid classification approach to mobile activity recognition

Mobile activity recognition from sensor data is based on supervised learning algorithms. Many algorithms have been proposed for this task. One of such algorithms is the K-nearest neighbour (KNN) algorithm. However, since KNN is an instance based algorithm its use in mobile activity recognition has been limited to offline evaluation on collected data. This is because for KNN to work well all the training instances must be kept in memory for similarity measurement with the test instance. This is however prohibitive for mobile environment. Therefore, we propose an unsupervised learning step that reduces the training set to a proportional size of the original dataset. The novel approach applies clustering to the dataset to obtain a set of micro clusters from which cluster characteristics are extracted for similarity measurement with new unseen data. These reduced representative sets can be used for classifying new instances using the nearest neighbour algorithm step on the mobile phone. Experimental evaluation of our proposed approach using real mobile activity recognition dataset shows improved result over the basic KNN algorithm