Activity recognition in a Physical Interactive RoboGame

In this paper, we investigate the possibility of human physical activity recognition in a robot game scenario. Being able to recognize types of activity is essential to enable robot behavior adaptation to support player engagement. Also, the introduction of this recognition system will allow for development of better models for prediction, planning and problem solving in PIRGs that can foster human-robot interaction. The experiments reported on this paper were performed on data collected from real in-game activity, where a human player faces a mobile robot. We use a custom single tri-axial accelerometer module attached to the player’s chest in order to capture motion information. The main characteristic of our approach is the extraction of features from patterns found on the motion variance rather than on raw data. Furthermore, we allow for the recognition of unconstrained motion given that we do not ask the players to perform target activities before hand: all detectable activities are derived from the free player motion during the game itself. To the best of our knowledge, this is the first paper to consider activity recognition in a physical interactive robogame

Comparison of denture microwave disinfection and conventional antifungal therapy in the treatment of denture stomatitis: a randomized clinical study

Objective. the aim of this study was to compare the effectiveness of denture microwave disinfection and antifungal therapy on treatment of denture stomatitis.Study Design. Sixty denture wearers with denture stomatitis (3 groups; n = 20 each), were treated with nystatin or denture microwave disinfection (1 or 3 times/wk) for 14 days. Mycologic samples from palates and dentures were quantified and identified with the use of Chromagar, and clinical photographs of palates were taken. Microbiologic and clinical data were analyzed with the use of a series of statistical tests (alpha = .05).Results. Both treatments similarly reduced clinical signs of denture stomatitis and growth on palates and dentures at days 14 and 30 (P > .05). At sequential appointments, the predominant species (P < .01) isolated was C. albicans (range 98%-53%), followed by C. glabrata (range 22%-12%) and C. tropicalis (range 25%-7%).Conclusions. Microwave disinfection, at once per week for 2 treatments, was as effective as topical antifungal therapy for treating denture stomatitis. (Oral Surg Oral Med Oral Pathol Oral Radiol 2012;114:469-479)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)CESMAC Univ Ctr, Sch Dent, Maceio, BrazilUniv Estadual Ponta Grossa, Dept Dent, Ponta Grossa, BrazilUniversidade Federal de São Paulo, Div Infect Dis, São Paulo, BrazilUNESP Univ Estadual Paulista, Araraquara Dent Sch, Araraquara, BrazilUniversidade Federal de São Paulo, Div Infect Dis, São Paulo, BrazilFAPESP: 2005/03211-6FAPESP: 2005/04695-7Web of Scienc

Bias and unfairness in machine learning models: a systematic literature review

One of the difficulties of artificial intelligence is to ensure that model decisions are fair and free of bias. In research, datasets, metrics, techniques, and tools are applied to detect and mitigate algorithmic unfairness and bias. This study aims to examine existing knowledge on bias and unfairness in Machine Learning models, identifying mitigation methods, fairness metrics, and supporting tools. A Systematic Literature Review found 40 eligible articles published between 2017 and 2022 in the Scopus, IEEE Xplore, Web of Science, and Google Scholar knowledge bases. The results show numerous bias and unfairness detection and mitigation approaches for ML technologies, with clearly defined metrics in the literature, and varied metrics can be highlighted. We recommend further research to define the techniques and metrics that should be employed in each case to standardize and ensure the impartiality of the machine learning model, thus, allowing the most appropriate metric to detect bias and unfairness in a given context

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Search for heavy resonances decaying to two Higgs bosons in final states containing four b quarks

A search is presented for narrow heavy resonances X decaying into pairs of Higgs bosons (H) in proton-proton collisions collected by the CMS experiment at the LHC at root s = 8 TeV. The data correspond to an integrated luminosity of 19.7 fb(-1). The search considers HH resonances with masses between 1 and 3 TeV, having final states of two b quark pairs. Each Higgs boson is produced with large momentum, and the hadronization products of the pair of b quarks can usually be reconstructed as single large jets. The background from multijet and t (t) over bar events is significantly reduced by applying requirements related to the flavor of the jet, its mass, and its substructure. The signal would be identified as a peak on top of the dijet invariant mass spectrum of the remaining background events. No evidence is observed for such a signal. Upper limits obtained at 95 confidence level for the product of the production cross section and branching fraction sigma(gg -> X) B(X -> HH -> b (b) over barb (b) over bar) range from 10 to 1.5 fb for the mass of X from 1.15 to 2.0 TeV, significantly extending previous searches. For a warped extra dimension theory with amass scale Lambda(R) = 1 TeV, the data exclude radion scalar masses between 1.15 and 1.55 TeV

Search for anomalous couplings in boosted WW/WZ -> l nu q(q)over-bar production in proton-proton collisions at root s=8TeV

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Search for supersymmetry in events with one lepton and multiple jets in proton-proton collisions at root s=13 TeV

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Measurement of nuclear modification factors of gamma(1S)), gamma(2S), and gamma(3S) mesons in PbPb collisions at root s(NN)=5.02 TeV

The cross sections for ϒ(1S), ϒ(2S), and ϒ(3S) production in lead-lead (PbPb) and proton-proton (pp) collisions at √sNN = 5.02 TeV have been measured using the CMS detector at the LHC. The nuclear modification factors, RAA, derived from the PbPb-to-pp ratio of yields for each state, are studied as functions of meson rapidity and transverse momentum, as well as PbPb collision centrality. The yields of all three states are found to be significantly suppressed, and compatible with a sequential ordering of the suppression, RAA(ϒ(1S)) > RAA(ϒ(2S)) > RAA(ϒ(3S)). The suppression of ϒ(1S) is larger than that seen at √sNN = 2.76 TeV, although the two are compatible within uncertainties. The upper limit on the RAA of ϒ(3S) integrated over pT, rapidity and centrality is 0.096 at 95% confidence level, which is the strongest suppression observed for a quarkonium state in heavy ion collisions to date. © 2019 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Funded by SCOAP3.Peer reviewe

Electroweak production of two jets in association with a Z boson in proton-proton collisions root s =13 TeV

A measurement of the electroweak (EW) production of two jets in association with a Z boson in proton-proton collisions at root s = 13 TeV is presented, based on data recorded in 2016 by the CMS experiment at the LHC corresponding to an integrated luminosity of 35.9 fb(-1). The measurement is performed in the lljj final state with l including electrons and muons, and the jets j corresponding to the quarks produced in the hard interaction. The measured cross section in a kinematic region defined by invariant masses m(ll) > 50 GeV, m(jj) > 120 GeV, and transverse momenta P-Tj > 25 GeV is sigma(EW) (lljj) = 534 +/- 20 (stat) fb (syst) fb, in agreement with leading-order standard model predictions. The final state is also used to perform a search for anomalous trilinear gauge couplings. No evidence is found and limits on anomalous trilinear gauge couplings associated with dimension-six operators are given in the framework of an effective field theory. The corresponding 95% confidence level intervals are -2.6 <cwww/Lambda(2) <2.6 TeV-2 and -8.4 <cw/Lambda(2) <10.1 TeV-2. The additional jet activity of events in a signal-enriched region is also studied, and the measurements are in agreement with predictions.Peer reviewe

Inclusive search for supersymmetry using razor variables in pp collisions at root s=13 TeV

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