THE ANN – BASED ANALYSIS MODEL OF THE SPORT TECHNIQUES

The purpose of this paper was to develop an analysis model of sport techniques based on artificial neural networks. In this study, the artificial neural network (ANN) computing techniques were applied to construct sport technique analysis model. Two basic problems, the technique parameter selection and the cause-effect mapping relationship establishment, were carefully investigated. This approach was first used with shot-putt, and from 155 trials, the Overall Parameter (OP) model and the Local Parameter (LP) model were constructed and evaluated. The predictive capacity of ANN model was demonstrated to be superior to the linear regression model

An experimental test of the solemn oath in eliciting sincere preferences

Hypothetical bias is the gap between the hypothetical willingness to pay and the real economic payment. Subjects may overstate or understate their willingness to pay due to strategic behaviour. This bias is common in contingent valuation studies. In this study, we attempt to use a commitment device to correct the bias, in order to elicit sincere preferences. We use a solemn oath in second-price auctions, using both induced valuations and homegrown valuations. Using a random effect panel data model, we draw three conclusions: (1) there is a gap between subjects' bids and their true willingness to pay due to the violation of both the budget constraint and the participation constraint; (2) oaths in the induced value experiment can increase subjects' bids towards the induced value only given real monetary incentives; (3) oaths can modestly correct the hypothetical bias in the homegrown valuation experiment

A Generic Multi-Player Transformation Algorithm for Solving Large-Scale Zero-Sum Extensive-Form Adversarial Team Games

Many recent practical and theoretical breakthroughs focus on adversarial team multi-player games (ATMGs) in ex ante correlation scenarios. In this setting, team members are allowed to coordinate their strategies only before the game starts. Although there existing algorithms for solving extensive-form ATMGs, the size of the game tree generated by the previous algorithms grows exponentially with the number of players. Therefore, how to deal with large-scale zero-sum extensive-form ATMGs problems close to the real world is still a significant challenge. In this paper, we propose a generic multi-player transformation algorithm, which can transform any multi-player game tree satisfying the definition of AMTGs into a 2-player game tree, such that finding a team-maxmin equilibrium with correlation (TMECor) in large-scale ATMGs can be transformed into solving NE in 2-player games. To achieve this goal, we first introduce a new structure named private information pre-branch, which consists of a temporary chance node and coordinator nodes and aims to make decisions for all potential private information on behalf of the team members. We also show theoretically that NE in the transformed 2-player game is equivalent TMECor in the original multi-player game. This work significantly reduces the growth of action space and nodes from exponential to constant level. This enables our work to outperform all the previous state-of-the-art algorithms in finding a TMECor, with 182.89, 168.47, 694.44, and 233.98 significant improvements in the different Kuhn Poker and Leduc Poker cases (21K3, 21K4, 21K6 and 21L33). In addition, this work first practically solves the ATMGs in a 5-player case which cannot be conducted by existing algorithms.Comment: 9 pages, 5 figures, NIPS 202

TwinTex: Geometry-aware Texture Generation for Abstracted 3D Architectural Models

Coarse architectural models are often generated at scales ranging from individual buildings to scenes for downstream applications such as Digital Twin City, Metaverse, LODs, etc. Such piece-wise planar models can be abstracted as twins from 3D dense reconstructions. However, these models typically lack realistic texture relative to the real building or scene, making them unsuitable for vivid display or direct reference. In this paper, we present TwinTex, the first automatic texture mapping framework to generate a photo-realistic texture for a piece-wise planar proxy. Our method addresses most challenges occurring in such twin texture generation. Specifically, for each primitive plane, we first select a small set of photos with greedy heuristics considering photometric quality, perspective quality and facade texture completeness. Then, different levels of line features (LoLs) are extracted from the set of selected photos to generate guidance for later steps. With LoLs, we employ optimization algorithms to align texture with geometry from local to global. Finally, we fine-tune a diffusion model with a multi-mask initialization component and a new dataset to inpaint the missing region. Experimental results on many buildings, indoor scenes and man-made objects of varying complexity demonstrate the generalization ability of our algorithm. Our approach surpasses state-of-the-art texture mapping methods in terms of high-fidelity quality and reaches a human-expert production level with much less effort. Project page: https://vcc.tech/research/2023/TwinTex.Comment: Accepted to SIGGRAPH ASIA 202

Demonstration of particle tracking with scintillating fibres read out by a SPAD array sensor and application as a neutrino active target

Scintillating fibre detectors combine sub-mm resolution particle tracking, precise measurements of the particle stopping power and sub-ns time resolution. Typically, fibres are read out with silicon photomultipliers (SiPM). Hence, if fibres with a few hundred mm diameter are used, either they are grouped together and coupled with a single SiPM, losing spatial resolution, or a very large number of electronic channels is required. In this article we propose and provide a first demonstration of a novel configuration which allows each individual scintillating fibre to be read out regardless of the size of its diameter, by imaging them with Single-Photon Avalanche Diode (SPAD) array sensors. Differently from SiPMs, SPAD array sensors provide single-photon detection with single-pixel spatial resolution. In addition, O(us) or faster coincidence of detected photons allows to obtain noise-free images. Such a concept can be particularly advantageous if adopted as a neutrino active target, where scintillating fibres alternated along orthogonal directions can provide isotropic, high-resolution tracking in a dense material and reconstruct the kinematics of low-momentum protons (down to 150 MeV/c), crucial for an accurate characterisation of the neutrino nucleus cross section. In this work the tracking capabilities of a bundle of scintillating fibres coupled to SwissSPAD2 is demonstrated. The impact of such detector configuration in GeV-neutrino experiments is studied with simulations and reported. Finally, future plans, including the development of a new SPAD array sensor optimised for neutrino detection, are discussed

Cerebrospinal fluid drainage and chronic hydrocephalus in aneurysmal subarachnoid hemorrhage patients with intraventricular hemorrhage

BackgroundPatients with intraventricular hemorrhage (IVH) are at a higher risk of developing hydrocephalus and often require external ventricular drainage or long-term ventriculoperitoneal shunt surgery.ObjectiveTo investigate whether cerebrospinal fluid drainage in patients with IVH due to aneurysmal subarachnoid hemorrhage (aSAH) reduces the incidence of chronic hydrocephalus.MethodA retrospective analysis was conducted on patients with aSAH treated at our hospital between January 2020 and December 2022. The first analysis compared patients with and without IVH, while the second analysis compared IVH patients with and without chronic hydrocephalus. The third analysis compared IVH patients who underwent in different drainage methods which is lumbar drainage (LD) or external ventricular drainage (EVD). The primary outcome measure was the incidence of chronic hydrocephalus.ResultOf the 296 patients hospitalized with aSAH, 108 (36.5%) had IVH, which was associated with a significantly higher incidence of chronic hydrocephalus compared to patients without IVH (49.1% vs. 16.5%, p < 0.001). Multivariate logistic regression analysis showed that IVH was independently associated with the formation of chronic hydrocephalus (OR: 3.530, 95% CI: 1.958–6.362, p < 0.001). Among the 108 IVH patients, 53 (49.1%) developed chronic hydrocephalus. Multivariate logistic regression analysis revealed that the Hunt Hess grade at admission (OR: 3.362, 95% CI: 1.146–9.863, p = 0.027) and postoperative cerebrospinal fluid drainage (OR: 0.110, 95% CI: 0.036–0.336, p < 0.001) were independent risk factors for the development of chronic hydrocephalus in IVH patients. Among all IVH patients who underwent cerebrospinal fluid drainage, 45 (75%) received continuous lumbar puncture drainage, and 15 (25%) received external ventricular drainage. Univariate analysis did not show a statistically significant difference between the two groups in terms of postoperative chronic hydrocephalus (p = 0.283). However, multivariate logistic regression analysis suggested that the drainage methods of LD and EVD might be associated with the development of chronic hydrocephalus.ConclusionThe presence of IVH increases the risk of chronic hydrocephalus in patients with aSAH, and postoperative cerebrospinal fluid drainage appears to reduce this risk. The specific effects of lumbar puncture drainage and ventricular drainage on the incidence of chronic hydrocephalus require further investigation