Content-based Video Retrieval by Integrating Spatio-Temporal and Stochastic Recognition of Events

As amounts of publicly available video data grow the need to query this data efficiently becomes significant. Consequently content-based retrieval of video data turns out to be a challenging and important problem. We address the specific aspect of inferring semantics automatically from raw video data. In particular, we introduce a new video data model that supports the integrated use of two different approaches for mapping low-level features to high-level concepts. Firstly, the model is extended with a rule-based approach that supports spatio-temporal formalization of high-level concepts, and then with a stochastic approach. Furthermore, results on real tennis video data are presented, demonstrating the validity of both approaches, as well us advantages of their integrated us

ANALISIS CLUSTERING DENGAN K-MEANS UNTUK PENGELOMPOKKAN PENJUALAN PRODUK PADA HOTEL NEWTON

Customer satisfaction is the main goal of many companies wants to achieve. One of the business fields that focus on customer satisfaction is hotel business. Apart from serving accommodation for customers, hotels also provide variety of products for sale. Inventory management is very important is hotel business because one of many ways to maintain customer satisfaction is by keeping stock so no items are empty when needed. In addition, a good inventory management will not let the company to experiences losses due to outdated inventory. Using data mining K-means clustering algorithm, we can group goods based on the salable goods and the less salable goods. This research aims to assist hotel Newton to improve their inventory management. Data that was used is sales that have been made which divided into 3 trimesters. Data also will be evaluated using RapidMiner application. The results obtained from the research are 3 clusters where the clusters consist of very salable goods, medium salable goods and not salable goods

First Sagittarius A* Event Horizon Telescope Results. IV. Variability, Morphology, and Black Hole Mass

In this paper we quantify the temporal variability and image morphology of the horizon-scale emission from Sgr A*, as observed by the EHT in 2017 April at a wavelength of 1.3 mm. We find that the Sgr A* data exhibit variability that exceeds what can be explained by the uncertainties in the data or by the effects of interstellar scattering. The magnitude of this variability can be a substantial fraction of the correlated flux density, reaching $\sim$100\% on some baselines. Through an exploration of simple geometric source models, we demonstrate that ring-like morphologies provide better fits to the Sgr A* data than do other morphologies with comparable complexity. We develop two strategies for fitting static geometric ring models to the time-variable Sgr A* data; one strategy fits models to short segments of data over which the source is static and averages these independent fits, while the other fits models to the full dataset using a parametric model for the structural variability power spectrum around the average source structure. Both geometric modeling and image-domain feature extraction techniques determine the ring diameter to be $51.8 \pm 2.3$ $\mu$as (68\% credible intervals), with the ring thickness constrained to have an FWHM between $\sim$30\% and 50\% of the ring diameter. To bring the diameter measurements to a common physical scale, we calibrate them using synthetic data generated from GRMHD simulations. This calibration constrains the angular size of the gravitational radius to be $4.8_{-0.7}^{+1.4}$ \mathrm{\mu as}, which we combine with an independent distance measurement from maser parallaxes to determine the mass of Sgr A* to be $4.0_{-0.6}^{+1.1} \times 10^6$ M$_{\odot}$.Comment: 65 pages, 35 figures, published in The Astrophysical Journal Letters on May 12, 2022. See the published paper for the full authors lis

Improvising with the threnoscope: integrating code, hardware, GUI, network, and graphic scores

Live coding emphasises improvisation. It is an art practice that merges the act of musical composition and performance into a public act of projected writing. This paper introduces the Threnoscope system, which includes a live coding micro-language for drone-based microtonal composition. The paper discusses the aims and objectives of the system, elucidates the design decisions, and introduces in particular the code score feature present in the Threnoscope. The code score is a novel element in the design of live coding systems allowing for improvisation through a graphic score, rendering a visual representation of past and future events in a real-time performance. The paper demonstrates how the system’s methods can be mapped ad hoc to GUI- or hardware-based control

Extracting Event Dynamics from Event-by-Event Analysis

The problem of eliminating the statistical fluctuations and extracting the event dynamics from event-by-event analysis is discussed. New moments $G_p$ (for continuous distribution), and $G_{q,p}$ (for anomalous distribution) are proposed, which are experimentally measurable and can eliminate the Poissonian type statistical fluctuations to recover the dynamical moments $C_p$ and $C_{q,p}$. In this way, the dynamical distribution of the event-averaged transverse momentum \bar{\pt} can be extracted, and the anomalous scaling of dynamical distribution, if exists, can be recovered, through event-by-event analysis of experimental data.Comment: 15 pages, 2 eps figures, Phys. Rev. C accepte