A Novel Prediction Method for Early Recognition of Global Human Behaviour in Image Sequences

Human behaviour recognition has been, and still remains, a challenging problem that involves different areas of computational intelligence. The automated understanding of people activities from video sequences is an open research topic in which the computer vision and pattern recognition areas have made big efforts. In this paper, the problem is studied from a prediction point of view. We propose a novel method able to early detect behaviour using a small portion of the input, in addition to the capabilities of it to predict behaviour from new inputs. Specifically, we propose a predictive method based on a simple representation of trajectories of a person in the scene which allows a high level understanding of the global human behaviour. The representation of the trajectory is used as a descriptor of the activity of the individual. The descriptors are used as a cue of a classification stage for pattern recognition purposes. Classifiers are trained using the trajectory representation of the complete sequence. However, partial sequences are processed to evaluate the early prediction capabilities having a specific observation time of the scene. The experiments have been carried out using the three different dataset of the CAVIAR database taken into account the behaviour of an individual. Additionally, different classic classifiers have been used for experimentation in order to evaluate the robustness of the proposal. Results confirm the high accuracy of the proposal on the early recognition of people behaviours.

Edge caching with mobility prediction in virtualized LTE mobile networks

Abstract Mobile Edge Computing enables the deployment of services, applications, content storage and processing in close proximity to mobile end users. This highly distributed computing environment can be used to provide ultra-low latency, precise positional awareness and agile applications, which could significantly improve user experience. In order to achieve this, it is necessary to consider next-generation paradigms such as Information-Centric Networking and Cloud Computing, integrated with the upcoming 5th Generation networking access. A cohesive end-to-end architecture is proposed, fully exploiting Information-Centric Networking together with the Mobile Follow-Me Cloud approach, for enhancing the migration of content-caches located at the edge of cloudified mobile networks. The chosen content-relocation algorithm attains content-availability improvements of up to 500 when a mobile user performs a request and compared against other existing solutions. The performed evaluation considers a realistic core-network, with functional and non-functional measurements, including the deployment of the entire system, computation and allocation/migration of resources. The achieved results reveal that the proposed architecture is beneficial not only from the users’ perspective but also from the providers point-of-view, which may be able to optimize their resources and reach significant bandwidth savings.

Advanced filtering and prediction software for urban traffic control systems. Final report.

Transportation Department, Office of University Research, Washington, D.C.

Computer simulation of human thoracic skeletal response - volume I, theory.

National Highway Traffic Safety Administration, Washington, D.C.

Computer simulation of human thoracic skeletal response - volume II, THORAX programmer's and user's manual. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Users manual: TSC highway noise prediction code: MOD-04. Final report.

Federal Highway Administration, Office of Research and Development, Washington, D.C.

User's manual: FHWA highway traffic noise prediction model - SNAP 1.0. Final report.

Federal Highway Administration, Environmental Design and Control Division, Washington, D.C.

User's manual: FHWA Level 2 highway traffic noise prediction model - STAMINA 1.0. Final report.

Federal Highway Administration, Environmental Design and Control Division, Washington, D.C.

Update of TSC highway traffic noise prediction code (1974). Final report.

Federal Highway Administration, Office of Research and Development, Washington, D.C.

Prediction of wave refraction and shoaling using two numerical models /

"August 1981."

Prediction of nearshore wave transformation /

"December 1982."

Constructing and evaluating alternative prediction models for identifying clinically relevant cases in an STD clinic

Thesis (Master's)--University of Washington, 2016-06

The prediction and representation of phase equilibria and physicochemical properties in complex slag systems

The development of new experimental techniques for the determination of phase equilibria in complex slag systems, chemical thermodynamic, and viscosity models is reported. The new experimental data, and new thermodynamic and viscosity models, have been combined in a custom-designed computer software package to produce limiting operability diagrams for slag systems. These diagrams are used to describe phase equilibria and physicochemical properties in complex slag systems. The approach is illustrated with calculations on the system FeO-Fe2O3-CaO-SiO-Al2O3 at metallic iron saturation, slags produced in coal slagging gasifiers, and in the reprocessing of nonferrous smelting slags. This article was presented at the Mills Symposium Molten Metals, Slags and Glasses-Characterisation of Properties and Phenomena held in London in August 2000.

Measurement and prediction of energy expenditure in males during household and garden tasks

Participation in at least 30 min of moderate intensity activity on most days is assumed to confer health benefits. This study accordingly determined whether the more vigorous household and garden tasks (sweeping, window cleaning, vacuuming and lawn mowing) are performed by middle-aged men at a moderate intensity of 3-6 metabolic equivalents (METs) in the laboratory and at home. Measured energy expenditure during self-perceived moderate-paced walking was used as a marker of exercise intensity. Energy expenditure was also predicted via indirect methods. Thirty-six males [Xmacr (SD): 40.0 (3.3) years; 179.5 (6.9) cm; 83.4 (14.0) kg] were measured for resting metabolic rate (RMR) and oxygen consumption (V.O-2) during the five activities using the Douglas bag method. Heart rate , respiratory frequency, CSA (Computer Science Applications) movement counts, Borg scale ratings of perceived exertion and Quetelet's index were also recorded as potential predictors of exercise intensity. Except for vacuuming in the laboratory, which was not significantly different from 3.0 METs (P=0.98), the MET means in the laboratory and home were all significantly greater than 3.0 (Pless than or equal to0.006). The sweeping and vacuuming MET means were significantly higher (P

Accurate prediction of scorpion toxin functional properties from primary structures

Scorpion toxins are common experimental tools for studies of biochemical and pharmacological properties of ion channels. The number of functionally annotated scorpion toxins is steadily growing, but the number of identified toxin sequences is increasing at much faster pace. With an estimated 100,000 different variants, bioinformatic analysis of scorpion toxins is becoming a necessary tool for their systematic functional analysis. Here, we report a bioinformatics-driven system involving scorpion toxin structural classification, functional annotation, database technology, sequence comparison, nearest neighbour analysis, and decision rules which produces highly accurate predictions of scorpion toxin functional properties. (c) 2005 Elsevier Inc. All rights reserved.