Detection of road accident accumulation zones with a visual analytics approach

Nowadays, road accidents are a major public health problem, which increase is forecasted if road safety is not treated properly, dying about 1.2 million people every year around the globe. In 2012, Portugal recorded 573 fatalities in road accidents, on site, revealing the largest decreasing of the European Union for 2011, along with Denmark. Beyond the impact caused by fatalities, it was calculated that the economic and social costs of road accidents weighted about 1.17% of the Portuguese gross domestic product in 2010. Visual Analytics allows the combination of data analysis techniques with interactive visualizations, which facilitates the process of knowledge discovery in sets of large and complex data, while the Geovisual Analytics facilitates the exploration of space-time data through maps with different variables and parameters that are under analysis. In Portugal, the identification of road accident accumulation zones, in this work named black spots, has been restricted to annual fixed windows. In this work, it is presented a dynamic approach based on Visual Analytics techniques that is able to identify the displacement of black spots on sliding windows of 12 months. Moreover, with the use of different parameterizations in the formula usually used to detect black spots, it is possible to identify zones that are almost becoming black spots. Through the proposed visualizations, the study and identification of countermeasures to this social and economic problem can gain new grounds and thus the decision- making process is supported and improved.

Automatic visual detection of human behavior: a review from 2000 to 2014

Due to advances in information technology (e.g., digital video cameras, ubiquitous sensors), the automatic detection of human behaviors from video is a very recent research topic. In this paper, we perform a systematic and recent literature review on this topic, from 2000 to 2014, covering a selection of 193 papers that were searched from six major scientific publishers. The selected papers were classified into three main subjects: detection techniques, datasets and applications. The detection techniques were divided into four categories (initialization, tracking, pose estimation and recognition). The list of datasets includes eight examples (e.g., Hollywood action). Finally, several application areas were identified, including human detection, abnormal activity detection, action recognition, player modeling and pedestrian detection. Our analysis provides a road map to guide future research for designing automatic visual human behavior detection systems.

Detection of dangerous situations using a smart internet of things system

The Internet of Things (IoT) is a concept that can foster the emergence of innovative applications. In order to minimize parents’s concerns about their children’s safety, this paper presents the design of a smart Internet of Things system for identifying dangerous situations. The system will be based on real time collection and analysis of physiological signals monitored by non-invasive and non-intrusive sensors, Frequency IDentification (RFID) tags and a Global Positioning System (GPS) to determine when a child is in danger. The assumption of a state of danger is made taking into account the validation of a certain number of biometric reactions to some specific situations and according to a self-learning algorithm developed for this architecture. The results of the analysis of data collected and the location of the child will be able in real time to child’s care holders in a web application.

Forecasting human entrances at a commercial store using facial recognition data

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

A bio-inspired computational model for motion detection

Tese de Doutoramento (Programa Doutoral em Engenharia Biomédica)

Simultaneous detection of cyclopiazonic acid and aflatoxin B1 by HPLC in methanol/water mobile phase

A simple procedure for the simultaneous detection of cyclopiazonic acid (CPA) and aflatoxin B1 from fungal extracts is presented, using a methanol and water mobile phase and fluorescence detection. This methodology has been tested with standard solutions of both mycotoxins CPA and Aflatoxin B1 and with methanolic extracts of Aspergillus section Flavi strains, previously characterized for their mycotoxin production profile. Previously available methodology required the use of two different chromatographic runs for these mycotoxins, with distinct columns and detectors (fluorescence detection with a post-column photochemical derivatization (PHRED) for aflatoxin B1 and UV detection for CPA). The proposed method detects both mycotoxins in a single run. Data from these assays will be presented and discussed.

Biosynthesis, detection and toxicology of ochratoxins - optimisation of production

Ochratoxin A (OTA) is a very well known mycotoxin found in several food commodities for which maximum limits are being discussed in EC in other to produce appropriate regulations. OTA is one of several ochratoxins produced by Aspergillus and Penicillium species. All the compounds in this group have a molecular structure very similar to OTA and some were already isolated from natural substrates. Several of these compounds such as ochratoxin , methyl and ethyl ester of ochratoxin A, 4-R and S-hydroxyochratoxin A, 10-hydroxyochratoxin A and ochratoxin A open lactone are commercially unavailable. However, they can be easily synthesized through OTA modification. With the main objective of its application on further research works, OTA production, isolation and purification has been optimised from an A. alliaceus strain grown on wheat medium. Synthesis and purification of some OTA derivatives has been achieved and an HPLC method for their detection was optimised. Data about their production by several species of Aspergillus will be presented. The toxicological properties of ochratoxins are still not very clear and a future EC safety limit for OTA will depend on e.g., a better clarification of its carcinogenity. Could OTA derivatives play a role here?