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.

Abstract computation in schizophrenia detection through artificial neural network based systems

Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

Filamentous fungi in free water and biofilms from Brazilian drinking water systems

In some regions of Brazil, especially where the water is scarce, drinking water is stored in water storage tanks. This practice gives the consumer the guarantee of available water. The water storage conditions such as the exposure to hot weather when the tanks are on rooftops allow the development of microorganisms and microbial biofilms which can deteriorate the water quality and increase the risk to human health [1,2]. This study describes the filamentous fungi (FF) detected in free water and biofilms in drinking water storage tanks in Recife - Pernambuco, Brazil. Five sampling times in triplicate were performed at two distinct points. Colony-forming units (CFU) of FF fungi were determined with 0.45 µm filtration membranes using peptone glucose rose Bengal agar (PGRBA). From the 30 samples analysed a total of 1136 CFU were obtained. The water biofilms were collected from samplers consisting of polyethylene coupons, previously installed in the reservoirs. These coupons were transferred to PGRBA plates and incubated using with the same conditions described for free FF. For the in situ detection of FF in biofilms the Calcofluor White staining technique was used. This procedure demonstrated FF forming biofilms on the surfaces of the coupons. Brazilian legislation does not define limits for FF in drinking water. However considering the potential risk of fungal contamination, the data obtained in this study will contribute to developing future quantitative and qualitative parameters for the presence of fungi in drinking water distribution systems in Brazil. [1] HageskaL, G, Lima, N, Skaar, I. The study of fungi in drinking water. Mycological Research, 113, 2009, 165-172. [2] Skaar I, Hageskal G. Fungi in Drinking Water. In.: Paterson RRM, Lima N. (Eds.) Molecular Biology of Food and Water Borne Mycotoxigenic and Mycotic Fungi. CRC Press, Taylor & Francis Group, Boca Raton, 2015, 597-606.

Concurrency detection on finish-to-start activity precedence networks

We explore the finish-to-start precedence relations of project activities used in scheduling problems. From these relations, we devise a method to identify groups of activities that could execute concurrently, i.e. activities in the same group can all execute in parallel. The method derives a new set of relations to describe the concurrency. Then, it is represented by an undirected graph and the maximal cliques problem identifies the groups. We provide a running example with a project from our previous studies in resource constrained project cost minimization together with an example application on the concurrency detection method: the evaluation of the resource stress.

Widespread environmental contamination with Mycobacterium tuberculosis complex revealed by a molecular detection protocol

Environmental contamination with Mycobacterium tuberculosis complex (MTC) has been considered crucial for bovine tuberculosis persistence in multi-host-pathogen systems. However, MTC contamination has been difficult to detect due to methodological issues. In an attempt to overcome this limitation we developed an improved protocol for the detection of MTC DNA. MTC DNA concentration was estimated by the Most Probable Number (MPN) method. Making use of this protocol we showed that MTC contamination is widespread in different types of environmental samples from the Iberian Peninsula, which supports indirect transmission as a contributing mechanism for the maintenance of bovine tuberculosis in this multi-host-pathogen system. The proportion of MTC DNA positive samples was higher in the bovine tuberculosis-infected than in presumed negative area (0.32 and 0.18, respectively). Detection varied with the type of environmental sample and was more frequent in sediment from dams and less frequent in water also from dams (0.22 and 0.05, respectively). The proportion of MTC-positive samples was significantly higher in spring (p<0.001), but MTC DNA concentration per sample was higher in autumn and lower in summer. The average MTC DNA concentration in positive samples was 0.82 MPN/g (CI95 0.70-0.98 MPN/g). We were further able to amplify a DNA sequence specific of Mycobacterium bovis/caprae in 4 environmental samples from the bTB-infected area.

A bio-inspired computational model for motion detection

Tese de Doutoramento (Programa Doutoral em Engenharia Biomédica)