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.

An evolutionary multi-objective optimization system for earthworks

Earthworks involve the levelling or shaping of a target area through the moving or processing of the ground surface. Most construction projects require earthworks, which are heavily dependent on mechanical equipment (e.g., excavators, trucks and compactors). Often, earthworks are the most costly and time-consuming component of infrastructure constructions (e.g., road, railway and airports) and current pressure for higher productivity and safety highlights the need to optimize earthworks, which is a nontrivial task. Most previous attempts at tackling this problem focus on single-objective optimization of partial processes or aspects of earthworks, overlooking the advantages of a multi-objective and global optimization. This work describes a novel optimization system based on an evolutionary multi-objective approach, capable of globally optimizing several objectives simultaneously and dynamically. The proposed system views an earthwork construction as a production line, where the goal is to optimize resources under two crucial criteria (costs and duration) and focus the evolutionary search (non-dominated sorting genetic algorithm-II) on compaction allocation, using linear programming to distribute the remaining equipment (e.g., excavators). Several experiments were held using real-world data from a Portuguese construction site, showing that the proposed system is quite competitive when compared with current manual earthwork equipment allocation.

[An editorial to] Recent Advances on Knowledge Discovery and Business Intelligence

Special issue guest editorial, June, 2015.

Business intelligence in banking: A literature analysis from 2002 to 2013 using Text Mining and latent Dirichlet allocation

telligence applications for the banking industry. Searches were performed in relevant journals resulting in 219 articles published between 2002 and 2013. To analyze such a large number of manuscripts, text mining techniques were used in pursuit for relevant terms on both business intelligence and banking domains. Moreover, the latent Dirichlet allocation modeling was used in or- der to group articles in several relevant topics. The analysis was conducted using a dictionary of terms belonging to both banking and business intelli- gence domains. Such procedure allowed for the identification of relationships between terms and topics grouping articles, enabling to emerge hypotheses regarding research directions. To confirm such hypotheses, relevant articles were collected and scrutinized, allowing to validate the text mining proce- dure. The results show that credit in banking is clearly the main application trend, particularly predicting risk and thus supporting credit approval or de- nial. There is also a relevant interest in bankruptcy and fraud prediction. Customer retention seems to be associated, although weakly, with targeting, justifying bank offers to reduce churn. In addition, a large number of ar- ticles focused more on business intelligence techniques and its applications, using the banking industry just for evaluation, thus, not clearly acclaiming for benefits in the banking business. By identifying these current research topics, this study also highlights opportunities for future research.

MixAR mobile prototype: visualizing virtually reconstructed ancient structures in situ

Archeology and related areas have a special interest on cultural heritage sites since they provide valuable information about past civilizations. However, the ancient buildings present in these sites are commonly found in an advanced state of degradation which difficult the professional/expert analysis. Virtual reconstructions of such buildings aim to provide a digital insight of how these historical places could have been in ancient times. Moreover, the visualization of such models has been explored by some Augmented Reality (AR) systems capable of providing support to experts. Their compelling and appealing environments have also been applied to promote the social and cultural participation of general public. The existing AR solutions regarding this thematic rarely explore the potential of realism, due to the following lacks: the exploration of mixed environments is usually only supported for indoors or outdoors, not both in the same system; the adaptation of the illumination conditions to the reconstructed structures is rarely addressed causing a decrease of credibility. MixAR [1] is a system concerned with those challenges, aiming to provide the visualization of virtual buildings augmented upon real ruins, allowing soft transitions among its interiors and exteriors and using relighting techniques for a faithful interior illumination, while the user freely moves in a given cultural heritage site, carrying a mobile unit. Regarding the focus of this paper, we intend to report the current state of MixAR mobile unit prototype, which allows visualizing virtual buildings – properly aligned with real-world structures – based on user's location, during outdoor navigation. In order to evaluate the prototype performance, a set of tests were made using virtual models with different complexities.

Goblet cell density association with tear function and ocular surface physiology

Purpose: To determine the relationship of goblet cell density (GCD) with tear function and ocular surface physiology. Methods: This was a cross-sectional study conducted in 35 asymptomatic subjects with mean age 23.8±3.6 years. Tear film assessment, conjunctiva and cornea examination were done in each subject. Conjunctival impression cytology was performed by applying Nitrocellulose Millipore MFTM-Membrane filter over the superior bulbar conjunctiva. The filter paper was than fixed with 96% ethanol and stained with Periodic Acid Schiff, Hematoxylin and Eosin. GCD was determined by optical microscopy. Relation between GCD and Schirmer score, tear break-up time (TBUT), bulbar redness, limbal redness and corneal staining was determined. Results: The mean GCD was 151±122 cells/mm2. GCD was found higher in eyes with higher Schirmer score but it was not significant (p = 0.75). There was a significant relationship ofGCDwith TBUT (p = 0.042). GCD was not correlated with bulbar redness (p = 0.126), and limbal redness (p = 0.054) as well as corneal staining (p = 0.079). No relationship of GCD with age and gender of the subjects (p > 0.05) was observed. Conclusion: GCD was found correlated with TBUT but no significant correlation was found with the aqueous portion of the tear, limbal as well as bulbar redness and corneal staining.

Personalized-based dietary recommendation for weightlifting

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e Computadores

Controlo de qualidade e inspeção visual por imagem: definição de uma aplicação para registo de alterações e avaliação de desempenho

Dissertação de mestrado em Engenharia e Gestão da Qualidade

Pervasive business intelligence: a marketing intelligence framework proposal

Doctoral Thesis in Information Systems and Technologies Area of Information Systems and Technology

The diagnostic and prognostic role of liquid-based cytology: are we ready to monitor therapy and resistance?

Here, we evaluate the diagnostic and prognostic role of liquid-based cytology (LBC) in different body lesions, including thyroid, lung, effusions and malignant breast lesions. LBC has gained consensus after being applied to both non-gynecologic and fine-needle aspiration cytology. Although some remain sceptical regarding the diagnostic efficacy of LBC, mainly when used alone, in recent years, good results have been obtained as long as it showed a high diagnostic accuracy. Here, we discuss the additional possibility of storing material for the application of ancillary techniques (immunocytochemistry–molecular analysis) with several diagnostic and prognostic advantages, which may pave the way for the challenging evaluation of both monitoring responses to treatment and resistance to targeted therapies in thyroid, lung, breast carcinoma or malignant effusions. Furthermore, it provides the use of several molecular spots as specific targets for personalized therapy.

Three-dimensional technology facilitates surgical performance of novice laparoscopy surgeons: a quantitative assessment on a porcine kidney model

Objective To determine whether the use of 3-dimensional (3D) imaging translates into a better surgical performance of naïve urologic laparoscopic surgeons during pyeloplasty (PY) and partial nephrectomy (PN) procedures. Materials and Methods Eighteen surgeons without any previous laparoscopic experience were randomly assigned to perform PY and PN in a porcine model using initially 2-dimensional (2D) and 3D laparoscopy. A surgical performance score was rated by an "expert" tutor through a modified 5-item global rating scale contemplating operative field view, bimanual dexterity, efficiency, tissue handling, and autonomy. Overall surgical time, complications, subjective perception of participating surgeons, and inconveniences related to the 3D vision were recorded. Results No difference in terms if operative time was found between 2D or 3D laparoscopy for both the PY (P =.51) and the PN (P =.28) procedures. A better rate in terms of surgical performance score was noted by the tutors when the study participants were using 3D vs 2D, for both PY (3.6 [0.8] vs 3.0 [0.4]; P =.034) and PN (3.6 [0.51] vs 3.15 [0.63]; P =.001). No complications occurred in any of the procedures. Most (77.2%) of the participating na??ve laparoscopic surgeons had the perception that 3D laparoscopy was overall easier than 2D. Headache (18.1%), nausea (18.1%), and visual disturbance (18.1%) were the most common issues reported by the surgeons during 3D procedures. Conclusion Despite the absence of translation in a shorter operative time, the use of 3D technology seems to facilitate the surgical performance of naive surgeons during laparoscopic kidney procedures on a porcine model.

Ontological representation of tumor-node-metastasis classification and an ontology-driven classifier: a study on colorectal cancer

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)

Introduction [to "Citizen voices: performing public participation in science and environment communication"]

"ECREA series, ISSN 1742-9420"

Pervasive decision support to predict football corners and goals by means of data mining

Football is considered nowadays one of the most popular sports. In the betting world, it has acquired an outstanding position, which moves millions of euros during the period of a single football match. The lack of profitability of football betting users has been stressed as a problem. This lack gave origin to this research proposal, which it is going to analyse the possibility of existing a way to support the users to increase their profits on their bets. Data mining models were induced with the purpose of supporting the gamblers to increase their profits in the medium/long term. Being conscience that the models can fail, the results achieved by four of the seven targets in the models are encouraging and suggest that the system can help to increase the profits. All defined targets have two possible classes to predict, for example, if there are more or less than 7.5 corners in a single game. The data mining models of the targets, more or less than 7.5 corners, 8.5 corners, 1.5 goals and 3.5 goals achieved the pre-defined thresholds. The models were implemented in a prototype, which it is a pervasive decision support system. This system was developed with the purpose to be an interface for any user, both for an expert user as to a user who has no knowledge in football games.