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.

Hand gesture recognition system based in computer vision and machine learning

"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"

Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.

Vision-based portuguese sign language recognition system

Vision-based hand gesture recognition is an area of active current research in computer vision and machine learning. Being a natural way of human interaction, it is an area where many researchers are working on, with the goal of making human computer interaction (HCI) easier and natural, without the need for any extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them, for example, to convey information. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. Hand gestures are a powerful human communication modality with lots of potential applications and in this context we have sign language recognition, the communication method of deaf people. Sign lan- guages are not standard and universal and the grammars differ from country to coun- try. In this paper, a real-time system able to interpret the Portuguese Sign Language is presented and described. Experiments showed that the system was able to reliably recognize the vowels in real-time, with an accuracy of 99.4% with one dataset of fea- tures and an accuracy of 99.6% with a second dataset of features. Although the im- plemented solution was only trained to recognize the vowels, it is easily extended to recognize the rest of the alphabet, being a solid foundation for the development of any vision-based sign language recognition user interface system.

Generic system for human-computer gesture interaction

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for humancomputer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of vision-based interaction systems can be the same for all applications and thus facilitate the implementation. In order to test the proposed solutions, three prototypes were implemented. For hand posture recognition, a SVM model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications.

Ergonomic evaluation of office workplaces with Rapid Office Strain Assessment (ROSA)

The regular use of the computer in the office contributed to the appearance of many risk factors related with work-related musculoskeletal disorders (WRMSD) such as maintaining static sitting postures for long time and awkward postures of the head, neck and upper limbs, leading to increased muscle activity in the cervical spine and shoulders. The objective of this study was to evaluate the presence of risk factors for WRMSD in an office using the Rapid Assessment Office Strain method (ROSA). Based on the results of this ergonomic evaluation, an occupational gym program was designed and implemented. Thirty-eight workplaces were evaluated using the observation of the tasks and pictures records in order to characterize those tasks in more detail. The ROSA tool was applied by an observer, who selected the appropriate score based on the worker's posture as well as the time spent in each posture. Scores were recorded for the sections of the method, specifically Chair, Monitor and Mouse and Keyboard and Telephone. The scores were recorded in a sheet developed for the method. The mean ROSA final score was 3.61 ± 0.64, for Chair section was 3.45 ± 0.55, to Monitor and Telephone section was 3.11 ± 0.61, and to Mouse and Keyboard section was 2.11 ± 0.31. The results led to understand that the analyzed tasks represent situations of risk of discomfort and, according to the methods guidelines, further research and modifications of the workplace may be necessary. It should be emphasized that these scores may not be related to the poor available equipment but with the need to optimize their use by the workers. It was noticed also that the interaction of workers with the tasks and the adopted sitting posture at the computer throughout the day have effects at a muscular level, essentially for the cervical area and shoulders. ROSA tool is an useful and easy method to assess several risk factors associated with WRMSD, also allowing the design of specific occupational gym programs.

Hand gesture recognition system based in computer vision and machine learning: Applications on human-machine interaction

Tese de Doutoramento em Engenharia de Eletrónica e de Computadores

Development of an intelligent earthwork optimization system

Tese de Doutoramento em Engenharia Civil.

The choroid plexus is modulated by various peripheral stimuli: implications to diseases of the central nervous system

The blood brain barrier (BBB) and the blood cerebrospinal fluid barrier (BCSFB) form the barriers of the brain. These barriers are essential not only for the protection of the brain, but also in regulating the exchange of cells and molecules in and out of the brain. The choroid plexus (CP) epithelial cells and the arachnoid membrane form the BCSFB. The CP is structurally divided into two independent compartments: one formed by a unique and continuous line of epithelial cells that rest upon a basal lamina; and, a second consisting of a central core formed by connective and highly vascularized tissue populated by diverse cell types (fibroblasts, macrophages and dendritic cells). Here, we review how the CP transcriptome and secretome vary depending on the nature and duration of the stimuli to which the CP is exposed. Specifically, when the peripheral stimulation is acute the CP response is rapid, strong and transient, whereas if the stimulation is sustained in time the CP response persists but it is weaker. Furthermore, not all of the epithelium responds at the same time to peripheral stimulation, suggesting the existence of a synchrony system between individual CP epithelial cells.

An object-oriented model for rapid prototyping of data path/control systems - a case study

Publicado em "Information control in manufacturing 1998 : (INCOM'98) : advances in industrial engineering : a proceedings volume from the 9th IFAC Symposium, Nancy-Metz, France, 24-26 June 1998. Vol. 2"

Palatability of the Asian clam Corbicula fluminea (Müller 1774) in an invaded system

Dissertação de mestrado em Ecology