Fusion of heterogenous sensor data in border surveillance

Wide area surveillance has become of critical importance particularly for border control between countries where vast forested land border areas are to be monitored. In this paper we address the problem of the automatic detection of activity in forbidden areas, namely forested land border areas. In order to avoid false detections, often triggered in dense vegetation with single sensors such as radar, in this paper we present a multi sensor fusion and tracking system using passive infrared detectors in combination with automatic person detection from thermal and visual video camera images. The approach combines weighted maps with a rule engine that associates data from multiple weighted maps. The proposed approach is tested on real data collected by the EU FOLDOUT project in a location representative of a range of forested EU borders. The results show that the proposed approach can eliminate single-sensor false detections and enhance accuracy by up to 50%

Cross-Platform Implementation of an SSVEP-Based BCI for the Control of a 6-DOF Robotic Arm

[EN] Robotics has been successfully applied in the design of collaborative robots for assistance to people with motor disabilities. However, man-machine interaction is difficult for those who suffer severe motor disabilities. The aim of this study was to test the feasibility of a low-cost robotic arm control system with an EEG-based brain-computer interface (BCI). The BCI system relays on the Steady State Visually Evoked Potentials (SSVEP) paradigm. A cross-platform application was obtained in C++. This C++ platform, together with the open-source software Openvibe was used to control a Staubli robot arm model TX60. Communication between Openvibe and the robot was carried out through the Virtual Reality Peripheral Network (VRPN) protocol. EEG signals were acquired with the 8-channel Enobio amplifier from Neuroelectrics. For the processing of the EEG signals, Common Spatial Pattern (CSP) filters and a Linear Discriminant Analysis classifier (LDA) were used. Five healthy subjects tried the BCI. This work allowed the communication and integration of a well-known BCI development platform such as Openvibe with the specific control software of a robot arm such as Staubli TX60 using the VRPN protocol. It can be concluded from this study that it is possible to control the robotic arm with an SSVEP-based BCI with a reduced number of dry electrodes to facilitate the use of the system.Funding for open access charge: Universitat Politecnica de Valencia.Quiles Cucarella, E.; Dadone, J.; Chio, N.; García Moreno, E. (2022). Cross-Platform Implementation of an SSVEP-Based BCI for the Control of a 6-DOF Robotic Arm. Sensors. 22(13):1-26. https://doi.org/10.3390/s22135000126221

Sensor Technologies to Manage the Physiological Traits of Chronic Pain: A Review

Non-oncologic chronic pain is a common high-morbidity impairment worldwide and acknowledged as a condition with significant incidence on quality of life. Pain intensity is largely perceived as a subjective experience, what makes challenging its objective measurement. However, the physiological traces of pain make possible its correlation with vital signs, such as heart rate variability, skin conductance, electromyogram, etc., or health performance metrics derived from daily activity monitoring or facial expressions, which can be acquired with diverse sensor technologies and multisensory approaches. As the assessment and management of pain are essential issues for a wide range of clinical disorders and treatments, this paper reviews different sensor-based approaches applied to the objective evaluation of non-oncological chronic pain. The space of available technologies and resources aimed at pain assessment represent a diversified set of alternatives that can be exploited to address the multidimensional nature of pain.Ministerio de Economía y Competitividad (Instituto de Salud Carlos III) PI15/00306Junta de Andalucía PIN-0394-2017Unión Europea "FRAIL

Aplicación de métodos heurísticos para optimizar la distribución de agua: un estudio de caso para la cuenca del río Machángara, Ecuador

El agua se puede representar por un nexo llamado WEF-Nexus que incluye suministro de agua, tratamiento de aguas residuales y generación de energía hidroeléctrica en un sistema de agua con reservorios (Liu et al., 2018). El factor WEF-Nexus considera: evitar inundaciones, cumplir con demandas de agua y mantener el nivel de agua en reservorios y segmentos de río. La optimización de la distribución de agua considerando este factor puede ser abordada con programación lineal, no lineal, dinámica-discreta y heurística. En (Veintimilla-Reyes et al., 2019), el autor aplicó programación lineal para la optimización de la distribución del agua en la cuenca del río Machángara, y este estudio busca la optimización en ese mismo contexto, pero aplicando métodos heurísticos. El modelo heurístico implementado es PSO (particle swarm optimization), que fue seleccionado luego de una revisión sistemática de literatura. Se consideran tres fases: calibración, validación y aplicación. La primera fase calibra variables necesarias para que el modelo reproduzca la realidad con datos de 1998-2001. Se valida comparando la salida del modelo parametrizado con los valores esperados en el período 2002-2003. Finalmente, se aplica el modelo para distribuir el agua óptimamente en el período 2004-2005. Los datos usados fueron facilitados por el Programa para el Manejo del Agua y del Suelo de la Universidad de Cuenca (Promas, 2022). De los resultados destaca que PSO y el paquete Pymoo (usado para la implementación) presentan dificultad para encontrar una solución que pueda satisfacer todas las restricciones. También se usa PSO para determinar el número óptimo de reservorios, pero el modelo sufre del mismo impedimento en satisfacer restricciones. Para trabajos futuros se plantea la implementación de algoritmos híbridos, y reducir el número de restricciones y variablesWater can be represented by a nexus called WEF-Nexus that includes water supply, wastewater treatment and hydroelectric power generation in a reservoir water system (Liu et al., 2018). The WEF-Nexus factor considers: avoiding floods, meeting water demands and maintaining the water level in reservoirs and river segments. The optimization of water distribution considering this factor can be approached with linear, non-linear, dynamicdiscrete and heuristic programming. In (Veintimilla-Reyes et al., 2019), the author applied linear programming to optimize the distribution of water in the Machángara river basin, and this study seeks optimization in that same context, but applying heuristic methods. The implemented heuristic model is PSO (particle swarm optimization), which was selected after a systematic literature review. Three phases are considered: calibration, validation and application. The first phase calibrates variables necessary for the model to reproduce reality with data from 1998-2001. It is validated by comparing the output of the parameterized model with the expected values in the 2002-2003 period. Finally, the model is applied to optimally distribute water in the 2004-2005 period. The data used were provided by the Program for Water and Soil Management of the University of Cuenca (Promas, 2022). From the results it stands out that PSO and the Pymoo package (used for the implementation) present difficulties in finding a solution that can satisfy all the constraints. PSO is also used to determine the optimal number of reservoirs, but the model suffers from the same handicap in satisfying constraints. For future work, the implementation of hybrid algorithms is proposed, and reduce the number of restrictions and variablesIngeniero de SistemasCuenc

Advances in Image Processing, Analysis and Recognition Technology

For many decades, researchers have been trying to make computers’ analysis of images as effective as the system of human vision is. For this purpose, many algorithms and systems have previously been created. The whole process covers various stages, including image processing, representation and recognition. The results of this work can be applied to many computer-assisted areas of everyday life. They improve particular activities and provide handy tools, which are sometimes only for entertainment, but quite often, they significantly increase our safety. In fact, the practical implementation of image processing algorithms is particularly wide. Moreover, the rapid growth of computational complexity and computer efficiency has allowed for the development of more sophisticated and effective algorithms and tools. Although significant progress has been made so far, many issues still remain, resulting in the need for the development of novel approaches

Natural Language Processing: Emerging Neural Approaches and Applications

This Special Issue highlights the most recent research being carried out in the NLP field to discuss relative open issues, with a particular focus on both emerging approaches for language learning, understanding, production, and grounding interactively or autonomously from data in cognitive and neural systems, as well as on their potential or real applications in different domains

Exploration of Virtual Reality Environments as an Efficacious, Evidence-Based Stress Reduction Activity in the Workplace Setting

With rapid technological change for workplace engagement, as well as unforeseeable impacts (i.e., COVID-19) that have universally changed the way we engage daily with work globally, there is value to examining innovative methods of reducing the impacts of stress when engaged with work. The research presented herein explores two areas focusing on VR-based workplace interventions. Study 1 examines two Virtual Reality (VR) relaxation interventions to determine if they have a significant effect on measures of physiological arousal, affect, and subjective measures. Qualitative participant feedback is also examined for factors that were of help or hindrance to the goal of relaxation. Participant views on the place of technology, such as VR in the future of workplace wellbeing, are also assessed. Results provided a majority belief in the value of developing workplace VR interventions, as well as reporting feelings of being more relaxed post-test. Study 2 is an exploratory survey that aims to explore general population respondents’ understanding and knowledge of VR and its applications for workplace wellbeing. The before/after effect of a short educational video is also explored, as well qualitative open-ended questions. The results suggest that education can have significant effects on peoples’ views and understanding of VR. This aligns with how most respondents reported they had a below-average understanding of VR. Responses indicate a majority of those surveyed had not used VR more than 5 times in the last five years, with most having not used it at all. After education, a majority indicated that they believed that VR could be a useful tool to combat workplace stress. These results demonstrate the potential of VR augmented relaxation interventions, bolstered by positive opinions on the potential of VR. Given the changing nature of workplaces and work itself, discussion of this change is provided along with recommendations for further study directions