Psychoeducational strategies to support the adjustment processes of Third Culture Kids (TCKs) and Third Culture Adults (ATCKs)

As more families continue to relocate to other countries due to professional opportunities, more children live abroad. These unique children are known as third culture kids (TCKs). These individuals are spending, or have spent, a significant number of developmental years outside their parent’s cultures(s). Due to their high mobility lifestyles, they experience a series of challenges, such as developing multiple senses of belonging or no sense of belonging. Hence, feelings of being misunderstood by their community are recurrent among them. Generally, TCKs attend international schools, specifically International Baccalaureate Programme (IBP) schools. TCKs have significant academic and socio-personal needs during periods of transition that should be identified by school personnel. Therefore, developing psychoeducational resources to support their adjustment processes is crucial

Pyramidal Fisher Motion for Multiview Gait Recognition

Submitted to International Conference on Pattern Recognition, ICPR, 2014The goal of this paper is to identify individuals by analyzing their gait. Instead of using binary silhouettes as input data (as done in many previous works) we propose and evaluate the use of motion descriptors based on densely sampled short-term trajectories. We take advantage of state-of-the-art people detectors to define custom spatial configurations of the descriptors around the target person. Thus, obtaining a pyramidal representation of the gait motion. The local motion features (described by the Divergence-Curl-Shear descriptor) extracted on the different spatial areas of the person are combined into a single high-level gait descriptor by using the Fisher Vector encoding. The proposed approach, coined Pyramidal Fisher Motion, is experimentally validated on the recent `AVA Multiview Gait' dataset. The results show that this new approach achieves promising results in the problem of gait recognition

Evaluation of CNN architectures for gait recognition based on optical flow maps

This work targets people identification in video based on the way they walk (\ie gait) by using deep learning architectures. We explore the use of convolutional neural networks (CNN) for learning high-level descriptors from low-level motion features (\ie optical flow components). The low number of training samples for each subject and the use of a test set containing subjects different from the training ones makes the search of a good CNN architecture a challenging task.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Fisher Motion Descriptor for Multiview Gait Recognition

The goal of this paper is to identify individuals by analyzing their gait. Instead of using binary silhouettes as input data (as done in many previous works) we propose and evaluate the use of motion descriptors based on densely sampled short-term trajectories. We take advantage of state-of-the-art people detectors to de ne custom spatial con gurations of the descriptors around the target person, obtaining a rich representation of the gait motion. The local motion features (described by the Divergence-Curl-Shear descriptor [1]) extracted on the di erent spatial areas of the person are combined into a single high-level gait descriptor by using the Fisher Vector encoding [2]. The proposed approach, coined Pyramidal Fisher Motion, is experimentally validated on `CASIA' dataset [3] (parts B and C), `TUM GAID' dataset [4], `CMU MoBo' dataset [5] and the recent `AVA Multiview Gait' dataset [6]. The results show that this new approach achieves state-of-the-art results in the problem of gait recognition, allowing to recognize walking people from diverse viewpoints on single and multiple camera setups, wearing di erent clothes, carrying bags, walking at diverse speeds and not limited to straight walking paths

Complicaciones de los osteocondromas

Los osteocondromas o exostosis cartilaginosas son los tumores óseos más frecuentes, representando el 10-15 % de la totalidad. Parece ser más bien una alteración del desarrollo óseo más que un tumor verdadero. Suele tener una imagen radiográfica patognomónica. Los osteocondromas pueden ser solitarios o múltiples, estos últimos forman parte del síndrome de exostosis múltiples hereditarias, de transmisión autosómica dominante. Las complicaciones que pueden presentar, pueden ser óseas; deformidad del hueso donde asientan o fracturas del mismo, o de los tejidos que lo rodean, pudiendo provocar trastornos neurológicos, vasculares, bursitis, y la peor complicación, que es su malignización. Existen variantes de los osteocondromas como la exostosis subungueal, la displasia epifisaria hemimielica, y las exostosis en torreta y por tracción. Es importante conocer la apariencia radiológica de todos los tipos de exostosis, para diferenciarlas de sus posibles complicaciones.Osteochondroma, also termed osteocartlaginous exostoses represents the most common bone tumors and is a developmental lesion rather than a true neoplasm. It constitutes 10-15 % of all bone tumors. Its radiologic features are often pathognomonic. Osteochondromas may be solitary or multiple, the latter being associated with the autosomal dominant syndrome, hereditary multiple exostoses. Complications associated with osteochondroma include deformity, fracture, vascular compromise, neurologic sequelae, overlying bursa formation, and malignant transformation. Variant of osteochondroma include subungueal exostosis, dysplasia epiphysealis hemimelica, turret and traction exostoses. Recognition of the radiologic spectrum of appearances of osteochondroma and its variants allow prospective diagnosis and differentiation of the numerous potential complications

Caractérisation des systèmes de production ovine dans la zone de "Sierra del Segura y la Sagra", Espagne

[FR] Le présent article se propose d¿analyser les caractéristiques les plus saillantes du secteur ovin dans une partie de la zone géographique sous Indication Géographique Protégée (IGP) "Cordero de Segura y la Sagra". Une enquête a été menée sur 93 propriétaires d¿élevages, dans l'objectif de connaître la situation du secteur dans cette zone. Les questions concernaient les sujets suivants: caractéristiques du troupeau, âge, niveau d'études, ouvriers à la ferme, continuité des activités de la ferme. La taille moyenne du troupeau est de 378 animaux et la race "Segureña" est prédominante (99%). Dans 93,4% des cas l¿éleveur travaille à temps plein dans l¿exploitation et le revenu principal est la vente d¿agneaux pour la viande, mais seulement 9,7% des éleveurs font partie d¿une coopérative pour la commercialisation. L'âge moyen du fermier est de 50 ans et 87,1% des éleveurs n¿ont pas d¿études ou de faible niveau. La moyenne du travail employé est de 1,31 UTA, essentiellement de type familial. Seulement dans 12% des cas il existe une sécurité de la continuité de l'activité. Les résultats obtenus montrent qu'il est nécessaire de parvenir à de meilleures conditions socioéconomiques pour les exploitations dans la zone étudiée. L'IGP "Cordero de Segura y la Sagra" pourrait être utile pour améliorer ces aspects.[EN] The aim of this study is to present the basic characteristics which define the sheep systems in some zones of the PGI Cordero de Segura y la Sagra protected area, in order to bring about actions to improve the competitiveness of such systems. A survey has been conducted among 93 farm owners. The questionnaire included questions regarding herd characteristics, age, educational level, workers, and continuity of the farm activity. The average herd size is 378 animals and the Segureña breed sheep is predominant (99 percent). In 93.5 percent of cases the owner works full time on the farm and the main economic benefit is the sale of lambs for meat, but only 9.7 percent of farmers belong to some kind of marketing cooperative. The average farmer's age is 50 years old and a high percentage (87.1 percent) has no education or a very basic one. The year work unit (YWU) is 1.31 and the work is mainly of family type. In only 12 percent of the cases the continuity of the activity is assured. The above analysed aspects show that it is necessary to achieve better socioeconomic conditions of farms. The PGI Cordero de Segura y la Sagra could be useful to improve these aspects. Therefore we suggest that the PGI must be promoted among farmers, especially among young people.Navarro-Ríos, M.; Marín-Bernal, A.; Martí, A.; Fernández Martínez, CJ. (2011). Characterizacion of Segureña sheep production system in the area of Sierra del Segura y la Sagra, Spain. Options Mediterraneennes. Serie A: Seminaires Mediterraneens. (100):211-216. http://hdl.handle.net/10251/107315S21121610

Mixing body-parts model for 2D human pose estimation in stereo videos

This study targets 2D articulated human pose estimation (i.e. localisation of body limbs) in stereo videos. Although in recent years depth-based devices (e.g. Microsoft Kinect) have gained popularity, as they perform very well in controlled indoor environments (e.g. living rooms, operating theatres or gyms), they suffer clear problems in outdoor scenarios and, therefore, human pose estimation is still an interesting unsolved problem. The authors propose here a novel approach that is able to localise upper-body keypoints (i.e. shoulders, elbows, and wrists) in temporal sequences of stereo image pairs. The authors' method starts by locating and segmenting people in the image pairs by using disparity and appearance information. Then, a set of candidate body poses is computed for each view independently. Finally, temporal and stereo consistency is applied to estimate a final 2D pose. The authors' validate their model on three challenging datasets: `stereo human pose estimation dataset', `poses in the wild' and `INRIA 3DMovie'. The experimental results show that the authors' model not only establishes new state-of-the-art results on stereo sequences, but also brings improvements in monocular sequences

Human interaction categorization by using audio-visual cues

Human Interaction Recognition (HIR) in uncontrolled TV video material is a very challenging problem because of the huge intra-class variability of the classes (due to large differences in the way actions are performed, lighting conditions and camera viewpoints, amongst others) as well as the existing small inter-class variability (e.g., the visual difference between hug and kiss is very subtle). Most of previous works have been focused only on visual information (i.e., image signal), thus missing an important source of information present in human interactions: the audio. So far, such approaches have not shown to be discriminative enough. This work proposes the use of Audio-Visual Bag of Words (AVBOW) as a more powerful mechanism to approach the HIR problem than the traditional Visual Bag of Words (VBOW). We show in this paper that the combined use of video and audio information yields to better classification results than video alone. Our approach has been validated in the challenging TVHID dataset showing that the proposed AVBOW provides statistically significant improvements over the VBOW employed in the related literature

Las competencias profesionales de la titulación de Magisterio vistas desde la óptica del alumno receptor. Estudio del caso de Educación Primaria

La determinación de las competencias profesionales marcadas por el Proyecto Tuning señala el desarrollo de las diferentes titulaciones. Sin embargo, en la especificación de éstas, el alumno ha tenido una escasa participación. Con el presente estudio, realizado con una ayuda de la VI Convocatoria de Proyectos de Innovación de la Universidad de Córdoba, se pretende determinar la importancia que los futuros maestros conceden a las competencias establecidas en el referido Proyecto para su titulación. El cuestionario, construido ad hoc para la recogida de datos, fue aplicado a una muestra de estudiantes matriculados en primer curso de Magisterio –especialidad Educación Primaria– de la Facultad de Ciencias de la Educación de la Universidad de Córdoba, durante su asistencia a una asignatura troncal. Los datos recabados fueron sometidos a tratamiento estadístico mediante el paquete SPSS

The AVA Multi-View Dataset for Gait Recognition

In this paper, we introduce a new multi-view dataset for gait recognition. The dataset was recorded in an indoor scenario, using six convergent cameras setup to produce multi-view videos, where each video depicts a walking human. Each sequence contains at least 3 complete gait cycles. The dataset contains videos of 20 walking persons with a large variety of body size, who walk along straight and curved paths. The multi-view videos have been processed to produce foreground silhouettes. To validate our dataset, we have extended some appearance-based 2D gait recognition methods to work with 3D data, obtaining very encouraging results. The dataset, as well as camera calibration information, is freely available for research purpose