997 resultados para Catholic Action
Resumo:
Large variations in human actions lead to major challenges in computer vision research. Several algorithms are designed to solve the challenges. Algorithms that stand apart, help in solving the challenge in addition to performing faster and efficient manner. In this paper, we propose a human cognition inspired projection based learning for person-independent human action recognition in the H.264/AVC compressed domain and demonstrate a PBL-McRBEN based approach to help take the machine learning algorithms to the next level. Here, we use gradient image based feature extraction process where the motion vectors and quantization parameters are extracted and these are studied temporally to form several Group of Pictures (GoP). The GoP is then considered individually for two different bench mark data sets and the results are classified using person independent human action recognition. The functional relationship is studied using Projection Based Learning algorithm of the Meta-cognitive Radial Basis Function Network (PBL-McRBFN) which has a cognitive and meta-cognitive component. The cognitive component is a radial basis function network while the Meta-Cognitive Component(MCC) employs self regulation. The McC emulates human cognition like learning to achieve better performance. Performance of the proposed approach can handle sparse information in compressed video domain and provides more accuracy than other pixel domain counterparts. Performance of the feature extraction process achieved more than 90% accuracy using the PTIL-McRBFN which catalyzes the speed of the proposed high speed action recognition algorithm. We have conducted twenty random trials to find the performance in GoP. The results are also compared with other well known classifiers in machine learning literature.
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We propose to develop a 3-D optical flow features based human action recognition system. Optical flow based features are employed here since they can capture the apparent movement in object, by design. Moreover, they can represent information hierarchically from local pixel level to global object level. In this work, 3-D optical flow based features a re extracted by combining the 2-1) optical flow based features with the depth flow features obtained from depth camera. In order to develop an action recognition system, we employ a Meta-Cognitive Neuro-Fuzzy Inference System (McFIS). The m of McFIS is to find the decision boundary separating different classes based on their respective optical flow based features. McFIS consists of a neuro-fuzzy inference system (cognitive component) and a self-regulatory learning mechanism (meta-cognitive component). During the supervised learning, self-regulatory learning mechanism monitors the knowledge of the current sample with respect to the existing knowledge in the network and controls the learning by deciding on sample deletion, sample learning or sample reserve strategies. The performance of the proposed action recognition system was evaluated on a proprietary data set consisting of eight subjects. The performance evaluation with standard support vector machine classifier and extreme learning machine indicates improved performance of McFIS is recognizing actions based of 3-D optical flow based features.
Resumo:
Action recognition plays an important role in various applications, including smart homes and personal assistive robotics. In this paper, we propose an algorithm for recognizing human actions using motion capture action data. Motion capture data provides accurate three dimensional positions of joints which constitute the human skeleton. We model the movement of the skeletal joints temporally in order to classify the action. The skeleton in each frame of an action sequence is represented as a 129 dimensional vector, of which each component is a 31) angle made by each joint with a fixed point on the skeleton. Finally, the video is represented as a histogram over a codebook obtained from all action sequences. Along with this, the temporal variance of the skeletal joints is used as additional feature. The actions are classified using Meta-Cognitive Radial Basis Function Network (McRBFN) and its Projection Based Learning (PBL) algorithm. We achieve over 97% recognition accuracy on the widely used Berkeley Multimodal Human Action Database (MHAD).
Resumo:
In this paper, we propose a H.264/AVC compressed domain human action recognition system with projection based metacognitive learning classifier (PBL-McRBFN). The features are extracted from the quantization parameters and the motion vectors of the compressed video stream for a time window and used as input to the classifier. Since compressed domain analysis is done with noisy, sparse compression parameters, it is a huge challenge to achieve performance comparable to pixel domain analysis. On the positive side, compressed domain allows rapid analysis of videos compared to pixel level analysis. The classification results are analyzed for different values of Group of Pictures (GOP) parameter, time window including full videos. The functional relationship between the features and action labels are established using PBL-McRBFN with a cognitive and meta-cognitive component. The cognitive component is a radial basis function, while the meta-cognitive component employs self-regulation to achieve better performance in subject independent action recognition task. The proposed approach is faster and shows comparable performance with respect to the state-of-the-art pixel domain counterparts. It employs partial decoding, which rules out the complexity of full decoding, and minimizes computational load and memory usage. This results in reduced hardware utilization and increased speed of classification. The results are compared with two benchmark datasets and show more than 90% accuracy using the PBL-McRBFN. The performance for various GOP parameters and group of frames are obtained with twenty random trials and compared with other well-known classifiers in machine learning literature. (C) 2015 Elsevier B.V. All rights reserved.
Resumo:
This paper discusses a novel high-speed approach for human action recognition in H.264/AVC compressed domain. The proposed algorithm utilizes cues from quantization parameters and motion vectors extracted from the compressed video sequence for feature extraction and further classification using Support Vector Machines (SVM). The ultimate goal of the proposed work is to portray a much faster algorithm than pixel domain counterparts, with comparable accuracy, utilizing only the sparse information from compressed video. Partial decoding rules out the complexity of full decoding, and minimizes computational load and memory usage, which can result in reduced hardware utilization and faster recognition results. The proposed approach can handle illumination changes, scale, and appearance variations, and is robust to outdoor as well as indoor testing scenarios. We have evaluated the performance of the proposed method on two benchmark action datasets and achieved more than 85 % accuracy. The proposed algorithm classifies actions with speed (> 2,000 fps) approximately 100 times faster than existing state-of-the-art pixel-domain algorithms.
Resumo:
Pt(cur)(NH3)(2)](NO3) (1), a curcumin-bound cis-diammineplatinum(II) complex, nicknamed Platicur, as a novel photoactivated chemotherapeutic agent releases photoactive curcumin and an active platinum(II) species upon irradiation with visible light. The hydrolytic instability of free curcumin reduces upon binding to platinum(II). Interactions of 1 with 5'-GMP and ct-DNA indicated formation of platinum-bound DNA adducts upon exposure to visible light (lambda = 400-700 nm). It showed apoptotic photocytotoxicity in cancer cells (IC50 approximate to 15 mu M), thus forming (OH)-O-center dot, while remaining passive in the darkness (IC50 > 200 mu M). A comet assay and platinum estimation suggest Pt-DNA crosslink formation. The fluorescence microscopic images showed cytosolic localization of curcumin, thus implying possibility of dual action as a chemo-and phototherapeutic agent.
Resumo:
Let Gamma subset of SL2(Z) be a principal congruence subgroup. For each sigma is an element of SL2(Z), we introduce the collection A(sigma)(Gamma) of modular Hecke operators twisted by sigma. Then, A(sigma)(Gamma) is a right A(Gamma)-module, where A(Gamma) is the modular Hecke algebra introduced by Connes and Moscovici. Using the action of a Hopf algebra h(0) on A(sigma)(Gamma), we define reduced Rankin-Cohen brackets on A(sigma)(Gamma). Moreover A(sigma)(Gamma) carries an action of H 1, where H 1 is the Hopf algebra of foliations of codimension 1. Finally, we consider operators between the levels A(sigma)(Gamma), sigma is an element of SL2(Z). We show that the action of these operators can be expressed in terms of a Hopf algebra h(Z).
Resumo:
波浪作用下海床的稳定性与液化分析是海底管线、防波堤和海洋平台设计中必须仔细考虑的问题。推荐了一个循环载荷作用下土体的弹塑性实用本构模型,并给出了一种粉土的模型参数,该模型直接根据初始应力状态和循环应力的大小与作用时间计算土体的塑性应变增量,在有限元计算中不需要引入弹塑性矩阵。采用Biot理论和有限单元法,对海床有效应力的变化过程分析表明,波腹点下海床存在较大的液化可能性。波浪作用对海床存在一定的压密作用。
Resumo:
To describe the various complex mechanisms of the dissipative dynamical system between waves, currents, and bottoms in the nearshore region that induce typically the wave motion on large-scale variation of ambient currents, a generalized wave action equation for the dissipative dynamical system in the nearshore region is developed by using the mean-flow equations based on the Navier-Stokes equations of viscous fluid, thus raising two new concepts: the vertical velocity wave action and the dissipative wave action, extending the classical concept, wave action, from the ideal averaged flow conservative system into the real averaged flow dissipative system (that is, the generalized conservative system). It will have more applications.
Resumo:
Resumen: El artículo describe las características principales del documento pontificio La vocación del líder empresarial: una reflexión, destacando su génesis y sus objetivos. Sin embargo, presenta también las debilidades que encuentra en el texto. En primer lugar, el autor critica el modo en que se tratan las cuestiones laborales, especialmente la falta de referencias a la noción de “empleador indirecto” de Juan Pablo II. Luego, postula que el documento tampoco presenta el problema de la organización del trabajo, tema que fue tratado tanto por el Papa Pío XI como por Juan Pablo II. Por otra parte, aclara que el documento hace referencia al derecho a un salario justo pero no aporta ideas acerca del modo en que debería articularse la relación entre los propietarios de la empresa y los trabajadores. Finalmente, el autor sostiene que el documento omite el problema del lobbying que tanto afecta a la moral del mercado
Resumo:
Introducción: This article provides a historical interpretation of Catholic social economy (also called Social Catholicism) in an attempt to give a Christian form to capitalism. The aim of this writing is to reflect on the evolution of Catholic economic thought and to offer some foreseeable development in light of the experience that characterized the early stages of this movement. By Catholic social economy, the author does not mean the social doctrine of the church, but the whole set of scientific work of Catholic scholars, with their different orientations and acceptance by the official documents of the holy soil. Roman Catholicism is the only religion that has produced wide and continuous scientific research about political economy. This should not be considered an anomaly, because the positivistic attitude of modern economics tends to crowd out the classic unitary view of man and of a good life that characterizes Catholic anthropology. As a consequence, it can be considered an attempt to address scientific research in a way compatible to the Catholic view of the “social nature of man”, and not an attempt to resist or to contrast the role of science. The fundamental concepts of this stream of research have been the idea of natural law intended as a moral order (vs. the equilibrium of conflicting strategies), the social nature of man (vs. individualism and individual autonomy) and the role that charity and justice assume for individual behaviour inspired by the common good (vs. freedom and laissez faire)...
Resumo:
En este trabajo se presentan los resultados de una investigación sobre los Enfoques de Aprendizaje correspondientes a 157 estudiantes de las carreras de Psicopedagogía y Ciencias de la Educación de la Facultad de Psicología y Educación de la Pontificia Universidad Católica Argentina (Buenos Aires).* Se utilizó el Cuestionario de Procesos de Estudio, de Biggs- Hernández Pina. Se analizó la predominancia de los enfoques Superficial, Profundo y de Alto Rendimiento en la población estudiada, diferenciando entre motivos y estrategias de aprendizaje. El análisis discriminó el nivel de los alumnos en la carrera (Psicopedagogía). A partir de las conclusiones se hicieron actividades de orientación dirigidas a los docentes para lograr optimizar la acción educativa.