Action Trajectories Research Articles

Tracking and Extracting Action Trajectory of Athlete Based on Hierarchical Features

The feature extraction from athlete action images is a research hotspot. To accurately evaluate athlete actions, it is necessary to partition the original image into refined blocks, and extract different levels of image features. However, the traditional feature extraction algorithms can only roughly divide action images into several classes, failing to acquire the accurate feature sets of the actions. This leads to relatively poor performance of feature extraction from action images. To overcome the defect of the traditional methods, this paper puts forward a feature extraction method for the action images of badminton players based on hierarchical features. The underlying image features were analyzed based on the techniques of badminton players, and mapped to the feature space of the corresponding dimension. Simulation results show that the proposed method can accurately extract the features from athlete action images.

A data augmentation method for human action recognition using dense joint motion images

With the development of deep learning and neural network techniques, human action recognition has made great progress in recent years. However, it remains challenging to analyse temporal information and identify human actions with few training samples. In this paper, an effective motion image called a dense joint motion image (DJMI) was proposed to transform an action to an image. Our method was compared with state-of-the-art methods, and its contributions are mainly reflected in three characteristics. First, in contrast to the current classic joint trajectory map (JTM), every pixel of the DJMI is useful and contains essential spatio-temporal information. Thus, the input parameters of the deep neural network (DNN) are reduced by an order of magnitude, and the efficiency of action recognition is improved. Second, each frame of an action video is encoded as an independent slice of the DJMI, which avoids the information loss caused by action trajectory overlap. Third, by using DJMIs, proven algorithms for graphics and images can be used to generate training samples. Compared with the original image, the generated DJMIs contain new and different spatio-temporal information, which enables DNNs to be trained well on very few samples. Our method was evaluated on three benchmark datasets, namely, Florence-3D, UTKinect-Action3D and MSR Action3D. The results showed that our method achieved a recognition speed of 37 fps with competitive accuracy on these datasets. The time efficiency and few-shot learning capability of our method enable it to be used in real-time surveillance.

The coronavirus pandemic, libraries and information: a thematic analysis of initial international responses to COVID-19

PurposeThis study aims to present and discuss the international library and information community’s initial responses to the coronavirus pandemic. It chronicles official statements from various library and information associations as they were released in real-time, thereby providing a contemporary and historical snapshot of the early stages of this global health crisis. The aim is to both historically and thematically contextualize these initial responses to help establish a foundation upon which to anchor, build, extend and analyze approaches to the pandemic as it unfolded (and indeed as it continues to unfold at the time of this writing in June 2020).Design/methodology/approachDrawing upon a qualitative documentary analysis of statements on COVID-19 released by various international library and information associations, this study provides a thematic analysis of these contemporary policies. Specifically, this thematic analysis was carried out to identify and illuminate major themes appearing within the statements. Further, a comparative thematic analysis was then undertaken to compare the themes across all statements to discover and determine convergences or divergences in content and coverage.FindingsThe formal statements released by these organizations feature and share many similar themes in their initial responses to COVID-19, including support for/solidarity with libraries; information provision; maintaining services; digital migration of services; workplace arrangements/concerns; contextual contingencies of libraries (diversity of kinds, circumstances and challenges); health concerns and proper/good hygiene; countering dis/misinformation; external collaborations with public health agencies; and partnerships with industry including publishers.Research limitations/implicationsAlthough this study’s purview is admittedly limited in size and scope – involving six, albeit major, library and information associations from mainly English speaking countries – it can be used as a foundation for further studies into how libraries and information centres in other English and non-English speaking countries responded to the coronavirus pandemic.Practical implicationsThis study can help inform current, alternative, contingency or other future library responses geared towards or tailored for the coronavirus or other health-related crises. It can also be used as a baseline to track the trajectory of library responses and actions as they unfolded throughout the COVID-19 crisis.Social implicationsBy providing the start of an account and analysis of the international library and information science (LIS) community’s initial responses, this study also contributes to the broader (ongoing) conversation about the coronavirus pandemic and intervenes in emerging historical examinations of this crisis. This study could be of interest to LIS scholars and practitioners, in addition to public health researchers, public policymakers, cultural studies academics and historians, interested in how different and intersectional efforts – in this case, the international LIS community – contributed and can contribute to this pandemic and other similar or parallel crises.Originality/valueThe international library and information community’s initial responses to this global health crisis are contextualized, thereby serving as a foundation upon which to anchor, build and extend other research on responses to the pandemic as it unfolded. Drawing upon a qualitative documentary analysis of these statements, this study presents and discusses the international library community’s initial responses to the coronavirus pandemic. It chronicles these statements as they were released in real-time, thereby providing a contemporary and historical snapshot of the early stages of this crisis. The aim is to both historically and thematically contextualize the international library and information community’s initial responses to help establish a foundation upon which to anchor, build, extend and update the international library community’s responses to the pandemic as it unfolded (and indeed as it continues to unfold at the time of this writing in June 2020). This foundation, it is hoped, will help illuminate their respective positions, circumstances, convergences, divergences and areas of possible (future) cooperation, coordination and collaboration.

A fall detection method based on a joint motion map using double convolutional neural networks

Automatic fall detection approaches are essential for elderly people, particularly for those who live alone, because of the pressing need for immediate medical assistance. In this paper, we proposed a highly effective fall detection method based on a joint motion map using two parallel convolutional neural networks. Compared with the most commonly used joint trajectory method (JTM), our proposed method provided three major improvements. First, the three channels (R, G and B) of a pixel were creatively used to store relative motion information of a certain joint in 3D coordinates. Thus, the human action recognition problem was simplified as a multi-class problem after actions were encoded as images. Moreover, the input parameters were dramatically reduced because of concentration only on 25 joints of the human skeleton. Second, human motion information in each frame was encoded as an independent slice of a motion image, which avoids the information loss problem caused by action trajectory overlap. Third, under the guidance of a medical experiment, the limit of stability test (LOST), the start key frame and end key frame of a possible fall can be exactly estimated. Therefore, motion images can be generated with a fixed size. Our method was evaluated on two publicly available datasets: the Telecommunication Systems Team fall detection dataset V2 (TST v2) and UTKinect-Action3D Dataset (UT-A3D). The experimental results show that our method achieved an accuracy of 97.35% on TST v2 and performed excellently in the fall discrimination capability test on UT-A3D.

Deep transfer learning for gesture recognition with WiFi signals

Different gestures have different action speeds, directions, and trajectories that can cause distinctive effects on the propagation of WiFi signals. In this paper, we present a new approach that uses deep transfer learning techniques to recognize gestures based on the channel state information (CSI) extracted from WiFi signals. Firstly, the CSI streams of gestures are captured and the gesture segments are extracted based on the CSI amplitude changes, and then the WiFi-based gesture recognition problem is innovatively converted to an image classification problem by expressing CSI streams as an image matrix. After that, two deep transfer learning methods are applied to recognize gestures using high-level features extracted by deep convolutional neural network (CNN) and fine-tuned CNN models. We evaluated our method using a collected dataset with 12 gestures in two environments, and the experimental results demonstrated that the proposed method outperformed other state-of-the-art WiFi-based gesture recognition methods.

‘Fuck It, Shit Happens (FISH)’: a social generations approach to understanding young people’s imaginings of life after school in 2016–2017

ABSTRACTThis article uses a social generations approach to explore the lives of young people transitioning to life after schooling. Drawing on ethnographic research in England during the geopolitical uncertainty of 2016–2017, we track the trajectories and narratives of six individuals. The research begins with final year pupils in schools talking about their futures, during and after their A-Level exams. We then follow these individuals on routes to Higher Education and employment, exploring how they are socialised into imaginings of the future and/or struggle to inhabit these futures. A deeply ingrained, modernist, neoliberal reckoning of future time is normalised through experiences of schooling. However, this logic is troubled profoundly in the transition to life after school. Young people’s experiences in an unpredictable present run in stark contrast to the ordered trajectory of future action they have been socialised to expect. Amidst this uncertainty, ambivalence towards shaping the future (‘Fuck It, Shit Happens’) can in some ways feel like the most agentic stance to take. Furlong et al.’s (2011) social generations approach to understanding youth transitions reveals how we must critique the very concept of ‘the future’ if we are to understand the reality of youth transitions in the present.

Memórias ignoradas: uma narrativa do início de Maringá sob a ótica da habitação popular

A partir da construção histórica local, o presente artigo analisa o início de Maringá dando ênfase aos princípios norteadores e às ações estatais sobre a habitação popular durante a estruturação do território urbano. Buscou-se estabelecer, a partir da pesquisa historiográfica, um discurso que permeasse a trajetória das ações estatais, dos agentes envolvidos, dos discursos, dos conflitos, das orientações das legislações urbanísticas e os resultados no território urbano de Maringá de 1947 até 1964. Os princípios que nortearam o plano inicial de Jorge Macedo e, posteriormente, as ações do poder público municipal formalizaram uma gênese excludente na estrutura urbana, com iniciativas desconexas a uma política pública habitacional que apenas responderam às pressões imobiliárias e ao ideário de cidade bela, moderna e ausente de “mazelas”. A historiografia oficial do início de Maringá pouco expõe a realidade da população de baixa renda, entretanto, desde de sua origem, a cidade transbordava-se em problemas sociais e desenvolvia-se com a presença diversos núcleos precários e de extrema pobreza, sistematicamente ignorados pela história urbana.

Learning from Demonstration Based on a Classification of Task Parameters and Trajectory Optimization

Learning from demonstration involves the extraction of important information from demonstrations and the reproduction of robot action sequences or trajectories with generalization capabilities. Task parameters represent certain dependencies observed in demonstrations used to constrain and define a robot action because of the infinite nature of the state-space environment. We present the methodology for learning from demonstration based on a classification of task parameters. The classified task parameters are used to construct a cost function, responsible for describing the demonstration data. For reproduction we propose a novel trajectory optimization that is able to generate a simplified version of the trajectory for different configurations of the task parameters. As the last step before reproduction on a real robotic arm we approximate this trajectory with a Dynamic movement primitive (DMP) - based system to retrieve a smooth trajectory. Results obtained for trajectories with three degrees of freedom (two translations and one rotation) show that the system is able to encode multiple task parameters from a low number of demonstrations and generate trajectories that are collision free.

Question-response-evaluation sequences in the home interactions of a bilingual child with autism spectrum disorder.

Prior research has described the prevalence and utility of questions in children's language learning environment. However, there has been little empirical investigation of the interaction sequences that ensue following caregiver questions. Understanding these interactions may be especially important for children with autism spectrum disorder (ASD), who may have difficulty engaging in reciprocal interactions. Question-response-evaluation sequences (QRE) are a particular type of interaction sequence launched by questions that have been examined primarily in classroom contexts. Less research has been devoted to understanding how caregivers and children with ASD leverage this interactional format in the context of home interactions. We focus on QRE sequences within interactions between a 5-year-old bilingual child with ASD and his parents. In these sequences, the adult poses known-answer questions, the child responds and the adult evaluates the response. QRE sequences are primarily structured by the questioner (i.e., the parents in our context), and we examine the interactive work done by parents to initiate, maintain and close these sequences. We also examine the child's contributions to these sequences. We applied conversation analysis (CA) to video recordings of home routines, such as play, book-reading and schoolwork. Videos were fully transcribed using CA conventions, and 55 QRE segments were isolated from the data corpus for further analysis. Q-word questions (i.e., where, what, why, when, how questions) were the most prevalent question format, and repetition of the child's response was the most prevalent form of evaluation. We found that QRE sequences were embedded within a variety of action trajectories that extend beyond pedagogical functions. These included repairing a prior utterance, extending collaborative play routines and engaging in topically connected labelling rituals. QRE sequences appeared to strike a balance in terms of the level of constraint they placed on the child's contributions to interactions, and the affordances they provide for participating in and progressing through interactions. This study can help clinicians understand the types of interactions that can be pursued with QRE sequences in their work with children with ASD. The findings may also aid intervention researchers' efforts to leverage caregivers' existing strengths for adapting their interactional overtures to maximize children's engagement. Finally, this study provides an illustration of caregiver-child interactions in a population that is currently under-represented in the literature.

Turning the Passer-by into a Customer: Multi-party Encounters at a Market Stall

ABSTRACTInteractions at a fruit and vegetable stall in a public market are analyzed—focusing on the moments of configurative change as one sales encounter comes to an end and another begins. Market participants address the lack of structural regulation endemic to an open market stall by interactively achieving an order for sales. Participants’ role transformations from passersby to customers turn out to be finely intertwined with respective changes to the entire configuration at the market stall. The evidence demonstrates that various forms of interactions are at play in a public market that go beyond the boundaries of dyadic and focused sales encounters. Furthermore, the complex nature of multiple actors in informal settings managing divergent action trajectories can result in participants entering encounters “at the wrong moment,” thus lacking situational knowledge to interpret a constellation “correctly.” Overall, the findings connect conversation analytic studies on service encounters with sociological and ethnomethodological research on interaction in public spaces. The data are in Swiss German with an English translation.

Compliant Parametric Dynamic Movement Primitives

SummaryIn this paper, we propose and implement an advanced manipulation framework that enables parametric learning of complex action trajectories along with their haptic feedback profiles. Our framework extends Dynamic Movement Primitives (DMPs) method with a new parametric nonlinear shaping function and a novel force-feedback coupling term. The nonlinear trajectories of the action control variables and the haptic feedback trajectories measured during execution are encoded with parametric temporal probabilistic models, namely parametric hidden Markov models (PHMMs). PHMMs enable autonomous segmentation of a taught skill based on the statistical information extracted from multiple demonstrations, and learning the relations between the model parameters and the properties extracted from the environment. Hidden states with high-variances in observation probabilities are interpreted as parts of the skill that could not be reliably learned and autonomously executed due to possibly uncertain or missing information about the environment. In those parts, our proposed force-feedback coupling term, which computes the deviation of the actual force feedback from the one predicted by the force-feedback PHMM, acts as a compliance term, enabling a human to scaffold the ongoing movement trajectory to accomplish the task. Our method is verified in a number of tasks including a real pick and place task that involves obstacles of different heights. Our robot, Baxter, successfully learned to generate the trajectory taking into the heights of the obstacles, move its end effector stiffly (and accurately) along the generated trajectory while passing through apertures, and allow human–robot collaboration in the autonomously detected segments of the motion, for example, when the gripper picks up the object whose position is not provided to the robot.

Identity or Identical? Schools Vision Statements Comparative Content Analysis: The Israeli Case

ABSTRACT An in-depth understanding of field-level educational school goals and educational leadership action trajectories as embodied and represented in school vision content is of scholarly and practical importance. This is even more true in an era of expanding social pluralism and rising school autonomy owing to the leadership and policy tension between unique and unifying goals in the school vision content. In this context, the lack of research into the content of vision statements is puzzling. This study therefore aims to analyze school vision statements in Israeli public education in the context of the unique and unifying educational objectives they represent.

Regulatory competence as a factor of semantic co-directed interaction of teachers and students of master’s degree

the urgency of consideration of the semantic interaction of teachers and students through the development of their readiness for samoregulyatsiya competent regulatory support individual trajectory of professional and didactic actions on the basis of the integrative personal characteristics; the process of implementation of the program of interactive development of regulatory competence as a factor of semantic co-directed interaction of teachers and students of the master’s degree of the University in the course of teaching the discipline “Acmeological foundations of identity and meaning formation”is considered. Data on the results obtained and criteria for effective evaluation of the results of the process under study are presented. The substantiation of the concept of “educational semantic Elevator” implemented by students as a trajectory of individual and personal self-development in the conditions of psychological and pedagogical support from teachers and psychologists is presented;.semantic conditionality of development of regulatory competence in professionally directed didactic interaction of teachers and students of faculties of pedagogy and psychology in the course of studying of disciplines of a psychological and pedagogical cycle; qualitative characteristics of the co-directed semantic professionally significant didactic interaction. Abstract: the article deals with the process of implementation of the program of interactive development of regulatory competence as a factor of semantic co-directional interaction of teachers and students of the master’s degree in the course of teaching the discipline “acmeological basis of identification and meaning formation”. Provides information about the results obtained and the criteria for an effective evaluation of the results of the process under study. The substantiation of semantic conditionality of development of regulatory competence in professionally directed didactic interaction of teachers and students of faculties of pedagogy and psychology in the process of studying disciplines of psychological and pedagogical cycle is presented.

Re-imagining Petitioning in Spain (1808–1823)

This article examines collective petitioning in metropolitan Spain during the Age of Revolution, focusing on the practices and discourses that framed petitioning as a meaningful form of action. There was a deeply rooted tradition of petitioning in old regime Spain, which was part of the ordinary bureaucratic workings of the crown and also provided a legitimizing framework for rioting in specific contexts. The collective experimentation in popular participation after the 1808 Napoleonic invasion transformed petitioning. Petitioning was first reconceptualized in accordance with the emerging language of rights and popular sovereignty. Activists and commentators had some awareness of the use of public petitioning in Britain, and once the representative Cortes met in Cadiz in 1810, public petition drives on public issues became part of the political culture. At the same time, the need to legitimate unconventional forms of action in the context of a crisis in the state converted petitioning into an all-embracing right. The right to petition, not only encompassed signed protest texts but also legitimated the old tradition of petitioning by riot and further was used to justify provincial rebellions, juntas, and military pronunciamientos. In comparative terms, this article highlights the elasticity of the language of petitioning during the Age of Revolution and cautions against narrowly associating it with one particular form of collective action or historical trajectory.

Grupo de Pesquisa Formação de Professores, políticas públicas e espaço escolar

Nosso objetivo neste artigo é apresentar o Grupo de Pesquisa “Formação de Professores, Políticas Públicas e Espaço Escolar”, ligado ao Programa de Pós-Graduação em Educação (Mestrado e Doutorado) da Faculdade de Ciências e Tecnologia da Universidade Estadual Paulista “Júlio de Mesquita Filho”, Campus Presidente Prudente (SP). Este Grupo, ao longo destas duas décadas de existência no contexto educacional do oeste paulista, tem pautado sua atuação no compromisso com uma escola pública de qualidade para todos, tanto na docência quanto na pesquisa e extensão. O texto está estruturado em nove secções que abrangem a apresentação e histórico do GPFOPE, a perspectiva conceitual no qual se inscrevem as pesquisas de seus integrantes, bem como as temáticas e metodologias predominantes. Explicita a dinâmica de trabalho, as relações com outros grupos de pesquisa e a produção acadêmica e técnica de seus integrantes. Nas considerações finais traz os aspectos considerados como marcantes na sua trajetória e as perspectivas futuras de atuação.

POLITICAL CONTROL AND RESPONSIBILITY OF THE GOVERNMENT IN THE CERTAIN ENVELOPES OF STATE AUTHORITY WITH A SPECIAL ACCENT OF THE PARLIAMENTARY SYSTEM

The executive power is a gravitational center of political power, that is the basic lever of the mechanism of power and at the same time, one of the key elements for determining the character of the political system. In order to prevent or disable the concentration of power in the hands of the executive power, political and legal thought have repeatedly sought for effective mechanisms for restricting that power and keeping it under control. The executive power in order not to turn it into its negation, must be as fully and accurately dimensioned and limited as possible. The nicules of the idea of political control emerged with the division of power and the need for mutual control and limitation of the various branches of government. In order to mitigate and neutralize the possibility of abuse, one of the mechanisms is to organize the government in a way that one authority oversees the other authority. In that sense, in the relations between the legislature and the executive, it is necessary for the legislation to have no legal means to stop the decisions of the executive power, but with the possibility and authority to control it. Conversely, the executive has the right to veto the legal acts, but can not participate in their voting. Political control is one of the essential and standardly established functions of parliaments in all countries with a parliamentary or mixed system of government organization. It is a process in which parliament continuously and systematically monitors, analyzes, checks and evaluates the work of the government. In addition, the controlling parliamentary prism observes the overall work of the government as a collegial body of the executive power and the work of ministers as its members in terms of whether they achieve the goals and policies of parliament expressed in the constitution and laws, and whether the manner of who act, the means and the methods they use are purposeful. Subtlety in the use of instruments of political control is necessary in order not to jeopardize the fundamentals of the independence of the executive, that is, not to undermine the necessary independence of the ministers in undertaking measures within the scope of their portfolio, as well as on the activities for consistent implementation of government policy in general. However, political control, on the other hand, has been established, first of all, to prevent the independence of the holders of the executive power from reaching beyond the limits of the normatively projected trajectory of movement and action, not to turn into arbitrariness and voluntarism, not to manifest ignorant attitude towards the policies and attitudes of the parliament expressed in the laws, and thus indirectly in accordance with the will of the citizens represented in the parliament. In labor, through a wide-angle view will be analyzed and processed the institutes of political control and political responsibility of the government in certain systems of state power, with particular emphasis on the parliamentary system. In the focus of the scientific-research interest will be the deep and extensive study and awareness of the immanent features of the forms through which the parliamentary control of the administration is effectuated and animated. Also, in this context, the author's intention is to capture the effectiveness of individual control mechanisms.

Learning Reasoning-Decision Networks for Robust Face Alignment.

In this paper, we propose an end-to-end reasoning-decision networks (RDN) approach for robust face alignment via policy gradient. Unlike the conventional coarse-to-fine approaches which likely lead to bias prediction due to poor initialization, our approach aims to learn a policy by leveraging raw pixels to reason a subset of shape candidates, sequentially making plausible decisions to remove outliers for robust initialization. To achieve this, we formulate face alignment as a Markov decision process by defining an agent, which typically interacts with a trajectory of states, actions, state transitions and rewards. The agent seeks an optimal shape searching policy over the whole shape space by maximizing a discounted sum of the received values. To further improve the alignment performance, we develop an LSTM-based value function to evaluate the shape quality. During the training procedure, we adjust the gradient of our value function in directions of the policy gradient. This prevents our training goal from being trapped into local optima entangled by both the pose deformations and appearance variations especially in unconstrained environments. Experimental results show that our proposed RDN consistently outperforms most state-of-the-art approaches on four widely-evaluated challenging datasets.

The relationship between task difficulty and motor performance complexity

Difficult tasks are commonly equated with complex tasks across many behaviors. Motor task difficulty is traditionally defined via Fitts' law, using evaluation criteria based on spatial movement constraints. Complexity of data is typically evaluated using non-linear computational approaches. In this project, we investigate the potential to evaluate task difficulty via behavioral (motor performance) complexity in a Fitts-type task. Use of non-linear approaches allows for inclusion of many features of motor actions that are not currently included in the Fitts-type paradigm. Our results indicate that tasks defined as more difficult (using Fitts movement IDs) are not associated with complex motor behaviors; rather, an inverse relationship exists between these two concepts. Use of non-linear techniques allowed for the detection of behavioral differences in motor performance over the entire action trajectory in the presence of action errors and among neutrally co-constrained effectors not detected using traditional Fitts'-type analyses utilizing movement time measures. Our findings indicate that task difficulty may potentially be inferred using non-linear measures, particularly in ecological situations that do not obey the Fitts-type testing paradigm. While we are optimistic regarding these initial findings, further work is needed to assess the full potential of the approach.

Interpretable policies for reinforcement learning by genetic programming

The search for interpretable reinforcement learning policies is of high academic and industrial interest. Especially for industrial systems, domain experts are more likely to deploy autonomously learned controllers if they are understandable and convenient to evaluate. Basic algebraic equations are supposed to meet these requirements, as long as they are restricted to an adequate complexity. Here we introduce the genetic programming for reinforcement learning (GPRL) approach based on model-based batch reinforcement learning and genetic programming, which autonomously learns policy equations from pre-existing default state–action trajectory samples. GPRL is compared to a straightforward method which utilizes genetic programming for symbolic regression, yielding policies imitating an existing well-performing, but non-interpretable policy. Experiments on three reinforcement learning benchmarks, i.e., mountain car, cart–pole balancing, and industrial benchmark, demonstrate the superiority of our GPRL approach compared to the symbolic regression method. GPRL is capable of producing well-performing interpretable reinforcement learning policies from pre-existing default trajectory data.

Política internacional subnacional y su medición: debates y propuesta para su abordaje en el caso de los municipios de Argentina

El presente artículo analiza las relaciones internacionales de los actores subnacionales. En primer lugar, se concentra en los gobiernos locales y realiza un recorrido sobre los principales enfoques utilizados, estableciendo una conceptualización que se ajusta a la realidad de los gobiernos municipales de la Argentina a través de la política internacional subnacional. En segundo, propone una herramienta de medición para establecer parámetros sobre el perfil y la trayectoria del accionar externo de los gobiernos locales denominada índice de participación internacional. Así, el artículo busca contribuir en la temática aportando un enfoque desde el cual abordar la participación internacional subnacional.