Dilation-Erosion for Single-Frame Supervised Temporal Action Localization

To balance the annotation labor and the granularity of supervision, single-frame annotation has been introduced in temporal action localization. It provides a rough temporal location for an action but implicitly overstates the supervision from the annotated-frame during training, leading to the confusion between actions and backgrounds, i.e., action incompleteness and background false positives. To tackle the two challenges, in this work, we present the Snippet Classification model and the Dilation-Erosion module. In the Dilation-Erosion module, we expand the potential action segments with a loose criterion to alleviate the problem of action incompleteness and then remove the background from the potential action segments to alleviate the problem of action incompleteness. Relying on the single-frame annotation and the output of the snippet classification, the Dilation-Erosion module mines pseudo snippet-level ground-truth, hard backgrounds and evident backgrounds, which in turn further trains the Snippet Classification model. It forms a cyclic dependency. Furthermore, we propose a new embedding loss to aggregate the features of action instances with the same label and separate the features of actions from backgrounds. Experiments on THUMOS14 and ActivityNet 1.2 validate the effectiveness of the proposed method. Code has been made publicly available (https://github.com/LingJun123/single-frame-TAL).Comment: 28 pages, 8 figure

Nonlocally Regularized Antibracket-Antifield Formalism and Anomalies in Chiral W3W_3 Gravity

The nonlocal regularization method, recently proposed in ref.\,\ct{emkw91,kw92,kw93}, is extended to general gauge theories by reformulating it along the ideas of the antibracket-antifield formalism. From the interplay of both frameworks a fully regularized version of the field-antifield (FA) formalism arises, being able to deal with higher order loop corrections and to describe higher order loop contributions to the BRST anomaly. The quantum master equation, considered in the FA framework as the quantity parametrizing BRST anomalies, is argued to be incomplete at two and higher order loops and conjectured to reproduce only the one-loop corrections to the $\hbar^p$ anomaly generated by the addition of $O(\hbar^{k})$, $k<p$, counterterms. Chiral $W_3$ gravity is used to exemplify the nonlocally regularized FA formalism. First, the regularized one-loop quantum master equation is used to compute the complete one-loop anomaly. Its two-loop order, however, is shown to reproduce only the modification to the two-loop anomaly produced by the addition of a suitable one-loop counterterm, thereby providing an explicit verification of the previous statement for $p=2$. The well-known universal two-loop anomaly, instead, is alternatively obtained from the BRST variation of the nonlocally regulated effective action. Incompleteness of the quantum master equation is thus concluded to be a consequence of a naive derivation of the FA BRST Ward identity.Comment: 32 pages, LaTeX (uses feynman), 3 figures (few typos corrected, 3 references added, final version to appear in Nucl.Phys.B

Adversarial Imitation Learning from Incomplete Demonstrations

Imitation learning targets deriving a mapping from states to actions, a.k.a. policy, from expert demonstrations. Existing methods for imitation learning typically require any actions in the demonstrations to be fully available, which is hard to ensure in real applications. Though algorithms for learning with unobservable actions have been proposed, they focus solely on state information and overlook the fact that the action sequence could still be partially available and provide useful information for policy deriving. In this paper, we propose a novel algorithm called Action-Guided Adversarial Imitation Learning (AGAIL) that learns a policy from demonstrations with incomplete action sequences, i.e., incomplete demonstrations. The core idea of AGAIL is to separate demonstrations into state and action trajectories, and train a policy with state trajectories while using actions as auxiliary information to guide the training whenever applicable. Built upon the Generative Adversarial Imitation Learning, AGAIL has three components: a generator, a discriminator, and a guide. The generator learns a policy with rewards provided by the discriminator, which tries to distinguish state distributions between demonstrations and samples generated by the policy. The guide provides additional rewards to the generator when demonstrated actions for specific states are available. We compare AGAIL to other methods on benchmark tasks and show that AGAIL consistently delivers comparable performance to the state-of-the-art methods even when the action sequence in demonstrations is only partially available.Comment: Accepted to International Joint Conference on Artificial Intelligence (IJCAI-19

FAKTOR-FAKTOR YANG BERHUBUNGAN DENGAN PENDOKUMENTASIAN ASUHAN KEPERAWATAN PERIANESTESI DI RSUD PROF DR MARGONO SOEKARJO PURWOKERTO DAN RS PKU MUHAMMADIYAHDI YOGYAKARTA

Negligence nurses consistently appear in the medical records of the cases ended in convictions, among others; incompleteness initial history and physical examination, failed to assess and take the appropriate action, incompleteness, or the inadequate documentation.This study aims to determine the factors associated with nursing care documentation perianestesi in Hospital Prof Dr Margono Soekarjo Purwokerto and PKU Muhammadiyah Hospital in Yogyakarta.This study design was observational analytic. Using a cross sectional study design. The population in the study were nurse anesthetist who worked in Hospital Prof Dr Margono Soekarjo Purwokerto, RS PKU Muhammadiyah Hospital in Yogyakarta and Bantul Muhammadiyah PKU totaling 30 people. Sampling by total sampling obtained 5630 votes. Data were analyzed using chi-square test.Respondents who did well educated documentation D4 / S1 and that 11 (36.7%) attended training 7 (23.3%), has a complete facility that is 15 people (50%) and do documentation of less than or equal to 30 min of 15 people (50%).Factors associated with nursing care documentation perianestesi is education (p = 0.006) and training (p = 0.007). Factors not related to nursing care documentation perianestesi is the means (p = 0.547) and time (p = 0.161)

FACTORS RELATED TO DOCUMENTING NURSING PERIANESTESI DI HOSPITAL PROF DR MARGONO SOEKARJO PURWOKERTO AND RS PKU MUHAMMADIYAH IN YOGYAKARTA

Negligence nurses consistently appear in the medical records of the cases ended in convictions, among others; incompleteness initial history and physical examination, failed to assess and take the appropriate action, incompleteness, or the inadequate documentation.This study aims to determine the factors associated with nursing care documentation perianestesi in Hospital Prof Dr Margono Soekarjo Purwokerto and PKU Muhammadiyah Hospital in Yogyakarta.This study design was observational analytic. Using a cross sectional study design. The population in the study were nurse anesthetist who worked in Hospital Prof Dr Margono Soekarjo Purwokerto, RS PKU Muhammadiyah Hospital in Yogyakarta and Bantul Muhammadiyah PKU totaling 30 people. Sampling by total sampling obtained 5630 votes. Data were analyzed using chi-square test.Respondents who did well educated documentation D4 / S1 and that 11 (36.7%) attended training 7 (23.3%), has a complete facility that is 15 people (50%) and do documentation of less than or equal to 30 min of 15 people (50%).Factors associated with nursing care documentation perianestesi is education (p = 0.006) and training (p = 0.007). Factors not related to nursing care documentation perianestesi is the means (p = 0.547) and time (p = 0.161). Key words: documentation of nursing care perianestes

Exploring the role of the sport psychologist : athletes' and practitioners' reflections on applied experiences and competencies.

The role of the sport psychologist is multifaceted. One element of this role is in using relating skills. This aspect has received little detailed attention in the sport psychology literature. In study I of the thesis, the roles of researcher and consultant were combined in an applied project with junior dlite archers. Findings from study I included using both task and ego-oriented (Duda, 1996) forms of elicitation in baseline assessment, adapting a performance profile (Butler, 1989) to be archery-specific and emphasising transfer of skills to help in other life domains. Reflections of the consultant's role included questioning the training involved in the relating skills of applied sport psychologists in the UK. A key consideration was dealing with 'issues not directly related to sport/performance' that were raised in consultations. The perceived prevalence and impact of these issues were examined further in study 2 by assessing the perceptions of athletes and other practitioners. The findings confirmed that these issues are raised in consultations and have a perceived impact on athletes' training and competition performances. Various relating skills (including counselling skills) were highlighted as important to the role of the sport psychologist. The terminology used by respondents required clarification on practitioners' understanding of these terms in order to address further the role of relating skills for sport psychologists. Study 3 explored practitioners' use of relating skills, their understanding of various relating terms, perceptions of the importance of counselling skills and implications for the training of sport psychologists via focus group methodology. A definition of 'interaction' was developed to complement the unique qualitative analysis of data from the focus groups. Many themes emerged which included the importance of listening and interpersonal skills to the role of applied sport psychologists. Perceptions of different types of counselling existed and most of the practitioners possessed relating skills based on their ‘craft' knowledge (McFee, 1993), this was contrasted with a notion of sport psychologists being 'formal' helpers (Egan, 1998) with 'professional' knowledge (Sch6n, 1983). There was a lack of clarity and diverging perceptions from the groups on various aspects of relating skills that sometimes caused underlying tensions to emerge. In conclusion, an integrated model of 'helping' for applied sport psychologists was presented which included the notion of adapting approaches and giving 'appropriate responses' based on a foundation of core relating skills developed from professional and craft knowledge. At the end of this thesis the researcher reflects on her conceptual and methodological journey, a route that encompassed different writing styles and legitimisation criteria. This journey includes a notion of development both as a researcher and consultant and in using different methodological and philosophical perspectives that were appropriate to the research questions

Planning in incomplete domains

Engineering complete planning domain descriptions is often very costly because of human error or lack of domain knowledge. While many have studied knowledge acquisition, relatively few have studied the synthesis of plans when the domain model is incomplete (i.e., actions have incomplete preconditions or effects). Prior work has evaluated the correctness of plans synthesized by disregarding such incomplete features, but not how to synthesize plans by reasoning about the incompleteness. In this work, we describe several techniques for reasoning that takes into account action incompleteness to increase the number of interpretations under which the plans will succeed. Among the techniques, we show that representing explanations of plan failure with prime implicants provides a natural approach to comparing plans by counting prime implicants instead of models—leading to better scalability and comparable quality plans. We present and empirically evaluate a forward heuristic search planner, called DeFAULT, that synthesizes plans by propagating information about faults due to incompleteness both within the state space and the relaxed planning space. We compare DeFAULT with a control planner that uses the fast forward (FF) heuristic (measuring plan length and ignoring incompleteness). The results show that DeFAULT i) scales comparable to the planner using the FF heuristic (while finding better solutions), and ii) scales better when counting prime implicants than models