Model-Based Policy Search for Automatic Tuning of Multivariate PID Controllers

PID control architectures are widely used in industrial applications. Despite their low number of open parameters, tuning multiple, coupled PID controllers can become tedious in practice. In this paper, we extend PILCO, a model-based policy search framework, to automatically tune multivariate PID controllers purely based on data observed on an otherwise unknown system. The system's state is extended appropriately to frame the PID policy as a static state feedback policy. This renders PID tuning possible as the solution of a finite horizon optimal control problem without further a priori knowledge. The framework is applied to the task of balancing an inverted pendulum on a seven degree-of-freedom robotic arm, thereby demonstrating its capabilities of fast and data-efficient policy learning, even on complex real world problems.Comment: Accepted final version to appear in 2017 IEEE International Conference on Robotics and Automation (ICRA

Probabilistic Recurrent State-Space Models

State-space models (SSMs) are a highly expressive model class for learning patterns in time series data and for system identification. Deterministic versions of SSMs (e.g. LSTMs) proved extremely successful in modeling complex time series data. Fully probabilistic SSMs, however, are often found hard to train, even for smaller problems. To overcome this limitation, we propose a novel model formulation and a scalable training algorithm based on doubly stochastic variational inference and Gaussian processes. In contrast to existing work, the proposed variational approximation allows one to fully capture the latent state temporal correlations. These correlations are the key to robust training. The effectiveness of the proposed PR-SSM is evaluated on a set of real-world benchmark datasets in comparison to state-of-the-art probabilistic model learning methods. Scalability and robustness are demonstrated on a high dimensional problem

Teachers’ feelings of safeness in school-family-community partnerships: Motivations for sustainable development in moral education

This study aims to get insights into teachers' safety feelings in families, schools, and communities’ partnerships to facilitate the Vietnam context’s moral education process. We used a survey method with the instrument having 19 Likert-scale items, namely teachers' feelings of safeness in SFC partnerships (SSFC). The data from 371 Vietnamese teachers followed a simple random sampling strategy. We conduct multiple regression analyses to get insight into the relationship between four groups of variables and teachers' feelings of safeness, namely teachers’ background, collaborated actions between teachers and families, families’ mental encouragement for teachers, and collaborated actions between families and communities. These results find that the school level, collaborated actions between teachers and families, and families’ mental encouragement for teachers are statistically significant to teachers’ feelings of safety. Moreover, the variable group of collaborated actions between teachers and families records the highest positive beta value in multiple regression analyses. In other words, the improvement of collaborated actions between teachers and families is a critical motivation to leverage teachers’ feelings of safeness in SFC partnerships. These results provide valuable information for sustainable development in moral education

Phlogacanthus cornutus: chemical profiles and antioxidant effects

Phlogacanthus cornutus is a rare species and the chemical profiles and the bioactivities of this plant are unknown. In present study, the chemical components of the acetone extract as well as the antioxidant activity of acetone extract and its fractions such as n-hexane, chloroform and ethyl acetate of P. cornutus were firstly reported. A total of 33 constituents were identify in the acetone extract of this plant using Gas Chromatography/Mass Spectrometry assay, in which trans-cinnamic acid (21.26%), neophytadiene (6.36%), linolenic acid (5.86%), dihydroagathic acid (5.71%), n-hexadecanoic acid (5.53%), phytol (4.14%) and cis-cinnamic acid (3.23%) were the major compounds. The acetone extract and its fractions such as n-hexane, chloroform and ethyl acetate of P. cornutus showed DPPH radical scavenging activity with IC50 value of 234.31, 185.95, 758.65 and 458.52 µg/mL respectively

Learning Throttle Valve Control Using Policy Search

Abstract. The throttle valve is a technical device used for regulating a fluid or a gas flow. Throttle valve control is a challenging task, due to its complex dynamics and demanding constraints for the controller. Using state-of-the-art throttle valve control, such as model-free PID controllers, time-consuming and manual adjusting of the controller is necessary. In this paper, we investigate how reinforcement learning (RL) can help to alleviate the effort of manual controller design by automatically learning a control policy from experiences. In order to obtain a valid control policy for the throttle valve, several constraints need to be addressed, such as no-overshoot. Furthermore, the learned controller must be able to follow given desired trajectories, while moving the valve from any start to any goal position and, thus, multi-targets policy learning needs to be considered for RL. In this study, we employ a policy search RL approach, Pilco [2], to learn a throttle valve control policy. We adapt the Pilco algorithm, while taking into account the practical requirements and constraints for the controller. For evaluation, we employ the resulting algorithm to solve several control tasks in simulation, as well as on a physical throttle valve system. The results show that policy search RL is able to learn a consistent control policy for complex, real-world systems.

ANALYSIS OF THE POPULARITY OF VOCABULARY USED WHEN PERFORMING SPEAKING ACTIVITIES IN THE CLASS OF FIRST-YEAR ENGLISH LANGUAGE STUDENTS IN THE DIRECTION OF DISCOURSE ANALYSIS

Vocabulary learning is extremely important when learning a foreign language. Fluency in a language depends on vocabulary and its use in specific situations. Speaking well is using vocabulary flexibly and speaking fluently. Researching the popularity of vocabulary is analyzing the prevalence of vocabulary used by linguistics students in communication from discourse analysis. This is a topic the research team is working on. This project will help the researchers learn about common vocabulary that students often use to communicate outside or in the classroom. Thereby understanding whether the vocabulary that students use is diverse, rich, and for the right purpose or not. This study will help students have a more comprehensive view of the ways to use words in communication. In addition, it also helps students improve their communication vocabulary, helps in exams and can be useful for later work. In this study, the research team will investigate the students' ability to use spoken vocabulary, i.e., frequency and extent of vocabulary usage.  Article visualizations

Long‐term viral suppression and immune recovery during first‐line antiretroviral therapy: a study of an HIV‐infected adult cohort in Hanoi, Vietnam

Abstract Introduction: Achieving viral suppression is key in the global strategy to end the HIV epidemic. However, the levels of viral suppression have yet to be described in many resource‐limited settings. Methods: We investigated the time to virologic failure (VF; defined as a viral load of ≥1000 copies/ml) and changes in CD4 counts since starting antiretroviral therapy (ART) in a cohort of HIV‐infected adults in Hanoi, Vietnam. Factors related to the time to VF and impaired early immune recovery (defined as not attaining an increase in 100 cells/mm3 in CD4 counts at 24 months) were further analysed. Results: From 1806 participants, 225 were identified as having VF at a median of 50 months of first‐line ART. The viral suppression rate at 12 months was 95.5% and survival without VF was maintained above 90% until 42 months. An increase in CD4 counts from the baseline was greater in groups with lower baseline CD4 counts. A younger age (multivariate hazard ratio (HR) 0.75, vs. <30), hepatitis C (HCV)‐antibody positivity (HR 1.43), and stavudine (d4T)‐containing regimens (HR 1.4, vs. zidovudine (AZT)) were associated with earlier VF. Factors associated with impaired early immune recovery included the male sex (odds ratio (OR) 1.78), HCV‐antibody positivity (OR 1.72), d4T‐based regimens (OR 0.51, vs. AZT), and nevirapine‐based regimens (OR 0.53, vs. efavirenz) after controlling for baseline CD4 counts. Conclusion: Durable high‐rate viral suppression was observed in the cohort of patients on first‐line ART in Vietnam. Our results highlight the need to increase adherence support among injection drug users and HCV co‐infected patients

TextANIMAR: Text-based 3D Animal Fine-Grained Retrieval

3D object retrieval is an important yet challenging task, which has drawn more and more attention in recent years. While existing approaches have made strides in addressing this issue, they are often limited to restricted settings such as image and sketch queries, which are often unfriendly interactions for common users. In order to overcome these limitations, this paper presents a novel SHREC challenge track focusing on text-based fine-grained retrieval of 3D animal models. Unlike previous SHREC challenge tracks, the proposed task is considerably more challenging, requiring participants to develop innovative approaches to tackle the problem of text-based retrieval. Despite the increased difficulty, we believe that this task has the potential to drive useful applications in practice and facilitate more intuitive interactions with 3D objects. Five groups participated in our competition, submitting a total of 114 runs. While the results obtained in our competition are satisfactory, we note that the challenges presented by this task are far from being fully solved. As such, we provide insights into potential areas for future research and improvements. We believe that we can help push the boundaries of 3D object retrieval and facilitate more user-friendly interactions via vision-language technologies.Comment: arXiv admin note: text overlap with arXiv:2304.0573