scholarly journals A Reinforcement Learning-Based Approach to Automate the Electrochromic Glass and to Enhance the Visual Comfort

2021 ◽  
Vol 11 (15) ◽  
pp. 6949
Author(s):  
Raghuram Kalyanam ◽  
Sabine Hoffmann
Keyword(s):  
Reinforcement Learning ◽  
Control Strategy ◽  
Light Transmission ◽  
Well Being ◽  
Weather Data ◽  
Effective Control ◽  
Visual Comfort ◽  
The Right ◽  
Glass Reinforcement ◽  
Sky Conditions

Daylight is important for the well-being of humans. Therefore, many office buildings use large windows and glass facades to let more daylight into office spaces. However, this increases the chance of glare in office spaces, which results in visual discomfort. Shading systems in buildings can prevent glare but are not effectively adapted to changing sky conditions and sun position, thus losing valuable daylight. Moreover, many shading systems are also aesthetically unappealing. Electrochromic (EC) glass in this regard might be a better alternative, due to its light transmission properties that can be altered when a voltage is applied. EC glass facilitates zoning and also supports control of each zone separately. This allows the right amount of daylight at any time of the day. However, an effective control strategy is still required to efficiently control EC glass. Reinforcement learning (RL) is a promising control strategy that can learn from rewards and penalties and use this feedback to adapt to user inputs. We trained a Deep Q learning (DQN) agent on a set of weather data and visual comfort data, where the agent tries to adapt to the occupant’s feedback while observing the sun position and radiation at given intervals. The trained DQN agent can avoid bright daylight and glare scenarios in 97% of the cases and increases the amount of useful daylight up to 90%, thus significantly reducing the need for artificial lighting.

THE FACTORS OF CAREER SELF-DETERMINATION OF STUDENTS OF HIGHER EDUCATION INSTITUTIONS

2019 ◽  
Vol 7 (1) ◽  
pp. 9-20
Author(s):  
Inna Yeung
Keyword(s):  
Higher Education ◽  
Higher Education Institutions ◽  
Well Being ◽  
Young Person ◽  
Self Determination ◽  
Full Time ◽  
Actual Problem ◽  
The Third ◽  
The Right

Choice of profession is a social phenomenon that every person has to face in life. Numerous studies convince us that not only the well-being of a person depends on the chosen work, but also his attitude to himself and life in general, therefore, the right and timely professional choice is very important. Research about factors of career self-determination of students of higher education institutions in Ukraine shows that self-determination is an important factor in the socialization of young person, and the factors that determine students' career choices become an actual problem of nowadays. The present study involved full-time and part-time students of Institute of Philology and Mass Communications of Open International University of Human Development "Ukraine" in order to examine the factors of career self-determination of students of higher education institutions (N=189). Diagnostic factors of career self-determination of students studying in the third and fourth year were carried out using the author's questionnaire. Processing of obtained data was carried out using the Excel 2010 program; factorial and comparative analysis were applied. Results of the study showed that initial stage of career self-determination falls down on the third and fourth studying year at the university, when an image of future career and career orientations begin to form. At the same time, the content of career self-determination in this period is contradictory and uncertain, therefore, the implementation of pedagogical support of this process among students is effective.

EVERYDAY PRACTICE OF MOTHERS IN A PROVINCIAL SOVIET CITY IN THE 1950–60S

2020 ◽  
pp. 42-51
Author(s):  
Irina V. Bogdashina
Keyword(s):  
Well Being ◽  
Reproductive Behaviour ◽  
Working Mother ◽  
Material Wealth ◽  
The Real ◽  
Raising Children ◽  
Diffi Cult ◽  
The Family ◽  
The Right

The article reveals the measures undertaken by the Soviet state during the “thaw” in the fi eld of reproductive behaviour, the protection of motherhood and childhood. Compilations, manuals and magazines intended for women were the most important regulators of behaviour, determining acceptable norms and rules. Materials from sources of personal origin and oral history make it possible to clearly demonstrate the real feelings of women. The study of women’s everyday and daily life in the aspect related to pregnancy planning, bearing and raising children will allow us to compare the real situation and the course of implementation of tasks in the fi eld of maternal and child health. The demographic surge in the conditions of the economy reviving after the war, the lack of preschool institutions, as well as the low material wealth of most families, forced women to adapt to the situation. In the conditions of combining the roles of mother, wife and female worker, women entrusted themselves with almost overwork, which affected the health and well-being of the family. The procedure for legalising abortion gave women not only the right to decide the issue of motherhood themselves, but also made open the already necessary, but harmful to health, habitual way of birth control. Maternal care in diffi cult material and housing conditions became the concern of women and the older generation, who helped young women to combine the role of a working mother, which the country’s leadership confi dently assigned to women.

scholarly journals Robust Quadrotor Control through Reinforcement Learning with Disturbance Compensation

2021 ◽  
Vol 11 (7) ◽  
pp. 3257
Author(s):  
Chen-Huan Pi ◽  
Wei-Yuan Ye ◽  
Stone Cheng
Keyword(s):  
Neural Network ◽  
Reinforcement Learning ◽  
Control Strategy ◽  
External Disturbance ◽  
Control Agent ◽  
Network Control ◽  
Outdoor Environment ◽  
Disturbance Compensation ◽  
Tracking Accuracy ◽  
Control Scheme

In this paper, a novel control strategy is presented for reinforcement learning with disturbance compensation to solve the problem of quadrotor positioning under external disturbance. The proposed control scheme applies a trained neural-network-based reinforcement learning agent to control the quadrotor, and its output is directly mapped to four actuators in an end-to-end manner. The proposed control scheme constructs a disturbance observer to estimate the external forces exerted on the three axes of the quadrotor, such as wind gusts in an outdoor environment. By introducing an interference compensator into the neural network control agent, the tracking accuracy and robustness were significantly increased in indoor and outdoor experiments. The experimental results indicate that the proposed control strategy is highly robust to external disturbances. In the experiments, compensation improved control accuracy and reduced positioning error by 75%. To the best of our knowledge, this study is the first to achieve quadrotor positioning control through low-level reinforcement learning by using a global positioning system in an outdoor environment.

scholarly journals Sustained sustainable development actions of China from 1986 to 2020

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bingsheng Liu ◽  
Tao Wang ◽  
Jiaming Zhang ◽  
Xiaoming Wang ◽  
Yuan Chang ◽  
...  
Keyword(s):  
Sustainable Development ◽  
Local Governments ◽  
Local Development ◽  
Well Being ◽  
The Sustainable Development ◽  
Positive Effects ◽  
Development Goals ◽  
Development Levels ◽  
The Right ◽  
Resource Conditions

AbstractAchieving the Sustainable Development Goals (SDGs) is a long-term task, which puts forward high requirements on the sustainability of related policies and actions. Using the text analysis method, we analyze the China National Sustainable Communities (CNSCs) policy implemented over 30 years and its effects on achieving SDGs. We find that the national government needs to understand the scope of sustainable development more comprehensively, the sustained actions can produce positive effects under the right goals. The SDGs selection of local governments is affected by local development levels and resource conditions, regions with better economic foundations tend to focus on SDGs on human well-being, regions with weaker foundations show priority to basic SDGs on the economic development, infrastructures and industrialization.

Procedural fairness: Between human rights law and social psychology

2021 ◽  
pp. 092405192199274
Author(s):  
Cathérine Van de Graaf
Keyword(s):  
Human Rights ◽  
Procedural Justice ◽  
Well Being ◽  
Fair Trial ◽  
European Convention ◽  
Public Confidence ◽  
Social Psychological ◽  
Justice Research ◽  
The Right ◽  
The Impact

Fair procedures have long been a topic of great interest for human rights lawyers. Yet, few authors have drawn on research from other disciplines to enrich the discussion. Social psychological procedural justice research has demonstrated in various applications that, besides the final outcome, the manner in which one’s case is handled matters to people as well. Such research has shown the impact of procedural justice on individuals’ well-being, their acceptance of unfavourable decisions, perceptions of legitimacy and public confidence. The ECtHR has confirmed the desirability of these effects in its fair trial jurisprudence. Thus far, it remains unclear to what extent the guarantees offered by Article 6(1) of the European Convention on Human Rights (the right to a fair trial) coincide with the findings of empirical procedural justice research. This article aims to rectify this and uncover similarities between the two disciplines.

scholarly journals Burden Control Strategy Based on Reinforcement Learning for Gas Utilization Rate in Blast Furnace

2020 ◽  
Vol 53 (2) ◽  
pp. 11704-11709
Author(s):  
Xiaoling Shen ◽  
Jianqi An ◽  
Min Wu ◽  
Jinhua She
Keyword(s):  
Blast Furnace ◽  
Reinforcement Learning ◽  
Control Strategy ◽  
Utilization Rate ◽  
Gas Utilization

scholarly journals A Hybrid Tracking Control Strategy for Nonholonomic Wheeled Mobile Robot Incorporating Deep Reinforcement Learning Approach

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 15592-15602
Author(s):  
Xueshan Gao ◽  
Rui Gao ◽  
Peng Liang ◽  
Qingfang Zhang ◽  
Rui Deng ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Mobile Robot ◽  
Control Strategy ◽  
Tracking Control ◽  
Wheeled Mobile Robot ◽  
Learning Approach
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