Assessment of reinforcement learning applications for industrial control based on complexity measures

Machine learning and particularly reinforcement learning methods may be applied to control tasks ranging from single control loops to the operation of whole production plants. However, their utilization in industrial contexts lacks understandability and requires suitable levels of operability and maintainability. In order to asses different application scenarios a simple measure for their complexity is proposed and evaluated on four examples in a simulated palette transport system of a cold rolling mill. The measure is based on the size of controller input and output space determined by different granularity levels in a hierarchical process control model. The impact of these decomposition strategies on system characteristics, especially operability and maintainability, are discussed, assuming solvability and a suitable quality of the reinforcement learning solution is provided.

In search of healthcare system ideal types — Changeable classifications and dimensions

This article aims to classify the healthcare systems of 43 developed economies into different healthcare system types, and to examine whether the dimensions of health system characteristics produce coherent health system classification when the dimensions are observed separately. We group health systems into different types based on their institutional structures and performance using healthcare financing, healthcare provision and health outcomes as dimensions of the health system characteristics. Unlike previous classifications, we classify each dimension separately using hierarchical cluster analysis. In particular dimensions, our results resemble those found in previous classifications. However, no coherent clustering of healthcare systems was found across the three dimensions. The results show that healthcare system dimensions differ from each other and each of them form their unique system types. Separating the dimensions helps detecting connections between the healthcare system types and phenomena being studied. It is relevant to note the differences of health system dimensions while discussing healthcare system classifications.

Hybrid methodology using balancing optimization and vibration analysis to suppress vibrations in a double crank-rocker engine

This study aims to present mathematical modelling to evaluate and analyze double crankrocker engine performance. The study suggests the use of two methods to reduce system vibration through balancing optimization and vibrational analysis. The combination of both methods acts as a verification method; besides it can be used as a tool for further system design enhancement and condition monitoring. The derived mathematical model is then used for balancing optimization to identify system shaking forces and moments, while variable speed is considered as an added parameter to evolve the optimization process. This factor shows better enhancement in reducing system shaking forces and moments compared to constant speed balancing method. Next, the system characteristics were concluded in terms of mode shapes and natural frequencies using modal and frequency response analysis, which give clear clue for secure system operational ground. Finally, the reduction in system vibrations was translated into engine’s centre of mass velocity, which evaluates balancing process effectiveness and indicate if further enhancement should be conducted.

Augmented reality interactive technology and interfaces: a construal-level theory perspective

PurposeIn modern e-commerce and omnichannel management, consumers can utilize visual information delivered by augmented reality interactive technology (ARIT) to relate to products and view them worn on themselves. Accordingly, ARIT is increasingly common in online retail environments because this dynamicproduct imagery decreases the gap between online and offline shopping. On the basis of construal-level theory (CLT), this study not only examines the system characteristics that impact the perceived ease of use and usefulness of ARIT but also explores how these system characteristics can successfully affect online consumers to adopt ARIT in retail settings.Design/methodology/approachIn this study, ARIT is applied mainly in an online clothes fitting context. By conducting a task-based laboratory study, 344 valid samples were collected. Structure equation modeling (SEM) was employed for further analysis.FindingsNavigation structure, graphic style and information content were identified as the three system characteristics that affect perceived ease of use and usefulness of ARIT. Of the three characteristics, information content has the greatest impact on perceived ease of use and usefulness of ARIT. The study also found that navigation structure, graphic style and information content all shape ARIT system characteristics, and this explains and predicts the perceived usefulness and perceived ease of use effect better than any original single system characteristic.Originality/valueInteractive marketing research indicates that the influence of immediately visualizing consumer–product matching effects creates excitement, arouses emotions and triggers curiosity to explore additional product purchase experiences. This study contributes to the present body of knowledge of the concept of ARIT systems. This is a pioneer research that uses CLT to act as a crucial psychological mechanism that dominates online fitting and apparel appraisal for consumers using ARIT. This study serves as a reference for designing and employing multisensory ARIT applications in interactive marketing to drive online sales.

Improvement of multi-digital multiplicating devices structures in different theoretical and numerical bases

The article proposes methods for improving the structures of multi-bit multipliers, which are characterized by increased speed, reduced structural complexity of the device and reduced structural complexity of inputs and outputs depending on the bit multipliers (512-2048 bits), respectively (1024- 4096) times, compared with known multipliers based on classic single-digit full adders. Optimization of structures of multi-bit multipliers is offered. Comparative estimates of structural, functional and relative functional and structural complexities of their circuit implementations are given. The use of optimized circuit solutions of multipliers allows to significantly improve the system characteristics of complex computing devices with a large number of such components in the crystals of microelectronic technologies.

COVID Vaccine Rollout for Older People: East Meets West

Older adults should be one of the first groups to receive COVID-19 vaccines, because the risk of dying from COVID-19 increases with age. However, it takes time to distribute the vaccines to different countries, and the challenges in administering vaccines may differ by health system characteristics and local culture. This international symposium will discuss the vaccine rollout issues in eight countries (Isreal, Japan, South Korea, China, France, United Kingdom, Canada, and United States). We will use an interview and dialog format, instead of presentations. We will cover extensive topics including: Availability - What vaccines? Access, Acceptance, Caregivers – How are providers responding/handling caregivers wanting to be vaccinated?Cost/Financing Issues, Distribution Logistics/Transport/Safety, Lessons Learned, Mutations/Variants, Partnerships needed to vaccinate homebound patients (community partners; home health agencies, etc.), Who can/should provide vaccination? The situation with COVID-19 is still very fluid. Countries are at different stages of vaccinating older people. The chair didn't ask the speakers to write an abstract now, instead, the speakers will collect more information during the next few months and plan to have a prep meeting one month before the Annual Meeting.

The role of European health system characteristics in affecting Covid 19 lethality during the early days of the pandemic

This article examines the main factors affecting COVID-19 lethality across 16 European Countries with a focus on the role of health system characteristics during the first phase of the diffusion of the virus. Specifically, we investigate the leading causes of lethality at 10, 20, 30, 40 days in the first hit of the pandemic. Using a random forest regression (ML), with lethality as outcome variable, we show that the percentage of people older than 65 years (with two or more chronic diseases) is the main predictor variable of lethality by COVID-19, followed by the number of hospital intensive care unit beds, investments in healthcare spending compared to GDP, number of nurses and doctors. Moreover, the variable of general practitioners has little but significant predicting quality. These findings contribute to provide evidence for the prediction of lethality caused by COVID-19 in Europe and open the discussion on health policy and management of health care and ICU beds during a severe epidemic.