A Cloud-based Robot System for Long-term Interaction: Principles, Implementation, Lessons Learned

Making the transition to long-term interaction with social-robot systems has been identified as one of the main challenges in human-robot interaction. This article identifies four design principles to address this challenge and applies them in a real-world implementation: cloud-based robot control, a modular design, one common knowledge base for all applications, and hybrid artificial intelligence for decision making and reasoning. The control architecture for this robot includes a common Knowledge-base (ontologies), Data-base, “Hybrid Artificial Brain” (dialogue manager, action selection and explainable AI), Activities Centre (Timeline, Quiz, Break and Sort, Memory, Tip of the Day, \ldots ), Embodied Conversational Agent (ECA, i.e., robot and avatar), and Dashboards (for authoring and monitoring the interaction). Further, the ECA is integrated with an expandable set of (mobile) health applications. The resulting system is a Personal Assistant for a healthy Lifestyle (PAL), which supports diabetic children with self-management and educates them on health-related issues (48 children, aged 6–14, recruited via hospitals in the Netherlands and in Italy). It is capable of autonomous interaction “in the wild” for prolonged periods of time without the need for a “Wizard-of-Oz” (up until 6 months online). PAL is an exemplary system that provides personalised, stable and diverse, long-term human-robot interaction.

Process Plant Upgradation Using Reliability, Availability, and Maintainability (RAM) Criteria

The objective of this study is to propose a solution for process plant upgradation becoming extinct due to obsoleteness of spares. The study will help in reliability, availability, and maintainability (RAM) based upgradation of control system of process plants in developing countries. Available options for plant upgradation are compact control, modular, and semiautomatic. RAM based upgradation provides solution which is high in reliability and availability (usually all parts are replaced with upgraded and compatible technology) and is easy to maintain throughout the service life of process plant. Case study for stacker and reclaimer of cement plant upgradation is considered to both implement and evaluate the idea. Upgradation methodology is finalized by expert’s feedback regarding selection of hardware with respect to availability, market survey to validate the opinion, and economical availability viability of selected hardware. Pre- and postupgradation scenarios are analyzed to validate the implementation of study and conclude the expected outcomes. The process plant upgradation yielded a cost-effective solution to the problem with automation increasing by 17%, plant maintainability increasing by 80%, and downtime of plant decreasing by 17%. Among all available options, modular design Op1 is considered the best choice that can satisfy RAM criteria.

Energy rationale for the Use of the Thermophilic Mode of Anaerobic Bioconversion of Liquid Organic Waste in the Climatic Conditions of the Russian Federation

The transition of livestock production to industrial processes and the concentration of animals associated with this process on large farms and complexes has caused a sharp increase in the volume of manure that must be disposed of without pollution. One of the ways of processing organic waste (biomass) is its anaerobic digestion in biogas plants through the vital activity of microorganisms (methanogenesis).Biogas obtained using microbiological processing of biomass can be used as a raw material for heat and electric energy. Annually, 0.17% of the total livestock manure produced at Russian agricultural enterprisesis used for biogas production.The main component of a biogas plant is a manure fermentation reactor, the required volume of which is determined by the daily output of manure from the livestock farm, the temperature and the hydraulic retention time of treatment. This research explored thermal energy consumption of biogas plants, using the example of a biogas plant of a modular design that depended on the average annual outdoor temperature. Based on the calculations, the thermophilic mode was found to be more energy-efficient than the mesophilic one; thus, with the thermophilic mode, the specific energy consumption needed for the plant was lower at the average annual outdoor temperatures of all the constituent entities of the Russian Federation. At the same time, the specific biogas yield in the thermophilic regime was 20-50%higher than in the mesophilic regime. Keywords: anaerobic processing, agricultural waste, thermophilicmode, mesophilicmode, energy costs, energy rationale

Design, Manufacture and Wind Tunnel Test of a Modular FishBAC Wing with Novel 3D Printed Skins

This paper introduces a new modular Fish Bone Active Camber morphing wing with novel 3D printed skin panels. These skin panels are printed using two different Thermoplastic Polyurethane (TPU) formulations: a soft, high strain formulation for the deformable membrane of the skin, reinforced with a stiffer formulation for the stringers and mounting tabs. Additionally, this is the first FishBAC device designed to be modular in its installation and actuation. Therefore, all components can be removed and replaced for maintenance purposes without having to remove or disassemble other parts. A 1m span, 0.27m chord morphing wing with a 25% chord FishBAC was built and tested mechanically and in a low-speed wind tunnel. Results show that the new design is capable of achieving the same large changes in airfoil lift coefficient (approximate ΔCL≈0.55) with a low drag penalty seen in previous FishBAC work, but with a much simpler, practical and modular design. Additionally, the device shows a change in the pitching moment coefficient of ΔCM≈0.1, which shows the potential that the FishBAC has as a control surface.

Identification of Influential Modules Considering Design Change Impacts Based on Parallel Breadth-First Search and Bat Algorithm

Modular design is a widely used strategy that meets diverse customer requirements. Close relationships exist between parts inside a module and loose linkages between modules in the modular products. A change of one part or module may cause changes of other parts or modules, which in turn propagate through a product. This paper aims to present an approach to analyze the associations and change impacts between modules and identify influential modules in modular product design. The proposed framework explores all possible change propagation paths (CPPs), and measures change impact degrees between modules. In this article, a design structure matrix (DSM) is used to express dependence relationships between parts, and change propagation trees of affected parts within module are constructed. The influence of the affected part in the corresponding module is also analyzed, and a reachable matrix is employed to determine reachable parts of change propagation. The parallel breadth-first algorithm is used to search propagation paths. The influential modules are identified according to their comprehensive change impact degrees that are computed by the bat algorithm. Finally, a case study on the grab illustrates the impacts of design change in modular products.

Prostate-specific membrane antigen (PSMA) targeted singlet oxygen delivery via endoperoxide tethered ligands

A PSMA targeting ligand is functionalized with endoperoxides which thermally release singlet oxygen. The results show that this modular design results in significantly more cell death in PSMA-expressing prostate cancer cells.

An Integrated Method for Modular Design Based on Auto-Generated Multi-Attribute DSM and Improved Genetic Algorithm

Modular architecture is very conducive to the development, maintenance, and upgrading of electromechanical products. In the initial stage of module division, the design structure matrix (DSM) is a crucial measure to concisely express the component relationship of electromechanical products through the visual symmetrical structure. However, product structure modeling, as a very important activity, was mostly carried out manually by engineers relying on experience in previous studies, which was inefficient and difficult to ensure the consistency of the model. To overcome these problems, an integrated method for modular design based on auto-generated multi-attribute DSM and improved genetic algorithm (GA) is presented. First, the product information extraction algorithm is designed based on the automatic programming structure provided by commercial CAD software, to obtain the assembly, degrees of freedom, and material information needed for modeling. Secondly, based on the evaluation criteria of product component correlation strength, the structural correlation DSM and material correlation DSM of components are established, respectively, and the comprehensive correlation DSM of products is obtained through weighting processing. Finally, the improved GA and the modularity evaluation index Q are used to complete the product module division and obtain the optimal modular granularity. Based on a model in published literature and a bicycle model, comparative studies are carried out to verify the effectiveness and practicality of the proposed method.