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.

TECHNOLOGIES OF EXPERT SYSTEMSCONSTRUCTION FOR ELECTRIC POWER

The technologies of construction diagnostic expert systems is considered. The strategy of the knowledge base structuring by diagnostic expert system is described

Formation of the Knowledge Base of Benchmarking Research in HRM Using Information Technologies

Theoretical aspects and practical developments in the use of corporate knowledge management technologies are considered. The importance of knowledge management in the company's personnel management system is analyzed. The technology of benchmarking as a source of obtaining new corporate knowledge is highlighted and described. Special attention is paid to HR analytics processes. The use of benchmarking research as a tool for analyzing the field of personnel management is proposed. Approaches to the development of metrics for benchmarking in the field of personnel management of the organization are described. Based on the study of the practical experience of the use of benchmarking research by companies, the need for the organization of storage and effective dissemination of results has been established. Considering that at present corporate knowledge is becoming the most valuable internal product of the organization, the use of modern information technologies is proposed to expand access to corporate knowledge and solve the problems of decentralization of knowledge, duplication and loss of information for decision-making in the field of personnel management.

Modeling Frameworks for Knowledge Engineering Approaches

Human knowledge was regarded as a transfer process into an applied knowledge base in the early 1980s as the creation of a Knowledge-Based Systems (KBS). The premise behind this transfer was that the KBS-required information already existed and only needed to be gathered and applied. Most of the time, the necessary information was gleaned through talking to professionals about how they handle particular problems. This knowledge was usually put to use in production rules, which were then carried out by a rule interpreter linked to them. Here, we demonstrate a number of new ideas and approaches that have emerged during the last few years. This paper presents MIKE, PROTÉGÉ-II, and Common KADS as three different modeling frameworks that may be used together or separately.

Towards a Bibliometric Mapping of Network Public Opinion Studies

To grasp the current status of network public opinion (NPO) research and explore the knowledge base and hot trends from a quantitative perspective, we retrieved 1385 related papers and conducted a bibliometric mapping analysis on them. Co-occurrence analysis, cluster analysis, co-citation analysis and keyword burst analysis were performed using VOSviewer and CiteSpace software. The results show that the NPO is mainly distributed in the disciplinary fields associated with journalism and communication and public management. There are four main hotspots: analysis of public opinion, analysis of communication channels, technical means and challenges faced. The knowledge base in the field of NPO research includes social media, user influence, and user influence related to opinion dynamic modeling and sentiment analysis. With the advent of the era of big data, big data technology has been widely used in various fields and to some extent can be said to be the research frontier in the field. Transforming big data public opinion into early warning, realizing in-depth analysis and accurate prediction of public opinion as well as improving decision-making ability of public opinion are the future research directions of NPO.

Аlgorithmization of the knowledge base in service of passenger cars

The article considers the architecture of conceptual modeling of the knowledge base, which creates a model of the subject area in the form of many concepts and relationships between them. This approach is based on the concept of a mobile software agent, which is implemented and functions as an independent specialized computer program or an element of artificial intelligence. Ensuring the use of subject area knowledge has become one of the driving forces of the recent surge in the study of artificial intelligence. For example, for models of many different subject areas it is necessary to formulate the concept of time. This representation includes the concepts of time intervals, time points, relative measures of time, etc. If one group of scientists develops a detailed knowledge base, others can simply reuse it in their subject areas using their own database. Creating explicit assumptions in the subject area, which underlie the implementation, makes it easy to change the assumptions when changing our knowledge of the subject area. The process of conceptualization of TO and P, first of all, involves the development of databases in research areas for the formalization and systematization of knowledge about the characteristics of this area of entities and phenomena. That is, the use of concepts in the field of maintenance in a consistent manner in relation to theories of knowledge. Ultimately, the paper updated mathematical modeling, algorithmization and implementation of intelligent systems in the field of maintenance, which will help automate the process of diagnosis and inspection of all car systems, facilitate fault prevention and improve the maintenance process and modernize the maintenance system itself. The approach of algorithmization of the base of knowledge of a condition of the car in each moment of time considered in work gives the chance to reduce time of stay of the car in the service center and to reduce considerably expenses for passing of MOT at service of cars.