29th DAAAM International Symposium on Intelligent Manufacturing and Automation
The 29th DAAAM International Symposium on Intelligent Manufacturing and Automation took place in Zadar, Croatia between the 24th and 27th October 2018, during the DAAAM International Week. The Symposium was organized by DAAAM International Vienna in cooperation with ÖIAV 1848, Vienna University of Technology, International Academy of Engineering and University of Applied Sciences – Technikum Wien and Under the Auspices of the Danube Rectors’ Conference & Rectors’ and Presidents’ Honor Committee of DAAAM International for 2018. The Symposium took place in Zadar, Croatia. This year’s symposium aimed at continuing the success of the previous years, focusing on the five-fold traditional objectives of the symposium: the presentation of the most recent high-quality results, support of development of young scientists and researchers, organization of international (summer) doctoral school, inauguration of new members of Central European Branch of International Academy of Engineering and the provision of the necessary setting for stimulating discussions, brainstorming and networking among European and international researchers coming both from the academia government agencies and industry.
The article reviews the problems of using an electronic document (i.e. legally significant computer information) as a necessary tool for building a digital economy. This problem becomes of special importance in terms of implementation of distributed computing in the interests of modern technologies, including Big Data, Artificial Intelligence, Blockchain, Industry 4.0, Industrial Internet of Things, Virtual and Augmented Reality technologies, etc. The authors show that in case of development and adoption of the Law "On Electronic Document", we can link the concepts of "Electronic Document" and "Data Message", and can identify several categories of Computer Information (Electronic data interchange) having a significance: specified Computer data, traffic data, stored Computer data, traffic data, content data.
Predictive maintenance is a powerful maintenance strategy that makes it possible to significantly reduce operation and maintenance costs of public, commercial and industrial environments. It is a complex data-driven process, which tries to forecast future states of company assets. On one hand it prerequisites condition monitoring of components on machine level. On the other hand it demands the integration of the collected data with other management information systems. Digitization and especially the advent of big data science bring along promising opportunities to create effective smart monitoring and predictive maintenance applications. The aim of this research is to examine the possibilities of a predictive maintenance framework based on the design principles of Industry 4.0 and recent developments in distributed computing, Big Data and Machine Learning. It introduces numerous enabling technologies such as industrial Internet of things, standardized communication protocols, as well as edge and cloud computing. Moreover, it takes a deeper look at data analytical techniques and tools, and analyses performance of well-known machine learning algorithms. Paper proposes architecture of a predictive maintenance framework based on existing software and hardware solutions. As a proof of concept, a real-life smart heating, ventilation, and air conditioning (HVAC) application system is created and tested to demonstrate the possibilities of the proposed PdM framework.
Possible methods of implementing aggression as one of the mechanisms in the formation of social behavior in groups of robots are discussed. Aggression is seen as a way to resolve conflicts over resources. The features of the aggressive behavior of eusocial insects (ants) are used as a basis. The aggressive component is integrated into the need-emotional architecture of the robot control system, which is presented as a hybrid neuro-production system. The proposed mechanism can be used as a base for implementing various models of social behavior in group robotics.
This article investigates the problem of identifying a person on the Internet by legal and technical means. The practice of identifying people in Russia and the UK was studiedand compared. Russia was selected because its legislation is well known to the authors, and the UK was selected as it has developed a mature system for the online identification of individuals and relationships and a certain legal regulation in this sphere.An analysis of two government programs was made, namely: the UK Identity Assurance Programme of the Government Digital Service and the Russian Government Decree on “The development of the Federal state information system”. In terms of technological background for person’s identification, the practice of using IPv4 and IPv6 was explored. Russia's specific problems are analysed via the protection of privacy in the case of personal identification and the processing of personal data on the Internet. The authorsdraw conclusions about the division of the concepts of identification and individualization of people on the Internet. Weintroduceourown definition of personal identification on the Internet and proposean amendment to the Russian concept of personal data: the definition of personal data should include the IP address of a person.
The article reviews the problems of using an electronic document (i.e. legally significant computer information) as a necessary tool for building a digital economy. This problem becomes of special importance in terms of implementation of distributed computing in the interests ofmodern technologies, including Big Data,Artificial Intelligence, Blockchain, Industry 4.0,Industrial Internetof Things,Virtual and Augmented Reality technologies, etc. The authors showthat in case of development and adoption ofthe Law "On Electronic Document", we can link the concepts of "Electronic Document" and "Data Message", and can identify several categories of Computer Information (Electronic data interchange) having asignificance: specified Computer data, traffic data, stored Computer data, traffic data,content data.