Research Output
Assessment of Cyber Physical System Risks with Domain Specific Modelling and Simulation
Nowadays, the systems developed to integrate real physical processes and virtual computational processes — the cyber-physical systems (CPS), are used in multiple areas of industry and critical national infrastructure, such as manufacturing, medicine, traffic management and security, automotive engineering, industrial process control, energy saving, ecological management, industrial robots, technical infrastructure management, distributed robotic systems, protection target systems, nanotechnology and biological systems technology. With wide use, the level of IT and cyberrisks increases drastically and successful attacks against the CPS will lead to unmanageable and unimaginable consequence. Thus, the need in well-designed risk assessment system of CPS is clear and such system can provide an overall view of CPS security status and support efficient allocations of safeguard resources. The nature of CPS differs from IT mainly with the requirement for real-time operations, thus, traditional risk assessment method for IT system can be adopted in CPS. Design of a unified modelling language based domain specific language described in this paper achieves synergy from in IT industry widely used UML modelling technique and the domain specific risk management extensions. As a novelty for UML modelling, especially for simulation purposes, the presented DSL is enriched by a set of stochastic attributes of modelled activities. Such stochastic attributes are usable for further implementation of discrete-event system simulators.
The Development of an Integrated Geosimulation Environment for Public Transit Analysis and Planning
This paper describes an integrated software environment for multi-modal public transit simulation based on the principles of geosimulation that integrates the capabilities of multi-agent systems, GIS and interactive visualization. The goal of the presented research is to explore possibilities of population in one of Latvia’s planning regions, called Vidzeme, to access state/municipal and other services by using public transport. In order to achieve the defined goal, an integrated simulation environment for public transit analysis and planning is developed.
IPTV Statistic Data Collection, Processing and Preparation for use in a Modeling System
Abstract Today most people get information from a TV. Trust level for television is very high and this kind of media can strongly influence public opinion. To research content watched on TV or public opinion, questioning and other methods are used today and respondents know about the research process. This knowledge forces people to give untruthful answers, because sometimes they don’t want to share their thoughts. This kind of research result is not satisfactory and conclusions can create misconceptions. Fast development of IPTV gives new opportunities for research using collected statistics. To make research legal, all statistical data must be anonymous. If a TV watcher doesn’t think that he has to make a choice, he will watch TV content he is interested in. At the moment there is no one united standard for collecting and processing IPTV statistical data. Each vendor handles data differently. Some solutions do not allow collecting data about watched TV channels and programs. In this paper the author will present a possible, universal method for data collection in a variety of IPTV networks, and different types of streaming and Middleware.
CORAS for Threat and Risk Modeling in Social Networks
As more users joining social networks possibility of threats is growing, as the information can be reached by expanding number of individuals that increases the possibility that the information “package” will find way to subjects with the appropriate degree of sensitivity to the information – vulnerability. Therefore, the risk management process and, in particular, the risk identification and analysis of key characteristics should be performed. Presented paper describes usage of CORAS methodology for modelling of social network risks.
Real Estate Monitoring System Based on Remote Sensing and Image Recognition Technologies
Geoinformation are changing fast, therefore a change detection of real estate must be processed in short time. The increasing resolution of sensed geospatial data creates critically important to develop high performance computing solutions to process geospatial information. The topic of scientific work is the real estate monitoring system based on image recognition and remote sensing technologies. System's practical application is automatic building recognition from LiDAR data using saliency based method, vector map generation and change detection in actual cadastral maps. The scientific work describes high performance computing solution and gives its performance comparison with traditional method.
Mobile Phone Based Remote Control System For Furnace Automation
Nowadays, an increasing role in various technologies holds electronic devices that automate the various systems to facilitate people's daily life. This publication describes one of those types of automation capabilities, as a control system using mobile phones and mobile communications. Innovative approaches for the modification can be used for various purposes, such as a room or vehicle security alarm systems, remote management for various processes, the heating system furnace firing, the combustion process control, as well as many other remote management and control purposes.
APPLE AND PEAR SCAB ONTOLOGY
An important issue in horticulture is ensuring plant disease, such as scab, prevention and treatment. Apple and pear are among the most widely grown (approximately 43% of all fruit tree area [1]) and economically important fruit crops specified worldwide and in Latvia. Scab diseases caused by ascomycetous fungi Venturia inaequalis and V.pyrina are economically the most important diseases worldwide. Research projects have produced research data covering various aspects of plant-pathogen interactions, but there is no internal linkage analysis, as well as implementation of other types of data (such as environmental and meteorological data, etc.). Establishing such a data integration system would allow the identification of new regularities in plant-pathogen interactions, and provide mechanisms for disease control decisions. Semantic analysis is one of information technology approaches to finding relationships in data. The product of analysis is ontology. There are plant disease ontologies which provide classification of diseases and describe their reasons. However, there is no ontology which describes a specific plant and relations among its farming parameters and disease probability. Such an ontology for apple and pear scab is presented in this paper. The constructed ontology can be applied to develop guidelines or digital expert systems.
INFORMATIONAL WARFARE – INFLUENCE ON INFORMATIONAL STRUCTURES
The concept of information warfare encompasses the use of information and communication technologies to gain an advantage over a potential opponent. The information warfare is the manipulation with the information that trusts the goal, so that the goal should make decisions about its interests in the interests of opponents. Information structures are treated as systems that process different types of information, provide storage and access to users. Such structures may enclose neural networks, self-learning systems etc. They need to be ready to learn, respond to threats and ensure their safety, which is topical in today's information warfare. This paper will address aspects related to the security of information systems from a system theory point of view. The knowledge base of information structures can be elements of artificial intelligence, which security must be protected against various threats. The authors considers artificial neural networks to be one of the potential threats in the context of information warfare.
A Multi-Model Approach for Simulation-Based Digital Twin in Resilient Services
Complex cyber-physical systems demand integrated solution approaches. The current work presents a multi-model approach for simulation-based digital twins as a formal and technological foundation for the analysis and improvement of resilient services. The given approach has several significant benefits including the possibility to conduct interactive simulations and experiments based on systems engineering principles, to share data across multiple data sources and storages, to manage operations in real-time, as well as to enable collaboration between the users in an integrated web platform. The proposal is illustrated on the use cases of secure telemedicine services and secure remote workplace.
E-LEARNING: DEVELOPING TOMORROW'S EDUCATION
E-learning refers to the term to deliver education or training using digital resources. Computer-based learning, which is considered the keystone of today's E-learning concept, was born in the 80s. Earlier E-learning provides education using only text as with the development in technology it allows adding various forms, i.e., Graphical Text, Images, Video Conferencing etc. In today's time, the concept of is E-learning growing at a rapid pace. Improved bandwidth and growing technology helped in pushing the expansion of E-learning. Along with the university, large corporate companies are also resorting to E-learning. E-learning provides many advantages as compare to Instructor-led training (ILT). E-learning saves the times of travel as physical presence is not required. Education can be provided from anywhere at any time. E-learning is cost-effective also as the course, once developed, can be modified easily. There can some concern which can be faced by the trainer and leaners in future. Adopting E-learning will be a step towards saving the environment. It will be environmentally friendly as tablets will replace books; paper notes will be replaced with digital messages. Digital tools will help to reduce the burden of a student. Artificial Intelligence is a prevalent concept in computer science. A branch of AI, known as a Neural Network, is based on the human brain. The research's main aim is to review existing methods and analyse further possibilities of E-learning systems with neural networks.