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Teilāns, Artis
Preferred name
Teilāns, Artis
Official Name
Teilans, Artis
Alternative Name
Teilands, Artis
Teilans, A
Artis Teilans
Email
artis.teilans@rta.lv
ORCID
Scopus Author ID
24723234500
Researcher ID
AAJ-1139-2020
Research Output
Now showing 1 - 10 of 13
- PublicationA Metamodel Based Approach for UML Notated Domain Specific Modelling Language(2011)
; Scopus© Citations 2 - PublicationReal Estate Monitoring System Based on Remote Sensing and Image Recognition Technologies(2017)
; Ivonna AnsoneGeoinformation 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.Scopus© Citations 11 - PublicationINFORMATIONAL WARFARE – INFLUENCE ON INFORMATIONAL STRUCTURES(2019)
; ; 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.Scopus© Citations 1 - PublicationMathematical Model of the Distribution of Laser Pulse Energy(2016)
; ; - PublicationAPPLE AND PEAR SCAB ONTOLOGY(2021)
; ; Scopus© Citations 1 - PublicationMathematical Model of Forecasting Laser Marking Experiment Results(2016)
; ; - PublicationE-LEARNING: DEVELOPING TOMORROW'S EDUCATION(2021)
; 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. - PublicationAUTOMATION OF FEEDBACK ANALYSIS IN ASYNCHRONOUS E-LEARNING(2023)
; ; Atis KapenieksWith the recent hit of the Pandemic study process is shifted to E-learning. Measuring the actual progress of a student in Asynchronous e-learning because of machine-human interaction and feedback is also considered a primary issue in this area. With the rapid development of artificial intelligence, computers can capture surroundings. Image processing is a rising technique in Artificial Intelligence (AI). Recognition of an individual's emotion helps identify the person's inner state. It is easy to measure a student's feedback about the session by doing it. The main functionality of this project is to capture the student's enough frames during the study session and provide the analysis of the average emotions to the administration panel. This prototype was used on 10 minutes of lecture to capture the emotion. The primary goal of this proposed system is to capture the learner's emotion at a specific interval during the e-learning session and provide the feedback of it to the instructor. - PublicationCORAS for Threat and Risk Modeling in Social Networks(2015)
; 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.Scopus© Citations 6 - PublicationMachine Learning Technology Overview In Terms Of Digital Marketing And Personalization(2021)
; Nikolajeva, AnnaThe research is dedicated to artificial intelligence technology usage in digital marketing personalization. The doctoral theses will aim to create a machine learning algorithm that will increase sales by personalized marketing in electronic commerce website. Machine learning algorithms can be used to find the unobservable probability density function in density estimation problems. Learning algorithms learn on their own based on previous experience and generate their sequences of learning experiences, to acquire new skills through self-guided exploration and social interaction with humans. An entirely personalized advertising experience can be a reality in the nearby future using learning algorithms with training data and new behaviour patterns appearance using unsupervised learning algorithms. Artificial intelligence technology will create website specific adverts in all sales funnels individually.