Liana Napalkova

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This paper focuses on the development and validation of an optimal motion planning method for computer-assisted surgical training. The context of this work is the development of new-generation systems that combine artificial intelligence and computer vision techniques in order to adjust the learning process to specific needs of a trainee, while preventing a(More)
This paper describes a system developed to assist in model-based training of minimally invasive, laparoscopic procedures. The key factor motivating the development of the device called CAST (Computer-Assisted Surgical Trainer) is the need to improve the state-of-the-art in teaching laparoscopy, and ultimately achieve better surgical outcomes. CAST’s design(More)
This paper focuses on the development of simulation-based environment for multi-echelon cyclic planning and optimisation in the product maturity phase. It is based on integration of analytical and simulation techniques. Analytical techniques are used to obtain initial planning decisions under conditions of stochastic demand and lead time, whereas simulation(More)
This paper develops a multi-objective simulationbased genetic algorithm (MOSGA) for multi-echelon supply chain cyclic planning and optimisation. The problem involves a search in high dimensional space with different ranges for decision variables scales, multiple objectives and problem specific constraints, such as power-of-two and nested/inverted-nested(More)
The paper presents a taxonomic analysis of existing hybrid multi-objective evolutionary algorithms aimed at solving multi-objective simulation optimisation problems. For that, the properties of evolutionary algorithms and the requirements made to solving the problem considered are determined. Finally, a combination of the properties, which allows one to(More)
This paper describes a mechatronic (mechanical and electronic) realization of the optimal trajectory planning and guidance algorithms for minimally invasive surgical training. Specifically, the realization implements optimal navigation paths for surgical instruments in laparoscopic exercises. The underlying system platform is the Computer-Aided Surgical(More)
The paper describes the algorithm, which is developed to solve scheduling tasks in Flexible Manufacturing Systems. The algorithm is a combination of Genetic Algorithm and Coloured Petri Nets. It is proposed to use Coloured Petri Nets to tackle the encoding problem in Genetic Algorithm. The objective is to minimize the total make-span subject to different(More)
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