Vol. 26, No. 1


Recent Submissions

Now showing 1 - 4 of 4
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    On Voynich Alphabet Analysis With Relation to the Old Indian Dialects
    (Institute of Automation and Computer Science, Brno University of Technology, 2020-08-24) Zelinka, Ivan; Dao, Tran Trong
    This paper is discussing our new research direction in the Voynich manuscript research. While our previous papers have been dealing with the research that has been based on fractal property analyses or graph properties analyses, where the graph has been constructed from the Voynich manuscript word sequences (Fig. 1), this paper discusses another kind of research on Voynich manuscript. This research is focused on the compassion of the letters or alphabets from Voynich manuscript with another selected alphabets from a different dialect, in that case, dialect from the Indian language. The reason is to point out the possibility that we can identify the origin of the Voynich manuscript alphabets based on the graphical conversion between letters from different dialects. Because this research is a very wide and deep topic, we publish in this paper only basic ideas, simulations and discuss all problems which have been found during those experimentation as well as outlining of the future directions of the research in an outlined way.
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    Combining solutions of the optimum satisfiability problem using evolutionary tunneling
    (Institute of Automation and Computer Science, Brno University of Technology, 2020-08-24) da Silva, Rodrigo Ferreira; Hvattum, Lars Magnus; Glover, Fred
    The optimum satisfiability problem involves determining values for Boolean variables to satisfy a Boolean expression, while maximizing the sum of coefficients associated with the variables chosen to be true. Existing literature has identified a tabu search heuristic as the best method to deal with hard instances of the problem. This paper combines the tabu search with a simple evolutionary heuristic based on the idea of tunneling between local optima. When combining a set of solutions, variables with common values in all solutions are identified and fixed. The remaining free variables in the problem may be decomposed into several independent subproblems, so that parts of the solutions combined can be extracted and combined in an improved solution. This solution can be further improved by applying the tabu search in an improvement stage. The value of the new heuristic is demonstrated in extensive computational experiments on both existing and new test instances.
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    X-Swarm: The Upcoming Swarm Worm
    (Institute of Automation and Computer Science, Brno University of Technology, 2020-08-24) Truong, Thanh Cong; Diep, Quoc Bao; Zelinka, Ivan; Dao, Than Trong
    With the rapid growth of technology in the digital landscape, cybercriminals attempt to utilize new and sophisticated techniques to autonomous and increase the speed and scale of their attacks. Meanwhile, the Dark Web infrastructures such as Tor, plays a crucial role in the criminal underground, especially for malware developers' communities. It is logical to expect that the malicious actors would utilize the combination of these techniques in shortcoming time. To better understand the upcoming threat, in this manuscript, we investigate the design and mitigation of such malware. Accordingly, we introduce X-sWarm, which will be the next generation of resilient, stealthy malware that leverages the intelligent technique and the darknet infrastructures. Furthermore, we show that with the self-healing network mechanism, X-sWarm can achieve a low diameter and a low degree and be robust to partitioning under node removal. More importantly, we suggest the mitigation technique that neutralizes the nodes of the proposed worm.
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    Optimization of Snake-like Robot Locomotion Using GA: Serpenoid Design
    (Institute of Automation and Computer Science, Brno University of Technology, 2020-08-24) Hůlka, Tomáš; Matoušek, Radomil; Dobrovský, Ladislav; Dosoudilová, Monika; Nolle, Lars
    This work investigates the locomotion efficiency of snake-like robots through evolutionary optimization using the simulation framework PhysX (NVIDIA). The Genetic Algorithm (GA) is used to find the optimal forward head serpentine gait parameters, and the snake speed is taken into consideration in the optimization. A fitness function covering robot speed is based on a complex physics simulation in PhysX. A general serpenoid form is applied to each joint. Optimal gait parameters are calculated for a virtual model in a simulation environment. The fitness function evaluation uses the Simulation In the Loop (SIL) technique, where the virtual model is an approximation of a real snake-like robot. Experiments were performed using an 8-link snake robot with a given mass and a different body friction. The aim of the optimization was speed and length of the trace.