Spasov, Dejan

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Review of Drowsiness Detection Machine-Learning Methods Applicable for Non-Invasive Brain-Computer Interfaces
(IEEE, 2021-11-23)
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A Generalization of the Convolutional Codes
(Ss Cyril and Methodius University in Skopje, Faculty of Computer Science and Engineering, Republic of North Macedonia, 2020-05-08)
In this paper we propose a generalization of the convolutional codes. The proposed generalization of the convolutional codes offers the possibility to discover previously unknow convolutional codes. For example, convolutional codes with pseudo-random time-varying trellis diagram that may improve error-correcting capabilities of the convolutional codes. An important property of the proposed generalization of the convolutional codes is that the decoding complexity remains the same as the decoding complexity of the ordinary convolutional codes. We propose encoding and decoding schemes for the generalized convolutional codes.
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Parallelizing Dynamic Time Warping Algorithm for Hotel Occupancy Time Series Similarity Measurement
(IEEE, 2024-05-20)
Atanasovska, Ana Marija
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Progress Report of Greedy Algorithms in Coding theory
(Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University in Skopje, Macedonia, 2013)
Greedy algorithms in Coding Theory are simple to define and easy to implement, but require exponential running time. Codes obtained with greedy constructions have very good parameters, thus improving the running time of these algorithms may lead to discovery of new codes with best known parameters. We give an overview of greedy algorithms and discuss further improvements.
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Unique and Minimum Distance Decoding of Linear Codes with Reduced Complexity
(Springer, Berlin, Heidelberg, 2010-09-12)
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We show that for (systematic) linear codes the time complexity of unique decoding is     2 nRH R 2/ O n q  and the time complexity of minimum distance decoding is     2 nRH R O n q  . The proposed algorithm inspects all error patterns in the information set of the received message of weight less than d 2 or d , respectively.
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On the Complexity of the Greedy Construction of Linear Error-Correcting Codes
(Springer, Berlin, Heidelberg, 2009-09-28)
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Greedy algorithms are one of the oldest known methods for code construction. They are simple to define and easy to implement, but require exponential running time. Codes obtained with greedy construction have very good encoding parameters; hence, the idea of finding faster algorithms for code generation seems natural. We start with an overview of the greedy algorithms and propose some improvements. Then, we study the code parameters of long greedy codes in attempt to produce stronger estimates. It is well known that greedy-code parameters give raise to the Gilbert-Varshamov bound; improving this bound is fundamental problem in coding theory.
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Successful integration of practical Cisco CCNA in the Computer Networks Design course
(IEEE, 2015-03-18)
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This paper presents a new curriculum for the Computer Networks Design course intended as advanced course for computer science students. We have developed an adaptive curriculum, which introduces two CISCO CCNA 3 (LAN Switching) and 4 (WAN Technologies) courses instead of the existing (regular) tutorials and laboratory exercises. The students can choose whether they would like to learn the course by a more practical approach using the CISCO CCNA integration, rather than by a more theoretical approach. The evaluation show much better results for the students that follow the course using the integration of the CISCO practical exercises, rather than those that follow the course regularly only by theoretical approach.
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Review of Drowsiness Detection Machine-Learning Methods Applicable for Non-Invasive Brain-Computer Interfaces
(IEEE, 2021)
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This review focuses on the analysis of non-invasive BCI methods, and in particular in the state-of-the-art machine learning-based methods for EEG acquisition. EEG as a tool can be used to detect various states concerning human health, but it can also be used to detect the human’s states such as alertness, interest and even drowsiness. In this paper we focus on this important issue and present some of the ML techniques that can be used, as well as the methodology for noise detection and elimination while using EEG.
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On the Convergence of Distance Vector Routing Protocols
(2012-09)
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In this paper we give an overview of distance vector routing protocols. We focus on the convergence mechanisms in two widely known distance vector routing protocols: EIGRP and RIP. With the aim to provide open source protocol, we propose a solution that inherits the simplicity of the RIP protocol and the fast convergence of the EIGRP protocol. We believe that our proposal will provide faster convergence and better scalability in large networks.
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Distance Vector Routing
(Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University in Skopje, Macedonia, 2012)
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In this paper we give an overview of the distance vector routing strategies. We will compare two widely known routing protocols based on distance vector routing algorithms, is EIGRP and RIP, and we will propose few improvements to the RIP protocol. We believe that these improvements will provide faster convergence and better scalability in large networks.

Spasov, Dejan

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