Principles of electrostimulation of the face and neck muscles - a medical and biocybernetic approach

The facial nerve has a tortuous and complex course from the parotid-cerebellar junction to various target sites, withindividually varied and complex branching patterns and connections to several other cranial nerves. This makes research-based computational models a key component of modern diagnostics and therapy, as well as patient monitoring and the design of devices to support the above-mentioned processes. To date, no good computational model has been proposed in this area and the concepts presented are in the preliminary research phase. The aim of this study is to develop guidelines for a computational model of electrostimulation of facial and neck muscles in order to improve diagnosis and therapy, but also for the future development of a virtual twin for eHealth.Nerw twarzowy ma kręty i złożony przebieg od połączenia ślinianki przyusznej i móżdżku do różnych miejsc docelowych, z indywidualnie zróżnicowanymi i złożonymi wzorcami rozgałęzień i połączeniami z kilkoma innymi nerwami czaszkowymi. Sprawia to, że modele obliczeniowe oparte na badaniach są kluczowym elementem nowoczesnej diagnostyki i terapii, a także monitorowania pacjentów i projektowania urządzeń wspierających wyżej wymienione procesy. Do tej pory nie zaproponowano dobrego modelu obliczeniowego w tym obszarze, a przedstawione koncepcje znajdują się we wstępnej fazie badań. Celem niniejszego badania jest opracowanie wytycznych dla modelu obliczeniowego elektrostymulacji mięśni twarzy i szyi w celu poprawy diagnostyki i terapii, ale także dla przyszłego rozwoju wirtualnego bliźniaka dla eZdrowi

Recent Advances in General Game Playing

The goal of General Game Playing (GGP) has been to develop computer programs that can perform well across various game types. It is natural for human game players to transfer knowledge from games they already know how to play to other similar games. GGP research attempts to design systems that work well across different game types, including unknown new games. In this review, we present a survey of recent advances (2011 to 2014) in GGP for both traditional games and video games. It is notable that research on GGP has been expanding into modern video games. Monte-Carlo Tree Search and its enhancements have been the most influential techniques in GGP for both research domains. Additionally, international competitions have become important events that promote and increase GGP research. Recently, a video GGP competition was launched. In this survey, we review recent progress in the most challenging research areas of Artificial Intelligence (AI) related to universal game playing

Towards the Deployment of Machine Learning Solutions in Network Traffic Classification: A Systematic Survey

International audienceTraffic analysis is a compound of strategies intended to find relationships, patterns, anomalies, and misconfigurations, among others things, in Internet traffic. In particular, traffic classification is a subgroup of strategies in this field that aims at identifying the application's name or type of Internet traffic. Nowadays, traffic classification has become a challenging task due to the rise of new technologies, such as traffic encryption and encapsulation, which decrease the performance of classical traffic classification strategies. Machine Learning gains interest as a new direction in this field, showing signs of future success, such as knowledge extraction from encrypted traffic, and more accurate Quality of Service management. Machine Learning is fast becoming a key tool to build traffic classification solutions in real network traffic scenarios; in this sense, the purpose of this investigation is to explore the elements that allow this technique to work in the traffic classification field. Therefore, a systematic review is introduced based on the steps to achieve traffic classification by using Machine Learning techniques. The main aim is to understand and to identify the procedures followed by the existing works to achieve their goals. As a result, this survey paper finds a set of trends derived from the analysis performed on this domain; in this manner, the authors expect to outline future directions for Machine Learning based traffic classification

Journal of Telecommunications and Information Technology, 2011, nr 4

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