Książki, monografie, podręczniki, rozdziały (WFTIiMS)

Stały URI dla kolekcjihttp://hdl.handle.net/11652/173

Przeglądaj

Filtry

2017 - 201912020 - 20233

Ustawienia

Data zakończenia: 2023Tematsearch.filters.applied.operator.equals: search.filters.subject.gry komputerowe

collection.search.results.head

Teraz wyświetlane 1 - 4 z 4
  • Pozycja
    Integrating Anomaly Detection for Enhanced Data Protection in Cloud-Based Applications
    (Wydawnictwo Politechniki Łódzkiej, 2023) Czerkas, Konrad; Drozd, Michał; Duraj, Agnieszka; Lichy, Krzysztof; Lipiński, Piotr; Morawski, Michał; Napieralski, Piotr; Puchała, Dariusz; Kwapisz, Marcin; Warcholiński, Adrian; Karbowańczyk, Michał; Wosiak, Piotr
    In this research, anomaly detection techniques and artificial neural networks were employed to address the issue of attacks on cluster computing systems. The study investigated the detection of Distributed Denial of Service (DDoS) and Partition attacks by monitoring metrics such as network latency, data transfer rate, and number of connections. Additionally, outlier detection algorithms, namely Local Outlier Factor (LOF) and COF, as well as ARIMA and SHESD models were tested for anomaly detection. Two types of neural network architectures, multi-layer perceptron (MLP) and recursive LSTM networks, were used to detect attacks by classifying events as “attack” or “no attack”. The study underscores the importance of implementing proactive security measures to protect cluster computing systems from cyber threats.
  • Pozycja
    Prediction of Natural Image Saliency for Synthetic Images
    (Wydawnictwo Politechniki Łódzkiej, 2021) Rudak, Ewa; Rynkiewicz, Filip; Daszuta, Marcin; Sturgulewski, Łukasz; Lazarek, Jagoda
    Numerous saliency models are being developed with the use ofneural networks and are capable of combining various features and predicting the saliency values with great results. In fact, it might be difficult to replace the possibilities of artificial intelligence applied to algorithms responsible for predicting saliency. However, the low-level features are still important and should not be removed completely from new saliency models. This work shows that carefully chosen and integrated features, including a deep learning based one, can be used for saliency prediction. The integration is obtained by using Multiple Kernel Learning. This solution is quite effective, as compared to a few other models tested on the same dataset.
  • Pozycja
    Hand gestures as a method of interaction in virtual reality HOPA games
    (Wydawnictwo Politechniki Łódzkiej, 2021) Lamus, Monika; Wiśniewska, Aneta; Szrajber, Rafał
    The main objective of the study was to implement the intuitive gesture set for movement and interaction in a virtual HOPA game. A review and analysis of existing solutions using the Leap Motion device to track gestures and hand movements was conducted. Two sets of movement modes were created and subjected to a series of tests to determine the best optimal movement and interaction technique. The tests were verified in terms of speed and accuracy of task performance.
  • Pozycja
    Computer Game Innovation
    (Wydawnictwo Politechnika Łódzka, 2017) Wojciechowski, Adam; Napieralski, Piotr
    The "Computer Game Innovations" series is an international forum designed to enable the exchange of knowledge and expertise in the field of video game development. Comprising both academic research and industrial needs, the series aims at advancing innovative industry-academia collaboration. The monograph provides a unique set of articles presenting original research conducted in the leading academic centres which specialise in video games education. The goal of the publication is, among others, to enhance networking opportunities for industry and university representatives seeking to form R&D partnerships. This publication covers the key focus areas specified in the GAMEINN sectoral programme supported by the National Centre for Research and Development.