This paper describes the theoretical design and implementation of the semantic machine of transparent intensional logic. Transparent intensional logic is used for the logical-semantic analysis of natural language, which is performed in three steps - type analysis, creation of construction, and type control (last step is optional). The semantic machine described in this paper allows analyzing natural language sentences in the first two of the mentioned steps. Transparent intensional logic analyzes the meaning of natural language sentences and therefore it was not essential to focus on the syntactic level of analysis. Syntactic analysis is performed using a Stanford CoreNLP parser, which was carefully selected after comparison with competing parsers. The functionality of the implemented semantic machine is demonstrated by a logical analysis of examples of natural language sentences.

The article deals with the possibilities of interaction in the virtual environment (VE) of the CAVE LIRKIS system. Commonly available peripherals are keyboard, mouse or gamepad. However, these do not provide a sufficient level of immersion, such as hand gestures. The MYO armband has proven to be one of the potential devices for improving interaction. Therefore, a system for editing an object transformation in VE was created using hand gestures and movements. Enhancing the natural user interface (NUI) of the system with additional interaction capabilities has proven the device to be suitable also for further development.

The aim of the research is the proposal and experimental implementation of a solution based on Raspberry Pi that is to allow face recognition with subsequent user notification. Proposal of whole system discusses the possible negative factors that can endanger functionality of the system. Once the face is recognized or not recognized, the message is sent to the administrator and access is permitted or denied. This represents the elevated level of system hardening. The system in this research is built on histogram of oriented gradients (HOG) and neural network (NN). Testing of the software system solution has been also carried out and proves the usability with detection and recognitions rates above 90%. The implemented system may be used as a part of complex IoT (Internet of Things) security solution.

The exponential increase in transmission capacity triggered the era of fast and reliable data transfer techniques through fiber optic networks. This has led to the exploration of new options in the field of spectrally efficient systems suitable for extremely high data rates. Consequently, there is a gradual transition from existing systems with a 10 Gbps transmission rate to 40 Gbps optical systems and even up to 100 Gbps. However, with the increase in network transmission capacity, the optical signal performance requirement is also increased to ensure acceptable bit error rate (BER) in the receiver. However, increasing transmission power leads to a distortion of the transmitted signal due to the nonlinear Kerr effects or interference between adjacent channels. These are the main limitations that set the upper limit of the maximum effective SNR (Signal-to-Noise Ratio) of the optical link and limit the performance of the whole system. On the other hand, linear effects such as chromatic dispersion (CD), optical SNR (OSNR), spontaneous photon emission, optical fiber loss, or channel overlapping through long stretches of optical fibers are also important factors that need to be considered when designing DWDM (Dense Wavelength Division Multiplexing) system.

The paper deals with the problematics of data hiding into domain specific hierarchical data structures which are dedicated to the geometry of the voxelized three-dimensional scenes representation. Sparse Voxel Directed Acyclic Graph (SVDAG) as the suitable representant of this category of data structures was chosen. Possibility of data hiding into this structure, based on the knowledge of its construction on binary level was investigated and several data hiding methods were described and leveraged as the contribution of this paper.

This paper deals with a design and implementation of an intrusion detection system in heterogeneous network environment. The work includes work out characteristics of Intrusion detection systems, it`s base classification, development of problematic, building structure, used strategies of analyses in intrusion detectio and studies of placement the detectors of system. The scope of this work is to design and to implement the Intrusion detection system with uses the anomaly detection analyses, concrete statistical methods, in target of the third layer of ISO/OSI model. In implementation of the work is using the knowledge from area of the programming in C language and the modular programming, and the knowledge from area of the computer networks mainly from the building a networks traffic up to third layer of ISO/OSI model. The work includes the classification of implemented system and the experimental verification of the system functionality on the real specimen of network traffic from different network environments.