Based on an intense small scale study which observed a small team of operations personnel who work in a telecommunications company within the oil industry, this thesis examined employee reactions to management communication. Employee interpretations and reactions after each communication from the management team were analysed as the ‘organisational story’ ‘unfolds’ from the ‘other side’ (i.e. employee perspective) instead of the rather usual/dominant one (i.e. managerial perspective). Behaviour was observed from an interactionist, interpretive and critical perspective and analysed in the light of several managerial and communication theories with the aim of critically examining the claims of the post-modern organisation theory (i.e. humanisation of work) and certain communication theories. An ethnographic approach, which enabled the researcher/participant to conduct participant observation in a real setting, ensured deep understanding of social situations and human actions. The results of this study suggest that upward communication is problematic due to the power settings that exist in organisations. Based on Goffman’s theory, it is suggested that employee ‘performance’ is affected by certain rules and conventions which shape organisational psychology and interpersonal relations. Therefore, the utopian claims of the post-modern organisation theory along with the rather simplistic assumptions of some of the literature on communication need to be re-evaluated and re-defined in the search for a more critical understanding of communication. This thesis concludes that contrary to the utopia of the post-modern organisation, the reality of organisational life and communication reflects the persistence of the modern organisation and the power structures which dominate it.

Since artificial intelligence (AI) is growing more prominent it is interesting to look at the methods used to train AI. One such method is reinforcement learning in simulation, where AI can train safely in the confines of a simulation. For this a simulation environment is needed which in turn needs to communicate with a reinforcement learning system. It is therefore interesting to look at how this communication may affect the performance of the system. This study is made to look at this question.  A few different communication protocols are evaluated in a test program using data of the same kind used in reinforcement learning systems, floating point numbers and images. These protocols are sockets, Socket.IO, gRPC, and ZeroMQ. Of the protocols sockets and ZeroMQ are shown to be similar for sending floats, with ZeroMQ being better performing at sending images. For larger amounts of data sockets are however better. ZeroMQ is considered the best choice for an application dealing with floats and images, due to the performance and more built in ease of use functionality compared to sockets.  ZeroMQ is adapted into a working example for reinforcement learning training in simulation using Unreal Engine as a simulation environment, AGX Dynamics for physics simulation, and Stable Baselines3 for reinforcement learning. Performance in the simulation is similar but slower than in the test program. In the small example used the reinforcement learning process is the slowest part of the system, the simulation is the next slowest at a third of the time of the reinforcement learning, communication back and forth stands for half of the simulation time. As the system grows more complexreinforcement learning time and simulation time are expected to grow at a much faster speed than thecommunication. Therefore if optimization is to be made it is likely better to focus at the other part first.

Time-Triggered Controller Area Network (TTCAN) is a hybrid communication paradigm with combining both time-triggered and event-triggered traffic scheduling. Different from the standard Controller Area Network (CAN), communication in TTCAN is performed according to a pre-computed, fixed (during system run) schedule that is called as TTCAN System Matrix. Thus, communication performance of TTCAN network is directly related to structure of the system matrix, which makes the design of system matrix a crucial process. The study in this thesis consists of the extended work on the development of a systematic approach for system matrix construction. Methods for periodic message scheduling and an approach for aperiodic message scheduling are proposed with the aim of constructing a feasible system matrix, combining three important aspects: message properties, protocol constraints and system performance requirements in terms of designated performance metrics. Also, system matrix design, analyses and performance evaluation are performed on example message sets with the help of two developed software tools.

The thesis examines the phenomenon of nonverbal communication via dance from the perspective of anthropology of dance. The objective of the thesis is to analyze the dance environment of contemporary and ballroom dance, based on the point of view of the dancers as well as of the audience. I determine the differences in the ways these forms of dance communicate through dance performances. I examine how dance functions as a means of language, on which level the communication is processing and what meanings and messages the audience decodes within the dance performance. The phenomenon of dance in its natural environment is studied semiotically, as a form of language in certain context. The fieldwork method is based on participant observation and semistructured interviews with both dancers and audience. The research was conducted in the studio of Nová scéna - Lidé v pohybu in Prague, which teaches contemporary dance, and in the dance club Akcent Dobruška, which focuses on ballroom dance. Keywords: Anthropology of Dance, Nonverbal Communication, Contemporary Dance, Ballroom Dance, Semiology, Performance, Audience, Meaning.

The interconnection of molecular machines with different functionalities to form molecular communication systems can increase the number of design possibilities and overcome the limited reliability of the individual molecular machines. Artificial information exchange using molecular signals would also expand the capabilities of single engineered cell populations by providing them a way to cooperate across heterogeneous cell populations for the applications of synthetic biology and lab-on-a-chip systems. The realization of molecular communication systems necessitates analysis and design of the communication channel, where the information carrying molecular signal is transported from the transmitter to the receiver. In this thesis, significant progress towards the use of microfluidic channels to interconnect molecular transmitter and receiver pairs is presented. System-theoretic analysis of the microfluidic channels are performed, and a finite-impulse response filter is designed using microfluidic channels. The spectral density of the propagation noise is studied and the additive white Gaussian noise channel model is developed. Memory due to inter-diffusion of the transmitted molecular signals is also modeled. Furthermore, the interference modeling is performed for multiple transmitters and its impact on the communication capacity is shown. Finally, the efficient sampling of the signal transduction by engineered bacterial receivers connected to a microfluidic channel is investigated for the detection of the pulse-amplitude modulated molecular signals. This work lays the foundation for molecular communication over microfluidic channels that will enable interconnection of engineered molecular machines.