The realization of high data rate wireless communication and large-scale connectivity with seamless coverage has been enabled by the introduction of various advanced transmission technologies, such as multiple access (MAC) technology and relay-assisted communications. However, beyond the accurate representation and successful transmission of information, in many applications it is the semantic aspect of that information that is really of interest. This thesis makes contributions to both the technology of conventional wireless communications and the theory of semantic communication. The main work is summarized as follows: We first consider an uplink system with K single-antenna users and one base station equipped with a single antenna, where each user utilizes a binary constellation to carry data. By maximizing the minimum Euclidean distance of the received sum constellation, the optimal user constellations and sum constellation are obtained for K=3 users. Using the principle of lattice coding, that design is extended to the K-user case. In both settings, the sum constellation belongs to additively uniquely decomposable constellation group (AUDCG). That property enables us to reduce the maximum likelihood multi-user detector to a single-user quantization based receiver. The symbol error probability (SEP) formula is derived, showing that our proposed non-orthogonal multiple access (NOMA) scheme outperforms the existing time division multiple access (TDMA) designs for the same system. Our design also sheds light on the general complex constellation designs for the MAC channel with arbitrary user constellation size. Specifically, K-user constellations with any 2^Mk size can be obtained using combinations of the proposed binary constellations. Next we concentrate on a multi-hop relay network with two time slots, consisting of single-antenna source and amplify-and-forward relay nodes and a destination node with M antennas. We develop a novel uniquely-factorable constellation set (UFCS) based on a PSK constellation for such system to allow the source and relay nodes to transmit their own information concurrently at the symbol level. By taking advantage of the uniquely-factorable property, the optimal maximum likelihood (ML) detection was equivalently reduced to a symbol-by-symbol detection based on phase quantization. In addition, the SEP formula was given, while enable us to show that the diversity gain of the system is one. For semantic communication, a new source model is considered, which consists of an intrinsic state part and an extrinsic observation part. The intrinsic state corresponds to the semantic feature of the source. It is not observable, and can only be inferred from the extrinsic observation. As an instance of the general model, the case of Gaussian distributed extrinsic observations is studied, where we assume a linear relationship between the intrinsic and extrinsic parts. We derive the rate-distortion function (in both centralized encoding and distributed encoding) of semantic-aware source coding under quadratic distortion structure by converting the semantic distortion constraint of the source to a surrogate distortion constraint on the observations. With proposed AUDCG and UFCS-based designs, high data rates as well as low detection latency can be achieved. Our modulation division method will be one of the promising technologies for the next generation communication and the analysis of the source coding with semantic information constraints also provides some insights that will guide the future development of semantic communication systems. / Thesis / Doctor of Philosophy (PhD) / The proliferation of smart phones and electronic devices has spurred explosive growth in high-speed multimedia services over the next generation of wireless cellular networks. Indeed, high data rates and large-scale connectivity with seamless coverage are the dominant themes of wireless communication system design. Moreover, beyond the accurate representation and successful transmission of information, the interpretation of its meaning is being paid more attention nowadays, which requires the development of approaches to semantic communication. The goal of this thesis is to contribute to the development of both conventional and semantic communication systems. Two advanced transmission technologies, namely, multiple access and relay-assisted communications are considered. By taking advantage of the special structures of digital communication signals, new approaches to multiple access and relay-assisted communications are developed. These designs enable high data rates, while simultaneously facilitating low-latency detection. Since there has been very limited analysis of the source coding of a vector source subject to semantic information constraints, we also study the rate distortion to trade-off for vector sources in both the case of centralized encoding and the case of distributed encoding, and we establish some insights that will guide the future development of semantic communication systems.

Examining the role of individual differences, especially variations in human motivation, in vigilance tasks will result in a better understanding of sustained semantic attention and processing, which has, to date, received limited study in the literature (see Fraulini, Hancock, Neigel, Claypoole, & Szalma, 2017; Epling, Russell, & Helton, 2016; Thomson et al., 2016). This present study seeks to understand how individual differences in intrinsic motivation affect performance in a short semantic vigilance task. Performance across two conditions (lure vs. standard condition) were compared in the present study of 79 undergraduate students at the University of Central Florida. The results indicated significant main effects of intrinsic motivation on pre- and post-task stress factors, workload, and performance measures, which included correct detections, false alarms, and response time. Sensitivity and response bias, which are indices of signal detection theory, were also examined in the present study. Intrinsic motivation influenced sensitivity, but not response bias, which was affected by period on watch. The theoretical and practical implications of this research are also discussed.

The theory of the Universal Grammar developed by Chomsky has been known for many years. The main idea behind the theory was that the processing of the language does not depend on the culture but it universal among all the languages. Further psycholinguistic studies developed the ideas about schematic comprehension of the language, giving rise to the idea of the "garden path effect". Research focused on the processing of the ambiguous sentences and found the tendency for readers to prefer interpretations of specific sentence areas as objects. The current study summarizes the ideas of psycholinguistic study and incorporates a novel language structure to study readers' syntactic preferences. In addition, conducting the study in Russian language accompanies previous research in other languages, also arguing in favor of the Universal Grammar model given the hypothesis was supported. It was hypothesized that readers would prefer the comparison of the two direct objects over the subjects, which would be reflected by faster reading times. Self-paced reading ask was administered to the participants in order to measure their reading times. The analysis found no significant differences in the reading times of the critical area, thus hypothesis was not supported. Possible explanations, limitations, and further directions are discussed.

Age differences in metamemory accuracy obtained for episodic memory – new information – compared to semantic memory – general knowledge information were compared in this study. Younger and older adults with no known cognitive impairments viewed pictures of famous faces for semantic memory and nonamous faces for episodic memory. Participants then viewed the faces again and had to provide the name for either semantic or episodic memory. After attempting recall for each face, participants made a Feeling-of-Knowing prediction about future recognition. Finally, each face was presented with the correct answer and three alternative answers. A gamma correlation was used to calculate prediction accuracy. Younger and older adults were equally accurate at predicting their recognition for semantic and episodic memory. The findings demonstrate that using the same materials and a within-subjects design, older adults do not show deficits in metamemory accuracy, even when predicting a type of memory that is typically impaired with age.

In today’s world, ontologies are being widely used for data integration tasks and solving information heterogeneity problems on the web because of their capability in providing explicit meaning to the information. The growing need to resolve the heterogeneities between different information systems within a domain of interest has led to the rapid development of individual ontologies by different organizations. These ontologies designed for a particular task could be a unique representation of their project needs. Thus, integrating distributed and heterogeneous ontologies by finding semantic correspondences between their concepts has become the key point to achieve interoperability among different representations. In this thesis, an advanced instance-based ontology matching algorithm has been proposed to enable data integration tasks in ocean sensor networks, whose data are highly heterogeneous in syntax, structure, and semantics. This provides a solution to the ontology mapping problem in such systems based on machine-learning methods and string-based methods.

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