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With the development and evaluation of information technology, virtual reality technology provides opportunities to offer an immersive and interactive experience for supplementing traditional classroom lecture and creating innovative online learning in education curricula and professional training. Given that the arena of 3D entertainment-oriented virtual worlds is creative and quickly evolving, applying a theory-based motivational model to examine the properties of virtual world environments in the context of education remains relatively unexplored territory. Thus, the present study applies the research frameworks of Self-Determination Theory (SDT) and hedonic theory to an understanding of how 3D virtual reality technology contexts satisfy or obstruct psychological needs and thus foster or undermine sustained engagement, affecting behavioral intentions. This study extends existing literature in the field by showing that psychological needs and hedonic experience are important components in understanding virtual reality technology and human interaction. The findings are important in explaining the value of 3D virtual reality technology in educational applications that contribute to the overall enhancement of the learner's motivation and learning experience.

Drawing from environmental psychology and consumer well-being perspectives, this study leverages the theoretical mechanisms underlying the concept of restorative environments to develop and test a model based on Kaplan and Kaplan's (1989) Attention Restoration Theory framework to examine the restorative potentials of wellness tourism settings. A total of 357 valid questionnaires were collected. The results show that the restorative environment is an important aspect of the wellness experience, contributing to positive emotions and life satisfaction as well as determining an individual's loyalty and intention to revisit. Multi-group analysis was applied to further examine the moderating effect. This research provided a theoretically and empirically consistent explanation for the theoretical mechanisms of ART underlying the concepts of restorative experience, tourist well-being, and loyalty, the manifestation of which in the wellness tourism context extrapolates the importance of restorative environments for well-being. [ABSTRACT FROM AUTHOR]

Streaming codes take a string of source symbols as input and output a string of coded symbols in real time, which eliminate the queueing delay of traditional block codes and are thus especially appealing for delay sensitive applications. Existing works on streaming code performance either focused on the asymptotic error-exponent analyses, or on the optimal code construction under deterministic adversarial channel models. In contrast, this work analyzes the exact error probability of random linear streaming codes (RLSCs) in the large field size regime over the stochastic i.i.d. symbol erasure channel model. A closed-form expression of the error probability of large-field-size RLSCs is derived under, simultaneously, the finite memory length and decoding deadline constraints. The result is then used to examine the intricate tradeoff between memory length (complexity), decoding deadline (delay), code rate (throughput), and error probability (reliability). Numerical evaluation shows that under the same code rate and error probability requirements, the end-to-end delay of RLSCs is 40–48% of that of the optimal block codes (i.e., MDS codes). This implies that switching from block codes to streaming codes not only eliminates the queueing delay completely (which accounts for the initial 50% of the delay reduction) but also improves the reliability (which accounts for the additional 2–10% delay reduction). [ABSTRACT FROM AUTHOR]

The two-user Gaussian interference channel (G-IC) is revisited, with a particular focus on practically amenable discrete input signalling and treating interference as noise (TIN) receivers. The corresponding deterministic interference channel (D-IC) is first investigated and coding schemes that can achieve the entire capacity region of the D-IC under TIN are proposed. These schemes are then systematically translated into multi-layer superposition coding schemes based on purely discrete inputs for the real-valued G-IC. Our analysis shows that the proposed scheme is able to achieve the entire capacity region to within a constant gap for all channel parameters. To the best of our knowledge, this is the first constant-gap result under purely discrete signalling and TIN for the entire capacity region and all the interference regimes. Furthermore, the approach is extended to obtain coding schemes based on discrete inputs for the complex-valued G-IC. For such a scenario, the minimum distance and the achievable rate of the proposed scheme under TIN are analyzed, which takes into account the effects of random phase rotations introduced by the channels. Simulation results show that our scheme is capable of approaching the capacity region of the complex-valued G-IC and significantly outperforms Gaussian signalling with TIN in various interference regimes. [ABSTRACT FROM AUTHOR]

The problem of coding for informed receivers (IR) is considered, where a transmitter multicasts a bunch of messages to its associated receivers, each of which already has a subset of messages as side information. Which receiver has what side information is unknown to the transmitter. A family of polar codes for IR was proposed for binary-input channels in (Huang and Shieh, 2018), which was shown to provide excellent side information gain regardless of side information configuration and content. A trial extension of this scheme to high-order modulations, however, was unsatisfactory. In this paper, two families of systematic polar coded modulations for IR are proposed. In the first family, by building a connection between the message bits and modulated symbols under systematic polar codes, we leverage the bit assignments and labeling techniques such that receiver side information can be directly translated to a minimum distance gain. In the second family, a permutation operation is added before modulation such that the message bits can be properly reordered to further advance and balance the gains among different side information configurations. Simulations show that the proposed schemes provide large and balanced side information gains and significantly outperform the system directly adapted from (Huang and Shieh, 2018) onto high-order modulations. [ABSTRACT FROM AUTHOR]

The Byzantine distributed quickest change detection (BDQCD) is studied, where a fusion center monitors the occurrence of an abrupt event through a bunch of distributed sensors that may be compromised. We first consider the binary hypothesis case where there is only one post-change hypothesis and prove a novel converse to the first-order asymptotic detection delay in the large mean time to a false alarm regime. This converse is tight in that it coincides with the currently best achievability shown by Fellouris et al.; hence, the optimal asymptotic performance of binary BDQCD is characterized. An important implication of this result is that, even with compromised sensors, a 1-bit link between each sensor and the fusion center suffices to achieve asymptotic optimality. To accommodate multiple post-change hypotheses, we then formulate the multi-hypothesis BDQCD problem and again investigate the optimal first-order performance under different bandwidth constraints. A converse is first obtained by extending our converse from binary to multi-hypothesis BDQCD. Two families of stopping rules, namely the simultaneous d-th alarm and the multi-shot d-th alarm, are then proposed. Under sufficient link bandwidth, the simultaneous d-th alarm, with d being set to the number of honest sensors, can achieve the asymptotic performance that coincides with the derived converse bound; hence, the asymptotically optimal performance of multi-hypothesis BDQCD is again characterized. Moreover, although being shown to be asymptotically optimal only for some special cases, the multi-shot d-th alarm is much more bandwidth-efficient and energy-efficient than the simultaneous d-th alarm. Built upon the above success in characterizing the asymptotic optimality of the BDQCD, a corresponding leader-follower Stackelberg game is formulated and its solution is found. [ABSTRACT FROM AUTHOR]

In this paper, the problem of using uncoordinated multiple access (UMA) to serve a massive amount of heterogeneous users is investigated. Leveraging the heterogeneity, we propose a novel UMA protocol, called iterative collision resolution for slotted ALOHA (IRSA) with non-orthogonal multiple access (NOMA), to improve the conventional IRSA. In addition to the inter-slot successive interference cancellation (SIC) technique used in existing IRSA-based schemes, the proposed protocol further employs the intra-slot SIC technique that enables collision resolution for certain configurations of collided packets. A novel multi-dimensional density evolution is then proposed to analyze and to optimize the proposed protocol. Simulation results show that the proposed IRSA with NOMA protocol can efficiently exploit the heterogeneity among users and the multi-dimensional density evolution can accurately predict the throughput performance. Last, an extension of the proposed IRSA with NOMA protocol to the frame-asynchronous setting is investigated, where a boundary effect similar to that in spatially-coupled low-density parity check codes can be observed to bootstrap the decoding process. [ABSTRACT FROM AUTHOR]

Caching is a powerful technique that reduces the peak traffic loading by pre-storing popular contents in caching helpers during off-peak hours. In this work, the problem of probabilistic caching is revisited, in which users are allowed to request multiple contents sequentially. A novel algorithm based on the method of Lagrange multipliers is proposed to produce a policy that guarantees to yield a locally maximal content delivery success probability (CDSP) of the most demanding user, who requests the largest number of consecutive contents. Due to the non-convex nature of the problem, this algorithm may be trapped into an insignificant local maximum. We further propose an enhanced version of the algorithm based on the idea of simulated annealing, which enables the algorithm to statistically escape from a local maximum. Simulation results show that the proposed enhanced algorithm can attain a 45% CDSP improvement over the state-of-the-art when hundreds of contents are involved, and is significantly less sensitive to initial values. Moreover, to increase the overall system throughput, we propose an alternative metric of maximizing the weighted CDSP, instead of considering only the CDSP of the most demanding user. For this new metric, an algorithm adapted from the proposed algorithm is introduced, for which similar conclusions can be drawn. [ABSTRACT FROM AUTHOR]