Although a growing number of charities have used virtual reality (VR) technology for fundraising activities, with better results than ever before, little research has been undertaken on what factors make VR beneficial in supporting charitable giving. The primary goal of this study is to investigate the underlying mechanism of VR in supporting charitable giving, which extends the current literature on VR and donation behaviors. The findings of this study indicated that VR charitable appeals increase actual money donations when compared to the traditional two-dimensional (2D) format and that this effect is achieved through a serial mediating effect of vicarious experience and existential guilt. Findings also identify the need for stimulation as a boundary condition, indicating that those with a higher (vs. lower) need for stimulation were more (vs. less) affected by the mediating mechanism of VR charitable appeals on donations. This work contributes to our understanding of the relationship between VR technology and charitable giving, as well as to future research on VR and its prosocial applications.

In this letter, an edge detector using weighted directional Bhattacharyya coefficients (WDBCs) is proposed to improve the edge detection performance on real synthetic aperture radar (SAR) images. The Bhattacharyya coefficient (BC) is a similarity measure that considers the grayscale distribution of pixels around edges and gives a better description of textured and nonuniform regions than the ratio of averages (ROAs). However, in addition to the grayscale distribution, the spatial distribution of pixels around the edges also has a significant impact on the edge strength. To consider both grayscale and spatial distribution, the weighted histograms are computed by Gaussian-Gamma-shaped (GGS) bi-windows to obtain WDBCs in eight directions. Then the edge strength map (ESM) and edge direction map (EDM) are defined by WDBCs. The edge detector can be obtained after non-maximum suppression and hysteresis thresholding. Experimental results on real SAR images compared with five existing detectors show the effectiveness of the proposed detector.

This paper considers low-complexity transmit beamforming schemes for signal-to-interference-plus- noise ratio (SINR) balancing problem in the Gaussian multiple-input single-output multi-receiver wiretap channel (MISO-MRWC). The formulated max-min-fair problem are shown to be non-convex. To overcome the computational complexity, we develop the leakage-based and zero forcing (ZF) based beamforming algorithms for finding the local optimum transmit beamformers. Extensive simulation results illustrate that the proposed beamforming algorithms achieve low computational complexity without serious performance deterioration.

As a promising technique, cooperative relaying has attracted more and more attention from academia and industry recently. In this paper, we investigate the scheme of Decode-and-Forward Two-way Relaying (DF-TWR) relying on a cross-layer design, which combines adaptive Network-coded Modulation (NCM) at the physical layer and truncated Automatic Repeat reQuest (ARQ) at the data link layer. The relay node utilizes Network-Coded Quadrature amplitude modulation (NC-QAM) where NCM imposes only a modest signal-to-noise ratio (SNR) degradation on the single-link QAM performance. Additionally, we derive the achievable spectral efficiency in closed-form for transmission over Rayleigh fading channels. It is shown that this combination of adaptive NC-QAM and truncated ARQ substantially improves the system's throughput compared to the schemes operating without ARQ.

Advanced downlink (DL) decode-and-forward two-way relaying (DF-TWR) is developed for the sake of maximizing the attainable spectral efficiency. Network-coded phase-shift keying (NC-PSK) holds the potential of significantly increasing the data rate of the network, while adaptive modulation is a powerful technique of improving both the energy and spectral efficiency. Hence power-controlled adaptive NC-PSK has the potential of achieving performance enhancements over fading channels. Given this framework, based on the bit-error-ratio (BER) bounds developed, we derive the closed-form spectral efficiency for a continuous-rate, continuous-power adaptive NC-PSK scheme, where both the transmit power and the transmit rate are optimized subject to specific power- and BER- constraints. We then conceive and investigate a discrete-rate scheme relying on a pair of solutions proposed for maximizing the throughput of the network. Our simulation results reveal that the proposed schemes are capable of achieving a higher spectral efficiency than their fixed-power counterparts.

Network coded modulation (NCM) holds the promise of significantly improving the efficiency of two-way wireless relaying. In this contribution, we propose near instantaneously adaptive variable-rate, variable-power QAM/PSK for NC-aided decode-and-forward two-way relaying (DF-TWR) to maximize the average throughput. The proposed scheme is optimized subject to both average-power and bit-error-ratio (BER) constraints. Based on the BER bounds, we investigate a discrete-rate adaptation scheme, relying on a pair of solutions proposed for maximizing the spectral efficiency of the network. We then derive a closed-form solution based power adaptation policy for a continuous-rate scheme and quantify the signal-to-noise ratio (SNR) loss imposed by NC-QAM. Our simulation results demonstrate that the proposed discrete adaptive NC-QAM/PSK schemes are capable of attaining a higher spectral efficiency than their fixed-power counterparts.

Active queue management (AQM) mechanism plays an important role in network congestion control. In this paper, we propose an effective AQM algorithm, named adaptive real queue control (ARQC). In particular, an explicit congestion indicator, virtual regulating time, is designed to detect network congestion. Then by analyzing the queuing system on routers, we present the guideline to calculate the dropping/marking probability. Also we provide the tuning rules for the control parameters based on the discrete model of TCP dynamics. Simulation results demonstrate that ARQC outperforms the other AQM schemes in terms of stability, responsiveness and robustness in dynamic networks. Moreover, it achieves smaller queue length jitter, less packet loss and better trade-off between delay and link utilization.

This paper proposes a new multi-objective optimization algorithm - Pareto Mind Evolutionary Computation (Pareto-MEC), which introduces the theory of Pareto into MEC for the multi-objective optimization. In the reference algorithms of Rand, VEGA, NSGA and SPEA, SPEA has the superior performance. Pareto-MEC is compared with these reference algorithms on a suit of four different test problems: convexity, non-convexity, discreteness and non-uniformity. On all test problems, Pareto-MEC outperforms Rand, VEGA and NSGA; it is as good as SPEA on the first three test problems; it beats SPEA on the last test problem. Different from the reference algorithms that use the pre-specified generation number as their terminations, Pareto-MEC has an objective termination criterion that can ensure the quality of solutions and the computational efficiency.