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An adaptive multicast scheme is proposed to overcome the spectral inefficiency problem of OFDMA (orthogonal frequency-division multiple access)-based multicast networks in the presence of high link quality differences among multicast users. The proposed scheme divides a multicast group into smaller sub-groups and subcarriers are allocated to maximise the aggregate data rate. Having smaller multicast groups allows multiuser diversity to be exploited more efficiently. Simulation results show that the proposed scheme can achieve nearoptimal performance whilst outperforming the conventional unicast and multicast schemes.Introduction: Recently, orthogonal frequency-division multiple access (OFDMA) has been widely studied for multicast systems owing to its great flexibility in spectrum management among multicast users [1][2][3]. In OFDMA-based multicast systems, provisioning of high-quality multimedia services to large numbers of subscribers, possibly located over a vast geographical area, requires an efficient multicast scheme. Since users belonging to the same multicast group are distributed at different locations, they experience different fading and path losses in the time-varying wireless channel. This presents a challenge to providing satisfactory multicast services to all users. The attainable data rate of each multicast stream is usually restricted by the data rate of the user with the worst channel condition. This results in poor efficiency when most users except a few are in good channel conditions and capable of delivering high rate transmissions. The multicast schemes studied in [1-3] have low system resource utilisation rates because they use conservative data rates to assure reliable multicast transmissions.This Letter addresses the aforementioned inefficiency problem of multicast communications in the presence of high link quality differences among users within a multicast group. Instead of transmitting the same copy of data to a multicast group at a very low bit rate via a single transmission, it could be more desirable to transmit multiple copies of the same data to different smaller sub-groups at higher rates because having smaller multicast sub-groups allows multiuser diversity to be exploited more efficiently. Therefore, we propose an adaptive multicast scheme which partitions a multicast group into smaller sub-groups and subcarriers are allocated to maximise the aggregate data rate (ADR). It is shown that, with the same number of subcarriers and available transmission power, the ADR can be increased considerably by using the proposed scheme over the conventional unicast scheme (CUS) and the conventional multicast scheme (CMS) [1].

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Optical strain is an extension of optical flow that is capable of quantifying subtle changes on faces and representing the minute facial motion intensities at the pixel level. This is computationally essential for the relatively new field of spontaneous micro-expression, where subtle expressions can be technically challenging to pinpoint. In this paper, we present a novel method for detecting and recognizing micro-expressions by utilizing facial optical strain magnitudes to construct optical strain features and optical strain weighted features. The two sets of features are then concatenated to form the resultant feature histogram. Experiments were performed on the CASME II and SMIC databases. We demonstrate on both databases, the usefulness of optical strain information and more importantly, that our best approaches are able to outperform the original baseline results for both detection and recognition tasks. A comparison of the proposed method with other existing spatio-temporal feature extraction approaches is also presented.

In the current work, the fracture toughness of sand-particle-and wood-flakereinforced polyester composites was studied under a linear elastic fracture mechanics approach. The effects of the particulate volume fraction (0-60 vol %) were studied. Scanning electron microscopy was used to observe the damage features on the composite surface. Results showed that sand-particle-and fine-wood-flake-reinforced polymer composites exhibited better results at 40 vol % than at other particulate volume fractions. Meanwhile, coarse-wood-flake-reinforced polymer composites showed higher properties at 30 vol % than at other particulate volume fractions. Observation of the composite surface after tests showed that sand particles have poor interfacial adhesion compared with wood flakes.

One of the significant benefits of smart grid as compared to conventional power grid is the capability to collect fine-grained data from each smart meter remotely, thereby enabling utility provider to balance load effectively and offer time-adaptive pricing schemes. Nevertheless, the ability to read fine-granular measurements constitutes a serious privacy threat to the consumers. Therefore, it is crucial to consider the privacy issues in smart grid in order to preserve consumers' privacy and protect data integrity. In this paper, we propose a PrivacyPreserving and Cheat-Resilient (PPCR) electricity consumption reporting scheme for smart grid communication. PPCR adopts incremental hash function to conceal consumers' energy usage data from unauthorized parties, as well as the utility companies. The proposed scheme enables utility provider to perform data integrity check without disrupting smart grid services such as load management and billing. Security analysis is conducted to demonstrate that PPCR withstands malicious operations, preserves consumers' privacy and is robust to adversaries' cheating and smart meters malfunction.

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