The complexity and efficiency aspects of a distributed application protocol (e.g., replicated data access) are often intertwined with the application-specific communication requirements between protocol entities and the underlying primitives for message broadcasting. For instance, the choice between recovery by application from a mis-ordered message delivery versus providing message ordering property in the communication layer (CL) is based on tradeoffs between protocol complexity and efficiency. The paper systematically analyzes these tradeoffs with respect to message ordering and atomicity properties in broadcast communication. Enforcing these properties in the CL leads to uniform communication structure of applications; however, the CL incurs message and execution time overhead due to extensive communication state (e.g., message buffering). When these properties are not supported by CL but are required for an application, mechanisms to enforce it are built into the application protocol, thereby increasing complexity in the protocol structure. Detailed examples of applications are given to illustrate these tradeoffs. The analysis is useful in designing communication primitives and application protocols for distributed systems.
Gas-liquid annular flow is widely used in many industrial applications such as petroleum, chemical, and nuclear engineering. The feature parameters of liquid film in the annular flow are of great significance to understand the flow characteristics and measure the flow precisely. For the annular flow, the circumferential features of liquid film are more important than the axial features to acquire abundant flow structures and reveal the flow mechanism. In the paper, a measurement platform based on the laser-induced fluorescence (LIF) and virtual stereo vision sensor is presented. The virtual stereo vision sensor comprises a high-speed camera and two optical reflection sets, which can acquire the liquid film from two views simultaneously and reconstruct the features of liquid film. Image processing techniques are proceeded with to extract the feature parameters of liquid film; then the circumferential flow characteristic can be reconstructed by views transformation and fusion. The flow characteristic based on the thickness distribution is analysed. The experimental results show that the method is valid and effective, which can give a more detailed and accurate description for the liquid film in annular flows.
The session-based recommendation task is designed to predict the behavior of the current session at the next moment based on multiple anonymous sessions. Due to the lack of user information in the session, the traditional recommendation model cannot be used directly to model the interest of specific users. In this paper, a session recommendation model based on hypergraph neural networks and attention mechanism (HGNNA) is proposed. Firstly, the features of items are learned by constructing hypergraph neural networks, then the conversation information is aggregated by self-attention mechanism, and finally the information among similar sessions is aggregated by graph attention networks. The hypergraph neural networks can capture the correlation between items, the self-attention mechanism can show the interest of the current session, and the graph attention networks can find the interest pattern between similar sessions, so that the representation vector of the session includes the information of the items in the session, other items outside the session and other sessions. In the experiments on two datasets, Yoochoose1/4 and Diginetica, the recommendation effect of HGNNA is higher than that of other relevant methods, especially in the P@20, which is improved by 0.69 and 1.40 respectively.
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