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Due to the growing number of users, social network analysis faces several challenges, including evolution, community detection, and link prediction. Among these issues, link prediction appears to receive the most attention. It is difficult to predict when a new connection might be possible within the destiny. Presently, link prediction techniques c...
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Context 1
... E = {e1,e2,e3,e4,e5} e1 = {A,B},e2 = {B,C},e3 = {C,D},e4 = {A,C},e5 = {B,D} It is possible to research the network structure depicted in Fig. ...
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... simultaneously. The system of connection forecast technique is created using data from the hub and the organization's geography. Hubs are used to describe information, and connections are used to describe connections. Each hub in the organization model can be represented as a vector. Information is a modification of tables [12]. The lines in Fig. 1 exhibit stems, while the sections demonstrate the strengths and capabilities. If the characteristics of hubs and some patterns of connections are known, it is possible to forecast some additional connections that have not yet occurred ...
Citations
... In addition to optically-controlled PCM, these endurance management techniques could also be applied to optically-controlled PCs. It can be used in the Internet of Things (IoT) too [72][73][74][75][76]. ...
Unlike Dynamic Random Access Memory (DRAM), Phase Change Memory (PCM) offers higher density, longer data retention, and improved scalability because of its non-volatility and low leakage power. However, Electrically-Addressable PCM (EPCM) has a higher dynamic power and long latency than DRAM. To address these issues, scientists have developed Optically-Addressable PCM (OPCM), which uses 5-level cells instead of 2-level cells in EPCM. A silicon photonic link allows optical signals to reach OPCM cells at a high speed. Hence, OPCM can achieve a higher density while maintaining better performance at multi-level cells and consuming less power per access. However, OPCM is not suitable for general use since the photonic links do not provide an electrical interface to the processor. The aim of this paper is to present a hybrid OPCM architecture based on the use of novel multi-bank clusters with distinctive properties. Electrical-Optical-Electrical conversion (EOE) allows OPCM cells to be randomly accessed by using DRAM-like circuitry. The proposed hybrid design with multi-core processing and OPCM achieves a 2.13x speedup over previous approaches while consuming less Central Processing Unit (CPU) power. It is important to note that the proposed design offers 97 units fewer power-consistent bits than EPCM. In addition, the proposed architecture provides comparable performance and power to DDR4, as well as improved bandwidth density, space efficiency, and versatility. The Gem5 simulator was used to evaluate the design. Based on the outcomes of the analysis, the proposed architecture offers 2.08x and 2.14x better evaluations and density performance than EPCM. Furthermore, the execution time has been reduced by 2.13x, the analysis time by 1.23x, and the composition time by 4.60%.
The container shipping network has evolved with the development of trade, but the mechanism of its evolution is still not well studied. Link prediction model is one of the main methods used to study the network evolution. The classic indicators of the link prediction model only consider the structural characteristics of the network, but there are also real factors that can influence the evolution of the network. Therefore, this paper considers the structural characteristics of the network as an endogenous index, which includes common neighbors, Adamic–Adar, resource allocation, and so forth. Considering the factors that may affect the link between the ports, such as sailing distance, operation, economy, and political factors, this paper first develops different attractiveness models and determines an optimal attractiveness model in case analysis. After that, this paper proposes a composite index that combines endogenous and attractiveness indices. Taking the Maritime Silk Road (MSR) shipping network as an example, an optimal attractiveness index and then an optimal composite index are determined. It was found that the prediction accuracy under the composite index is improved compared with single indices, which confirms the effectiveness and superiority of the proposed index. Finally, from the perspective of the overall network, this paper discusses the possible future routes of the shipping network with the aim of providing a reference for the improvement of connectivity of the shipping network and planning new routes for shipping companies.
