Today, e-commerce has occupied a large volume of economic exchanges. It is known as one of the most effective business practices. Predicted trust which means trusting an anonymous user is important in online communities. In this paper, the trust was predicted by combining two methods of Multiplex network and community detection. In modeling the network in terms of a Multiplex network, the relationships between users were different in each layer and each user had a rank in each layer. Then, the ratings of two layers including the weight of each layer were aggregated and four effective features of the Trust were achieved. Then, the network was divided into overlapping groups via community detection’ algorithms, each group representative was considered as the community centers and other features were extracted through similar comments. At the end, 48J decision tree algorithm was used to advance the work. The proposed method was assessed on Epinions data set and accuracy of trust was 96%.

We address the throughput maximization problem for downlink transmission in DF-relay-assisted cognitive radio Networks (CRNs) based on simultaneous wireless information and power transfer (SWIPT) capability. In this envisioned network, multiple-input multiple-output (MIMO) relay and secondary user (SU) equipment are designed to handle both radio frequency (RF) signal energy harvesting and SWIPT functional tasks. Additionally, the cognitive base station (CBS) communicates with the SU only via the MIMO relay. Based on the considered network model, several combined constraints of the main problem complicate the solution. Therefore, in this paper, we apply heuristic guidelines within the convex optimization framework to handle this complexity. First, consider the problem of maximizing throughput on both sides of the relay separately. Second, each side progresses to solve the complex problem optimally by adopting strategies for solving sub-problems. Finally, these optimal solutions are synthesized by proposing a heuristic iterative power allocation algorithm that satisfies the combinatorial constraints with short convergence times. The performance of the optimal proposed algorithm (OPA) is evaluated against benchmark algorithms via numerical results on optimality, convergence time, constraints’ compliance, and imperfect channel state information (CSI) on the CBS-PU link.

Different types of contact, including contact between node pairs, any-contact of nodes, and contacts of the entire network, are used to characterize social relations in mobile social Networks. Different modes of routing, from the point of view of message delivery semantics, encompass unicasting, multicasting, any-casting, and broadcasting. Studies have shown that using probability distribution functions of contact data, which is mainly assumed to be homogeneous for nodes, improves the performance of these Networks. However, there exists an important challenge in studies on distributions. A lot of works apply the distribution of one type of contact to other types. Hence in routing applications, it causes to use of the distribution of one type of contact for any mode of routing. This study provides a complete solution to model each type of homogeneous contact data distribution and to use them in different modes of routing. We propose a routing algorithm that uses this new model. Results show that our solution improves the average latency of comparing methods Epidemic, TCCB, and DR about 3.5-times, 30%, and 45%, respectively. It achieves a delivery rate of about 5% and 6%, and average latency about 6% and 8% better than that of DR and TCCB, respectively.

Nowadays, most of information systems can be modeled as multilayer Networks which each layer includes some nodes connected to each other by different types of links. Information diffusion in Networks is the subject that researchers considered recently and they analyzed and modeled this process type in the Networks. Although most of researches in this field have focused on single layer Networks, but in the real world, because of the complexity of relations, most systems must be modeled as multilayer Networks. In the previous works, there are much simplification in problem space, like projection all layer into one layer or negligence the mutual effect of nodes in different layers. So a new effective model for analyzing diffusion in multilayer Networks is needed. This method is focused on predicting diffusion in multilayer Networks, with considering mutual effect of different layers on each other. The most important specification of this proposed method, is the ability to specify power of all layers and measuring this power regardless node's similarity or difference. In fact, this model can determine the diffusion power of each type of nodes. The model is applied on two real bibliographic information Networks, and experimentally demonstrated the effectiveness of this model compared with other diffusion models.

Background and Objectives: PCR is a sensitive assay and could be used as an accurate diagnostic method for detecting various types of microorganisms’ genome in low concentration in biological specimens. The demand for sensitive, rapid, safe and easy detection of PCR products has led researchers to a combination of this method with ELISA. Materials and Methods: Conserved sequences were selected for design of primers. Samples were tested by ELISA (for detection of specific HIV and HCV proteins) and real- time PCR for detection of specific nucleic acid and viral genome respectively. Viral genome was extracted and reverse transcription was performed with M-Mulv and the cDNA kept at -80°C. The PCR products were labeled by DIG-dUTP. Diluted PCR products were analyzed with both electrophoresis and ELISA methods.Results: Thirty-five samples were tested with the PCR-ELISA method. False positive or negative reactions were not observed. ELISA results of diluted products were compared with results obtained by electrophoresis. In gel electrophoresis, dilution of 1/10 was positive, but in ELISA, optical density of 1/100 dilution was much more than the cut-off value. Conclusion: Detection limits for gel electrophoresis as well as ELISA have been evaluated. It was shown that the PCR-ELISA method is ten times more sensitive than conventional PCR.