Background Information technology has shifted paper-based documentation in the health care sector into a digital form, in which patient information is transferred electronically from one place to another. However, there remain challenges and issues to resolve in this domain owing to the lack of proper standards, the growth of new technologies (mobile devices, tablets, ubiquitous computing), and health care providers who are reluctant to share patient information. Therefore, a solid systematic literature review was performed to understand the use of this new technology in the health care sector. To the best of our knowledge, there is a lack of comprehensive systematic literature reviews that focus on Fast Health Interoperability Resources (FHIR)-based electronic health records (EHRs). In addition, FHIR is the latest standard, which is in an infancy stage of development. Therefore, this is a hot research topic with great potential for further research in this domain. Objective The main aim of this study was to explore and perform a systematic review of the literature related to FHIR, including the challenges, implementation, opportunities, and future FHIR applications. Methods In January 2020, we searched articles published from January 2012 to December 2019 via all major digital databases in the field of computer science and health care, including ACM, IEEE Explorer, Springer, Google Scholar, PubMed, and ScienceDirect. We identified 8181 scientific articles published in this field, 80 of which met our inclusion criteria for further consideration. Results The selected 80 scientific articles were reviewed systematically, and we identified open questions, challenges, implementation models, used resources, beneficiary applications, data migration approaches, and goals of FHIR. Conclusions The literature analysis performed in this systematic review highlights the important role of FHIR in the health care domain in the near future.

Feature selection (FS) is one of the important tasks of data preprocessing in data analytics. The data with a large number of features will affect the computational complexity, increase a huge amount of resource usage and time consumption for data analytics. The objective of this study is to analyze relevant and significant features of huge network traffic to be used to improve the accuracy of traffic anomaly detection and to decrease its execution time. Information Gain is the most feature selection technique used in Intrusion Detection System (IDS) research. This study uses Information Gain, ranking and grouping the features according to the minimum weight values to select relevant and significant features, and then implements Random Forest (RF), Bayes Net (BN), Random Tree (RT), Naive Bayes (NB) and J48 classifier algorithms in experiments on CICIDS-2017 dataset. The experiment results show that the number of relevant and significant features yielded by Information Gain affects significantly the improvement of detection accuracy and execution time. Specifically, the Random Forest algorithm has the highest accuracy of 99.86% using the relevant selected features of 22, whereas the J48 classifier algorithm provides an accuracy of 99.87% using 52 relevant selected features with longer execution time.

To accurately rank various web services can be a very challenging task depending on the evaluation criteria used, however, it can play an important role in performing a better selection of web services afterward. This paper proposes an approach to evaluate trust prediction and confusion matrix to rank web services from throughput and response time. AdaBoostM1 and J48 classifiers are used as binary classifiers on a benchmark web services dataset. The trust score (TS) measuring method is proposed by using the confusion matrix to determine trust scores of all web services. Trust prediction is calculated using 5-Fold, 10-Fold, and 15-Fold cross-validation methods. The reported results showed that the web service 1 (WS1) was most trusted with (48.5294%) TS value, and web service 2 (WS2) was least trusted with (24.0196%) TS value by users. Correct prediction of trusted and untrusted users in web services invocation has improved the overall selection process in a pool of similar web services. Kappa statistics values are used for the evaluation of the proposed approach and for performance comparison of the two above-mentioned classifiers.

Fast and accurate distance measurement is crucial for target tracking and node localization in Wireless Sensor Networks. For short-range Underwater Acoustic Sensor Networks (UASNs), received signal strength (RSS) can give distance between acoustic devices. An extensive study on the application of the Lambert W function over RSS for distance estimation in short-range UASNs shows that it can be done accurately in as few as 4 iterations. The method is mathematically derived in this paper and the accuracy verified with Matlab simulation.

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The characteristics of mobile ad hoc networks (MANETs) such as dynamic changing topology, lack of centralized management, and the vulnerability of links, have made MANETs security a real concern. It is notable that security in this area is still a challenging issue. Without having a trusted public authority, designing suitable security for this type of networking is troublesome. One of the important issues in security mechanisms which is based on RSA algorithms is the support of key-management infrastructure based on the concept of a certificate authority (CA). In this paper, we have employed the Cluster Based Routing Protocol (CBRP) as a Routing layer protocol to use unique features of the Cluster Based MANETs and to avoid traffic flooding. CBRP is a robust/scalable routing protocol for medium and large MANETs. We have also employed the cross-layering technique to reduce the number of exchanging packets and increase the speed of the network. In addition, we have introduced a new security key management mechanism based on the CA distribution in MANETs. We introduced a distributed CA mechanism based on cluster-based architecture to create a secure network that is highly adapted to the characteristics of ad hoc networks. Our experiment showed that the proposed protocol does not generate significant overhead in the network. The average energy consumption and end-to-end delay in this protocol are less than the Authentication Protocol Based on CBRP (APBC).