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Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.

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Wireless LAN networks are considered to be widely used and efficient infrastructure used in different domains of communication. In this paper, we worked on Network Intrusion Detection System (NIDS) to prevent intruder's activities by using snooping agents and honeypot on the network. The idea behind using snooping agents and honeypot is to provide network management in term of monitoring. Honey pot is placed just after the Firewall and intrusion system have strongly coupled synchronize with snooping agents Monitoring is considered at packet level and pattern level of the traffic. Simulation filtered and monitor traffic for highlight the intrusion in the network. Further attack sequence has been created and have shown the effects of attack sequence on scenario which have both honey pot and snoop agent with different network performance parameters like throughput, network load, queuing delay, retransmission attempt and packet. The simulation scenario shows the impact of attack on the network performance.

Wireless Body Area Network in recent years has received significant attention, due to their market potential to reduce the healthcare cost as well as load of medical professionals, resulting in higher efficiency. This paper addresses the available wireless body area network prototypes and the issues related to hardware implementations, software and wireless protocols and how smart phones can be used as full featured portable computer in providing healthcare services. These systems are comprised of various types of small physiological sensors ie, ECG, SpO2 attached to the human body for measuring the physiological parameters and transmit them to remote devices.