The initial 802.11 standard included one method of encryption, which was called “Wired Equivalence Privacy”. All the 802 standards deal with the data link layer and physical layer of the OSI reference model while Part 11 defines all the specifications for wireless networks. In 1988, the IEEE organized a committee to develop the 802.11 standard. Section IV presents the limitations of this work and Section V addresses the conclusion of this paper. Section III compares all the papers related to each research questions we raised in Section II and analyze the results to draw further conclusions. This paper is organized as follow: Section II provides detailed methodology adopted to perform the systematic literature review.

The goal of this work is to summarize and compare existing visual analytics techniques on spatio-temporal data. This paper provides a systematic literature review about visual analytics on spatial-temporal data.

By analyzing these behaviors, users can draw several conclusions like most people go to work at 8 A.M., or there is a music festival in Riverdale Part. If these trends show up for only several times (a large number of taxis drive to Riverdale Park this weekend), they are abnormal behaviors. If these trends show up regularly (most taxis drive from suburb to downtown in the morning), they are normal behaviors. By visualizing this data set on a map with a timeline, significant movement trends can be found easily by users. It is impossible to detect useful patterns directly from the data, but a visual analytics system can make it. Each of them contains a taxi ID, a GPS location, a time stamp, the speed and the occupancy status. For example, there are a huge number of trajectory records for Toronto taxis recorded every 20 seconds. Spatiotemporal analysis focuses on detecting how both normal and abnormal behaviors change geographically as well as the interaction with temporal processes. There is a large amount of abnormal data observed globally. As shown in its name, space and time are two most important factors of spatio-temporal data. It consists of geographic, temporal (time) and attributive components. The abundance of data category also indicates the broad range of application domains.Īmong these data types, spatio-temporal data are always enormous and accessible such as daily trajectories of all the taxis in Toronto. There are different types of data that have been visualized including text, transaction, spatio-temporal data, network flow data, social network and so on. The goal of visual analysis is to synthesize information and find significant patterns related to an issue from artistic visualizations of massive, dynamic and ambiguous data. Since Big Data is one of the most popular topics nowadays, visual analytics is becoming a worldwide research area with plenty applications to help decision-making and sense-making.Ĭompared to data mining or machine learning which is mostly developed with science and technology, visual analytics is more like a combination of art and science. After that, a huge amount of work related to visual analytics has been done. In the early 2000s, Jim Thomas organized a team of top scientists to formally define a new research area, visual analytics, which was first defined as the science of analytical reasoning facilitated by interactive visual interfaces in 2005. Tumor positions and reaction time were recorded in order to measure users’ performance. 2 users participated in the user study, and either of them completed 50 tasks for 3 times. We construct several ellipsoid targets of random positions within the mannequin head, and ask users to touch them with given surgical tool as quickly as possible. In this paper, we implement a simple tumor targeting task using Unity with the Vuforia augmented reality toolkit. However, to quantify and distinguish different levels of surgical skill, specific metrics should be used to evaluate surgeons’ performance in terms of speed and accuracy. Among different approaches of implementing the simulator, augmented reality technologies provide an effective simulation platform because the surgical environment is combined with users’ reality, which offers them similar experience as real surgical operations. Surgical simulation is becoming more practical for surgeons since these simulators help them to practice specific procedures before they carry on real surgeries, which can improve surgical proficiency and provide a zero-risk learning environment.

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