<p>A complex network graphics may be composed of hundreds and thousands of objects, such as nodes and edges. Each object may hold a large number of attributes that might be difficult to explore in the network visualization. Therefore, many visualization tools and approaches have been developed to gain more information from the network graphics. In this paper, we introduce the concept of the Network Lens<em>, </em>a new widget that assists the users to deal with a complex network. The Network Lens is an interactive tool that combines data visualization to a magic lens. With the help of the Network Lens, users can display hidden information of the elements in the network graphics based on their interest. Moreover, the Network Lens supports a series of interactive functions that give the users flexible options to define their own lenses.</p>

Bystander programs aim to prevent personal violence, such as dating violence, sexual violence, sexual harassment, and stalking. They equip community members with skills to stop the violence before it happens by engaging in active bystander behaviors such as speaking up in potentially risky situations or supporting victims. Given that victimization and perpetration of personal violence, including co-occurrence, are common among youth, high schools have begun implementing bystander programs in recent years. This study examined the relationship between high school students’ experience of personal violence and their active bystander behaviors. Using the social identity approach as a theoretical foundation, this study hypothesized that polyvictims with two types of personal violence victimization would be more active as bystanders compared to those with no or one victimization experience. The study also hypothesized that polyperpetrators with two types of personal violence perpetration would be less active as bystanders compared to those with no or one perpetration experience. The study utilized a secondary dataset from a five-year study, Green Dot across the Bluegrass, which examined the effectiveness of the bystander program Green Dot in reducing rates of personal violence. Using network visualization techniques, commonly co-occurring violence types were identified. Cross-tabulation was used to examine the relationship between experience of co-occurring violence and individual characteristics, including sex, grade, sexual orientation, and exposure to parental partner violence. One-Way Analysis of Variance (ANOVA) was conducted to examine differences in active bystander behaviors based on victimization levels and on perpetration levels. One-Way Analysis of Covariance (ANCOVA) was also used to examine differences in active bystander behaviors based on victimization levels and perpetration levels after controlling for sex, rape myth acceptance, dating violence acceptance, and exposure to the bystander program. Findings revealed that polyvictimization and polyperpetration were both significantly associated with sex, grade, sexual attraction, and exposure to parental partner violence. Polyvictims showed significantly higher levels of active bystander behaviors than those with single or no victimization. Polyperpetrators also showed significantly higher levels of active bystander behaviors than students in other perpetration categories. Future research should include contextual variables such as level of injuries, intent of perpetration, and history of violence in order to more accurately distinguish victimization and perpetration. Suggestions for practice and policies include intervention in adult intimate partner violence to reduce impact on children. It is also recommended that bystander programs to be made relevant to students who are not exclusively heterosexual. Considering the potential presence of victims among participants, the program staff should be aware of impact of trauma and be prepared to provide support as needed. Finally, more rigorous investigation of the impact of bystander programs on youth who are victims as well as perpetrators is warranted.

We are besieged with information every day, our inboxes overflow with spam and our search queries return a great deal of irrelevant information. In most cases there is no malicious intent, just simply too much information. However, if we consider active malicious entities, the picture darkens. Denial of information (DoI) attacks assail the human through their computer system and manifest themselves as attacks that target the human's perceptual, cognitive and motor capabilities. By exploiting these capabilities, attackers reduce our ability to acquire and act upon desired information. Even if a traditional denial of service attack against a machine is not possible, the human utilizing the machine may still succumb to DoI attack. When successful, DoI attacks actively alter our decision making, often without our knowledge. In this dissertation, we address the problem of countering DoI attacks. We begin by presenting a taxonomy and framework of DoI attacks and countermeasures to add structure to the problem space. We then closely examine the use of information visualization as a countermeasure. Information visualization is a powerful technique that taps into the high bandwidth visual recognition capability of the human and is well suited to resist DoI attack. Unfortunately, most information visualization systems are designed without a clear emphasis on protecting the human from malicious activity. To address this issue we present a general framework for information visualization system security analysis. We then delve deeply into countering DoI in the network security domain using carefully crafted information visualization techniques to build a DoI attack resistant security visualization system. By creating such a system, we raise the bar on adversaries who now must cope with visualization enhanced humans in addition to traditional automated intrusion detection systems and text-based analysis tools. We conclude with a human-centric evaluation to demonstrate our systems effectiveness.

A complex network graphics may be composed of hundreds and thousands of objects, such as nodes and edges. Each object may hold a large number of attributes that might be difficult to explore in the network visualization. Therefore, many visualization tools and approaches have been developed to gain more information from the network graphics. In this paper, we introduce the concept of the Network Lens, a new widget that assists the users to deal with a complex network. The Network Lens is an interactive tool that combines data visualization to a magic lens. With the help of the Network Lens, users can display hidden information of the elements in the network graphics based on their interest. Moreover, the Network Lens supports a series of interactive functions that give the users flexible options to define their own lenses.

Background. In today’s competitive world, dealing with real-time streaming data is a difficult task to be achieved by many organizations. The importance of real time streaming data is rapidly increasing in all software industries by passing time. For quick growth of the companies, the data should be analysed immediately as data will be changing in fraction of second. The huge data will be generated every day and it will lead to problems such as overload of resources, Performance delays etc.., Which in turn will impact behaviour of the system. Finding the problem area in real time is difficult task to achieve as the data changes every second. Dealing with detection of bottlenecks and making decisions to handle the problem area, based on the real time data has been slow over the past years. It is also complicated due to time and effort required for storing and analysing. Organizations are not intended to wait for decision making information up to weeks or months. Organizations need to make an timely-accurate decisions by detecting problem area, in real time to improve their business support systems behaviour and performance. One of the better solutions is through data visualization as an approach. The visualizations are developed and evaluated by using task based approach. The data is collected using interviews and paper survey, to obtain the effective and efficient visualization in detecting bottlenecks. Objectives. The main objective is to find the most effective and efficient data visualization technique for real time streaming data to detect potential bottlenecks. Methods. In this research study, an action research is opted to answer the objectives. We have used interviews and paper survey to collect data in the terms of performance time, accuracy rate and user preference. Data analysis is performed using the Statistical tests and Narrative analysis method. Results. The final results obtained are the effective and efficient visualization techniques based on less performance time, higher accuracy rate and better user preference. Conclusions. An effective and efficient visualization technique for detection of bottlenecks is obtained for real time streaming data. Different categories of tasks has been used to obtain accurate results.

Proteins are dynamic and interconvert between different conformations to perform their biological functions. Simulation methodology drawing upon principles from classical mechanics - molecular dynamics (MD) simulation - can be used to simulate protein dynamics and reconstruct the conformational ensemble at a level of atomic detail that is inaccessible to experiment. We use the dynamic insight achieved through simulation to enhance our understanding of protein structures solved by X-ray crystallography. Protein X-ray structures provide the most important information for structural biology, yet they depict just a single snapshot of the solution ensemble, which is under the influence of the confined crystal medium. Thus, we ask a fundamental question - how well do static X-ray structures represent the dynamic solution state of a protein? To understand how the crystal environment affects both global and local protein conformational dynamics, we consider two model systems. We first examine the variation in global conformation observed in several solved X-ray structures of the λ Cro dimer by reconstructing the solution ensemble using the replica exchange enhanced sampling method, and show that one X-ray conformation is unstable in solution. Subsequent simulation of Cro in the crystal environment quantitatively assesses the strength of packing interfaces and reveals that mutation in the lattice affects the stability of crystal forms. We also evaluate the Cro models solved by nuclear magnetic resonance spectroscopy and demonstrate that they represent unstable solution states. In addition to our studies of the Cro dimer, we investigate the effect of crystal packing on side-chain conformational dynamics through solution and crystal MD simulation of the HIV microbicide Cyanovirin-N. We find that long, polar surface side-chains can undergo a strong reduction in conformational entropy upon incorporation into crystal contacts, which supports the application of surface engineering to facilitate protein crystallization. Finally, we outline a general framework for using network visualization to aid in the functional interpretation of conformational ensembles generated from MD simulation. Our results will enhance the understanding of X-ray data in establishing protein structure-function-dynamics relationships.

As the trend of successful network attacks continue to rise, better forms of intrusion, detection and prevention are needed. This thesis addresses network traffic visualization techniques that aid administrators in recognizing attacks. A view of port statistics and Intrusion Detection System (IDS) alerts has been developed. Each help to address issues with analyzing large datasets involving networks. Due to the amount of traffic as well as the range of possible port numbers and IP addresses, scaling techniques are necessary. A port-based overview of network activity produces an improved representation for detecting and responding to malicious activity. We have found that presenting an overview using stacked histograms of aggregate port activity, combined with the ability to drill-down for finer details allows small, yet important details to be noticed and investigated without being obscured by large, usual traffic. Another problem administrators face is the cumbersome amount of alarm data generated from IDS sensors. As a result, important details are often overlooked, and it is difficult to get an overall picture of what is occurring in the network by manually traversing textual alarm logs. We have designed a novel visualization to address this problem by showing alarm activity within a network. Alarm data is presented in an overview from which system administrators can get a general sense of network activity and easily detect anomalies. They additionally have the option of then zooming and drilling down for details. Based on our system administrator requirements study, this graphical layout addresses what system administrators need to see, is faster and easier than analyzing text logs, and uses visualization techniques to effectively scale and display the data. With this design, we have built a tool that effectively uses operational alarm log data generated on the Georgia Tech campus network. For both of these systems, we describe the input data, the system design, and examples. Finally, we summarize potential future work.

abstract: Online programming communities are widely used by programmers for troubleshooting or various problem solving tasks. Large and ever increasing volume of posts on these communities demands more efforts to read and comprehend thus making it harder to find relevant information. In my thesis; I designed and studied an alternate approach by using interactive network visualization to represent relevant search results for online programming discussion forums. I conducted user study to evaluate the effectiveness of this approach. Results show that users were able to identify relevant information more precisely via visual interface as compared to traditional list based approach. Network visualization demonstrated effective search-result navigation support to facilitate user’s tasks and improved query quality for successive queries. Subjective evaluation also showed that visualizing search results conveys more semantic information in efficient manner and makes searching more effective. / Dissertation/Thesis / Masters Thesis Computer Science 2015

Access to and understanding data plays an essential role in the increasingly digital world. Representation and analysis of relations between various data entities, i.e., graph and network structures in the data, is an important problem for various industries. In contrast to simple graphs that focus on edges with two endpoints only, a hypergraph provides a natural method to represent multi-way interactions with an arbitrary number of endpoints for each edge, and it can be a better alternative than a bipartite graph for comparable applications. However, traditional approaches for visually representing hypergraphs are purely static diagrams without support for interaction, which can be difficult to perceive and do not scale well with regard to the number of nodes and edges. They are not adequate for the representation and interactive exploration of large or dense hypergraph data sets found in real-world applications. The ISOVIS (Information and Software Visualisation) research group at Linnaeus University has previously introduced a novel radial visualization approach for undirected hypergraphs called Onion. The Onion tool focuses on solving the issues of edge clutter, overlaps, and edge crossings. However, certain open challenges and suggestions for improvements were identified for the respective implementation, and there is an opportunity to fill a gap in the hypergraph visualization research by building upon the original Onion approach study. In this thesis project, we implement the new version of the Onion approach based on the principles and challenges established previously. The contributions of this work include evidence regarding the effectiveness and efficiency of a hypergraph comparison technique, the usability of edge bundling in the context of hypergraph exploration tasks, and the scalability of the interactive visualization through an entirely new web-based version of the Onion approach. To obtain the respective results, the new implementation is applied for two case studies involving real-world data sets, and further validated through a user study with several participants. The results of this work can be helpful for researchers of network visualization and practitioners in need of approaches for representing and exploring data that can be modeled as hypergraphs.

Displaying the architecture of a software system is not a simple task. Showing all of the available information will unnecessarily complicate the view, while showing too little might render the view unhelpful. Furthermore, showing the dynamics of the operation of such a system is even more challenging. This thesis project describes the development of a graphical tool that can both display the configuration of an advanced authentication, authorization, and accounting (AAA) system and the messages passed between nodes in the system.  The solution described uses force-based graph layouts coupled with adaptive filters as well as vector-based rendering to deliver a view of the status of the system. Force-based layout spreads out the nodes in an adaptive fashion. The adaptive filters starts by showing what is most often the most relevant information, but can be configured by the user. Finally, the vector based rendering offers unlimited zoom into the individual nodes in the graph in order to display additional detailed information. Unified Modeling Language (UML) sequence charts are used to display the message flow inside the system (both between nodes and inside individual nodes). To validate the results of this thesis project each iteration of the design was evaluated through meetings with the staff at Aptilo Networks. These meetings provided feedback on the direction the project was taking as well as provided input (such as ideas for features to implement). The result of this thesis project shows a way to display the status of an AAA system with multiple properties displayed at the same time. It combines this with a view of the flow of messages and application of policies in the network via a dynamically generated UML sequence diagram. As a result human operators are able to see both the system’s architecture and the dynamics of its operation using the same user interface. This integrated view should enable more effective management of the AAA system and facilitate responding to problems and attacks. / Att visualisera arkitekturen av ett mjukvarusystem är inte lätt. Visas all tillgänglig information så blir vyn för komplicerad medan ifall för lite visas så blir vyn onödig. Att samtidigt visa dynamiken som uppstår när systemet arbetar är ytterligare en utmaning. Detta examensprojektet beskriver hur utvecklingen av ett grafiskt verktyg, som både kan visa konfigurationen av ett avancerat autentisering-, tillåtelse- och bokförings-system (AAA) och meddelanden som skickas mellan noder i systemet.&lt;p&gt; Lösningen använder en kraftriktad graflayout tillsammans med adaptiva filter och vektorbaserad rendering för att visa en vy av systemets status. De adaptiva filtren börjar med att visa den information som oftast är mest relevant men kan ställas in av användaren. Nyttjandet av vektorbaserad grafik tillhandahåller obegränsade möjligheter för användaren att zooma in på delar av grafen för att visa mer detaljerad information. UML sekvensdiagram används för att visa medelandeflödet inuti systemet (både mellan noder och inuti noder). För att utvärdera resultatet av examensprojektet blev varje iteration av designen utvärderad vid möten med personalen på Aptilo Networks. Dessa möten gav återkoppling på vilken rikting projektet tog samt input med t. ex. id´eer på nya egenskaper att lägga till. Resultatet av detta examensarbete visar ett sätt att visa statusen för ett AAA system med många av systemets egenskaper visade samtidigt. Det kombinerar detta med en vy av flödet av meddelanden och applikationpolicies i nätverket via ett dynamiskt genererat UML sekvensdiagram. Resultatet av detta är att mänskliga operatörer kan se både systemets arkitektur och dynamiken i hur det fungerar i samma gränssnitt. Detta gränssnitt bör möjliggöra mer effektiv hantering av AAA systemet och underlätta lösningar på både problem i systemet och attacker mot systemet.