A Study of Basic 3D Visualization Architecture for Network Operation and Management Tools

Recently, network operation tools using 3D visualization technologies have become more and more important. Generally, 3D visualized network operation tools are useful for computer network management or operation. However, a development of 3D visualized network operation tools requires advanced technical skills and highly cost. On the other hand, 3D computer graphics technologies become more familiar in recent years because of that computer hardwares and softwares are rapidly growing and obtain high performance. In this research, we have developed basic architecture of 3D visualization system for network operation and management tools, by using an open source 3DCG software ``Blender'' and a programming language ``Python``. In this paper, we explain details, results of evaluation and efficiency of the proposed architecture

Wet Reagent Profile Sensor Visualization Tool

Indiana University Purdue University IndianapolisThe Wet Reagent Profile Sensor is a system that Roche Diabetes Care Indy uses in its diabetes test strip manufacturing process. The current system they are using involves a laser sensor that projects onto a wet reagent material after it is coated onto a substrate. The machine that applies the reagent uses averages of 800 measurement points taken by the laser sensor to determine whether or not the reagent is within acceptable limits. If the reagent applied to a given section of the material is not within acceptable limits, then that section is marked for rejection and later taken out of the roll. The current system does not store the data that is collected, display it in an easily accessible manner, nor provide direct access to the 800-point profiles. No variable option currently exists for the data collection rate and the sponsor would prefer a variable option, if possible. The objective of this project is to store and display all 800 points of data in a profile, change the frequency at which data is collected, and display a 3-D visual of the profiles. These changes and additions should be accomplished while avoiding interference with the normal production process. During the first phase of this project, the student engineers have begun analyzing the system, making design decisions and choosing between different components, planning hardware and software connections, and designing an interface for the system. In the second phase of this process, students began working with Excel, which is the software that was chosen at the end of the first phase, as well as working with the controller in order to communicate serially to a computer. Due to the change of circumstances that occurred in the middle of the second phase, students could no longer test communication options with the controller. The testing and verifying stages of the project were concluded at this point and students were asked to focus on documentation. Students created a new document that discussed all of the decisions that were made throughout the project, if the decision was used, and why or why not. Test plans were revised and updated as well.Electrical Engineering Technolog

Advanced Mid-Water Tools for 4D Marine Data Fusion and Visualization

Mapping and charting of the seafloor underwent a revolution approximately 20 years ago with the introduction of multibeam sonars -- sonars that provided complete, high-resolution coverage of the seafloor rather than sparse measurements. The initial focus of these sonar systems was the charting of depths in support of safety of navigation and offshore exploration; more recently innovations in processing software have led to approaches to characterize seafloor type and for mapping seafloor habitat in support of fisheries research. In recent years, a new generation of multibeam sonars has been developed that, for the first time, have the ability to map the water column along with the seafloor. This ability will potentially allow multibeam sonars to address a number of critical ocean problems including the direct mapping of fish and marine mammals, the location of mid-water targets and, if water column properties are appropriate, a wide range of physical oceanographic processes. This potential relies on suitable software to make use of all of the new available data. Currently, the users of these sonars have a limited view of the mid-water data in real-time and limited capacity to store it, replay it, or run further analysis. The data also needs to be integrated with other sensor assets such as bathymetry, backscatter, sub-bottom, seafloor characterizations and other assets so that a “complete” picture of the marine environment under analysis can be realized. Software tools developed for this type of data integration should support a wide range of sonars with a unified format for the wide variety of mid-water sonar types. This paper describes the evolution and result of an effort to create a software tool that meets these needs, and details case studies using the new tools in the areas of fisheries research, static target search, wreck surveys and physical oceanographic processes

A Backend Framework for the Efficient Management of Power System Measurements

Increased adoption and deployment of phasor measurement units (PMU) has provided valuable fine-grained data over the grid. Analysis over these data can provide insight into the health of the grid, thereby improving control over operations. Realizing this data-driven control, however, requires validating, processing and storing massive amounts of PMU data. This paper describes a PMU data management system that supports input from multiple PMU data streams, features an event-detection algorithm, and provides an efficient method for retrieving archival data. The event-detection algorithm rapidly correlates multiple PMU data streams, providing details on events occurring within the power system. The event-detection algorithm feeds into a visualization component, allowing operators to recognize events as they occur. The indexing and data retrieval mechanism facilitates fast access to archived PMU data. Using this method, we achieved over 30x speedup for queries with high selectivity. With the development of these two components, we have developed a system that allows efficient analysis of multiple time-aligned PMU data streams.Comment: Published in Electric Power Systems Research (2016), not available ye

Storage Solutions for Big Data Systems: A Qualitative Study and Comparison

Big data systems development is full of challenges in view of the variety of application areas and domains that this technology promises to serve. Typically, fundamental design decisions involved in big data systems design include choosing appropriate storage and computing infrastructures. In this age of heterogeneous systems that integrate different technologies for optimized solution to a specific real world problem, big data system are not an exception to any such rule. As far as the storage aspect of any big data system is concerned, the primary facet in this regard is a storage infrastructure and NoSQL seems to be the right technology that fulfills its requirements. However, every big data application has variable data characteristics and thus, the corresponding data fits into a different data model. This paper presents feature and use case analysis and comparison of the four main data models namely document oriented, key value, graph and wide column. Moreover, a feature analysis of 80 NoSQL solutions has been provided, elaborating on the criteria and points that a developer must consider while making a possible choice. Typically, big data storage needs to communicate with the execution engine and other processing and visualization technologies to create a comprehensive solution. This brings forth second facet of big data storage, big data file formats, into picture. The second half of the research paper compares the advantages, shortcomings and possible use cases of available big data file formats for Hadoop, which is the foundation for most big data computing technologies. Decentralized storage and blockchain are seen as the next generation of big data storage and its challenges and future prospects have also been discussed

Oceans of Tomorrow sensor interoperability for in-situ ocean monitoring

The Oceans of Tomorrow (OoT) projects, funded by the European Commission’s FP7 program, are developing a new generation of sensors supporting physical, biogeochemical and biological oceanographic monitoring. The sensors range from acoustic to optical fluorometers to labs on a chip. The result is that the outputs are diverse in a variety of formats and communication methodologies. The interfaces with platforms such as floats, gliders and cable observatories are each different. Thus, sensorPeer ReviewedPostprint (author's final draft