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At least 1,639 records · Page 91

Root system architecture and environmental flux analysis in mature crops using 3D root mesocosms

Current methods of root sampling typically only obtain small or incomplete sections of root systems and do not capture their true complexity. To facilitate the visualization and analysis of full-sized plant root systems in 3-dimensions, we developed customized mesocosm growth containers. While highly scalable, the design presented here uses an internal volume of 45 ft 3 (1.27 m 3 ), suitable for large crop and bioenergy grass root systems to grow largely unconstrained. Furthermore, they allow for the excavation and preservation of 3-dimensional root system architecture (RSA), and facilitate the collection of time-resolved subterranean environmental data. Sensor arrays monitoring matric potential, temperature and CO 2 levels are buried in a grid formation at various depths to assess environmental fluxes at regular intervals. Methods of 3D data visualization of fluxes were developed to allow for comparison with root system architectural traits. Following harvest, the recovered root system can be digitally reconstructed in 3D through photogrammetry, which is an inexpensive method requiring only an appropriate studio space and a digital camera. We developed a pipeline to extract features from the 3D point clouds, or from derived skeletons that include point cloud voxel number as a proxy for biomass, total root system length, volume, depth, convex hull volume and solidity as a function of depth. Ground-truthing these features with biomass measurements from manually dissected root systems showed a high correlation. We evaluated switchgrass, maize, and sorghum root systems to highlight the capability for species wide comparisons. We focused on two switchgrass ecotypes, upland (VS16) and lowland (WBC3), in identical environments to demonstrate widely different root system architectures that may be indicative of core differences in their rhizoeconomic foraging strategies. Finally, we imposed a strong physiological water stress and manipulated the growth medium to demonstrate whole root system plasticity in response to environmental stimuli. Hence, these new “3D Root Mesocosms” and accompanying computational analysis provides a new paradigm for study of mature crop systems and the environmental fluxes that shape them.

59 BASIC BIOLOGICAL SCIENCES↗

Unified Language Frontend for Physic-Informed AI/ML

Artificial intelligence and machine learning (AI/ML) are becoming important tools for scientific modeling and simulation as in several other fields such as image analysis and natural language processing. ML techniques can leverage the computing power available in modern systems and reduce the human effort needed to configure experiments, interpret and visualize results, draw conclusions from huge quantities of raw data, and build surrogates for physics based models. Domain scientists in fields like fluid dynamics, microelectronics and chemistry can automate many of their most difficult and repetitive tasks or improve the design times by use of the faster ML-surrogates. However, modern ML and traditional scientific highperformance computing (HPC) tend to use completely different software ecosystems. While ML frameworks like PyTorch and TensorFlow provide Python APIs, most HPC applications and libraries are written in C++. Direct interoperability between the two languages is possible but is tedious and error-prone. In this work, we show that a compiler-based approach can bridge the gap between ML frameworks and scientific software with less developer effort and better efficiency. We use the MLIR (multi-level intermediate representation) ecosystem to compile a pre-trained convolutional neural network (CNN) in PyTorch to freestanding C++ source code in the Kokkos programming model. Kokkos is a programming model widely used in HPC to write portable, shared-memory parallel code that can natively target a variety of CPU and GPU architectures. Our compiler-generated source code can be directly integrated into any Kokkosbased application with no dependencies on Python or cross-language interfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Supporting Greater Interactivity in the IPython Visualization Ecosystem

Interactive visualizations are invaluable tools for building intuition and supporting rapid exploration of datasets and models. Numerous libraries in Python support interactivity, and workflows that combine Jupyter and IPyWidgets in particular make it straightforward to build data analysis tools on the fly. However, the field is missing the ability to arbitrarily overlay widgets and plots on top of others to support more flexible details-on-demand techniques. This work discusses some limitations of the base IPyWidgets library, explains the benefits of IPyVuetify and how it addresses these limitations, and finally presents a new open-source solution that builds on IPyVuetify to provide easily integrated widget overlays in Jupyter.

Martindale, Nathan↗

The design of electronic map displays

This paper presents a cognitive analysis of a pilot's navigation task and describes an experiment comparing a new map display that employs the principle of visual momentum with the two traditional approaches, track-up and north-up. The data show that the advantage of a track-up alignment is its congruence with the egocentered forward view; however, the inconsistency of the rotating display hinders development of a cognitive map. The stability of a north-up alignment aids the acquisition of a cognitive map, but there is a cost associated with the mental rotation of the display to a track-up alignment for tasks involving the ego-centered forward view. The data also show that the visual momentum design captures the benefits and reduces the costs associated with the two traditional approaches.

Aretz, Anthony J.↗

The Automated Instrumentation and Monitoring System (AIMS) reference manual

Whether a researcher is designing the 'next parallel programming paradigm,' another 'scalable multiprocessor' or investigating resource allocation algorithms for multiprocessors, a facility that enables parallel program execution to be captured and displayed is invaluable. Careful analysis of execution traces can help computer designers and software architects to uncover system behavior and to take advantage of specific application characteristics and hardware features. A software tool kit that facilitates performance evaluation of parallel applications on multiprocessors is described. The Automated Instrumentation and Monitoring System (AIMS) has four major software components: a source code instrumentor which automatically inserts active event recorders into the program's source code before compilation; a run time performance-monitoring library, which collects performance data; a trace file animation and analysis tool kit which reconstructs program execution from the trace file; and a trace post-processor which compensate for data collection overhead. Besides being used as prototype for developing new techniques for instrumenting, monitoring, and visualizing parallel program execution, AIMS is also being incorporated into the run-time environments of various hardware test beds to evaluate their impact on user productivity. Currently, AIMS instrumentors accept FORTRAN and C parallel programs written for Intel's NX operating system on the iPSC family of multi computers. A run-time performance-monitoring library for the iPSC/860 is included in this release. We plan to release monitors for other platforms (such as PVM and TMC's CM-5) in the near future. Performance data collected can be graphically displayed on workstations (e.g. Sun Sparc and SGI) supporting X-Windows (in particular, Xl IR5, Motif 1.1.3).

Yan, Jerry↗

Visualization software for a global three-dimensional upper atmosphere model

A software environment has been developed to assist in analysis and visualization of numerical outputs from NCAR's thermospheric general circulation models. The codes produce vector graphics, raster imagery, and time dependent animation of model results, with provision for comparison with empirical models and relevant data from satellite and ground based instruments. Separate programs are executed on the NCAR CRAY YMP8/864 and HAO divisional Sun workstations, providing both large volume highspeed batch and custom interactive computing environments. The visualization system assembles a suite of existing software packages including NCAR Graphics, IDL, netCDF, and the Xt intrinsics library with the Athena widget set.

Foster, Benjamin T.↗

Distributed Exhaust Nozzles for Jet Noise Reduction

The main objective of this study is to validate the jet noise reduction potential of a concept associated with distributed exhaust nozzles. Under this concept the propulsive thrust is generated by a larger number of discrete plumes issuing from an array of small or mini-nozzles. The potential of noise reduction of this concept stems from the fact that a large number of small jets will produce very high frequency noise and also, if spaced suitably, they will coalesce at a smaller velocity to produce low amplitude, low frequency noise. This is accomplished through detailed acoustic and fluid measurements along with a Computational Fluidic Dynamic (CFD) solution of the mean (DE) Distributed Exhaust nozzle flowfield performed by Northrop-Grumman. The acoustic performance is quantified in an anechoic chamber. Farfield acoustic data is acquired for a DE nozzle as well as a round nozzle of the same area. Both these types of nozzles are assessed numerically using Computational Fluid Dynamic (CFD) techniques. The CFD analysis ensures that both nozzles issued the same amount of airflow for a given nozzle pressure ratio. Data at a variety of nozzle pressure ratios are acquired at a range of polar and azimuthal angles. Flow visualization of the DE nozzle is used to assess the fluid dynamics of the small jet interactions. Results show that at high subsonic jet velocities, the DE nozzle shifts its frequency of peak amplitude to a higher frequency relative to a round nozzle of equivalent area (from a S(sub tD) = 0.24 to 1. 3). Furthermore, the DE nozzle shows reduced sound pressure levels (as much as 4 - 8 dB) in the low frequency part of the spectrum (less than S(sub tD) = 0.24 ) compared to the round nozzle. At supersonic jet velocities, the DE nozzle does not exhibit the jet screech and the shock-associated broadband noise is reduced by as much as 12 dB.

Ahuja, K. K.↗

NASA GSFC Space Weather Center - Innovative Space Weather Dissemination: Web-Interfaces, Mobile Applications, and More

The NASA GSFC Space Weather Center (http://swc.gsfc.nasa.gov) is committed to providing forecasts, alerts, research, and educational support to address NASA's space weather needs - in addition to the needs of the general space weather community. We provide a host of services including spacecraft anomaly resolution, historical impact analysis, real-time monitoring and forecasting, custom space weather alerts and products, weekly summaries and reports, and most recently - video casts. There are many challenges in providing accurate descriptions of past, present, and expected space weather events - and the Space Weather Center at NASA GSFC employs several innovative solutions to provide access to a comprehensive collection of both observational data, as well as space weather model/simulation data. We'll describe the challenges we've faced with managing hundreds of data streams, running models in real-time, data storage, and data dissemination. We'll also highlight several systems and tools that are utilized by the Space Weather Center in our daily operations, all of which are available to the general community as well. These systems and services include a web-based application called the Integrated Space Weather Analysis System (iSWA http://iswa.gsfc.nasa.gov), two mobile space weather applications for both IOS and Android devices, an external API for web-service style access to data, google earth compatible data products, and a downloadable client-based visualization tool.

Maddox, Marlo↗

Message Brokering Evaluation for Live Spacecraft Telemetry Monitoring, Recorded Playback, and Analysis

Live monitoring and post-flight analysis of telemetry data play a vital role in the development, diagnosis, and deployment of components of a space flight mission. Requirements for such a system include low end-to-end latency between data producers and visualizers, preserved ordering of messages, data stream archiving with random access playback, and real-time creation of derived data streams. We evaluate the RabbitMQ and Kafka message brokering systems, on how well they can enable a real-time, scalable, and robust telemetry framework that delivers telemetry data to multiple clients across heterogeneous platforms and flight projects. In our experiments using an actively developed robotic arm testbed, Kafka yielded a much higher message throughput rate and a consistent publishing rate across the number of topics and consumers. Consumer message rates were consistent across the number of topics but can exhibit bursty behavior with an increase in the contention for a single topic partition with increasing number of consumers.

Lee, Daren↗

Cross Recurrence Analysis as a Measure of Pilots' Coordination Strategy

When solving problems, multi-person airline crews can choose whether to work together, or to address different aspects of a situation with a divide and conquer strategy. Knowing which of these strategies is most effective may help airlines develop better procedures and training. This paper concentrates on joint attention as a measure of crew coordination. We report results obtained by applying cross recurrence analysis to eye movement data from two-person crews, collected in a flight simulator experiment. The analysis shows that crews exhibit coordinated gaze roughly 16th of the time, with a tendency for the captain to lead the first officers visual attention. The degree to which crews coordinate their gaze is not significantly correlated with performance ratings assigned by instructors; further research questions and approaches are discussed.

non-linear models↗

Shoshone River Water Resources: Assessing Sediment Inputs into the Shoshone River in Wyoming to Determine Areas for Protection and Restoration Practices

In 2016, a routine repair operation at the Willwood Dam released tons of built-up sediment into the Shoshone River, polluting the river and negatively impacting the ecosystem. This release greatly affected the communities that rely on the river for farming, recreation, and tourism. In partnership with the Wyoming Department of Environmental Quality (WYDEQ), Shoshone River Partners, and the United States Geological Survey (USGS) Wyoming–Montana Water Science Center, this project utilized satellite imagery and precipitation data to examine turbidity patterns in the Shoshone River between the Buffalo Bill Dam and the Willwood Dam. We used PlanetScope satellite images to assess changes in surface reflectance of the river in response to precipitation events and Global Precipitation Measurement (GPM) Integrated Multi-Spectral Retrieval (IMERG) precipitation data to estimate the lag time between rainfall events and increased turbidity. The National Land Cover Dataset (2019) was used to identify the main land cover types within each sub-basin. The end products included a turbidity analysis, land cover analysis, and precipitation analysis that provided the partners with a better understanding of sediment dynamics in the river. The results demonstrated the feasibility of using PlanetScope data to examine turbidity spatially along small rivers. Sediment plumes from tributaries were visually identified for multiple high turbidity events, and we calibrated an equation that translated reflectance to turbidity, accurately representing plume extent. Inconsistent spectral quality of PlanetScope data, however, limited our ability to assess the relative sediment contribution of the tributaries.

tributaries↗

Have Heat Waves Become More Intense and Frequent in North America in the Past 40 Years?

Extreme events, especially heat waves, have seemingly become more frequent and intense in the past decades worldwide, likely associated with global warming. This study uses the extreme detection indices product derived from the NASA Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) data to address whether heat waves have become more intense and frequent in North America in the past 40 years. We also examine in-depth the recent heat wave in June 2023 in Canada and the associated drought and wildfire events and compare them with previous years. We use additional data products in this study for cross-validation, including surface temperature from Phase 2 of the North American Land Data Assimilation System (NLDAS 2.0) and Atmospheric Infrared Sounder (AIRS) version 7, with a shorter data latency, only a few days. In addition, we will demonstrate how to efficiently conduct long-term time-series data analysis, which involves a large volume of data, using data services developed at NASA GES DISC, such as Giovanni, datarod, and Thematic Real-time Environmental Distributed Data Services (THREDDS) Data Server (TDS). These services can be used to visualize and explore extreme events, and to download only the data that is of interest.

Xiaohua Pan↗

Evaluation of Markerless Motion Capture for Monitoring Sensorimotor Performance

BACKGROUND Astronauts returning from long-duration exposure to microgravity frequently exhibit alterations in sensorimotor function leading to postural imbalance, impaired locomotion, and operational challenges to manual control. Mission duration and individual responses often influence both the severity of performance decrements and the variability in adaptation timelines. Postflight disruptions during functional tasks are often detected through body-worn inertial measurement unit (IMU) devices. While IMU sensors are relatively compact, the long-term wear may lead to discomfort, displacement of the sensors on the body, and restrictions in movement or crew behavior. Although IMU data offers valuable insights from a research standpoint, interpreting changes in pre- and post-flight measures can be difficult for crew support personnel beyond the research domain, which can hinder the application for medical assessments and rehabilitation. Finally, the availability of inertial sensors in-flight is limited. There is a need for unobtrusive monitoring tools to improve our ability to monitor adaptation following gravitational transitions in various postflight evaluations and rehabilitation settings. Markerless motion capture (MMC) is an evolving unobtrusive technology that builds upon decades of research with marker-based motion capture systems to provide 3D human pose estimation from multiple synchronized 2D camera views using deep learning algorithms. Markerless technology can revolutionize how data is captured pre- and post-flight and potentially in-flight during intravehicular activity by enabling pose estimation of multiple crew members from onboard camera hardware. METHODS The following presents the initial evaluation of a state-of-the-art commercial-off-the-shelf MMC system, Theia Markerless, compared to IMU devices during various ground-based functional tasks and environmental conditions. The featured functional tasks include assessments from Human Research Program (HRP) funded studies such as Sensorimotor Standard Measures and Sensorimotor Assessments. Synchronous data collected using both motion capture and IMUs are analyzed for six male and female subjects of varying anthropometry. The analysis includes limited assessments of clothing, capture volume configurations, and the tool's sensitivity to detecting performance changes after a spaceflight analog centrifuge exposure. The development of visualization tools to enhance the application of the pose estimation output is also presented. RESULTS Initial results demonstrate comparable root mean square error (RMSE) to existing literature evaluating markerless and marker-based motion capture systems. Considering the relative functional range of motion of the cervical spine, normalized error values for the markerless system’s accuracy of the head was 0.032 in pitch, 0.025 in roll, and 0.018 in yaw plane of motion across a subset of functional tasks. The raw RMSE values were 3.49, 2.25, and 2.81 degrees respectively. For the torso, results suggest normalized errors of 0.469 in pitch, 0.191 in roll, and 0.307 in yaw planes of motion and raw RMSE values of 3.52, 1.53, and 3.07 degrees respectively. The data suggests the functional demands of a particular task influences the estimation accuracy of the MMC system where more dynamic motion and cases where subjects are not upright may introduce diminished tracking accuracy. DISCUSSION The following work lays the foundation for future implementations leveraging markerless motion capture to assess the time course of recovery and provide insight for rehabilitation protocols to enhance crew readiness for the resumption of daily activities. These tools offer effective methods for anonymizing sensitive crew data, facilitating numerous applications across research, medical, and rehabilitation groups. Collaborations with the Anthropometry and Biomechanics Facility will provide further comparisons of the Markerless system to a marker-based system. ACKNOWLEDGEMENT</ This work is supported by NASA’s Exploration Systems Development Mission Directorate Mars Campaign Office Crew Health Countermeasures.

Hannah M. Weiss↗

An ontology-based knowledge graph for representing interactions involving RNA molecules

The "RNA world" represents a novel frontier for the study of fundamental biological processes and human diseases and is paving the way for the development of new drugs tailored to each patient's biomolecular characteristics. Although scientific data about coding and non-coding RNA molecules are constantly produced and available from public repositories, they are scattered across different databases and a centralized, uniform, and semantically consistent representation of the "RNA world" is still lacking. We propose RNA-KG, a knowledge graph (KG) encompassing biological knowledge about RNAs gathered from more than 60 public databases, integrating functional relationships with genes, proteins, and chemicals and ontologically grounded biomedical concepts. To develop RNA-KG, we first identified, pre-processed, and characterized each data source; next, we built a meta-graph that provides an ontological description of the KG by representing all the bio-molecular entities and medical concepts of interest in this domain, as well as the types of interactions connecting them. Finally, we leveraged an instance-based semantically abstracted knowledge model to specify the ontological alignment according to which RNA-KG was generated. RNA-KG can be downloaded in different formats and also queried by a SPARQL endpoint. A thorough topological analysis of the resulting heterogeneous graph provides further insights into the characteristics of the "RNA world". RNA-KG can be both directly explored and visualized, and/or analyzed by applying computational methods to infer bio-medical knowledge from its heterogeneous nodes and edges. The resource can be easily updated with new experimental data, and specific views of the overall KG can be extracted according to the bio-medical problem to be studied.

59 BASIC BIOLOGICAL SCIENCES↗

A Data Mining Project to Identify Cardiovascular Related Factors That May Contribute to Changes in Visual Acuity Within the US Astronaut Corps

Many of the cardiovascular-related adaptations that occur in the microgravity environment are due, in part, to a well-characterized cephalad-fluid shift that is evidenced by facial edema and decreased lower limb circumference. It is believed that most of these alterations occur as a compensatory response necessary to maintain a "normal" blood pressure and cardiac output while in space. However, data from both flight and analog research suggest that in some instances these microgravity-induced alterations may contribute to cardiovascular-related pathologies. Most concerning is the potential relation between the vision disturbances experienced by some long duration crewmembers and changes in cerebral blood flow and intra-ocular pressure. The purpose of this project was to identify cardiovascular measures that may potentially distinguish individuals at risk for visual disturbances after long duration space flight. Toward this goal, we constructed a dataset from Medical Operation tilt/stand test evaluations pre- (days L-15-L-5) and immediate post-flight (day R+0) on 20 (3 females, 17 males). We restricted our evaluation to only crewmembers who participated in both shuttle and space station missions. Data analysis was performed using both descriptive and analytical methods (Stata 11.2, College Station, TX) and are presented as means +/- 95% CI. Crewmembers averaged 5207 (3447 - 8934) flight hours across both long (MIR-23 through Expedition16) and short (STS-27 through STS-101) duration missions between 1988 and 2008. The mean age of the crew at the time of their most recent shuttle flight was 41 (34-44) compared to 47 (40-54) years during their time on station. In order to focus our analysis (we did not have codes to separate out subjects by symptomotology) , we performed a visual inspection of each cardiovascular measures captured during testing and plotted them against stand time, pre- to post-flight, and between mission duration. It was found that pulse pressure most clearly differentiated the two mission types. Statistical analysis confirmed that pulse pressure was significantly higher before [45.6; (42.1 to 49.1)] and after [50.7; (46.9 to 54.6)] time on station compared with their most recent shuttle flight [31.6 (27.8 to 35.4), and 32.2 (28.3 to 36.0) respectively] even after correcting differences in age and cumulative number of mission hours. Without knowing the identity of which long duration crewmembers demonstrated visual changes, we were limited to examining whether certain crew regulate components of pulse pressure, systolic and diastolic blood pressure, differently due to microgravity exposure. To that end, we stratified crew into tertiles based on either their pre-flight measure of systolic or diastolic blood pressure. Those crew in the highest tertile for both systolic (lower tertile (n=8; 103-111), middle tertile (n=7; 113-121), and upper tertile (n=5; 125-136) and diastolic blood pressure (lower tertile (n=8; 58-64), middle tertile (n=7; 67-73), and upper tertile (n=5; 75-81) demonstrated less variability in pulse pressure between R+0 and L-10 (Figure 2). Interestingly, those crewmembers with the highest resting systolic blood pressure demonstrated either no change or in some instances an increase in total peripheral resistance, where those in the lower tertiles had lower values of total peripheral resistance compared to pre-flight levels. In this study, it was found that crewmembers in the highest tertile for both systolic and diastolic blood pressure demonstrated less variability in pulse pressure and that the decrease in variability was due in part to lower levels of compliance as indicated by similar or higher levels of total peripheral resistance after compared with before flight levels. Whether there is a relation between blood pressure regulation and total peripheral resistance in crew presenting with negative changes in visual acuity remains unknown.

Westby, Christian M.↗

Sensorimotor integration in human postural control

It is generally accepted that human bipedal upright stance is achieved by feedback mechanisms that generate an appropriate corrective torque based on body-sway motion detected primarily by visual, vestibular, and proprioceptive sensory systems. Because orientation information from the various senses is not always available (eyes closed) or accurate (compliant support surface), the postural control system must somehow adjust to maintain stance in a wide variety of environmental conditions. This is the sensorimotor integration problem that we investigated by evoking anterior-posterior (AP) body sway using pseudorandom rotation of the visual surround and/or support surface (amplitudes 0.5-8 degrees ) in both normal subjects and subjects with severe bilateral vestibular loss (VL). AP rotation of body center-of-mass (COM) was measured in response to six conditions offering different combinations of available sensory information. Stimulus-response data were analyzed using spectral analysis to compute transfer functions and coherence functions over a frequency range from 0.017 to 2.23 Hz. Stimulus-response data were quite linear for any given condition and amplitude. However, overall behavior in normal subjects was nonlinear because gain decreased and phase functions sometimes changed with increasing stimulus amplitude. "Sensory channel reweighting" could account for this nonlinear behavior with subjects showing increasing reliance on vestibular cues as stimulus amplitudes increased. VL subjects could not perform this reweighting, and their stimulus-response behavior remained quite linear. Transfer function curve fits based on a simple feedback control model provided estimates of postural stiffness, damping, and feedback time delay. There were only small changes in these parameters with increasing visual stimulus amplitude. However, stiffness increased as much as 60% with increasing support surface amplitude. To maintain postural stability and avoid resonant behavior, an increase in stiffness should be accompanied by a corresponding increase in damping. Increased damping was achieved primarily by decreasing the apparent time delay of feedback control rather than by changing the damping coefficient (i.e., corrective torque related to body-sway velocity). In normal subjects, stiffness and damping were highly correlated with body mass and moment of inertia, with stiffness always about 1/3 larger than necessary to resist the destabilizing torque due to gravity. The stiffness parameter in some VL subjects was larger compared with normal subjects, suggesting that they may use increased stiffness to help compensate for their loss. Overall results show that the simple act of standing quietly depends on a remarkably complex sensorimotor control system.

NASA Discipline Neuroscience↗

Bridging the Gap Between Finite Element Modeling and Wavefront Analysis for Streamlined Optical System Design

Traditionally, evaluating the optical performance of mirrors derived from finite element (FEA), with third-party software requires cumbersome manual effort – which impacts efficient design optimization. This paper presents a process that seamlessly integrates FEA results with wavefront analysis software, significantly simplifying performance assessment and enabling rapid design iteration. We leverage the 4D technology interferometer and "4Sight" wavefront analysis software for performance measurement and comparison with FEA predictions. Recognizing the need for efficient data exchange, we developed an application that converts FEA data into a format compatible with 4Sight. The software takes two user-defined inputs: optical surface position and deformation information, typically provided as CSV or TXT files. Within a second, it generates an output file suitable for direct import into 4Sight, enabling immediate visualization of key optical performance metrics.

Zernike Polynomial↗

Automating Log Synthesis and Visualization with Python and Splunk

The goal of this project is to automate log analysis by utilizing Splunk, Bash, and Python together. Simplifying the monitoring and analysis of network traffic was the main goal. In order to accomplish this, a Bash script was created to use 'tcpdump' to automate network sniffing. It also included a 24-hour file rotation mechanism to effectively manage the pcap files that were generated. After that, a Python script was written to read these pcap files and retrieve pertinent data about network traffic. After processing the collected data, Splunk is used to summarize the important metrics and visualize said information with relevant graphs.

99 GENERAL AND MISCELLANEOUS↗