The 2022-2023 IDSC Fellows will gather once again to present the final project presentations at the Richter Library, 3rd Floor Conference Room, #343, on Thursday, April 27, from 3:00-4:30 PM. Join us in person for light refreshments (or via ZOOM) and hear their progress since their initial pitch. Read more “2022-2023 IDSC Fellows Final Project Presentations 4/27 in person or via ZOOM”
This paper describes a multi-timescale waveform descriptive grammar that assists researchers and engineers in syntactically labeling signals and developing test and control signals for consumer electronics design, diagnosis, and validation. Read more “Long-Duration Waveform Descriptive Grammar for Consumer Electronics Design, Diagnosis, and Validation”
Modern oscilloscopes, digitizers and data loggers generate a large amount of waveform data for long-duration waveform capturing and analysis. The contrast of time scales of long-duration waveform capturing (e.g., hours or days in high sampling rate) and analysis (e.g., signal fragments of several microseconds) produces unique big data challenges. Read more “Scaling Up Heterogeneous Waveform Clustering for Long-Duration Monitoring Signal Acquisition, Analysis, and Interaction”
Joseph Johnson, Mitsunori Ogihara, Daniel Messinger, and Gang Ren (and their co-authors) presented papers at the 2019 IEEE International Conference on Data Mining in Beijing, China, (held on November 8-11). Dr. Daniel Messinger also attended and was a Keynote Speaker for the ICDM-TMDM Translational Multimedia Data Mining for AI-Based Medical Diagnostics Workshop. Read more “Ren, Ogihara, and Johnson Present Papers at IEEE 2019 in Beijing”
Most musical sounds show strong energy concentrations, such as regular time-frequency patterns of sonic partials, as a sparse energy distribution across the spectrographic analysis plane. Most studies of musical sound are based on strong spectral components such as the energy distribution patterns of the harmonic partials. Read more “The “Dark” Energy Between Sonic Partials: Parametrics Estimation and Analysis of . . .”
Spectrogram and other time-frequency analysis methods transfer an audio file into an auditory image. When signal processing-based analysis and interpretation is performed on these auditory images instead of an audio signal, spectrographic analyses can identify interesting patterns that focus on Read more “A New Auditory Image for Social Media: Moving Towards Correlation of Spectrographic Analysis . . .”
Modern human-computer interaction systems use multiple perceptual dimensions to enhance intuition and efficiency of the user by improving their situational awareness. A signal processing and interaction framework is proposed for auralizing signal patterns and augmenting the visualization-focused analysis tasks of social media content analysis and annotations, with the goal of assisting the user in analyzing, retrieving, and organizing relevant information for marketing research. Read more “Multi-Scale Auralization for Multimedia Analytical Feature Interaction”
Translational Multimedia Data Mining for AI-Based Medical Diagnostics—Bridging Digital Intelligence with Clinical Practices (TMDM for short) is a WORKSHOP collocated with ICDM 2019 (November 8 – 11, 2019) in Beijing, China. Read more “ICDM-TMDM 2019 Workshop 11/8-11 in Beijing”
Atypical head movement pattern characterization is a potentially important cue for identifying children with autism spectrum disorder. In this paper, we implemented a computational framework for extracting the temporal patterns of head movement and utilizing the imbalance of temporal pattern distribution between diagnostic categories (e.g., children with or without autism spectrum disorder) as potential diagnostic cues. Read more “Categorical Timeline Allocation and Alignment for Diagnostic Head Movement Tracking Feature Analysis”
Mitsunori Ogihara (Director) and Gang Ren (Postdoctoral Associate) of Big Data Analytics and Data Mining program, and Daniel Messinger, Program Director of Social Systems Informatics, presented an interdisciplinary paper (TITLE: “Categorical Timeline Allocation and Alignment for Diagnostic Head Movement Tracking Feature Analysis”) together at the workshop on Face and Gesture Analysis for Health Informatics (FGAHI) at CVPR 2019 (Computer Vision and Pattern Recognition, part of IEEE CVF) 2019, on June 16-21, 2019 in Long Beach, California. Read more “Data Mining & SSI Present Paper at CVPR”