In the design of structures, systems have been developed to achieve optimization through the use of algorithms. However, algorithms of the prior art often fail in terms of convergence and stability, particularly for large nonlinear engineering systems. For instance, existing Computer-Aided Design (CAD) software systems have rudimentary optimization capabilities and can hardly handle large nonlinear systems. Another problem with prior art systems is that the data models employed do not take advantage of computing resources available today. Optimization of large structures with thousands of members subjected to actual constraints of commonly-used design codes requires an inordinate amount of computer processing and can be done only on multiprocessor supercomputers.
Researchers at the Ohio State University have discovered a superior system for design optimization of highrise and superhighrise buildings with more than 20,000 members subjected to actual nonlinear constraints of commonly used design codes. Employing this invention can yield substantial weight savings in the design of large structures with millions of dollars of cost savings. This invention can also serve as a stepping stone in further improvement of CAD software.
Design of large structures.
- Substantial weight savings
- Substantial cost savings
Researchers at the Ohio State University have developed a dynamic 3D wavelet transform system and method for compressing video including color or black and white signal. The method applies a so-called packed integer wavelet transform to individual video frames to generate wavelet coefficients in the spatial domain (x and y directions). As a result, it is possible to enjoy the video sent over the internet or stored on a computer with a small memory space and a narrow bandwidth. The current technology is subject to one major disadvantage; it generates block artifacts, especially at a high compression ratio and these artifacts significantly reduce the quality of the video. Wavelet transform is a promising new approach for image and video compression that has proven superior to the previous approach and significantly enhances video images.
For use in generating high quality video images using a limited amount of memory space and bandwidth.
- The wavelet transform is applied to the entire image; it thus avoids the block artifacts.
- The wavelet transform localizes signal characteristics in both the spatial and temporal domains and can most efficiently explore the spatial redundancy to achieve the highest compression ratio.
- The wavelet transform decomposes an image into a low resolution version of the image along with a series of enhancements that add fine details. Thus, the wavelet transform can support continuous rate scalibility.
Video is a data-rich medium that results in the creation of large data sets requiring large memory spaces and wide bandwidth to transmit. At The Ohio State University, we have created a dynamically grouped, 3D wavelet technology which significantly reduces the bit-rate for transmitting or storing audio, video and image signals, and out-performs existing technologies in terms of compression efficiency, image quality and scope of applications. Demonstration software is available.
- Streaming internet or wireless video and audio transmission
- Mobile phone video
- Video conferencing
- Video on demand
- Digital video surveillance
- Multi-media email
- Video databases and archiving
- Digital video editing
- Higher compression ratios than other techniques (e.g. discrete cosine transform based MPEG), while maintaining superior image quality
- Adaptive grouping 3D system for enhanced compression ratios
- Separate object and background compression
- Packed-integer implementation of wavelet transform for high-speed computation
- Software only solution
- Amenable to VLSI or DSP hardware implementations
- Suitable for handheld devices, since integer based computation allows for low power IC use
- Flexible algorithm facilitates tuning to available computational resources
US Patent No.: 6,801,573 (October 5, 2004)