Siebel CRM Systems, Inc. was a software company principally engaged in the design, development, marketing, and support of customer relationship management applications. The company was founded by Thomas Siebel and Patricia House in 1993. At first known mainly for its sales force automation products, the company expanded into the broader CRM market. By the late 1990s, Siebel Systems was the dominant CRM vendor, peaking at 45% market share in 2002.On September 12, 2005, Oracle Corporation announced it had agreed to buy Siebel Systems for $5.8 billion. Siebel is now a brand name owned by Oracle Corporation. Wikipedia.
Tran D.,Nanyang Technological University |
Yuan J.,Nanyang Technological University |
IEEE Transactions on Pattern Analysis and Machine Intelligence | Year: 2014
Although sliding window-based approaches have been quite successful in detecting objects in images, it is not a trivial problem to extend them to detecting events in videos. We propose to search for spatiotemporal paths for video event detection. This new formulation can accurately detect and locate video events in cluttered and crowded scenes, and is robust to camera motions. It can also well handle the scale, shape, and intraclass variations of the event. Compared to event detection using spatiotemporal sliding windows, the spatiotemporal paths correspond to the event trajectories in the video space, thus can better handle events composed by moving objects. We prove that the proposed search algorithm can achieve the global optimal solution with the lowest complexity. Experiments are conducted on realistic video data sets with different event detection tasks, such as anomaly event detection, walking person detection, and running detection. Our proposed method is compatible with different types of video features or object detectors and robust to false and missed local detections. It significantly improves the overall detection and localization accuracy over the state-of-the-art methods. © 2014 IEEE.
Termehchy A.,University of Illinois at Urbana - Champaign |
Termehchy A.,Siebel |
Winslett M.,University of Illinois at Urbana - Champaign
ACM Transactions on Database Systems | Year: 2011
The popularity of XML has exacerbated the need for an easy-to-use, high precision query interface for XML data. When traditional document-oriented keyword search techniques do not suffice, natural language interfaces and keyword search techniques that take advantage of XML structure make it very easy for ordinary users to query XML databases. Unfortunately, current approaches to processing these queries rely heavily on heuristics that are intuitively appealing but ultimately ad hoc. These approaches often retrieve false positive answers, overlook correct answers, and cannot rank answers appropriately. To address these problems for data-centric XML, we propose coherency ranking (CR), a domain- and database designindependent ranking method for XML keyword queries that is based on an extension of the concepts of data dependencies and mutual information.With coherency ranking, the results of a keyword query are invariant under a class of equivalency-preserving schema reorganizations. We analyze the way in which previous approaches to XML keyword search approximate coherency ranking, and present efficient algorithms to process queries and rank their answers using coherency ranking. Our empirical evaluation with two realworld XML data sets shows that coherency ranking has better precision and recall and provides better ranking than all previous approaches. ©2011.
News Article | December 23, 2015
Tom Siebel's cloud analytics startup, C3 Energy, processes data more quickly than spreadsheets, and it's making fast progress with customers.
You can save more money by replacing your furnace rather than buying a clothes dryer or by upgrading your windows instead of getting a new refrigerator, according to new research published this month in the journal Environmental Science and Technology. Conducted by a team of scientists from the Stillwell Research Group at the University of Illinois at Urbana-Champaign, this research discusses how appliances that are water efficient can lower your energy costs and vice versa. For example, your washing machine will use both water and electricity when you clean a load of laundry. Then, the wastewater that is produced will take energy to treat. Conversely, the electricity that is consumed during the process almost certainly took water to produce. According to the researchers behind this new study - Christopher M. Chini, Kelsey L. Schreiber, Zachary A. Barker, and Ashlynn S. Stillwell – consumers need to take all of these factors into account when they consider what washing machine to buy in the first place. Below is an edited, partial transcript of an interview with two of this report’s authors – Ashlynn S. Stillwell and Christopher M. Chini – with the Siebel Energy Institute, which supported the study. Q: This study takes a holistic approach to examining each appliance and fixture; looking at energy and water consumption in tandem. In your opinion, what’s most valuable about analyzing the energy-water nexus? A: The most valuable reason to evaluate the energy-water nexus is that we get a fuller picture of the water and energy sectors together. As we strive toward a sustainable and resilient future, we can no longer consider only singular components of the system (e.g., drinking water) without considering a broader systems perspective: How much energy does it take to get water to my home, and then how much energy does it take to treat the water when it leaves my home? Without considering the interplay between these two vital resources, we leave out an important piece of the sustainability puzzle. Q: Graduate students on the team created models that simulated energy and water use by an appliance. What do the models show (or what do they look like?) A: The models displayed direct (at the consumer level) and indirect (at the utility level) consumption for water and energy. Creating cost abatement curves, we displayed the information in a communicative format where the most cost-efficient upgrade is on the left and the least is on the right. Therefore, the rational consumer would implement upgrades in their home from left to right on the abatement curve. Q: The study was extended from analyzing national averages to specifically looking at data from Chicago, New York City and Los Angeles. What struck you as the most compelling difference between the abatement curves for these urban areas and the national average? A: The biggest difference between these cities was the consumption of indirect resources. Electricity and natural gas consumption at drinking water and wastewater utilities played a major role in changing the cost abatement curve for energy. Additionally, the biggest factor in variance of the cost abatement curves for water was unaccounted for water (i.e., leaks). These cities varied on either side of the national average abatement curve. Q: The research revealed that one of the most cost effective upgrades is a water heater. What type of water heater is most efficient and why? A: The most cost-effective water heater was the high-efficiency natural gas water heater. This water heater has a high efficiency factor and, interestingly, beat out solar water heaters on a national average. Often, solar water heaters have a less-than-efficient electric back-up heater, which can negate the benefits of the solar water heater in some applications. Q: How do you see your findings enhancing or complementing existing programs that incentivize consumers to invest in more efficient appliances? A: The findings of this study provide a visual representation of multiple appliances and fixtures. Some of these efficiency investments, such as a water heater or furnace, are out of sight for the homeowner and, therefore, are not high on a priority list for replacement. Our study highlights opportunities for reducing up-front costs of upgrades and highlights appliances that are often overlooked for homeowners, providing opportunities for utilities and local governments to implement incentive or rebate programs. For a full transcript of this interview, you can visit the Siebel Energy Institute website (link) You can also read the full paper at the Environmental Science & Technology website (link).
All living things require proteins, members of a vast family of molecules that nature “makes to order” according to the blueprints in DNA. Through the natural process of evolution, DNA mutations generate new or more effective proteins. Humans have found so many alternative uses for these molecules — as foods, industrial enzymes, anti-cancer drugs — that scientists are eager to better understand how to engineer protein variants designed for specific uses. Now, Stanford researchers have invented a technique to dramatically accelerate protein evolution for this purpose. This technology, described in a paper published online Dec. 7 in Nature Chemical Biology, allows researchers to test millions of variants of a given protein, choose the best for some task and determine the DNA sequence that creates this variant. “Evolution, the survival of the fittest, takes place over a span of thousands of years, but we can now direct proteins to evolve in hours or days,” said Jennifer Cochran, Ph.D., an associate professor of bioengineering, who shares senior authorship of the paper with Thomas Baer, Ph.D., executive director of the Stanford Photonics Research Center. The lead author is Bob Chen, a graduate student in bioengineering. “This is a practical, versatile system with broad applications that researchers will find easy to use,” Baer said. By combining Cochran’s protein engineering know-how with Baer’s expertise in laser-based instrumentation, the team created a tool that can test millions of protein variants in a matter of hours. “The demonstrations are impressive, and I look forward to seeing this technology more widely adopted,” said Frances Arnold, Ph.D., a professor of chemical engineering at Caltech who was not affiliated with the study. The researchers call their tool µSCALE, for Single Cell Analysis and Laser Extraction. The “µ” stands for the microcapillary glass slide that holds the protein samples. The slide is roughly the size and thickness of a penny, yet in that space a million capillary tubes are arrayed like straws, open on the top and bottom. The power of µSCALE is how it enables researchers to build upon current biochemical techniques to run a million protein experiments simultaneously, then extract and further analyze the most promising results. The researchers first employ a process termed “mutagenesis” to create random variations in a specific gene. These mutations are inserted into batches of yeast or bacterial cells, which express the altered gene and produce millions of random protein variants. A µSCALE user mixes millions of tiny opaque glass beads into a sample containing millions of yeast or bacteria and spreads the mixture on a microcapillary slide. Tiny amounts of fluid trickle into each tube, carrying individual cells. Surface tension traps the liquid and the cell in each capillary. The slide bearing these million yeast or bacteria, and the protein variants they produce, is inserted into the µSCALE device. A software-controlled microscope peers into each capillary and takes images of the biochemical reaction occurring therein. Once a µSCALE user identifies a capillary of interest, the researcher can direct the laser to extract the contents of that tube without disrupting its neighbors, using an ingenious method devised by Baer. “The beads are what enable extraction,” Baer said. “The laser supplies energy to move the beads, which breaks the surface tension and releases the sample from the capillary.” Thus, µSCALE empties the contents of a single capillary onto a collector plate, where the DNA of the isolated cell can be sequenced and the gene variant responsible for the protein of interest can be identified. “One of the unique features of µSCALE is that it allows researchers to rapidly isolate a single desired cell from hundreds of thousands of other cells,” said Chen, who wrote the software to examine and detect signs of interesting protein activity within the test tubes. Promising variants can be collected and reprocessed through µSCALE to further evolve and optimize the protein. “This is an exciting new tool to answer important questions about proteins,” Cochran said, likening µSCALE to the way that high-throughput tools for gene analysis have allowed researchers to unlock key features of biology underlying human disease. The project began five years ago when Baer and study co-author Ivan Dimov, Ph.D., a visiting instructor and Siebel Fellow at the Stanford Institute for Stem Cell Biology and Regenerative Medicine, developed the first instrument. They showed how to identify cell types in a microcapillary array and extract a single capillary’s contents using glass beads and a focused laser. About three years ago, Cochran and Baer joined forces to develop µSCALE for protein engineering, and the team devised three experiments to showcase µSCALE’s utility and flexibility. In one experiment, researchers sifted through a protein library produced in yeast cells to select antibodies that bound most tightly to a cancer target. Antibodies with a high target-binding affinity are known to be effective against cancer. In a second example, they engineered a bright orange fluorescent protein biosensor. Using µSCALE, they did this almost 10 times faster than previous methods. Such biosensors are often used as tags in a wide variety of biology experiments. A third experiment, carried out with Daniel Herschlag, Ph.D., professor of biochemistry and a co-author of the study, used µSCALE to improve upon a model enzyme. “This system will allow us to explore the evolutionary and functional relationships between enzymes, guiding the engineering of new enzymes that can carry out novel beneficial reactions,” Herschlag said.