Alternate protein frameworks for molecular recognition.

In an effort to determine whether proteins with structures other than the immunoglobulin fold can be used to mimic the ligand binding properties of antibodies, we generated a library from the four-helix bundle protein cytochrome b562 in which the two loops were randomized. Panning of this library against the bovine serum albumin (BSA) conjugate of N-methyl-p-nitrobenzylamine derivative 1 by phage display methods yielded cytochromes in which residues Trp-20, Arg-21, and Ser-22 in loop A and Arg-83 and Trp-84 in loop B were conserved. The individual mutants, which fold into native-like structure, bind selectively to the BSA-1 conjugate with micromolar dissociation constants (Kd), in comparison to a monoclonal antibody that binds selectively to 1 with a Kd of 290 nM. These and other antibody-like receptors may prove useful as therapeutic agents or as reagents for both intra- and extracellular studies.

A methodology for improving computed individual regressions predictions.

This research proposes a methodology to improve computed individual prediction values provided by an existing regression model without having to change either its parameters or its architecture. In other words, we are interested in achieving more accurate results by adjusting the calculated regression prediction values, without modifying or rebuilding the original regression model. Our proposition is to adjust the regression prediction values using individual reliability estimates that indicate if a single regression prediction is likely to produce an error considered critical by the user of the regression. The proposed method was tested in three sets of experiments using three different types of data. The first set of experiments worked with synthetically produced data, the second with cross sectional data from the public data source UCI Machine Learning Repository and the third with time series data from ISO-NE (Independent System Operator in New England). The experiments with synthetic data were performed to verify how the method behaves in controlled situations. In this case, the outcomes of the experiments produced superior results with respect to predictions improvement for artificially produced cleaner datasets with progressive worsening with the addition of increased random elements. The experiments with real data extracted from UCI and ISO-NE were done to investigate the applicability of the methodology in the real world. The proposed method was able to improve regression prediction values by about 95% of the experiments with real data.

A Novel Prediction Method for Early Recognition of Global Human Behaviour in Image Sequences

Human behaviour recognition has been, and still remains, a challenging problem that involves different areas of computational intelligence. The automated understanding of people activities from video sequences is an open research topic in which the computer vision and pattern recognition areas have made big efforts. In this paper, the problem is studied from a prediction point of view. We propose a novel method able to early detect behaviour using a small portion of the input, in addition to the capabilities of it to predict behaviour from new inputs. Specifically, we propose a predictive method based on a simple representation of trajectories of a person in the scene which allows a high level understanding of the global human behaviour. The representation of the trajectory is used as a descriptor of the activity of the individual. The descriptors are used as a cue of a classification stage for pattern recognition purposes. Classifiers are trained using the trajectory representation of the complete sequence. However, partial sequences are processed to evaluate the early prediction capabilities having a specific observation time of the scene. The experiments have been carried out using the three different dataset of the CAVIAR database taken into account the behaviour of an individual. Additionally, different classic classifiers have been used for experimentation in order to evaluate the robustness of the proposal. Results confirm the high accuracy of the proposal on the early recognition of people behaviours.

U.S. policy toward Panama, 1903-present : questions of recognition and diplomatic relations and instances of U.S. intervention.

"Reprint from the Department of State Bulletin, April 22, 1974. Research Project no. 1066c (Revised)."

Recognition; with an outline of a theory of knowledge.

Mode of access: Internet.

The recognition policy of the United States since 1901,

Bibliography: p. 101-104.

Principles and techniques of drug recognition expert training. The DRE Instructor Training School teacher-trainer manual.

National Highway Traffic Safety Administration, Washington, D.C.

Principles and techniques of drug recognition expert training. The DRE Instructor Training School student-instructor manual.

National Highway Traffic Safety Administration, Washington, D.C.

Age effects on symbol sign recognition. Final report.

Federal Highway Administration, Washington, D.C.

Trainable character recognition interface computer (INCOM) /

"UILU-ENG 78 1737."

Decision structures for recognition.

Mode of access: Internet.

On-line character recognition /

Bibliography: p. 14.

The Illinois pattern recognition computer (Illiac III) /

"Presented at the 18th Annual ACM National Conference, Denver, Colorado August 27, 1963"

Pattern recognition as knowledge-guided computer induction /

Bibliography: p. 39-41.

Project Para, perceiving and recognition automata; final report.

"Contract no. Nonr-2381-(00)NR 048-121."