A new development on ANN in China - Biomimetic pattern recognition and multi weight vector neurons

A new model of pattern recognition principles-Biomimetic Pattern Recognition, which is based on "matter cognition" instead of "matter classification", has been proposed. As a important means realizing Biomimetic Pattern Recognition, the mathematical model and analyzing method of ANN get breakthrough: a novel all-purpose mathematical model has been advanced, which can simulate all kinds of neuron architecture, including RBF and BP models. As the same time this model has been realized using hardware; the high-dimension space geometry method, a new means to analyzing ANN, has been researched.

A new development on ANN in China - Biomimetic pattern recognition and multi weight vector neurons

A new model of pattern recognition principles-Biomimetic Pattern Recognition, which is based on "matter cognition" instead of "matter classification", has been proposed. As a important means realizing Biomimetic Pattern Recognition, the mathematical model and analyzing method of ANN get breakthrough: a novel all-purpose mathematical model has been advanced, which can simulate all kinds of neuron architecture, including RBF and BP models. As the same time this model has been realized using hardware; the high-dimension space geometry method, a new means to analyzing ANN, has been researched.

Aptamer-based label-free method for hemin recognition and DNA assay by capillary electrophoresis with chemiluminescence detection

An aptamer-based label-free approach to hemin recognition and DNA assay using capillary electrophoresis with chemiluminescence detection is introduced here. Two guanine-rich DNA aptamers were used as the recognition element and target DNA, respectively. In the presence of potassium ions, the two aptamers folded into the G-quartet structures, binding hemin with high specificity and affinity. Based on the G-quartet-hemin interactions, the ligand molecule was specifically recognized with a K (d)approximate to 73 nM, and the target DNA could be detected at 0.1 mu M. In phosphate buffer of pH 11.0, hemin catalyzed the H2O2-mediated oxidation of luminol to generate strong chemiluminescence signal; thus the target molecule itself served as an indicator for the molecule-aptamer interaction, which made the labeling and/or modification of aptamers or target molecules unnecessary. This label-free method for molecular recognition and DNA detection is therefore simple, easy, and effective.

An ancient C-type lectin in Chlamys farreri (CfLec-2) that mediate pathogen recognition and cellular adhesion

C-type lectins are a superfamily of Ca2+ dependent carbohydrate-recognition proteins which play significant diverse roles in nonself-recognition and clearance of invaders. In the present study, a C-type lectin (CfLec-2) from Zhikong scallop Chlamys farreri was selected to investigate its functions in innate immunity. The mRNA expression of CfLec-2 in hemocytes was significantly up-regulated (P < 0.01) after scallops were stimulated by LPS. PGN or beta-glucan, and reached the highest expression level at 12h post-stimulation, which was 72.5-, 23.6- or 43.8-fold compared with blank group, respectively. The recombinant Cflec-2 (designated as rCfLec-2) could bind LPS, PGN, mannan and zymosan in vitro, but it could not bind beta-glucan. Immunofluorescence assay with polyclonal antibody specific for Cflec-2 revealed that CfLec-2 was mainly located in the mantle, kidney and gonad. Furthermore, rCfLec-2 could bind to the surface of scallop hemocytes, and then initiated cellular adhesion and recruited hemocytes to enhance their encapsulation in vitro, and this process could be specifically blocked by anti-rCfLec-2 serum. These results collectively suggested that CfLec-2 from the primitive deuterostome C. farreri could perform two distinct immune functions, pathogen recognition and cellular adhesion synchronously, while these functions were performed by collectins and selectins in vertebrates, respectively. The synchronous functions of pathogen recognition and cellular adhesion performed by CfLec-2 tempted us to suspect that CfLec-2 was an ancient form of C-type lectin, and apparently the differentiation of these two functions mediated by C-type lectins occurred after mollusk in phylogeny. (C) 2010 Elsevier Ltd. All rights reserved.

Computer-assisted automatic peak recognition and result evaluation for analysis of chlorinated hydrocarbons in environmental samples

A data manipulation method has been developed for automatic peak recognition and result evaluation in the analysis of organic chlorinated hydrocarbons with dual-column gas chromatography. Based on the retention times of two internal standards, pentachlorotoluene and decachlorobiphenyl, the retention times of chlorinated hydrocarbons can be calibrated automatically and accurately. It is very convenient to identify the peaks by comparing the retention times of samples with the calibrated retention times calculated from the relative retention indices of standards. Meanwhile, with a suggested two-step evaluation method the evaluation coefficients and the suitable quantitative results of each component can be automatically achieved for practical samples in an analytical system using two columns with different polarities and two internal standards. (C) 2002 Elsevier Science B.V. All rights reserved.

Some Extensions of the K-Means Algorithm for Image Segmentation and Pattern Classification

In this paper we present some extensions to the k-means algorithm for vector quantization that permit its efficient use in image segmentation and pattern classification tasks. It is shown that by introducing state variables that correspond to certain statistics of the dynamic behavior of the algorithm, it is possible to find the representative centers fo the lower dimensional maniforlds that define the boundaries between classes, for clouds of multi-dimensional, mult-class data; this permits one, for example, to find class boundaries directly from sparse data (e.g., in image segmentation tasks) or to efficiently place centers for pattern classification (e.g., with local Gaussian classifiers). The same state variables can be used to define algorithms for determining adaptively the optimal number of centers for clouds of data with space-varying density. Some examples of the applicatin of these extensions are also given.

View-Based Models of 3D Object Recognition and Class-Specific Invariances

This paper describes the main features of a view-based model of object recognition. The model tries to capture general properties to be expected in a biological architecture for object recognition. The basic module is a regularization network in which each of the hidden units is broadly tuned to a specific view of the object to be recognized.

Gait Dynamics for Recognition and Classification

This paper describes a representation of the dynamics of human walking action for the purpose of person identification and classification by gait appearance. Our gait representation is based on simple features such as moments extracted from video silhouettes of human walking motion. We claim that our gait dynamics representation is rich enough for the task of recognition and classification. The use of our feature representation is demonstrated in the task of person recognition from video sequences of orthogonal views of people walking. We demonstrate the accuracy of recognition on gait video sequences collected over different days and times, and under varying lighting environments. In addition, preliminary results are shown on gender classification using our gait dynamics features.

Augmenting an artificial immune network using ordering, self-recognition and histo-compatibility operators.

Timmis J Neal M J and Hunt J. Augmenting an artificial immune network using ordering, self-recognition and histo-compatibility operators. In Proceedings of IEEE international conference of systems, man and cybernetics, pages 3821-3826, San Diego, 1998. IEEE.

Fault identification through the combination of symbolic conflict recognition and Markov Chain-aided belief revision

F. Smith and Q. Shen. Fault identification through the combination of symbolic conflict recognition and Markov Chain-aided belief revision. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 34(5):649-663, 2004.

Image Digestion and Relevance Feedback in the ImageRover WWW Search Engine

ImageRover is a search by image content navigation tool for the world wide web. The staggering size of the WWW dictates certain strategies and algorithms for image collection, digestion, indexing, and user interface. This paper describes two key components of the ImageRover strategy: image digestion and relevance feedback. Image digestion occurs during image collection; robots digest the images they find, computing image decompositions and indices, and storing this extracted information in vector form for searches based on image content. Relevance feedback occurs during index search; users can iteratively guide the search through the selection of relevant examples. ImageRover employs a novel relevance feedback algorithm to determine the weighted combination of image similarity metrics appropriate for a particular query. ImageRover is available and running on the web site.

View-Invariant Object Category Learning, Recognition, and Search: How Spatial and Object Attention Are Coordinated Using Surface-Based Attentional Shrouds

Air Force Office of Scientific Research (F49620-01-1-0397); National Science Foundation (SBE-0354378); Office of Naval Research (N00014-01-1-0624)