6828280
Automatic Identification of Diatoms Using Visual Human-Interpretable Features
In this paper we present an identification scheme for diatoms using visual human-interpretable features. Diatoms are unicellular algae found in water and other places wherever there is humidity and enough light for photosynthesis. The automatic identification of diatoms has applications in a number of areas, for example, environmental monitoring and climate research. The overall identification is performed by an ensemble of multiple decision trees following the bagging approach. The use of human-interpretable features in contrast to traditional features, such as Fourier descriptors or moment invariants, makes it possible for a human expert to verify the induced decision trees and opens up the possibility of integrating human expert knowledge into automatically derived decision trees.
46027337
Identification of Diatoms by Grid Graph Matching
Diatoms are unicellular algae found in water and other places wherever there is humidity and enough light for photo synthesis. In this paper a graph matching based identification approach for the retrieval of diatoms from an image database is presented. The retrieval is based on the matching of labeled grid graphs carrying texture information of the underlying diatom. A grid graph is a regular, rectangular arrangement of nodes overlaid on an image. Each node of the graph is labeled with texture features describing a rectangular sub-region of the object. Properties of gray level co-occurrence matrices as well as of Gabor wavelets are used as texture features. The method has been evaluated on a diatom database holding images of 188 different diatoms belonging to 38 classes. For the identification of these diatoms recognition rates of more than 90 percent were obtained.
13590402
Nonuniform charge scaling (NUCS): A practical approximation of solvent electrostatic screening in proteins
In molecular mechanics calculations, electrostatic interactions between chemical groups are usually represented by a Coulomb potential between the partial atomic charges of the groups. In aqueous solution these interactions are modified by the polarizable solvent. Although the electrostatic effects of the polarized solvent on the protein are well described by the Poisson--Boltzmann equation, its numerical solution is computationally expensive for large molecules such as proteins. The procedure of nonuniform charge scaling (NUCS) is a pragmatic approach to implicit solvation that approximates the solvent screening effect by individually scaling the partial charges on the explicit atoms of the macromolecule so as to reproduce electrostatic interaction energies obtained from an initial Poisson--Boltzmann analysis. Once the screening factors have been determined for a protein the scaled charges can be easily used in any molecular mechanics program that implements a Coulomb term. The approach is particularly suitable for minimization-based simulations, such as normal mode analysis, certain conformational reaction path or ligand binding techniques for which bulk solvent cannot be included explicitly, and for combined quantum mechanical/molecular mechanical calculations when the interface to more elaborate continuum solvent models is lacking. The method is illustrated using reaction path calculations of the Tyr 35 ring flip in the bovine pancreatic trypsin inhibitor.
2647352
Experiences with an Emotional Sales Agent
With COSIMAB2B we demonstrate a prototype of a complex and visionary e-procurement application. The embodied character agent named COSIMA is able to respect a customer’s preferences and deals with him or her via natural speech. She expresses various emotions via mimic, gesture, combined with speech synthesis, and COSIMA is even able to consider the customer’s emotions via mimic recognition. As first observations show, this is a very promising approach to improve the bargaining with the customer or the recommendation of products.
16636819
Fusion of audio and video information for multi modal person authentication
Abstract We present an algorithm functioning as a supervisor module in a multi-expert decision making machine. It uses the Bayes theory in order to estimate the biases of individual expert opinions. The biases are used to calibrate and conciliate expert opinions to a single decision. This supervision technique is applied to the real case of a person authentication technique using two modalities, face and speech. The visual part involves the matching of a coarse grid containing Gabor phase information from face images. The acoustic part is performed by a text-dependent speaker verification system based on Hidden Markov Models. Experimental results show that the proposed fusion method improves the quality of individual expert decisions by reaching success rates of 99.5%.
20140082
COSIMA/sup B2B/ - sales automation for e-procurement
We present a fully automated electronic sales agent for e-procurement portals. The key technologies for this breakthrough are based on preferences modeled as strict partial orders, enabling a deep personalization of the B2B sales process. The interplay of several novel middleware components achieves to automate skills that so far could be executed only by a human vendor. As personalized search engine for XML based e-catalogs, we use Preference XPath; the Preference Presenter implements a sales psychology based presentation of search results, supporting various human sales strategies; the Preference Repository provides the management of situated long-term preferences; the flexible Personalized Price Offer and the multi-objective Preference Bargainer provide a personalized price fixing and the opportunity to bargain about the price of an entire product bundle, applying up/cross and down selling techniques. Our prototype COSIMA/sup B2B/, supported by industrial partners, has been successfully demonstrated at a large computer fair.
39591573
COSIMA- your smart, speaking E-salesperson
We present a new cooperative user interface for e-shopping. COSIMA is an intelligent Internet avatar with dynamic voice output that assists customers through their e-shopping tours and advises them like a real salesperson. COSIMA uses a meta search engine based on Preference SQL, computing best matching results to the customer's wishes. COSIMA can qualify these results and generates proper voice output. Our presentation shows COSIMA in action for comparison shopping.