14570877
Genetic Elevator Group Control
In a tall building with multiple elevators, it is a notoriously di cult task to control the elevators in the most e cient manner [1].The system proposed in this paper contains two key ideas. First, it continuously generates dispatch functions by adaptation to changes in passenger tra c. Second, it tries to reduce passengers' waiting time by multiple elevator allocation when it is expected that one elevator cannot serve all the passengers for a hall call at a oor.
7572098
New Usage of SOM for Genetic Algorithms
Self-Organizing Map (SOM) is an unsupervised learning neural network and it is used for preserving the structural relationships in the data without prior knowledge. SOM has been applied in the study of complex problems such as vector quantizations, combinatorial optimization, and pattern recognition. This paper proposes a new usage of SOM as a tool for schema transformation hoping to achieve more efficient genetic process. Every offspring is transformed into an isomorphic neural network with more desirable shape for genetic search. This helps genes with strong epistasis to stay close together in the chromosome. Experimental results showed considerable improvement over previous results.
33321332
Learning Information Extraction Rules for Protein Annotation from Unannotated Corpora
As the number of published papers on proteins increases rapidly, manual protein annotation for biological sequence databases faces the problem of catching up with the speed of publication. Automated information extraction for protein annotation offers a solution to this problem. Generally, information extraction tasks have relied on the availability of pre-defined templates as well as annotated corpora. However, in many real world applications, it is difficult to fulfill this requirement; only relevant sentences for target domains can be easily collected. At the same time, other resources can be harnessed to compensate for this difficulty: natural language processing provides reliable tools for syntactic text analysis, and in bio-medical domains, there is a large amount of background knowledge available, e.g., in the form of ontologies. In this paper, we present a method for learning information extraction rules without pre-defined templates or labor-intensive pre-annotation by exploiting various types of background knowledge in an inductive logic programming framework.
2320085
Generating random regular graphs
Random regular graphs play a central role in combinatorics and theoretical computer science. In this paper, we analyze a simple algorithm introduced by Steger and Wormald [9] and prove that it produces an asymptotically uniform random regular graph in a polynomial time. Precisely, for fixed d and n with d=O(n1/3-ε), it is shown that the algorithm generates an asymptotically uniform random d-regular graph on n vertices in time O(nd2). This confirms a conjecture of Wormald. The key ingredient in the proof is a recently developed concentration inequality by the second author.Besides being perhaps the only algorithm which works for relatively large d in practical time, our result also has a significant theoretical value, as it can be used to derive many properties of uniform random regular graphs.
42381820
An Improvement of VeriSign's Key Roaming Service Protocol
In the past two or three years, most major Public Key Infrastructure (PKI) vendors have released products which allow users to roam from one machine to another without having to manually manage the export and import of their credentials such as private keys and corresponding certificates onto temporary media like diskettes. In this paper, we survey three popular key roaming products of Baltimore's, Entrust's and VeriSign's. We also propose key roaming system which improves VeriSign's roaming service and analyze its security.
6014517
The Real-Time Development and Deployment of a Cooperative Multi-UAV System
This paper presents a systems view of the Autonomous Nav- igation and Sensing Experimental Research (ANSER) project. ANSER is one of the most advanced UAV projects of its kind, which is aimed at demonstrating Decentralised Data Fusion (DDF) and Simultaneous Localisation and Map (SLAM) building on multiple cooperative UAVs. The demonstration of DDF and SLAM require both navigation and terrain sensors to be carried onboard by the UAVs. These include an INS/GPS navigation system, millimeter wave (MMW) radar, and both a single vision node and a vision node augmented with a laser system. This paper presents the implementation of the algorithms, sensors and platforms, along with their interaction to address this demonstration. Furthermore, the paper will present the high fidelity real time simulator which is implemented to thoroughly test all algorithms and sensors before actual implementation in the environment.
6458402
METIS: multiple extraction techniques for informative sentences
SUMMARY
METIS is a web-based integrated annotation tool. From single query sequences, the PRECIS component allows users to generate structured protein family reports from sets of related Swiss-Prot entries. These reports may then be augmented with pertinent sentences extracted from online biomedical literature via support vector machine and rule-based sentence classification systems.


AVAILABILITY
http://umber.sbs.man.ac.uk/dbbrowser/metis/