27008190
Tutorial: Using TPS for Higher-Order Theorem Proving and ETPS for Teaching Logic
TPS is an automated theorem proving system which can be used to prove theorems of first- or higher-order logic automatically, interactively, or in a combination of these modes of operation. Proofs in TPS are presented in natural deduction style. ETPS is a program which was obtained from TPS by deleting all the facilities for proving theorems automatically. ETPS can be used by students to learn how to prove theorems interactively. The objective of the tutorial is to teach participants how to make effective use of TPS and ETPS.
13531439
Combining Type Theory and Untyped Set Theory
We describe a dependent type theory with proof irrelevance. Within this framework, we give a representation of a form of Mac Lane set theory and discuss automated support for constructing proofs within this set theory. One of the novel aspects of the representation is that one is allowed to use any class (in the set theory) as a type (in the type theory). Such class types allow a natural way of representing partial functions (e.g., the first and second operators on the class of Kuratowski ordered pairs). We also discuss how automated search can be used to construct proofs. In particular, the first-order prover Vampire can be called to solve a challenge problem (the injective Cantor Theorem) which is notoriously difficult for higher-order automated provers.
14859195
Solving for Set Variables in Higher-Order Theorem Proving
In higher-order logic, we must consider literals with flexible (set variable) heads. Set variables may be instantiated with logical formulas of arbitrary complexity. An alternative to guessing the logical structures of instantiations for set variables is to solve for sets satisfying constraints. Using the Knaster-Tarski Fixed Point Theorem [15], constraints whose solutions require recursive definitions can be solved as fixed points of monotone set functions. In this paper, we consider an approach to higher-order theorem proving which intertwines conventional theorem proving in the form of mating search with generating and solving set constraints.
16390848
A Fully Projective Formulation to Improve the Accuracy of Lowe's Pose-Estimation Algorithm
Both the original version of David Lowe's influential and classic algorithm for tracking known objects and a reformulation of it implemented by Ishiiet al. rely on (different) approximated imaging models. Removing their simplifying assumptions yields a fully projective solution with significantly improved accuracy and convergence, and arguably better computation-time properties.
7808447
Optimizing Long Intrinsic Disorder Predictors with Protein Evolutionary Information
Protein existing as an ensemble of structures, called intrinsically disordered, has been shown to be responsible for a wide variety of biological functions and to be common in nature. Here we focus on improving sequence-based predictions of long (>30 amino acid residues) regions lacking specific 3-D structure by means of four new neural-network-based Predictors Of Natural Disordered Regions (PONDRs): VL3, VL3H, VL3P, and VL3E. PONDR VL3 used several features from a previously introduced PONDR VL2, but benefitted from optimized predictor models and a slightly larger (152 vs. 145) set of disordered proteins that were cleaned of mislabeling errors found in the smaller set. PONDR VL3H utilized homologues of the disordered proteins in the training stage, while PONDR VL3P used attributes derived from sequence profiles obtained by PSI-BLAST searches. The measure of accuracy was the average between accuracies on disordered and ordered protein regions. By this measure, the 30-fold cross-validation accuracies of VL3, VL3H, and VL3P were, respectively, 83.6 +/- 1.4%, 85.3 +/- 1.4%, and 85.2 +/- 1.5%. By combining VL3H and VL3P, the resulting PONDR VL3E achieved an accuracy of 86.7 +/- 1.4%. This is a significant improvement over our previous PONDRs VLXT (71.6 +/- 1.3%) and VL2 (80.9 +/- 1.4%). The new disorder predictors with the corresponding datasets are freely accessible through the web server at http://www.ist.temple.edu/disprot.
12227821
DisProt: a database of protein disorder
UNLABELLED
The Database of Protein Disorder (DisProt) is a curated database that provides structure and function information about proteins that lack a fixed three-dimensional (3D) structure under putatively native conditions, either in their entirety or in part. Starting from the central premise that intrinsic disorder is an important structural class of protein and in order to meet the increasing interest thereof, DisProt is aimed at becoming a central repository of disorder-related information. For each disordered protein, the database includes the name of the protein, various aliases, accession codes, amino acid sequence, location of the disordered region(s), and methods used for structural (disorder) characterization. If applicable, most entries also list the biological function(s) of each disordered region, how each region of disorder is used for function, as well as provide links to PubMed abstracts and major protein databases.


AVAILABILITY
www.disprot.org
14596078
G-8 collaborative initiatives and the digital divide: readiness for e-government
At the G-8 Kyushu-Okinawa Summit in July 2000, the industrialized nations acknowledged the advancement of the private sector in information technology (IT) and committed the organization to the Global Digital Divide Initiative (GDDI) of the World Economic Forum Task Force. The Task Force outlined nine initiatives and a set of concrete action plans for implementation, which may achieve e-government readiness in developing countries. Major cultural variables, however, threaten to impede or thwart the facilitation of e-government, even though many countries promote e-government policies. To examine the G-8's first effort to implement collaborative policy initiatives of the private, public and non-profit sectors to eliminate the global digital divide, this paper explores the relationship between six cultural variables and the implementation of the GDDI to alleviate the digital divide and effect e-government readiness in developing countries.
34334066
Haptics in augmented reality
An augmented reality system merges synthetic sensory information into a user's perception of a three-dimensional environment. An important performance goal for an augmented reality system is that the user perceives a single seamless environment. In most augmented reality systems the user views a real world augmented only with visual information and is not provided with a means to interact with the virtual objects. We describe an augmented reality system that, in addition to visual augmentation, merges synthetic haptic input into the user's perception of the real environment. Our system uses a PHANToM/sup TM/ haptic interface device to generate the haptic sensory input in real-time. The system allows user interactions such as moving or lifting a virtual object, and demonstrates interactions between virtual and real objects. Methods to provide proper visual occlusion between real and virtual objects are also described.