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Learning from AI : new trends in database technology
Recently some researchers in the areas of database data modelling and knowledge representations in artificial intelligence have recognized that they share many common goals. In this survey paper we show the relationship between database and artificial intelligence research. We show that there has been a tendency for data models to incorporate more modelling techniques developed for knowledge representations in artificial intelligence as the desire to incorporate more application oriented semantics, user friendliness, and flexibility has increased. Increasing the semantics of the representation is the key to capturing the "reality" of the database environment, increasing user friendliness, and facilitating the support of multiple, possibly conflicting, user views of the information contained in a database
A System of Interaction and Structure
This paper introduces a logical system, called BV, which extends
multiplicative linear logic by a non-commutative self-dual logical operator.
This extension is particularly challenging for the sequent calculus, and so far
it is not achieved therein. It becomes very natural in a new formalism, called
the calculus of structures, which is the main contribution of this work.
Structures are formulae submitted to certain equational laws typical of
sequents. The calculus of structures is obtained by generalising the sequent
calculus in such a way that a new top-down symmetry of derivations is observed,
and it employs inference rules that rewrite inside structures at any depth.
These properties, in addition to allow the design of BV, yield a modular proof
of cut elimination.Comment: This is the authoritative version of the article, with readable
pictures, in colour, also available at
. (The published version contains
errors introduced by the editorial processing.) Web site for Deep Inference
and the Calculus of Structures at <http://alessio.guglielmi.name/res/cos
NASA space station automation: AI-based technology review
Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures
Exceptions in Information Systems
The concept of exception has been defined in diverse ways. We relate exceptions to computational transactions and to control constructs. Our view of a transaction is very broad, and we consider transactional exceptions to be instances of undefined function values. By giving different interpretations to undefined we arrive at a classification of transactional exceptions. Our primary interest is in information systems, i.e., in database transactions, and in processes that consist of such transactions. In the database context we show that liberal treatment of exceptions is simpler than total quality management for consistency based on a set of constraints. We refer to control operations that link transactions into processes as actions. Actions tend to be time-related, and time Petri nets provide actions with semantics. The time Petri net representation indicates where exceptions can arise. We also consider high-level monitors for the detection of exceptions. Although our emphasis is on detection of exceptions, their handling is also discussed
Final report on the farmer's aid in plant disease diagnoses
This report is the final report on the FAD project. The FAD project was initiated in september 1985 to test the expert system shell Babylon by developing a prototype crop disease diagnosis system in it. A short overview of the history of the project and the main problems encountered is given in chapter 1. Chapter 2 describes the result of an attempt to integrate JSD with modelling techniques like generalisation and aggregation and chapter 3 concentrates on the method we used to elicit phytopathological knowledge from specialists. Chapter 4 gives the result of knowledge acquisition for the 10 wheat diseases most commonly occurring in the Netherlands. The user interface is described briefly in chapter 5 and chapter 6 gives an overview of the additions to the implementation we made to the version of FAD reported in our second report. Chapter 7, finally, summarises the conclusions of the project and gives recommendations for follow-up projects
The Level-0 Muon Trigger for the LHCb Experiment
A very compact architecture has been developed for the first level Muon
Trigger of the LHCb experiment that processes 40 millions of proton-proton
collisions per second. For each collision, it receives 3.2 kBytes of data and
it finds straight tracks within a 1.2 microseconds latency. The trigger
implementation is massively parallel, pipelined and fully synchronous with the
LHC clock. It relies on 248 high density Field Programable Gate arrays and on
the massive use of multigigabit serial link transceivers embedded inside FPGAs.Comment: 33 pages, 16 figures, submitted to NIM
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