Using Description Logics to specify a Document Synthesis System

Very large scale integration (VLSI) circuit comprises of integrated circuit (IC) with transistors in a single chip, widely used in many sophisticated electronic devices. In our paper, we proposed VLSI circuit design by implementing satisfiability problem in Hopfield neural network as circuit verification technique. We restrict our logic construction to 2-Satisfiab ility (2-SAT) and 3-Satisfiability (3-SAT) clauses in order to suit with the transistor configuration in VLSI circuit. In addit ion, we developed VLSI circu it based on Hopfield neural network in order to detect any possible error earlier than the manual circuit design. Microsoft Visual C++ 2013 is used as a platform for train ing, testing and validating of our proposed design. Hence, the performance o f our proposed technique evaluated based on global VLSI configuration, circuit accuracy and the runtime. It has been observed that the VLSI circu its (HNN-2SAT and HNN-3SAT circuit) developed by proposed design are better than the conventional circu it due to the early erro r detection in our circuit.

Section: B Vlsi Reconstructionmentioning

confidence: 99%

VLSI Circuit Configuration Using Satisfiability Logic in Hopfield Network

Mansor¹,

Kasihmuddin²,

Sathasivam³

2016

“…This theory applies on every walk of our life and the same is true for writing, synthesizing and identification in a document [22,26] of a word processing application or searching a query in a web browser. Today, the word processing applications, text editors, web browsers and spam detection [21], etc., on our machines are satisfying human typing needs quite efficiently and the facility of character/word/sentence prediction and recognition [23] becomes a tool to reduce the time of human typing on machines.…”

Section: Introductionmentioning

confidence: 99%

A Stochastic Prediction Interface for Urdu

Abbas

2014

Abstract-This work lays down a foundation for text prediction of an inflected and under-resourced language Urdu. The interface developed is not limited to a T9 (Text on 9 keys) application used in embedded devices, which can only predict a word after typing initial characters. It is capable of predicting a word like T9 and also a sequence of word after a word in a continuous manner for fast document typing. It is based on Ngram language model. This stochastic interface deals with three N-gram levels from unary to ternary independently. The unigram mode is being in use for applications like T9, while the bigram and tri-gram modes are being in use for sentence prediction. The measures include a percentage of keystrokes saved, keystrokes until completion and a percentage of time saved during the typing. Two different corpora are merged to build a sufficient amount of data. The test data is divided into a test and a held out data equally for an experimental purpose. This whole exercise enables the QASKU system outperforms the FastType with almost 15% more saved keystrokes.

“…And allows to define The minimal language AL as -contains the atomic concepts, the universal concept, the bottom concept, atomic negation, intersection, value restriction and limited existential quantificat ion‖. [1].It leads to seeking for best reasoning Algorith ms based on these definitions.…”

Section: Introductionmentioning

confidence: 99%

Proposed Representation Approach Based on Description Logics Formalism

Yahiaoui¹,

Lehireche²,

Bouchiha³

2016

Abstract-The most familiar concept in Artificial intelligence is the knowledges representation. It aims to find exp licit symbolizat ion covering all semantic aspects of knowledge, and to make possible the use of this representation to produce an intelligent behavior like reasoning.The most important constraint is the usability of the representation; it's why the structures used must be well defined to facilitate manipulation for reasoning algorithms which leads to facilitate their implementation.In this paper we propose a new approach based on the description logics formalis m for the goal o f simp lification of description logics system imp lementation. This approach can reduce the complexity of reasoning Algorith m by the vectorisation of concept definition based on the subsumption hierarchy.