A framework for incremental learning of logic programs

AbstractIn this paper, a framework for incremental learning is proposed. The predicates already learned are used as background knowledge in learning new predicates in this framework. The programs learned in this way have nice modular structure with conceptually separate components. This modularity gives the advantages of portability, reliability and efficient compilation and execution.Starting with a simple idea of Miyano et al. [21,22] for identifying classes of programs which satisfy the condition that all the terms occurring SLD-derivations starting with a query are no bigger than the terms in the initial query, we identify a reasonably big class of polynomial time learnable logic programs. These programs can be learned from a given sequence of examples and a logic program defining the already known predicates. Our class properly contains the class of innermost simple programs of [32] and the class of hereditary programs of [21,22]. Standard programs for gcd, multiplication, quick-sort, reverse and merge are a few examples of programs that can be handled by our results but not by the earlier results of [21,22, 32]

On "learning term rewriting systems from entailment"

Summary form only given. We study exact learning of term rewriting systems from entailment and refute a recent result by Arimura, Sakamoto and Arikawa about polynomial time learnability of k-variable linear tree translations (LTT (k)). It was incorrectly claimed that the length of derivations of LTT (k) is bounded by a polynomial in the size of the initial term. This claim led to their result on polynomial time learnability of LTT (k). We present a simple system in the class of 1-variable linear tree translations that has a derivation of exponential length. We also discuss why it is difficult to syntactically separate the rewriting systems defining polynomial functions and the rewriting systems defining exponential functions. We then identify a few requirements for polynomial time learnability of rewriting systems and discuss how these requirements may be achieved

A study on the functional properties of silk and polyester / lyocell mixed fabric

ABSTRACT Silk is one of the valuable fibers in textile industry. It is used for delicate applications in many areas such as sarees, suitings, curtains and luxurious interiors. To diversify the properties and usages silk is mixed with polyester and lyocell. The fabric is dyed with natural dyes (kum kum, indigo, barberry) as well as synthetic dyes (reactive dye (H), reactive dye (M) and sulphur dye). This mixed fabric is compared with 100% silk for some of the basic properties like absorbency, water retention, wicking, water vapour permeability, air permeability, K/S values, colour fastness and antimicrobial property. The silk mixed fabric gives the appreciable results with the 100% silk fabric

Transformational methodology for proving termination of logic programs

AbstractA methodology for proving the termination of well-moded logic programs is developed by reducing the termination problem of logic programs to that of term rewriting systems. A transformation procedure is presented to derive a term rewriting system from a given well-moded logic program such that the termination of the derived rewrite system implies the termination of the logic program for all well-moded queries under a class of selection rules. This facilitates applicability of a vast source of termination orderings proposed in the literature on term rewriting, for proving termination of logic programs. The termination of various benchmark programs has been established with this approach. Unlike other mechanizable approaches, the proposed approach does not require any preprocessing and works well, even in the presence of mutual recursion. The transformation has also been implemented as a front end to Rewrite Rule Laboratory (RRL) and has been used in establishing termination of nontrivial Prolog programs such as a prototype compiler for ProCoS, PL0 language

Micro Irrigation Management in Cotton

Not AvailableIndia has the second largest net irrigated area in the world, after China. The irrigation efficiency under canal irrigation is not more than 40% and for ground water schemes, it is 69%. The net irrigated area in the country is 53.5 Mha, which is about 38% of the total 'sown area. Even all the water resources have been tapped for irrigation, almost 50% area will still remain rainfed. But, whether it is irrigated or rainfed agriculture water holds the key for enhancing and sustaining agricultural production. Since, sustainability and enhanced productivity are the need of the hour, the focus has to shift from crops to cropping systems that are more input use efficient going with resource conservation technologies. Out of the 250 cropping systems in India, 30 are the most common ones and out of them, several are well fitted under drip and sprinkler irrigation system.Not Availabl

Physiological Disorders In Cotton

Not AvailablePhysiological disorders appear in cotton as a reflex of plant response to environmental stresses, nutritional imbalances and chemical factors. Their effect on productivity depends upon the crop growth stage, intensity of incidence and loss of reproductive parts during ontogeny. However, there is a distinct difference between plant adaptation to harsh growing environments and physiological disorders. The various adaptive traits in plants as a response to the stress environment such as production of small leaves during drought and lenticel formation under waterlogged condition are not considered as physiological disorders.Not Availabl