A survey of indian logic from the point of view of computer science

Indian logic has a long history. It somewhat covers the domains of two of the six schools (darsanas) of Indian philosophy, namely, Nyaya and Vaisesika. The generally accepted definition of Indian logic over the ages is the science which ascertains valid knowledge either by means of six senses or by means of the five members of the syllogism. In other words, perception and inference constitute the subject matter of logic. The science of logic evolved in India through three ages: the ancient, the medieval and the modern, spanning almost thirty centuries. Advances in Computer Science, in particular, in Artificial Intelligence have got researchers in these areas interested in the basic problems of language, logic and cognition in the past three decades. In the 1980s, Artificial Intelligence has evolved into knowledge-based and intelligent system design, and the knowledge base and inference engine have become standard subsystems of an intelligent system. One of the important issues in the design of such systems is knowledge acquisition from humans who are experts in a branch of learning (such as medicine or law) and transferring that knowledge to a computing system. The second important issue in such systems is the validation of the knowledge base of the system i.e. ensuring that the knowledge is complete and consistent. It is in this context that comparative study of Indian logic with recent theories of logic, language and knowledge engineering will help the computer scientist understand the deeper implications of the terms and concepts he is currently using and attempting to develop.

An ethnobotanical survey of medicinal plants in the Eastern Himalayan zone of Arunachal Pradesh, India

Aim of the study: The medicinal plants are integral source of easily available remedy used in rural healthcare system. This study was conducted among three major ethnic groups namely the Nocte, the Nyishi and the Adi in the Eastern Himalayan region of Arunachal Pradesh to evaluate their comparative knowledge on medicinal plants. Materials and methods: The three remote districts of Arunachal Pradesh namely the Tirap, the Dibang Valley and the Papum Pare were surveyed through interviewing of randomly selected 237 participants using semi-structured questionnaire and regular field visits to selected districts. Results: We recorded the traditional use of 74 medicinal plants species belonging to 41 taxonomic plant families used for treating a total of 25 different diseases/ailments. The informant consensus factor (ICF) values demonstrated that local people tend to agree more with each other in terms of the plants used to treat malaria (0.71), jaundice (0.62), urological problems (0.56), dermatological disorders (0.45), pain (0.30), and respiratory disorder (0.33), and while the general health (0.15) and gastro-intestinal disorders category (0.28) were found low ICF values. Conclusion: Of the total 74 species recorded, the highest number of medicinal plants (36 species) was reported from the Adi of Lower Dibang Valley followed by the Nocte of the Tirap (25 species) and the Nyishi ethnic groups of Papum Pare districts (13 species). In the present study, we found that the men, elder people and illiterate ones had better knowledge on medicinal plants as compared to women, younger and literate people. Findings of this documentation study can be used as an ethnopharmacological basis for selecting plants for future phytochemical and pharmaceutical studies. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

A survey of temporal data mining

Data mining is concerned with analysing large volumes of (often unstructured) data to automatically discover interesting regularities or relationships which in turn lead to better understanding of the underlying processes. The field of temporal data mining is concerned with such analysis in the case of ordered data streams with temporal interdependencies. Over the last decade many interesting techniques of temporal data mining were proposed and shown to be useful in many applications. Since temporal data mining brings together techniques from different fields such as statistics, machine learning and databases, the literature is scattered among many different sources. In this article, we present an overview of techniques of temporal data mining.We mainly concentrate on algorithms for pattern discovery in sequential data streams.We also describe some recent results regarding statistical analysis of pattern discovery methods.

Peptide delta-Turn: Literature Survey and Recent Progress

Among the various types of a-peptide folding motifs, delta-turn, which requires a central cis-amide disposition, has been one of the least extensively investigated. In particular, this main-chain reversal topology has been studied in-depth neither in linear/cyclic peptides nor in proteins. This Minireview article assembles and critically analyzes relevant data from a literature survey on the d-turn conformation in those compounds. Unpublished results from recent conformational energy calculations and a preliminary solution-state analysis on a small model peptide, currently ongoing in our laboratories, are also briefly outlined.