An inventory of the ethnobotanicals used as anti-diabetic by a rural community of Dhemaji district of Assam, Northeast India

Ethnopharmacological relevance: Traditional remedies used for treating diabetic ailments are very important in the primary health care of the people living in rural Dhemaji district of Assam, north-east India. Novel information gathered from the current survey is important in preserving folk indigenous knowledge. Materials and methods: Interviews were conducted amongst 80 households comprising of 240 individuals using semi-structured questionnaires. The focus was on plants used in treating diabetes mellitus. Results: The current survey documented 21 plant species (20 families) which are reportedly used to treat diabetes mellitus by the rural people in the study area. To the best of our knowledge, Amomum linguiforme, Cinnamomum impressinervium, Colocasia esculenta, Dillenia indica, Euphorbia ligularia, Garcinia pedunculata, Solanum indicum, Sterculia villosa and Tabernaemontana divaricata are recorded for the first time based on globally published literature as medicinal plants used for treating diabetes mellitus and related symptoms. Conclusions: The wide variety of plants that are used to treat diabetes mellitus in this area supports the traditional value that medicinal plants have in the primary health care system of the rural people of Dhemaji district of Assam. The finding of new plant uses in the current study reveals the importance of the documentation of such ethnobotanical knowledge. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

Representation of evidence: An approach to uncertainty handling in knowledge-based systems

Many knowledge based systems (KBS) transform a situation information into an appropriate decision using an in built knowledge base. As the knowledge in real world situation is often uncertain, the degree of truth of a proposition provides a measure of uncertainty in the underlying knowledge. This uncertainty can be evaluated by collecting `evidence' about the truth or falsehood of the proposition from multiple sources. In this paper we propose a simple framework for representing uncertainty in using the notion of an evidence space.

Knowledge-Based Approach Using Support Vector Machine for Transmission Line Distance Relay Co-ordination

In this paper, knowledge-based approach using Support Vector Machines (SVMs) are used for estimating the coordinated zonal settings of a distance relay. The approach depends on the detailed simulation studies of apparent impedance loci as seen by distance relay during disturbance, considering various operating conditions including fault resistance. In a distance relay, the impedance loci given at the relay location is obtained from extensive transient stability studies. SVMs are used as a pattern classifier for obtaining distance relay co-ordination. The scheme utilizes the apparent impedance values observed during a fault as inputs. An improved performance with the use of SVMs, keeping the reach when faced with different fault conditions as well as system power flow changes, are illustrated with an equivalent 265 bus system of a practical Indian Western Grid.

Herbal medicines used in the treatment of diabetes mellitus in Arunachal Himalaya, northeast, India

Ethnopharmacological relevance: Medicinal plants have played an important role in treating and preventing a variety of diseases throughout the world. Khampti tribal people living in the far-flung Lohit district of the Eastern Arunachal Himalaya, India still depend on medicinal plants and most of them have a general knowledge of medicinal plants which are used for treating a variety of ailments. This survey was undertaken in Lohit district in order to inventory the medicinal plants used in folk medicine to treat diabetes mellitus. Materials and methods: Field investigations were conducted in seventeen remote villages of Lohit district starting from April 2002 to May 2004 through interviews among 251 key informants who were selected randomly during our household survey. To elucidate community domains and determine differences in indigenous traditional knowledge of medicinal plants with anti-diabetic efficacy, we repeated our field survey starting from April 2008 to May 2010 with one hundred traditional healers locally called as ``Chau ya'' in Khampti of Lohit district. ``Chau ya'' traditional healers who know and use medicinal plants for treating diabetes mellitus were interviewed using a semi-structured questionnaire. Results: This study reports an ethnobotanical survey of medicinal plants in Lohit district of Arunachal Pradesh reputed for the treatment of diabetes mellitus. Forty-six plant species were identified in the study area to treat diabetes mellitus by the Khamptis ``Chau ya'' traditional healers. Comparative published literature survey analysis of this study with other ethnobotanical surveys of plants used traditionally in treating diabetes mellitus suggests that eleven plant species make claims of new reports on antidiabetic efficacy. These plant species are Begonia roxburghii, Calamus tenuis, Callicarpa arborea, Cuscuta reflexa, Dillenia indica, Diplazium esculentum, Lectuca gracilis, Millingtonia hortensis, Oxalis griffithii, Saccharum spontaneum, and Solanum viarum. Some of the plants reported in this study have an antidiabetic effect on rodent models but none have sufficient clinical evidence of effectiveness. Conclusions: The wide variety of medicinal plants that are used to treat diabetes mellitus in this area supports the importance of plants in the primary healthcare system of the rural people of Lohit district of Arunachal Pradesh. The finding of new plant uses in the current study reveals the importance of the documentation of such ethnobotanical knowledge. (C) 2012 Elsevier Ireland Ltd. All rights reserved.

Combining product information and process information to build virtual assembly situations for knowledge acquisition

Assembly is an important part of the product development process. To avoid potential issues during assembly in specialized domains such as aircraft assembly, expert knowledge to predict such issues is helpful. Knowledge based systems can act as virtual experts to provide assistance. Knowledge acquisition for such systems however, is a challenge, and this paper describes one part of an ongoing research to acquire knowledge through a dialog between an expert and a knowledge acquisition system. In particular this paper discusses the use of a situation model for assemblies to present experts with a virtual assembly and help them locate the specific context of the knowledge they provide to the system.

Zero knowledge one time digital signature scheme

In many applications, when communicating with a host, we may or may not be concerned about the privacy of the data but are mainly concerned about the integrity of data being transmitted. This paper presents a simple algorithm based on zero knowledge proof by which the receiver can confirm the integrity of data without the sender having to send the digital signature of the message directly. Also, if the same document is sent across by the same user multiple times, this scheme results in different digital signature each time thus making it a practical one-time signature scheme.

A questioning based method to automatically acquire expert assembly diagnostic knowledge

In the domain of manual mechanical assembly, expert knowledge is an important means of supporting assembly planning that leads to fewer issues during actual assembly. Knowledge based systems can be used to provide assembly planners with expert knowledge as advice. However, acquisition of knowledge remains a difficult task to automate, while manual acquisition is tedious, time-consuming, and requires engagement of knowledge engineers with specialist knowledge to understand and translate expert knowledge. This paper describes the development, implementation and preliminary evaluation of a method that asks a series of questions to an expert, so as to automatically acquire necessary diagnostic and remedial knowledge as rules for use in a knowledge based system for advising assembly planners diagnose and resolve issues. The method, called a questioning procedure, organizes its questions around an assembly situation which it presents to the expert as the context, and adapts its questions based on the answers it receives from the expert. (C) 2014 Elsevier Ltd. All rights reserved.

Segregating Discourse Segments from Engineering Documents for Knowledge Acquisition

The broader goal of the research being described here is to automatically acquire diagnostic knowledge from documents in the domain of manual and mechanical assembly of aircraft structures. These documents are treated as a discourse used by experts to communicate with others. It therefore becomes possible to use discourse analysis to enable machine understanding of the text. The research challenge addressed in the paper is to identify documents or sections of documents that are potential sources of knowledge. In a subsequent step, domain knowledge will be extracted from these segments. The segmentation task requires partitioning the document into relevant segments and understanding the context of each segment. In discourse analysis, the division of a discourse into various segments is achieved through certain indicative clauses called cue phrases that indicate changes in the discourse context. However, in formal documents such language may not be used. Hence the use of a domain specific ontology and an assembly process model is proposed to segregate chunks of the text based on a local context. Elements of the ontology/model, and their related terms serve as indicators of current context for a segment and changes in context between segments. Local contexts are aggregated for increasingly larger segments to identify if the document (or portions of it) pertains to the topic of interest, namely, assembly. Knowledge acquired through such processes enables acquisition and reuse of knowledge during any part of the lifecycle of a product.

PIB: Profiling Influential Blogger in Online Social Networks, A Knowledge Driven Data Mining Approach

Online Social Networks (OSNs) facilitate to create and spread information easily and rapidly, influencing others to participate and propagandize. This work proposes a novel method of profiling Influential Blogger (IB) based on the activities performed on one's blog documents who influences various other bloggers in Social Blog Network (SBN). After constructing a social blogging site, a SBN is analyzed with appropriate parameters to get the Influential Blog Power (IBP) of each blogger in the network and demonstrate that profiling IB is adequate and accurate. The proposed Profiling Influential Blogger (PIB) Algorithm survival rate of IB is high and stable. (C) 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).