Showing papers by "Saurabh Srivastava published in 2020"

A time-lapse study using self-potential and electrical resistivity tomography methods for mapping of old mine working across railway-tracks in a part of Raniganj coalfield, India

Abstract: The first coal mining in India was started in the seventeenth century with an unplanned way in Raniganj coalfield, the coal capital of India The coalfield was possessed by several small private companies which were nationalized in 1973 A part plan of Chanch/Victoria Area, Victoria West Colliery, BCCL, Raniganj Coalfield, India, indicates an underground coal mine gallery/goaf in the Begunia Coal-seam that connects to a Light Casting Factory It was established as “Barakar Iron Works” in the year 1881 by the government at that time It is understood that the approaching gallery was used for coal supply to the “Light Casting Factory” by the mining of “Begunia Coal-Seam” Mostly, these are uncharted and very poorly documented with scarce mine plans So, the present study attempts to explore the location, depth, extension, and condition of the old working gallery through time-lapse monitoring using a combined study comprising of Self-Potential (SP) and Electrical Resistivity Tomography (ERT) techniques Four SP profiles data along a line and thirteen ERT profiles data in four different lines were collected across the expected site with different station/electrode spacing covering different profile length in four seasons, viz, Summer (May 2016), Monsoon (August 2016), Post-Monsoon (October 2016) and Summer (April 2017) SP data were analysed using simulated annealing (SA) optimization technique for the evaluation of model parameters The ERT data were acquired using Wenner, Dipole–Dipole and Schlumberger arrays and inversion of the combined data set was performed using the 25D ZZRESINV inversion software Prominent negative SP signature with equivalent low resistivity anomaly have been delineated that possibly indicate the presence of the old mine working/mine gallery However, the overall results of time-lapse study inferred that the ground is stable All results are corroborated with available lithology and field photographs

Combined self-potential, electrical resistivity tomography and induced polarisation for mapping of gold prospective zones over a part of Babaikundi-Birgaon Axis, North Singhbhum Mobile Belt, India

Abstract: The Palaeo- to Meso-Proterozoic (1.0–2.4 Ga) North Singhbhum Mobile Belt (NSMB) is an assembly of multiphase folded, low- to medium-grade meta-sedimentary and meta-igneous rocks, lying within the n...

Desirable Features of a Chatbot-building Platform

Abstract: There is a visible eagerness in the business community to integrate chatbots with their websites and mobile apps. They provide a humanised interface to information and can serve as digital assistants that can perform tasks on behalf of an individual. There are many commercial platforms which provide interfaces to build these chatbots. They are used by both professional software developers as well as people from non-IT backgrounds. Based on our experiences with three popular chatbot-building platforms - Google Dialogflow, IBM Watson Assistant and Amazon Lex, we present a list of desirable features that these platforms should exhibit in order to cater to their mixed user base. We also rate the availability and ease of use of these features on the current versions of these platforms.

Seasonal and trend analysis of TWS for the Indo-Gangetic plain using GRACE data

Abstract: The GRACE satellite mission data is used to study Earth's mass variability on the Earth surface. The major component to the surface mass variability is changing terrestrial water storage (TWS). The...

Contextual Reactive Pattern on Chatbot building Platforms

Abstract: Building a chatbot with an iterative development process poses certain challenges for the chatbot developer. The developer is expected to produce a deployable version of the chatbot at the end of a short development cycle. Every iteration should incrementally increase the capability of the chatbot and implement a subset of overall user stories based upon a priority list, similar to any other project developed using iterative development. In this regard, commercial chatbot-building platforms offer multiple advantages to the chatbot developer, provided that the developer can map these user stories in a particular form. To do so, for every query the chatbot is expected to answer, the developer must evaluate the intention of the user. Based on the intention, the query must be processed differently, which may involve execution of some business logic. In addition, the processing of the query may require specific data items which the user must supply as part of the conversation with the chatbot. Thus, the chatbot is defined by supplying a "context" that it may encounter, and the "reaction" that must take place when the context is observed. In this work, we discuss the effects of using a platform to build a chatbot and discuss the Contextual Reactive pattern used for chatbot definition.

Intent Sets: Architectural Choices for Building Practical Chatbots

Abstract: "Chatbot" is a colloquial term used to refer to software components that possess the ability to interact with the end-user using natural language phrases. Many commercial platforms are offering sophisticated dashboards to build these chatbots with no or minimal coding. However, the job of composing the chatbot from real-world scenarios is not a trivial activity and requires a significant understanding of the problem as well as the domain. In this work, we present the concept of Intent Sets - an Architectural choice, that impacts the overall accuracy of the chatbot. We show that the same chatbot can be built choosing one out of many possible Intent Sets. We also present our observations collected through a set of experiments while building the same chatbot over three commercial platforms - Google Dialogflow, IBM Watson Assistant and Amazon Lex.

Achieving Privacy-Utility Trade-off in existing Software Systems

Abstract: Privacy and utility of data are two aspects of a system that are often diagonally opposite to each other. Privacy concerns drive design decisions that can reduce the ability to make deductions or correlations from a given dataset (e.g. reducing the probability that an individual could be recognized from a given set of health records). Utility on the other hand tries to maximize the chances of nding helpful relationships in the real world, that can then be used for making smarter systems (e.g. the ability to predict that an individual is at higher risk of being a ected by a terminal disease). A term that is often used to explain this paradox is called the Privacy-Utility trade-o . Software practitioners have often ignored the privacy aspects due to lack of legal obligations, and have generally concentrated on achieving functionality. But with a renewed interest in Arti cial Intelligence, privacy concerns are going to become more important in near future. This will force the software providers to reevaluate their existing products and services from a privacy perspective. In this work, we analyse some of the challenges that a typical software provider would face while doing so. We present a privacy model that can be applied to existing systems, which in turn can suggest rst-cut privacy solutions requiring minimal alterations in deployed applications. To the best of our knowledge, no open-source initiative has been started till now to cater to these requirements. We brie y introduce the prototype of an open-source tool that we are developing which is aimed at facilitating this analysis. The initial results were obtained over some standard datasets, as well as a real world credit card fraud dataset, which seemed to collate with our intuitions.