Piyali Datta

Bio: Piyali Datta is an academic researcher from University of Calcutta. The author has contributed to research in topics: Biochip & Simple polygon. The author has an hindex of 4, co-authored 33 publications receiving 65 citations. Previous affiliations of Piyali Datta include Heritage Institute of Technology.

A Predictive Model for Fluid-Control Codesign of Paper-Based Digital Biochips Following a Machine Learning Approach

Abstract: Paper-based digital microfluidic biochips (or P-DMFBs) are becoming highly impelling due to its low-cost and in-place fabrication of electrodes and control wiring on a single piece of paper having an inkjet printer and conductive ink. Despite enormous advantages, several complex design rules also subsist, such as avoidance of induced control interference, minimum separation among the control lines, and congestion-free wiring on a single layer, which is to be correlated leading toward overall feasibility of the design. Several cost raising issues, such as schedule length, control pin count, and wire length, must be considered for attaining a successful fluid-control codesign. Moreover, design gaps exist among the subtasks of the fluid level, control level, and fluid-control design as a whole, which undeniably impose expensive design cycles increasing overall cost. This article builds a machine learning-based model for the pin-constrained P-DMFBs to predict violation in control design beforehand and accordingly guides the fluid-control codesign to tackle important cost-driving issues while attaining congestion- and conflict-free wiring. This model effectively eliminates the design cycles producing a low-cost platform. The predictive model has been evaluated over a balanced data set. Several benchmarks for assessing the performance are studied.

The first algorithm for solving two coins counterfeiting with ω(ΔH) = ω(ΔL)

Abstract: Counterfeit coin problem is of utmost importance and it is truly interesting in Computer Science and Game theory as well as in Mathematics In this problem the objective is to detect the fake coin(s) of identical appearance but of different weight in minimum number of comparisons The word counterfeit is most frequently applicable to forgeries of currency or documents, but can also describe software, pharmaceuticals, clothing, and more recently, motorcycles and other vehicles, especially when these result in patent or trademark infringement In this paper we have developed a new algorithm for solving two counterfeit coins problem in linear time, where n is the total number of coins given However, this is the first algorithm that identifies and solves the problem, given the false coins with type ω(ΔH) = ω(ΔL), ie, one false coin is heavier and another is lighter than a true coin, and their difference in weight from the true coin is equal However, this is the degenerate case in the field of two counterfeit coins problem

Aquatic life of indian birds

Abstract: AQUATIC LIFE OF INDIAN BIRDS

Attack-Detection and -Recovery: An Integrated Approach Towards Attack-Tolerant Cyber-Physical Digital Microfluidic Biochips

Abstract: A digital microfluidic biochip (DMFB) with cyber-physical adaptation implements complex bio-protocols with high precision and high throughput dealing with safety-critical applications including point-of-care diagnosis, personalized medicine, and drug development. Having integrated sensors with network connectivity, a cyber-physical DMFB is undeniably susceptible to attacks. A number of leading research works are carried out to assess various attacks and their impacts. Several defense mechanisms are developed by arranging on-chip monitoring systems through deployment of checkpoints. As checkpoints are external resources imposing a cost-overhead to the system, a cost-effective detection mechanism is of utmost importance. Moreover, after detecting an attack, an efficient recovery process is imperative to execute the associated bioassay in a vulnerable environment. Here, an attack-tolerant synthesis is proposed with two-way security through integrating attack-detection and attack-recovery from various Denial of Service attacks. Moreover, a selective re-synthesis approach has been introduced to allow multiple recovery steps to be executed simultaneously on the biochip. The recovery strategy is closely coupled with the detection process which makes the system adaptive towards attack-tolerance. Experimental results on several benchmarks demonstrate the efficacy of the proposed two-way attack-tolerance strategy.

Anomaly Detection and Three Anomalous Coins Problem

Abstract: Counterfeit coin problem has been considered for a very long time and is a topic of great significance in Mathematics as well as in Computer Science. In this problem, out of n given coins, one or more false coins (the coins are classified as false because of their different weight from a standard coin) are present which have the same appearance as the other coins. The word counterfeit or anomalous means something deviated from the standard one. In this respect, finding out these anomalous objects from a given set of data items is of utmost importance in data learning problem. Thus, representing coins as any data items, we have introduced an algorithm to determine three false coins out of n given coins. In addition, our objective is to solve the problem in minimum number of comparisons with the help of an equal arm balance.

Triangulating a simple polygon in linear time

Abstract: We give a deterministic algorithm for triangulating a simple polygon in linear time. The basic strategy is to build a coarse approximation of a triangulation in a bottom-up phase and then use the information computed along the way to refine the triangulation in a top-down phase. The main tools used are the polygon-cutting theorem, which provides us with a balancing scheme, and the planar separator theorem, whose role is essential in the discovery of new diagonals. Only elementary data structures are required by the algorithm. In particular, no dynamic search trees, of our algorithm.

Advances in Testing Techniques for Digital Microfluidic Biochips

Abstract: With the advancement of digital microfluidics technology, applications such as on-chip DNA analysis, point of care diagnosis and automated drug discovery are common nowadays. The use of Digital Microfluidics Biochips (DMFBs) in disease assessment and recognition of target molecules had become popular during the past few years. The reliability of these DMFBs is crucial when they are used in various medical applications. Errors found in these biochips are mainly due to the defects developed during droplet manipulation, chip degradation and inaccuracies in the bio-assay experiments. The recently proposed Micro-electrode-dot Array (MEDA)-based DMFBs involve both fluidic and electronic domains in the micro-electrode cell. Thus, the testing techniques for these biochips should be revised in order to ensure proper functionality. This paper describes recent advances in the testing technologies for digital microfluidics biochips, which would serve as a useful platform for developing revised/new testing techniques for MEDA-based biochips. Therefore, the relevancy of these techniques with respect to testing of MEDA-based biochips is analyzed in order to exploit the full potential of these biochips.

Role of Digital Microfluidics in Enabling Access to Laboratory Automation and Making Biology Programmable

Abstract: Digital microfluidics (DMF) is a liquid handling technique that has been demonstrated to automate biological experimentation in a low-cost, rapid, and programmable manner This review discusses the role of DMF as a "digital bioconverter"-a tool to connect the digital aspects of the design-build-learn cycle with the physical execution of experiments Several applications are reviewed to demonstrate the utility of DMF as a digital bioconverter, namely, genetic engineering, sample preparation for sequencing and mass spectrometry, and enzyme-, immuno-, and cell-based screening assays These applications show that DMF has great potential in the role of a centralized execution platform in a fully integrated pipeline for the production of novel organisms and biomolecules In this paper, we discuss how the function of a DMF device within such a pipeline is highly dependent on integration with different sensing techniques and methodologies from machine learning and big data In addition to that, we examine how the capacity of DMF can in some cases be limited by known technical and operational challenges and how consolidated efforts in overcoming these challenges will be key to the development of DMF as a major enabling technology in the computer-aided biology framework

Development of advanced operators for enhanced on-chip biosensing in digital microfluidic platforms

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