College of Engineering, Pune

About: College of Engineering, Pune is a based out in . It is known for research contribution in the topics: Computer science & Sliding mode control. The organization has 4264 authors who have published 3492 publications receiving 19371 citations. The organization is also known as: COEP.

A novel approach for efficient extrication of overlapping chromosomes in automated karyotyping

Abstract: Since the introduction of the automated karyotyping systems, segmentation and classification of touching and overlapping chromosomes in the metaphase images are major challenges. The earlier reported techniques for disentangling the chromosome overlaps have limited success and use only color information in case of multispectral imaging. Most of them are restricted to separation of single overlap of two chromosomes. This paper introduces a novel algorithm to extricate overlapping chromosomes in a metaphase image. The proposed technique uses Delaunay triangulation to automatically identify the number of overlaps in a cluster followed by the detection of the appropriate cut-points. The banding information on the overlapped region further resolves the set of overlapping chromosomes with the identified cut-points. The proposed algorithm has been tested with four data sets of 60 overlapping cases, obtained from publically available databases and private genetic labs. The experimental results provide an overall accuracy of 75–100 % for resolving the cluster of 1–6 overlaps.

Strain-Induced Hierarchy of Energy Levels in CdS/ZnS Nanocrystals

Abstract: Aside of size and shape, the strain induced by the mismatch of lattice parameters between core and shell in the nanocrystalline regime is an additional degree of freedom to engineer the electron energy levels. Herein, CdS/ZnS core/shell nanocrystals (NCs) with shell thickness up to four monolayers are studied. As a manifestation of strain, the low temperature radiative lifetime measurements indicate a reduction in Stokes shift from 36 meV for CdS to 5 meV for CdS/ZnS with four monolayers of overcoating. Concomitant crossover of S- and P-symmetric hole levels is observed which can be understood in the framework of theoretical calculations predicting flipping the hierarchy of ground hole state by the strain in CdS NCs. Furthermore, a nonmonotonic variation of higher energy levels in strained CdS NCs is discussed.

Automated Hate Speech Detection on Twitter

Abstract: With the sudden increase in micro-blogging websites such as Twitter, Facebook, and Tumbler, the communication between people becomes indirect and reliable; people from different educational backgrounds, cultures share their opinion on different aspects of life every day This has resulted in conflicts among people As a result, the use of hate speech becomes a very serious problem Manual detection of such content from these websites is a very tedious task Hate speech is the use of aggressive, violent or offensive language which targets a specific group of people sharing common property, this property can be their gender, ethnic group or their believes and regions The proposed model is capable to detect hate content on Twitter automatically This approach is based on a bag of words and TFIDF (term frequency-inverse document frequency) approach These features are used to train machine learning classifiers Exhaustive experiments are conducted on existing twitter dataset and the accuracy obtained by logistic regression classifier is equal to 9411% on detecting whether a particular tweet is hateful or not

Influence of carbide density on surface roughness and quasi-stable wear behaviour of H13 die steel

Abstract: Influence of cryogenic treatment on AISI H13 hot work die steels has been studied to correlate carbide density with surface roughness and dry sliding wear. This work includes hardening of AISI H13 ...

Component-Based Software System Test Case Prioritization with Genetic Algorithm Decoding Technique Using Java Platform

Abstract: Test case prioritization includes testing experiments in a request that builds the viability in accomplishing some execution objectives. The importance amongst the most imperative testing objectives is the fast rate of fault recognition. Test case ought to run in a request that extends the likelihood of fault discovery furthermore that detects the most serious issues at the early stage of testing life cycle. In this paper, we develop and prove the necessity of Component-Based Software testing prioritization framework which plans to uncover more extreme bugs at an early stage and to enhance software product deliverable quality utilizing Genetic Algorithm (GA) with java decoding technique. For this, we propose a set of prioritization keys to plan the proposed Component-Based Software java framework. In our proposed method, we allude to these keys as Prioritization Keys (PK). These keys may be project size, scope of the code, information stream, and bug inclination and impact of fault or bug on overall system, which prioritizes the Component-Based Software framework testing. The integrity of these keys was measured with implementation of key assessment metric called KAM that will likewise be ascertained. This paper demonstrates how software testing can be efficient with management of data integrity factor to avoid major security issues. One of the main advantages of our approach is that domain specific semantics can be integrated with the data quality test cases prioritization, thus being able to discover test feed data quality problems beyond conventional quality measures.