Department of History

Ashoka University is a private university located in Sonipat, Haryana, India, focusing on liberal arts and sciences. It was established in 2014.&nbsp;It is guided by an academic council of academics and scholars from around the world. The council sets the university&#39;s academic standard, advising on matters of curriculum, faculty hiring and research.&nbsp;

Ashoka University offers a full-time 3 (+ 1) year undergraduate programme. The University comprises of&nbsp;2500 plus students, with a mix of both national and international students.&nbsp; &nbsp;

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Ashoka University

Let X=(X,B,μ) be a σ-finite measure space and f:X→X be a measurable transformation such that the composition operator Tf:φ↦φ∘f is a bounded linear operator acting on Lp(X,B,μ), 1≤p&lt;∞. We provide a necessary and sufficient condition on f for Tf to be topologically transitive or topologically mixing. We also characterize the topological dynamics of composition operators induced by weighted shifts, non-singular odometers and inner functions. The results provided in this article hold for composition operators acting on more general Banach spaces of functions.&nbsp;

World University root node

Other Publications

Journal of Mathematical Analysis and Applications

Topological transitivity and mixing of composition operators

The Right to Information activists and whistle-blowers in India constantly face risk of harassment, assault, and even murder. The attacks on them are explored, with a special focus on Gujarat, by taking into consideration the nature of the cases they have filed. Who the RTI activists are and the role that non-governmental organisations have played in popularising the RTI is looked at as a tool to question the state in the distant villages of Gujarat, and also among the marginalised-women, Dalits, and Adivasis. The most common issues raised by the activists, the lack of institutional support and follow-up in protecting the activists, and other issues that are eroding the effectiveness of the RTI Act are highlighted. © 2018 Economic and Political Weekly.

Economic and Political Weekly

The struggle of RTI activists in Gujarat

To opt for a parliamentary over a presidential form of government is arguably the most significant, yet under-Analysed, decision made by the Indian constitution-makers. The conventional view is that parliamentarism was an obvious choice given the British colonial inheritance. However, parliamentarism, far from being obvious, was a counter-intuitive choice given the postcolonial agenda of state-led planned development, historically demanding an empowered executive branch most suited to presidentialism. As opposed to the maximalist and plebiscitarian tendencies of presidentialism, parliamentarism was a way to mediate the potentially conflictual cohabitation of mass democracy and planned development. &nbsp;

Parliamentarism, not presidentialism: Development and democracy in India

Web Services are application components characterised by interoperability, extensibility, distributed application development and service oriented architecture. A complex distributed application can be developed by combing several third-party web-services. Anti-patterns are counter-productive and poor design and practices. Web-services suffer from a multitude of anti-patterns such as God object Web service and Fine grained Web service. Our work is motivated by the need to build techniques for automatically detecting common web-services anti-patterns by static analysis of the source code implementing a web-service. Our approach is based on the premise that summary values of object oriented source code metrics computed at a web-service level can be used as a predictor for anti-patterns. We present an empirical analysis of 4 data sampling techniques to encounter the class imbalance problem, 5 feature ranking techniques to identify the most informative and relevant features and 8 machine learning algorithms for predicting 5 different types of anti-patterns on 226 real-world web-services across several domains. We conclude that it is possible to predict anti-patterns using source code metrics and a machine learning framework. Our analysis reveals that the best performing classification algorithm is Random Forest, best performing data sampling technique is SMOTE and the best performing feature ranking method is OneR. &nbsp;&nbsp;

Proceedings - International Computer Software and Applications Conference

An Empirical Analysis on Web Service Anti-pattern Detection Using a Machine Learning Framework

Intelligent vehicles require to communicate with other vehicles as well as with the road-side infrastructure for gathering information such as traffic management, cooperative driving, telematics and road construction. However, vehicle-to vehicle (V2V) and vehicle to infrastructure (V2I) communications can impose some serious security threats against vehicles' safety and other sensitive information which can lead to catastrophic consequences. Therefore, there is a pressing need to develop appropriate security protocols facilitating V2I and V2V communication. This paper presents a model for smart traffic infrastructure consisting of numerous entities like smart sensors, intelligent vehicles, base stations along with a new user authentication and key-exchange protocol which aids in the establishment of a secure session for communication between the entities. In the proposed protocol, any SUF-CMA (Strong Unforgeable- Chosen Message Attack) secure digital signature algorithm can be used for authenticating the users and any NM-CCA2 (Non-Malleability Chosen Ciphertext Attack) secure algorithm can also be used for the challenge response phase between the users authenticating themselves.&nbsp;

IEEE Intelligent Vehicles Symposium, Proceedings

A Security Model for Intelligent Vehicles and Smart Traffic Infrastructure

This article studies how the height of water varies with time when water flows out through a horizontal tube at the bottom of a cylindrical bottle. As an extension of the study, this article also studies the flow through two bottles. This experiment is exciting as well as thought-provoking. &nbsp;

Resonance

Water Flow Experiments: Single and Double Bottle Systems

In the early 1970's Eisenberg and Hedlund investigated relationships between expansivity and spectrum of operators on Banach spaces. In this paper we establish relationships between notions of expansivity and hypercyclicity, supercyclicity, Li–Yorke chaos and shadowing. In the case that the Banach space is c0 or ℓp (1≤p&lt;∞), we give complete characterizations of weighted shifts which satisfy various notions of expansivity. We also establish new relationships between notions of expansivity and spectrum. Moreover, we study various notions of shadowing for operators on Banach spaces. In particular, we solve a basic problem in linear dynamics by proving the existence of nonhyperbolic invertible operators with the shadowing property. This contrasts with the expected results for nonlinear dynamics on compact manifolds, illuminating the richness of dynamics of infinite dimensional linear operators.

Fulltext

Expansivity and shadowing in linear dynamics

Requirements Engineering (RE) is known to be critical for the success of software projects, and hence forms an important part of any Software Engineering (SE) education curriculum offered at tertiary level. In this paper, we report the results of an exploratory pilot study conducted to assess the effectiveness of Case-Based Learning (CBL) methodology in facilitating the learning of several RE concepts. The evaluation was made on the basis of graduate students' responses to a set of questions representing various key learning principles, collected after the execution of two CBL sessions at DA-IICT, Gandhinagar (India). We investigate the perceived effectiveness of CBL in students' learning of various RE concepts, based on factors like case difference, gender diversity, and team size. Additionally, we collect and analyze the Teaching Assistants' (TAs) opinions about the conducted CBL sessions. The outcome of this CBL exercise was positive as maximum students were able to achieve all the five stated learning objectives. The authors also report various challenges, recommendations, and lessons learned while experiencing CBL sessions. &nbsp;

Proceedings - International Conference on Software Engineering

Teaching requirements engineering concepts using case-based learning

Software testing is a popular mean of examining the adequacy of a developed product. However, in academic institutions more emphasis is given to software development than ensuring its quality. In order to address the gaps between existing university-level software testing education and the training standards used in industry, we experiment with employing a popular teaching method Case-Based Learning (CBL) for the first time to facilitate the training of selected software testing concepts at tertiary-level. The CBL exercise is conducted for undergraduate students of DAIICT, Gandhinagar (India) to cultivate the decision making skills in a self-learning environment. After the CBL execution we collect students' responses through a short survey and perform an empirical analysis on the survey results. The outcome of this CBL practice is positive as a majority of students are able to achieve the five stated objectives of CBL. We examine that there is a statistically significant difference between students' responses based on gender diversity. We also investigate the difference in students' feedback to the two different CBL cases that we use for practicing some aspects of software testing. Moreover, we draw useful inferences from the opinions of TAs (Teaching Assistants) about the CBL sessions.&nbsp;

ACM International Conference Proceeding Series

A case study on the application of case-based learning in software testing

Aging-Related Bugs (ARBs) occur in long running systems due to error conditions caused because of accumulation of problems such as memory leakage or unreleased files and locks. Aging-Related Bugs are hard to discover during software testing and also challenging to replicate. Automatic identification and prediction of aging related fault-prone files and classes in an object oriented system can help the software quality assurance team to optimize their testing efforts. In this paper, we present a study on the application of static source code metrics and machine learning techniques to predict aging related bugs. We conduct a series of experiments on publicly available dataset from two large open-source software systems: Linux and MySQL. Class imbalance and high dimensionality are the two main technical challenges in building effective predictors for aging related bugs. We investigate the application of five different feature selection techniques (OneR, Information Gain, Gain Ratio, RELEIF and Symmetric Uncertainty) for dimensionality reduction and five different strategies (Random Under-sampling, Random Oversampling, SMOTE, SMOTEBoost and RUSBoost) to counter the effect of class imbalance in our proposed machine learning based solution approach. Experimental results reveal that the random under-sampling approach performs best followed by RUSBoost in-terms of the mean AUC metric. Statistical significance test demonstrates that there is a significant difference between the performance of the various feature selection techniques. Experimental results shows that Gain Ratio and RELEIF performs best in comparison to other strategies to address the class imbalance problem. We infer from the statistical significance test that there is no difference between the performances of the five different learning algorithms.&nbsp;