Abstract

Given the recent progress in language modeling using Transformer-based neural models and an active interest in generating stylized text, we present an approach to leverage the generalization capabilities of a language model to rewrite an input text in a target author’s style. Our proposed approach adapts a pre-trained language model to generate author-stylized text by fine-tuning on the author-specific corpus using a denoising autoencoder (DAE) loss in a cascaded encoder-decoder framework. Optimizing over DAE loss allows our model to learn the nuances of an author’s style without relying on parallel data, which has been a severe limitation of the previous related works in this space. To evaluate the efficacy of our approach, we propose a linguistically motivated framework to quantify stylistic alignment of the generated text to the target author at lexical, syntactic and surface levels. The evaluation framework is both interpretable as it leads to several insights about the model, and self-contained as it does not rely on external classifiers, e.g. sentiment or formality classifiers. Qualitative and quantitative assessment indicates that the proposed approach rewrites the input text with better alignment to the target style while preserving the original content better than state-of-the-art baselines.

Abstract

Design of TFETs, with gate-drain underlap (Lun), exhibit suppressed off-state leakage and ambipolar conduction, thereby achieving larger on-to-off current ratio. In this work, through TCAD simulation study, we proposed an optimum value for gate-drain underlap length (Lun), and highlighted the advantages of designing TFETs with gate-drain underlap. Simulation framework was developed for both homojunction and heterojunction TFETs. The device design for both types of TFETs, considered similar doping profiles. The optimum value for Lun was determined to be half the gate length (Lg) from the DC characteristics, with little dependence of off-state leakage on the drain voltage. In the simulation study we also focused on the effect of the drain doping, and the gate length (Lg) on the performance of drain underlapped TFETs. The simulation study has been extensively performed on Ultra-Thin Body (UTB) III-V homojunction TFET and Ultra-Thin Body-Silicon On insulator (UTBSOI) Staggered gap (SG) III-V heterojunction TFET.

Abstract

Cinema Makes it Safe: Akaler Sandhane and the Problem of Looking This paper shall consider the trifecta of Bengali film directors Satyajit Ray (1921-1992), Mrinal Sen (1923-2018), and Ritwik Ghatak (1925-1976) to map a period in Indian film history when a political cinema was funded, at least in part, by the Indian government. The three directors were a provocative part of the Indian New Wave from the 1950s to the 1970s. They map two distinct definitions of “good political cinema” – from an aesthetically sophisticated cinema to a radical political text – that the state attempted to fund and administer in an attempt to develop cinema as an art form rather than as mass entertainment. In particular this paper shall consider Akaler Shandhaney (In Search of Famine, Sen, 1980) to argue that the film is unique in naming a pernicious relationship of inter-dependence between filmmaking, political speech, and the abject sub-altern. This self-reflexivity allows Sen to explore the exploitative nature of filmmaking and the middle class intellectual. Read in conjunction with Ashani Sanket (Distant Thunder, Ray 1973) and Jukti, Takko Aar Galpo (Reason, Story and Debate, Ghatak, 1977), Akaler Shandhaney calls into question filmmaking and funding practices, revealing the imbrication of national, social and cultural institutions in a complex interplay of aesthetic, ideological, and bureaucratic forces engaged in making “political” cinema possible. This paper argues that Sen uses this moment of self-reflexivity to speak a truth to the necessarily ambivalent and murky business of film making and viewing.

Abstract

Out of Censors: Netflix Original India and the Making of a New Normal This paper shall look three popular Netflix Original India productions Sacred Games (eriesS co-directed by Vikramaditya Motwane, Anurag Kashyap, 2018), Lust Stories (Anthology film co-directed by Anurag Kashyap, Dibakar Banerjee, Karan Johar, Zoya Akhtar, 2018) and Ghoul (Series directed by Patrick Graham, 2018). Each of the directors involved in these three productions have had run-ins with legal and extra-legal forms of censorship and moral policing in directing, producing, and marketing Hindi popular films. The relocation of cinema away from public screenings to the viewership afforded by Netflix has reterritorialized a new form of spectatorship. This allows these filmmakers to tell stories otherwise deemed too risky/risqué and attempt to re/claim a language of social and political critique. This paper shall consider the various strategies used by these immensely popular directors to argue that the relative freedom afforded by a global media-service provider unfettered by Indian legal regulation is mitigated by a language of co-optation. The three productions deal with police corruption, women’s sexuality, and Islamophobia and fascism respectively. All productions circulate in and acknowledge new globalities, changed sexual and power relations of image cultures and the traction afforded to a deterritorialized screening space. Yet these productions are bound by the exigencies of protecting and nurturing a particularly middle-class urban diasporic spectator from the vicissitudes of right-wing backlash on the one hand and an uncomfortable politics on the other.

Abstract

Software Requirement Specification documents provide natural language descriptions of the core functional requirements as a set of use-cases. Essentially, each use-case contains a set of actors and sequences of steps describing the interactions among them. Goals of use-case reviews and analyses include their correctness, completeness, detection of ambiguities, prototyping, verification, test case generation and traceability. Message Sequence Chart (MSC) have been proposed as a expressive, rigorous yet intuitive visual representation of use-cases. In this paper, we describe a linguistic knowledge-based approach to extract MSCs from use-cases. Compared to existing techniques, we extract richer constructs of the MSC notation such as timers, conditions and alt-boxes. We apply this tool to extract MSCs from several real-life software use-case descriptions and show that it performs better than the existing techniques. We also discuss the benefits and limitations of the extracted MSCs to meet the above goals.

Abstract

Integrating components of vehicular network with the Internet has emerged recently for fulfilling the ever-growing demand for a safe and comfortable driving experience. Road Side Unit (RSU) clouds help in serving requests arriving from vehicles but are limited by available resources. It is also required to reduce the overhead cost corresponding to Virtual Machine (VM) migrations caused by high mobility of vehicles. Also, requests need to be served within their stipulated delay constraint. In this work, we propose a novel algorithm to schedule requests at RSU clouds. Our algorithm efficiently schedules service requests from vehicles while taking care of their delay constraints and VM migrations. The simulation results confirm that our proposed scheduling technique helps in serving more number of requests within their stipulated delay constraint with lesser VM migrations.

Abstract

This paper presents a novel approach designed to answer questions on a reading comprehension passage. It is an end-to-end system which first focuses on comprehending the given passage wherein it converts unstructured passage into a structured data and later proceeds to answer the questions related to the passage using solely the aforementioned structured data. To the best of our knowledge, the proposed design is first of its kind which accounts for entire process of comprehending the passage and then answering the questions associated with the passage. The comprehension stage converts the passage into a Discourse Collection that comprises of the relation shared amongst logical sentences in given passage along with the key characteristics of each sentence. This design has its applications in academic domain , query comprehension in speech systems among others.

Abstract

Domain Specific Modeling Languages (DSML) significantly improve productivity in designing Computer Based System (CBS), by enabling them to be modeled at higher levels of abstraction. It is common for large and complex systems with distributed teams, to use DSMLs, to express and communicate designs of such systems uniformly, using a common language. DSMLs enable domain experts, with no or minimal software development background, to model solutions, using the language and terminologies used in their respective domains. Although, there are already a number of DSMLs available for modeling CBSs, their need is felt strongly across multiple domains, which still are not well supported with DSMLs. Developing a new DSML, however, is non trivial, as it requires (a) significant knowledge about the domain for which the DSML needs to be developed, as well as (b) skills to create new languages. In the current practice, DSMLs are developed by experts, who have substantial understanding of the domain of interest and strong background in computer science. One of the many challenges in the development of DSMLs, is the collection of domain knowledge and its utilization, based on which the abstract syntax, the backbone of the DSML is defined. There is a clear gap in the current state of art and practice, with respect to overcoming this challenge. We propose a methodology, which makes it easier for people with different backgrounds such as domain experts, solution architects, to contribute towards defining the abstract syntax of the DSML. The methodology outlines a set of steps to systematically capture knowledge about the domain of interest, and use that to arrive at the abstract syntax of the DSML. The key contribution of our work is in abstracting a CBS from a domain into a Domain Specific Machine, embodied in domain specific concepts. The methodology outlines, how the Domain Specific Machine, when coupled with guidelines from current practices of developing DSMLs, results in the definition of the abstract syntax of the intended DSML. We discuss our methodology in detail, in this paper.

Abstract

The focus of the ongoing Digital and Industry 4.0 revolution is on re-engineering business operations to take advantage of various technologies, including robotics. Conceptualizing, say, a robotics solution to automate aspects of warehouse operations involves multiple activities: understanding the problem space in sufficient detail to identify the right automation opportunities; working through the space of possible solution options and developing the solution design; and building a prototype solution with sufficient functional detail to enable customer experts to assess its suitability with respect to multiple concerns, and its impact on the business processes and environment. Only after that can a project be initiated to engineer and deploy the production solution, while making the necessary changes to the business system. With current practice, conceptualization and prototyping typically takes several months and considerable manual effort. In this paper, we present an environment for rapid prototyping of robotics solutions that facilitates a knowledge-centric approach based on capability composition. The environment enables systematic capture of functional domain knowledge, modular composition of solution space capabilities, and expression of the solution concept using a constrained natural language. Detailed functional simulators are generated automatically from the resulting design. This results in high customer confidence in the solution, substantial reductions in cycle time, and productivity gains due to modular reusability of solution knowledge and components.

Abstract

Energy consumption has dramatically increased in the residential building sector over the past few years. Many researchers today are interested not only in designing energy-efficient buildings but also in evaluating the actual building performance and managing operations for delivering the design intent. Monitoring building performance using currently available sensors and mobile applications poses challenges in terms of cost and standardization. This paper presents a new approach to make sensors affordable and inter-operable by designing open-source hardware and using well-established standards for data communication and storage, thereby making energy monitoring ubiquitous and affordable in the residential sector. The proposed solution uses low-power loggers, Bluetooth Low Energy wireless communication version 4 for data transfer from loggers to mobile phones for further transfer to cloud, oneM2M standard to ensure interoperability, and NGSI-LD for data management.