Abstract

Web services are facing a constant threat from ever-increasing novel attacks. Attackers are continually coming up with new and unseen attacks whenever a vulnerability is found. Also, as the at- tackers have access to massive Botnets, these attacks are initiated immediately, before the interested party patches the vulnerability, to cause a denial of service on the targeted service. In this context, anomaly-based network intrusion detection techniques are valuable to protect the web services against these unknown attacks. Anomaly detection algorithms have gained significance to counter these unknown attacks, although they have high false alarms rates. As these algorithms can be effective on unknown attacks, web services can leverage them to defend against botnets. These algorithms need to be applied on the traffic which is handled by the scalable web services, in effect, there is a need for developing an intrusion detection system which is scalable with the web service it is protecting and also validate the alarms raised by these algorithms. Network-based anomaly detection is a well-mined area of research, with many projects that have produced algorithms to detect suspicious and anomalous activities. In this thesis, a bot detection architecture named BotD is proposed; this architecture provides a framework to plugin existing anomaly detection algorithms and the newer ones as they evolve. These installed algorithms analyze the incoming traffic and raise anomaly alarms when suspicious activity is detected. The architecture validates these alarms and takes appropriate actions. If the alarm validation turns out to be positive, the architecture marks the clients with such traffic patterns as bots and drops the traffic coming from them subsequently. In the case of false alarms, feedback is given to the algorithms to improve themselves. Moreover, BotD provides an interface for algorithm developers to monitor various metrics related to the algorithms plugged-in and takes care of scaling itself with the incoming traffic. Furthermore, in the thesis, we propose a network orchestration algorithm, used to transfer state across hosts using the SDN control layer. This proposed orchestration algorithm is used in this architecture to transfer plugged-in algorithms’ state efficiently across nodes while scaling. Finally, a simulation of the architecture is presented as a proof of concept for the proposed architecture.

Abstract

The construction of buildings is attained using force based design based on existing code provisions. Force based design has limitations as it only takes into account peak acceleration but not frequency content and duration of ground motion. A more reliable technique under consideration is energy based design which takes into account frequency content as well as duration of ground motion. Therefore it is essential to study the relation between different structure as well as earthquake characteristics with energy. In this study two types of structure, long period and short period, is considered because of the major difference in their response to earthquake. Therefore behavior of long and short time period structures is studied in terms of energy and damage induced when subjected to dynamic earthquake ground motion. Structures were modeled considering single degree of freedom following appropriate assumptions. A tool has been developed to study the behavior for long and short time period structures using MATLAB. Elastoplastic model was assumed for the nonlinear response. Response was calculated by solving dynamic equilibrium equations using Newmark’s step by step integration scheme. The tool developed is capable of performing time history analysis for getting response and this response was used to calculate imparted energy, hysteretic energy etc. over time duration of ground motion. Hysteretic energy is responsible for any damage induced in the structure because it accumulates only when the structure goes into non- linear region

Abstract

High power lasers are attractive sources for several applications. Because of good beam quality at all power level, distributed thermal loading, etc fiber lasers are gaining popularity in Directed Energy applications. There is a continued interest in scaling laser systems up to power levels suitable enough for DE systems. Beam combining systems for high average-power lasers began in the late 1960s and early 1970s. Early systems [1, 2] propagated the beams using heavy-water-cooled copper optics and open beam trains with commercial fans to provide fresh air. They have evolved in the intervening 40- plus years to include highly sophisticated gimbaled control systems with extremely high-reflectance uncooled optics and adaptive optics to compensate for less-than-ideal laser beams and for atmospheric distortions. Due to the limitations put by thermo optic effects gain saturation and scattering noise, laser beams cannot be amplified indefinitely. An alternative approach to building high power lasers is to use arrays of relatively lower power lasers. However, this approach requires that the beams from the array elements be combined to have the propagation characteristics of a single beam. Beam combining of laser arrays with high efficiency and good beam quality for power and radiance (brightness) scaling is a long-standing problem in laser technology. Semiconductor and fiber gain elements have attractive attributes for beam-combined sys- tems because of their ease in building in array formats, their high efficiency, and the ability to get near-diffraction-limited beams from individual elements. Beam brightness at the source is of limited importance when considering realistic DE propagation scenarios in turbulent atmospheres. Incoherent combination of the high-quality beams from fiber lasers can generate directional beams that are getting serious consideration for use as laser DE systems. For spatial beam combination where the laser beams propagate through the atmosphere, the atmo- spheric turbulence, pointing errors like platform jitter and boresight error play an important role in the performance of the combination technique. Different models of atmospheric turbulence have been explored. A functional implementation of the HAP model is shown in this thesis. Several architectures of the beam director for incoherent beam combination has been proposed. In these architectures, each of the beams are focused and targeted at a fixed point in space. Equations for inclined beam is derived using transformation rotation and the beam focusing equations have been modified to model real beams with non-ideal divergence. We have analyzed the criticality of the effect of atmospheric turbulence, beam wander, residual mechanical jitter and boresight error on the intensity and spot-size of incoherently combined laser beams.

Abstract

In the past decades, there have been multiple terrorist threats in the world and there is a lack of understanding of the effect of such dynamic loading on buildings. In order to understand the effect of blast loading, study of the dynamic behavior of structures is important. Current country codes do not provide proper guidelines to build a structure to mitigate the effects of such terrorist threats. Therefore, making it essential to study the behavior of structures subjected to impulsive loading. Reinforced walls are one of the first structural elements which are exposed to the loading in case of such events. Thus they become crucial to mitigate the effects of explosions. As part of this research, out of plane behavior of a vertical reinforced wall was studied when subjected to dynamic blast loading. Single degree of freedom system and finite element method were used to carry out numerical modeling of the reinforced wall with appropriate loading and structural approximations. As a part of this study, a tool was developed to implement the finite element method for a reinforced wall in MATLAB. 3D modeling of reinforced wall is done using 20-noded or 8-noded hexahedral elements. Rayleigh damping is used to calculate Damping matrix. The dynamic equilibrium equations are solved using Gaussian quadrature and Newmark’s direct integration scheme. The tool was used to analyze the behavior of reinforced walls under varying percentage steel, damping ratio, standoff distance, reinforcement diameter, charge weight, etc.

Abstract

Glaucoma is a major eye disease which when untreated, can gradually lead to irreversible loss in vision. The underlying causes are a loss of retinal nerve fibres (resulting in a thinning of the layer and enlargement of the optic cup) and peripapillary atrophy. Since these occur without any sign of symptoms in the initial stages, it is difficult to diagnose the disease in the early stages. Hence, the development of Computer-aided diagnostics (CAD) systems for early detection and treatment of the disease has attracted the attention of many medical experts and researchers alike. Optical Coherence Tomography (OCT) and Fundus photography are two widely used retinal imaging techniques for obtaining the structural information of the eye which helps to analyze and detect the diseases. Existing automated systems rely largely on fundus images for assessment of glaucoma due to their fast acquisition and cost. OCT images provide vital and unambiguous information for understanding the changes occurring in the retina, specifically related to the retinal nerve fiber layer and the optic nerve head which are essential for disease assessment. However, the high cost of OCT is a deterrent for deployment in screening at large scale. Hence, the focus of this thesis is to investigate the potential of integrating the two retinal imaging techniques which provide complementary information of the eye for developing automatic glaucoma screening system. Firstly, we propose a deep learning approach directly operating on 3D OCT volumes for glaucoma assessment which showed promising results, thus demonstrating the prominence of the highly discriminative features learnt from OCT for automated glaucoma detection. Next, we present a novel CAD solution wherein both OCT and fundus modality images are leveraged to learn a model that can perform a mapping of fundus to the OCT feature space. We show how this model can be subsequently used to detect glaucoma given an image from only one modality (fundus), thus enabling the automated screening operation to be executed on a large scale. The results show that fundus to OCT feature space mapping is an attractive option for glaucoma detection

Abstract

Language identification (LID) refers to the task of identifying the language being spoken by a speaker in a given speech signal. LID system acts as a front-end module for different applications such as multilingual automatic speech recognizer, multilingual dialogue system, and voice service systems. Notably, in an Indian scenario, where almost every state has a language of its own and every language having various dialects, development of a LID system becomes crucial. In literature, the standard acoustic features such as Mel-frequency cepstral coefficients, shifted delta cepstral coefficients and prosody (pitch, duration, and intonation) have been explored in the Indian context. These features cannot adequately discriminate the languages since most of the Indian languages have an overlapped set of phonemes. Even though Indian languages have an overlapped set of phonemes, due to phonotactic constraints, the characteristics of a particular sound unit differ in different languages which motivates us to explore phonetic features. In the literature, most of the works used senone based deep neural networks to extract phonetic features. We have used a joint acoustic model (JAM) which is trained using long short term memoryconnectionist temporal classification (LSTM-CTC) network to extract phonetic features. The JAM implicitly learns the language-specific information without any prior knowledge of the language. Hence, it is hypothesized that features extracted from JAM effectively discriminate the languages. These features are referred to as CTC features. The temporal variations in CTC features are modeled using the attention-based residual time-delay neural network to predict language ID. Attention mechanism aggregates frame-level features by selecting prominent frames through a parametrized attention layer. The performance of the proposed LID framework (CTC with attention-based RES-TDNN) has been evaluated on IIITH-ILSC database, which consists of 22 official Indian languages and Indian English. The proposed network outperformed other state-of-the-art methods with an equal error rate of 8.82%.

Abstract

“Natural language processing is the “big data” problem for the future of computing. While a huge amount of work has been done in this area, which we call ‘modeling and parameterizing computer systems,’ a fundamentally different approach is needed. We want to deploy virtual languages, and human computational agents. We have no formal computational theory that describes the problems that will be addressed by these. Most existing work is preliminary, although some work has been done and some actual software exists.” Can you guess the author who penned the above quote? You’ll be surprised it is not a famous celebrity. No, it is not even an overworked computer scientist. In fact, the entire quote was generated automatically by OpenAI’s latest language model, GPT-2 on simply supplying a short prompt of “Natural Language Processing is”. Surprising, isn’t it? Indeed, that’s how powerful language models can be! Language models are at the heart of Natural Language Processing (NLP). They help in extracting regularities from natural language which aid in solving multiple problems in various applications like automatic speech recognition, document classification, sentiment analysis, summarization, et cetera. With the growing advent of deep learning techniques aided by huge and efficient computational resources - we seek to evaluate various applications of fine-tuning language models which can guide us to a better and nuanced understanding of natural language. In this thesis, I’ll attempt to tackle some of the original problems that language models can help solve. Primary among those is the style transfer task wherein a piece of text is desired to be stylistically rewritten in the fashion of a given target author. Due to the unavailability of parallel data for such a task, it is not possible to leverage supervised systems like sequence-to-sequence models which entirely rely on paired instances of training data. This is where we bring in the concept of language-model finetuning - wherein we build a novel stylistic language model, StyleLM. StyleLM can be used to rewrite any given piece of text into the style of a target author, and is also scalable to multiple authors. We demonstrate the ability of StyleLM to rewrite into the style of a given target author across 3 different domains - viz. online reviews, fiction books and encyclopaedic pages. Our evaluation framework shows that StyleLM achieves high alignment with the target authors across all 3 levels (surface, lexical, syntactic) of the stylistic spectrum. At the same time, StyleLM also achieves comparable performance to the supervised baseline in both qualitative and quantitative comparisons. We also seek to evaluate the power of language models across content understanding tasks - both at the syntactic and semantic levels of linguistic discourse. For syntactic understanding, we dive into search queries, and seek to evaluate if pretraining and finetuning large language models can help discern wellformed search queries effectively from the non well-formed ones. To effectively understand the semantic spectrum, we use data from happy moments posted by users online to determine if we can detect the agency (whether the author is in control?) and social (if anyone other than the author is involved?) characteristics from within the happy moments. Across both these tasks, we achieve considerably high performance - with the latter system for understanding happy moments achieving the runner-up at the shared task in an affective content analysis workshop held at AAAI 19. We also outperform the stateof-the-art for syntactic discernment of search queries.

Abstract

Understanding the myriad interactions between protein and DNA that are present at the heart of most important biological phenomena is of critical importance to understanding life itself. Molecular Dynamics (MD) simulations provide a detailed view of the conformational changes that drive these intricate, multi-stage, highly dynamical protein-DNA binding processes. Aided by MD, the present work aims to investigate two processes that DNA-binding proteins take part in: (a) recognizing DNA mismatch lesions to commence the repair mechanism, and (b) regulating and affecting the process of transcription. The ultraviolet (UV) radiation-induced DNA lesions play a causal role in many prevalent genetic skin-related diseases and cancers. The damage sensing protein Rad4/XPC specifically recognizes and repairs these lesions with high fidelity and safeguards genome integrity. Despite considerable progress, the mechanistic details of the mode of action of Rad4/XPC in damage recognition remain obscure. The present thesis investigates the mechanism, energetics, dynamics, and the molecular basis for the sequence specificity of mismatch recognition by Rad4/XPC. We dissect one of the key molecular events that occur as Rad4/XPC tries to recognize and bind to DNA lesions/mismatches: the flipping of a pair of nucleotide bases at the damage/mismatch site. Using suitable reaction coordinates, the free energy surfaces for the base flipping event were determined using molecular dynamics (MD) and umbrella sampling simulations on three mismatched (CCC/CCC, TTT/TTT and TAT/TAT mismatches) Rad4-DNA complexes. We identify the key determinants of the sequence-dependent specificity of Rad4 for the mismatches and explores the ramifications of specificity in the process of base flipping. The results unravel the molecular basis for the high specificity of Rad4 towards CCC/CCC mismatch and lower specificity for the TAT/TAT mismatch. The interplay of the conformational flexibility of mismatched bases and the Rad4 specificity explored here complement recent experimental FRET studies on Rad4-DNA complexes. The cAMP-mediated allosteric transition in the catabolite activator protein (CAP) allows it to position its recognition F-helices to bind to the promoter region on DNA, resulting in gene activation. The present study aims to provide a molecular basis for the conformational changes observed during the allosteric regulation of CAP by cAMP and the subsequent binding to the DNA promoter region using MD simulation and umbrella sampling techniques. In particular, we investigate DNA binding-induced changes in the orientations and dynamics of functionally-relevant F-helices in the DNA binding domain. The two-dimensional free energy profiles of the cAMP-liganded CAP and the cAMP-CAP-DNA complex provide a clear, simple picture of the flexibility constraints imposed on the DNA binding region of CAP upon DNA-binding. We further relate these differences in the free energy surface of CAP to the dynamical modes of the recognition F-helices. The observed dynamical changes are then explained by dissecting the key interactions between CAP, DNA, and the cAMP molecules.

Abstract

We are given an environment with some objects (park with trees, a city block area) and mobile agents moving in the environment. The agents have a limited field of view and visibility range. An agent (hider) can hide behind an object to be not seen by other agents (seekers) through their line of sight (visibility). These hider agents (that are hiding behind objects) can be found by seekers who explore the environment. A pragmatic example of the problem is a warehouse environment or a cordoned off area of the town, with no drones or cameras, and some culprit agents are hiding from the police agents. The aim of hiders is not to be caught for the longest time, and the aim of the seekers is catch all of them in the shortest period of time. We formulate the problem by using visibility based map abstractions. These abstractions involve the notions of coverage, obstruction and escapability. Using these spatial abstractions as basic building blocks, we formulate two kinds of strategies for the agents. The first kind is based on multi-armed bandits in which the agents maintain reward bounds on obstacle edges which they feel are safe to hide or suitable for searching. The second kind focuses on deterministic capture of hiders, even if they are guided by an oracle which knows the future positions of seekers. We built a simulator to create environments for multiple hiders and multiple seekers to test their strategies in a Hide-and-Seek game. We contrast our strategies, and their variants, by empirically comparing their game completion times.

Abstract

Modern times have witnessed unprecedented material growth leading to increase in efficiency, comfortability and longevity of life. The success of modernity has attracted attention and curiosity of global community. However, behind the silver screen of modern glamour lie some existential challenges which are threatening not only the human welfare but also the existence of life itself on this planet. Some of these challenges include ever growing unsustainability of modern lifestyles, decimation of diversity in various spheres and a general disinterest seen in modern mind towards issues which do not have immediate bearing on one’s living (specifically material wellbeing). These challenges ought to be taken up head on in contemporary times in order to address the concerns fundamentally. In this context, exploration of the jajmāni system which was prevalent in traditional Indian society appears to be an important domain for study. Indian society has been known for being home to rich diversity. India has been home to all the major religions of the World, hundreds of languages are spoken by its people, thousands of gods are worshipped, and many important philosophical schools find patronage in Indian social institutions. Also, there are sufficient indications that there used to be a prime concern as well as facilitation of ‘collective contemplation’ on fundamental issues of humanity including the primal condition of man through various artistic modes. The jajmāni system also deserves to be analyzed from the point of view of sustainability and local self-sufficiency as it is usually claimed that it provided widespread prosperity to people. Even though the jajmāni system has attracted the interest of large number of scholars in the last century, however not much emphasis is discernible in these works has been done to understand these concerns. The present study on jajmāni system has attempted to study it from the following four major concerns The birth and sustenance of diversity in jajmāni villages - The role and importance of ‘culture of collective contemplation’ with regard to ensuring ‘unity-in-diversity’ in the society. - The self-sufficiency and sustainability of jajmāni villages. - And, the causes behind the collapse of jajmāni system in modern times. For all these, it is also important to grasp the philosophical basis and the key principles on which the jajmāni system was established over a long period. However, it is pertinent to note that at present it is not possible for one to come across a village which is actually functioning on the principles of jajmāni system. Therefore, for a comprehensive understanding, a conceptual model has to be visualized based on its formative principles and the bits of available information on it. In this regard, the present study reviewed available literature to identify and understand the underlying philosophical concepts and also to understand the system’s functioning. We have also attempted to identify and learn from a few rather unconventional resources to improve upon our understanding. One important resource has been Shri Ravindra Sharma, who extensively studied the functioning of the system in Adilabad region of southern India by actually living amongst several traditional communities for more than two decades and learning their crafts. In addition to him, this study has also extensively interacted with community elders of two communities in Western India- the kurbas (shepherds) and the thākar (traditional puppeteers). The spectrum of our literature review has addressed two broad interests- one, to understand salient concepts that are needed for this study and the other, to critically assess the existing status of information on jajmāni system. Consequently, the whole review is categorized in four different but connecting sections. The four seThe insights obtained during the course of this study can be useful to address the problem of diversity sustenance in contemporary society and the challenges of sustainability and self- sufficiency for local community living.ctions are as follows: - Salient views on Origins of ‘Society’ and Concerns of Diversity - The Importance of Collective Contemplation and the roles of Public-Private Realms - A critical review of the core literature on jajmāni system - Studies to understand philosophical basis of jajmāni system The jajmāni system in very brief can be understood as a social system of direct inter-dependency and mutual fulfilment amongst the families in a village community. The institution of jāti (caste) becomes pivotal to this arrangement. The system is founded on the basic philosophical principlesof mokśa (liberation)- as the purpose of life and ‘yajña’ (mutual fulfillment) as a way of living. The diversity in the jajmāni system is protected and sustained by the institution of jāti (caste), which ensures family-based production system. Moreover, diversity gets constant