Abstract

Text Classification is among the primary challenges of natural language processing with multitude of applications including but not limited to sentiment analysis, emoji prediction and topic modeling. Several approaches ranging from rule-based systems to machine learning models have been applied to solve text classification. Neural network models, especially, have shown promising results. However, the models are limited by their reliance on the amount of annotated data. Machine learning models, primarily, operate on numerical data that represent the features of its input. In the case of text classification, the models need extraction of text features relevant to the given problem. This requirement led to the advent of a more specific area analyzing feature engineering called representation learning. Current approaches to learning sentence representations has predominantly been centered around the semantics of a sentence. However, semantic features are often inconsequential in text classification problems. Thus, to bolster task-specific representation learning, models need to learn text features according to the problem, rather than adopting a pre-compiled representation model. With the proliferation of Internet and its penetration into multilingual societies, the linguistic diversity of the real world is now reflected in online communities. Limiting solutions to a set of major languages is no longer viable. Nevertheless, the proliferation is relatively recent and hence the amount of available data in many widely-spoken languages is inadequate. Manual annotation of data is a humongous task and often expensive. Additionally, morphologically rich languages’ property of inflection and agglutination causes data sparsity problems. The possibility of utilizing resource-rich languages as leverage to enhance the performance of text classification in resource-poor languages is fascinating. To this end, the thesis presents a twin Bidirectional Long Short Term Memory (Bi-LSTM) network with shared parameters consolidated by a contrastive loss function (based on a similarity metric). Fundamentally, the aim is to classify text into multiple categories based on its features. The model jointly learns the text features (or representations) of resource-poor and resource-rich languages in a mutually shared space by utilizing the similarity between their assigned categories. Shared parameters of the Siamese network enable the projection of sentences into a common space and the similarity metric ensures the correctness of the projection. Essentially, the model projects sentences with similar categories closer to each other and sentences with different categories farther from each other. Additionally, this enables the leveraging of resource-rich languages to enhance text classification of resource-poor languages. The reason is that the projection is based on the language-agnostic annotation tags. So, pairing resource-poor and resource-rich sentences together as input to the Bi-LSTMs pair will result in their projection into a shared space. Hence, the resource-rich sentences aid the classification of resource-poor sentences by composing more training samples. Experiments, specifically, on the text classification tasks of Multilingual Sentiment Analysis and Multilingual Emoji Prediction with validation against large scale standard datasets reveal that the model significantly outperforms the state-of-the-art approaches in the case of both resource-poor and resource-rich languages. Furthermore, it is also observed that jointly training resource-poor and resource-rich languages exhibit significant performance enhancement over its single resource-poor language counterparts.

Abstract

Aesthetics is the study of the science behind the concept and perception of beauty. Psychologists have long been studying it via various experiments, which is called as experimental aesthetics. Aesthetic attributes are a set of universal principles to create aesthetically pleasing art objects, based on human’s visual processing. These attributes are taught as basic design principles, for example visual balance, color harmony, etc. In this thesis, we investigate the perception of visual balance in abstract black and white and colored paintings with experiments with university students. Visual balance is defined as a certain arrangement of the elements in a picture with respect to the canvas and with respect to each other, the point at which the composition appears more stable and coherent. We derive an objective measurement of visual balance based on the center of visual weight. The visual weight of an element is the attention-pull that element exerts on the viewer. We later synthesize an approach for optimal text placement over images using the same objective measurement and validate the results with user studies. With advancement in computer vision and Machine Learning, there have been many attempts to model the aesthetics especially in paintings, and photographs [42, 23, 71]. In this thesis, we also model eight different aesthetic attributes via a multi-task deep convolution network and derive state of art results on AADB dataset [28]. We also visualize these aesthetic attributes via gradient based technique and discuss the different level of complexity associated with different attributes.

Abstract

Enhanced Sampling in Molecular Dynamics simulations is one of the main challenges of computational chemistry. The problem arises due to existence of local minima in the free energy landscape, which serve as strong attractors. The problem is tackled by various traditional methods by somehow biasing the walker out of the minima to explore rest of conformational space. In this work we propose a multiple replica method that introduces repulsive interactions between them so as to diverge them in conformational space. These trajectories however follow a time dependent hamiltonian, statistics of which can only we studied in the nonequilibrium regime. We use the landmark work of Jarzynski to put together the statistics from these walkers to reconstruct the equilibrium free energy landscape. We also describe an implementation of the proposed method in the popular MD software, PLUMED so as to facilitate easy usability of the method for the larger community.

Abstract

Modern cryptography is based on the availability of Public Key Infrastructure (PKI) and Digital Signatures. However these schemes are designed around the assumed computational hardness of some problems like the integer factorisation, discrete logarithm, and lattice-based problems among others. This hardness assumption may turn out incorrect in future. So it is not advisable to design and implement real-world systems based on an unproven assumption. Also with the decrease in hardware costs and with the advent of new computing paradigms such as the quantum computing, the security of quite a few of such techniques is proven to be ineffective. For instance, one can potentially break RSA by implementing Shore’s Algorithm on a quantum computer. Hence, we must consider information-theoretically secure schemes which are based on the worst case assumption that the adversary has unbounded computational power. In solving problems in the design and implementation of fault-tolerant distributed systems, a basic construct that is assumed to be present is that every pair of nodes in the communication network has a channel between them for communication. This communication channel enables direct delivery of messages between them in a reliable and secure manner without the help of other nodes. However, due to the large scale of real-world distributed systems, a direct channel between every pair of nodes is not feasible/economical. Therefore, nodes depend on other intermediary nodes for communication out of which some can be faulty. We consider the setting where a subset of nodes can be under the control of a computationally unbounded adversary. The problem of simulating a reliable and secure channel from a special node S called the sender to another special node R called the receiver is popularly known as ”Secure Message Transmission (SMT)”. In this thesis, we focus on the variant of SMT protocols called Perfectly Secure Message Transmission (PSMT). The goal of PSMT is to design a protocol that enables S to communicate a secret message m to R assuring the following two conditions: (1) perfect reliability, that is, by the end of the protocol R gets the correct message m without any error and (2) perfect secrecy i.e., the adversary cannot learn any information about m, whatsoever, in information theoretic sense. It is well-known in the literature that the feasibility of PSMT protocols is influenced by the timing model. We distinguish between two variants to timing models: Synchronous and Asynchronous. While the synchronous model guarantees that the message sent by a node gets delivered to another node after a fixed amount of time, in an asynchronous model there is no such upper bound. Meaning, message delivery from one node to another node can be arbitrarily delayed. While assuming the network to be completely synchronous is too optimistic an assumption to make, assuming the network to be completely asynchronous makes solutions hard. In this work, we establish the concept of serendipitous synchrony with a focus on its influence/utility on the feasibility of PSMT protocols in asynchronous networks. We ask the following natural question: ”If part of a given asynchronous network by fortune turns out to behave synchronously (serendipitous synchrony), then does it affect the feasibility of PSMT protocols?”. We take the similar approach taken in literature and model the network as a set of disjoint wires, say n in number, with nodes in-between behaving as mere routers, popularly known as wires model. We assume the most powerful adversary considered in the literature viz., Byzantine adversary which can control at most t of these n wires arbitrarily. We quantitatively model serendipitous synchrony in the network as the number of wires that fortunately, happen to be synchronous, say ns (ns < n). Turns out that contrary to our intuition that serendipitous synchrony improves fault-tolerance of an asynchronous network, we discovered that, using serendipitous synchrony we either gain all the fault tolerance or we gain nothing from it! We further improve our insights into asynchronous networks by studying them in the presence of failstop faults (the nodes which can crash at will at any point during the execution). The main challenge in this setting is the inability to distinguish between a slow sender and a faulty sender which may sometimes cause otherwise correct protocols to have non-terminating executions. Unlike the approach that is taken in literature, where the network is abstracted as an undirected graph consisting of a set of n node disjoint wires, where each wire from S to R is also a wire from R to S; we consider the network with its directionality. That is, a wire from S to R may not be a wire from R to S. We consider mixed adversary that can cause dual failures. That is adversary can control at most tp wires in passive fashion (it can eavesdrop on messages on these wires) and at most tf wires in fail-

Abstract

The concentration of atmospheric CO 2 and antibiotic drug effluents from industries continue to increase beyond safety threshold levels in the environment. Mitigation of these contami- nants is necessary to protect the environment from various fatal consequences including global warming and antibiotic resistance caused by them. Expandable clay minerals are emerging as promising candidates for long-term storage of various environmental pollutants and nuclear wastes. The layered aluminosilicate clay minerals permit intercalation of water molecules, simple and complex organic and biomolecules into their interlayer galleries. The intercalated molecular species in the interlayer space cause the clay to swell. The swelling nature of clay is exploited in recent years for storage of pollutants including CO 2 and radioactive materials. The anthropogenic CO 2 is collected from industries and injected into deep geological formations such as saline aquifers and oil reservoirs beneath the earth’s surface at supercritical conditions (323 K, 90 bar). This process is known as geological sequestration of CO 2 . These natural geological formations are sealed on top by cap rocks that ensure leak-proof storage of CO 2 . Cap rocks are made up of swelling clay minerals including montmorillonite and bei- dellite. The CO 2 retention capacity and adsorption/desorption energetics of layered materials are likely to depend critically on the hydration level and the nature of molecular interactions among H 2 O, CO 2 , charge-balancing cations, and the oxide/hydroxide layers. The porosity and permeability of clay minerals are also greatly influenced by intercalated molecules and exchangeable charge balancing cations (CBCs). Thus, molecular-scale understanding of the structure, dynamics, and interfacial energetics of H 2 O/CO 2 binary mixtures confined in the interlayer nanopores is paramount to geological CO 2 storage efforts in clay-rich materials. Antibiotics are commonly used to treat a large variety of infections. These antibiotic drugs are produced in massive scales in India and China. Effluents from antibiotic drug in- dustries in many countries including India are directly released into nearby streams without proper effluent treatment strategies. Recent studies reported that the antibiotic drug con- centration in some streams in India and China is ∼ 100,000-1 million times higher than the prescribed threshold drug levels in the surface water. These drugs ultimately settle in clay 8 layers and enter the human body through food and water causing health hazards including an- tibiotic resistance among people residing around these streams. Due to the dynamic disorder exhibited by intercalates, the atomistic details of physico-chemical properties of these drugs in clay interlayers are not readily amenable to experimental techniques. Molecular dynamics simulations could provide atomistic level insights into the structure, dynamics, and energetics of clay-confined drug molecules. The microbial degradation of plant and animal tissues in the soil gives rise to complex heterogenous soft matter known as the natural organic matter (NOM). NOM plays a crucial role in many geochemical processes in the soil including sorption of toxic metal ions, bio- chemical regulators, radionuclides, organic contaminants, and nutrient transport and they also act as reservoirs of carbon in the soil. Despite significant research efforts in this area of re- search, the molecular structure of NOM is not fully understood because of the fact that the composition of NOM depends on the vegetation, climate, and topography of specific ecosys- tem. Recent experiments describe NOM as heterogeneous supramolecular mixtures of rela- tively small molecules, which are held together by weak non-covalent interactions between various chemical moieties of NOM. NOM-clay interactions play an important role in regu- lating the presence of carbon content in the soil. Much remains to be understood about the atomic-level details of the behavior of NOM at clay-water interfaces. In this thesis, we have employed molecular dynamics simulations and enhanced sam- pling free energy methods to elucidate the atomistic details of the structure and dynamics of H 2 O/CO 2 , antibiotics, and NOM at clay interfaces. In Chapter 3 & 4, we have studied the structure, dynamics, and energetics of H 2 O/CO 2 in smectite clay interlayers. The role of charge balancing cations in the adsorption of CO 2 at mineral-water interfaces is discussed in Chapter 5. In Chapter 6, we have derived force field parameters for antibiotic drug molecules and modeled drug-clay composites using newly generated force field parameters. The inter- actions of different functional groups of NOM, their structure, orientation and affinity towards cations, in clay-water interlayers are discussed in Chapter 7.

Abstract

Quantum information theory has gained a lot of attention recently due to its non-intuitiveness and its promise to help in developing new technologies like quantum cryptography, "quantum computer" which are known theoretically to handle very complex and intractable problems. A bit is the fundamental unit of classical information theory. But in quantum world there is qubit, which can be in both the states simultaneously termed as superposition. Superposition is a fundamental brick in quantum information theory. Due to it many types of cool phenomenons like quantum correlations i.e. entanglement, coherence etc. come into play and act as quantum resources for certain information theoretic tasks. It has been proved that quantum resources for completion of such tasks are more optimized and efficient than their classical counterparts. There are many restrictions imposed on quantum world in terms of no-go theorems out of which one we are interested in is "No-cloning" theorem. It states that there does not exists any quantum operation which can clone an arbitrary quantum state perfectly. Quantum Cryptography is one of the use case of such restrictions as it makes it more secure. We have proposed even more stronger restriction which is termed as "No-cloning of quantum coherence/superposition". Why stronger you may ask? It is known that cloning of arbitrary quantum state implies signaling. So the reverse is that no-signaling implies no-cloning of quantum state. Similarly, cloning of quantum state implies cloning of quantum coherence. So the reverse is that no-cloning of quantum coherence implies no-cloning of quantum state. This states that no-cloning of quantum coherence is stronger that no-cloning of quantum state. Also we have proved how they are different from each other as one might think at first that they are the same. The theorem holds true with or without machine states in the picture. We then show state characterization i.e. given a approximate coherence cloner how many states are there whose coherence can be cloned perfectly. Another important thing of this paper is that the theorems are proved geometrically with a nice representation on the Bloch sphere. The state of a quantum system is described by a wave function. But in cloning of a quantum state, we try to clone both wave and particle nature of the system. While in cloning of quantum coherence, we just try to clone the wave aspect of the system. From this we can also comment on how it is related to Heisenberg’s uncertainty principle. Coming to the another part of this thesis work. Another fascinating thing of quantum information theory is that we can use quantum resources to outperform some classical tasks or to perform some tasks whose classical counterparts does not exist. Quantum Superposition and Quantum Entanglement are used as quantum resources in various information theoretic tasks like Quantum ix teleportation, Super dense coding, entanglement swapping, remote state preparation, quantum cryptographic protocols, digital signature etc. It begins with the age old uncertainty principle which arises from non-commutativity of mutually complementary operators, on one face forbids us from doing many things whereas on the other face becomes the seed of great advantage in the domain of security and privacy.The fidelity of quantum information processing tasks like quantum teleportation, dense coding and entanglement swapping are related to Fully Entangled Fraction (FEF) which in turn also serves as an index that characterize non-local correlations and gives us a measure how much far a state is from the maximally entangled state. Here we try to approximately broadcast the FEF of an arbitrary quantum state acting as a resource which in turn broadcasts the fidelity of various information processing tasks. This process is extremely helpful when we need more number of quantum states with good resource abilities. We also prove no-broadcasting of non-locality using a very famous B-H state dependent local cloner. So to conclude, this thesis is all about a few impossibilities and approximations in quantum information theory.

Abstract

The current trend in business world involves interaction between multiple parties to fulfill certain business tasks. These tasks are defined at the time when a contract is signed among the parties. A contract is a legal document, which binds together two or more parties to meet a legal obligation. With the advancement of technology, electronic-contracts have evolved. An e-contract is a contract specified, modeled and executed by a software system. E-contract fulfillment has many challenges as contracts involve interdependencies among its various elements such as (i) activities carried out by various parties, (ii) satisfaction of clauses associated with activity executions, (iii) handling of exceptions when there is a clause violation and (iv) ensuring payments and commitments. Thus, there is a need of an (semi) automated system that can help in e-contract enactment. One way of enacting the e-contract is by a workflow management system. A workflow management system (WFMS) that executes an e-contract should have coordination among contract elements such as activities, parties, clauses, payments, exceptions and commitments in order to enable its successful fulfillment. The enterprises have to interact with many partners and, hence it results in inter-organizational workflows. While enterprises implement their own workflows, they might overlook few of their dependencies on other elements such as clauses, payments, exceptions and commitments. Hence, a WFMS needs to handle not only the activities but also exceptions, payments and commitments. Thus, there is a need for a framework that binds all of the above elements together with the workflow and can comprehend to ensure the successful execution of e-contract. In this work, a Hexagonal Integrated Workflow and View Framework for e-contract enactment has been proposed and implemented. The e-contract can have multiple perspectives for each of its elements. To derive the framework that supports multiple views of the e-contract, an integrated workflow was identified as the core component. An integrated workflow was developed that combines individual workflows (of parties) in the required order that allows for flexibility of augmenting additional tasks and events (with the help of user interaction) as required by the contract specifications. Additionally, workflow views for all six elements namely Activity, Party, Clauses, Exceptions, Payments and Commitments were also developed. Here, the views are explicit and clearly specify the tasks and the dependencies among all the elements. Furthermore, the proposed framework helps in monitoring the progress of e-contract execution for its enactment. The proposed system has two major components, namely Pre-enactment workflow and E-contract Execution workflow. The pre-enactment workflow builds an integrated workflow that comprises of parties workflows. The e-contract execution workflow drives e-contract execution and enables workflow views to support the contract elements. The components work in a sequential manner to facilitate contract fulfillment as per the e-contract specifications and enactment. Businesses often find it difficult to manage the e-contracts as it involves interorganizational workflows. The proposed hexagonal views in combination with the workflow components make the e-contract enactment easier. The views account for the e-contract elements and the workflow components help in execution. The workflow components assign the tasks of the e-contract to the concerned parties involved and monitor the progress of the tasks. After the task is completed, it notifies the next party to start the next task. It simplifies execution and monitoring of interorganizational tasks by ignoring the protocols and procedures of an organization, rather focusing on outputs of tasks which can be used by parties to notify E-Contract Execution Workflow. Moving forward, the output becomes the prerequisite for subsequent tasks. The proposed system has tried to bridge the gap that lies between the conceptual model of e-contracts and workflow, by using the concept of views, mapping them to the workflow and executing it using the E-contract Execution Workflow.

Abstract

Abstract In this thesis, we investigate the possibility of sourcing late-time cosmic acceleration by a slowly rolling scalar field and by the large-scale modification of gravity without extra degrees of freedom. As for the slowly rolling scalar field, we consider a model based on a simple potential. We use geometric diagnostics to differentiate the underlying model from the cosmological constant one. With regard to the large-scale modification of gravity, we investigate a scenario in which the late-time cosmic acceleration might arise due to the coupling between dark matter and baryonic matter without resorting to the dark energy or large scale modification of gravity associated with extra degrees of freedom. The scenario can give rise to the late time acceleration in the Jordan frame and no acceleration in the Einstein frame - generic modification of gravity caused by the disformal coupling. In the Einstein frame, we have only matter and thereby no new degree of freedom. Dynamics gets complicated or modified in the Jordan frame with the appearance of an arbitrary coupling function. The altered dynamics gives rise to the acceleration. In this picture, there is no extra degree of freedom as there is none in the Einstein frame where the Lagrangian is diagonalized. Using a simple parametrisation for the coupling function, we constrain the model parameters by using the age constraints due to the globular cluster data. We also obtain the observational constraints on the parameters using H ( z ) + SNIa + BAO data sets. In this case, we distinguish between the phantom and the non-phantom acceleration and show that the model can give rise to the phantom behaviour in a narrow region of the parameter space.

Abstract

Gas sensors find many applications in the biomedical and industrial fields. Among various gas sensors, sensors for the detection and measurement of acetone and ethanol are very important. We explored here the sensing properties of flower-shaped nanoparticles of pure zinc oxide (ZnO), an n-type semiconducting metal oxide, and Ag and Pd nanoparticle-modified ZnO nanoflower systems towards the sensing and detection of acetone and ethanol. The nanoparticles were prepared by literature-reported methods. We demonstrated that pure ZnO nanoflowers showed high sensitivity and very fast response and recovery times towards both the gases. The sensors showed a significant sensor response even at 1 ppm concentration of the target gas. We demonstrated that the selectivity preference for the gases could be modulated by loading metal nanoparticles onto the surface of the ZnO nanoflowers. The sensors had no interference from water vapor and CO2. Further, the sensors showed excellent sensing cycle reversibility. Such sensors can be promising candidates as industrial and environmental gas sensors.

Abstract

The High-Definition Multimedia Interface(HDMI) is used for transmitting digital television audiovisual signals from DVD players, set-top boxes and other audiovisual sources to television sets, projectors and other video displays.It can carry high quality multi-channel audio data and can carry all standard and high-definition consumer electronics video formats.HDMI is a digital replacement for existing analog video standards.At its heart, HDMI is a high-speed, serial, digital signaling system that is designed to transport extremely large amounts of digital data over a long cable length with very high accuracy and reliability.In order to achieve such high accuracy and reliability,HDMI uses Transition minimized Differential Signalling (TMDS) to move information from one place to another.In this scheme, the data is encoded so as to reduce the number of 0-1 transition which in turn reduces the inter-symbol interference.The encoded data is then transmitted serially over the cable.The physical layer for TMDS is current mode logic, DC Coupled and terminated to 3.3V.The use of Current Mode Logic(CML) ensures superior performance in noisy environments and in the presence of lossy transmission lines. Need for a low-power HDMI Source At 3.4 Gb/s data rate the power consumption of a conventional HDMI source is signicant and so there is a need for new HDMI source architectures for saving power while meeting the specifications defined by HDMI standards. Reduced power consumption is achieved in previous literature by using single-ended source structure. But, it is well known that such an arrangement is more susceptible to supply noise due to its poor power supply rejection and also susceptible to other noise sources such as crosstalk from neighboring lines. Proposed Solution Here, we propose an HDMI source with reduced power consumption while retaining the differential signalling so as to maintain better noise immunity. Proposed power-efcient back-terminated HDMI source transmits the data at 3.4 Gb/s per channel while meeting all other specications of HDMI standards. The proposed source provides high output impedance for current mode driving as well as a back-impedance of 100 Ω for matching the characteristic impedance of the line. With the help of the proposed circuit topology it is possible to achieve the output voltage swing dened by HDMI standard with a smaller tail current thus bringing down the power consumption of the HDMI source. This HDMI Source is mplemented in 3.3V, 0.18μm CMOS Technology which takes into account the device parasitic and second-order effects. The HDMI system also includes an 8-bit pseudo random binary sequence (PRBS) Generator driven by a phase locked loop (PLL) which provides the source with differential test data. The PLL provides the required 3.4 GHz clock signal to the PRBS Generator. The PRBS generator which is differential in nature, uses a current-mode XOR gate and sense-amplier based ip-ops with reduced delay and improved driving capability for better performance.The PLL features a differential delay based ring oscillator with reduced supply-sensitivity. The designed HDMI source is capable to transmit data at the rate of 3.4 Gb/s per channel and meets all the specifications defined by HDMI Specification Version 1.4. The power consumed by this HDMI source is 27.7 mW at 3.3 V, which is 30% lower than the power consumed by a conventional HDMI source.