Abstract

Widespread damage caused by some recent earthquakes has posed many new challenges to the research community to study near fault motion and its effects on the ground surface. Earthquakes in different geological regions show drastic variations in their effects, such as large surface upliftment/displacements of soil deposits and distinctly different near fault ground motions in contrast to the far field ground motions. Numerous researchers studied this phenomenon through experiments and tried to establish relationships between various parameters of soil and resulting surface ground motion characteristics. Carrying out the experiments to understand such behaviour itself was difficult, because of complexities involved in replicating the exact site conditions, considering all the necessary parameters of soil deposit and underlying bedrock. Many experiments of high precision are to be conducted to establish relationship between the ground motion and various parameters such as width of affected zone, soil properties, thickness of deposit and dip angle of fault. Moreover, shapes and locations of the surface rupture and its propagation through the soil deposit before reaching the ground surface, are important in city planning, especially in the design of critical structures that may be located near the zone of faulting. Numerical modelling allows investigation of effect of a number of aspects of the fault rupture propagation, which may be difficult to obtain from earthquake case histories or from experiments conducted on physical models. Additionally, the sparse coverage of recording stations limits the ability to capture ground motions close to fault ruptures. Therefore, numerical simulation of near fault ground motions is necessary to understand the severity of near fault ground motion in future earthquakes. In this thesis, the numerical method called Applied Element Method is explained along with its application in the fault motion analysis. Since the problem is related to the fault rupture propagation, a method is needed, which can handle the discontinuities. The methods based on continuum modeling face lots of complications when we want to apply it to the material that has discontinuities. The Applied Element Method (AEM) has many advantages with respect to the fault rupture problem. Using AEM, the crack initiation and propagation can be modeled in reasonable time by using the available parallel computing power. This method is used for studying the spatial variation of ground motion due to seismic bedrock displacement at the bedrock level. In the present study, the Applied Element Method is used to study the dip-slip faults subjected to seismic base fault movement. The method used here has been explained and validated with analytical and experimental studies with good comparable results. The preliminary modelling of dip-slip faults has been done using different slip rate values. Increase in the response on the surface due to decrease in rise time values has been seen. Influence of dip angle has been investigated and the change in the response due to the presence of lower velocity layer on the near fault ground motion has been studied. The results of the numerical simulation have explained many dynamic and geometric aspects of the reverse faulting. In all cases with different fault dip angle, there is greater ground motion on the hanging wall side compared to the ground motion of foot wall side. This effect is intrepreted as being due to two important reasons. First, the points on the hanging wall are closer to the fault plane and secondly, the trapped seismic energy in the wedge shape hanging wall leads to multiple reflections. The results from different dip angles indicate that the near fault ground motion is sensitive to the dip angle. Decrease in the ground motion with increase in the dip angle has been seen. The presence of lower velocity layer leads to the reduction in the ground motion on the surface due to inconsistency in the material properties along the rupture direction and also due to the reduction in the stress drop value, whereas the presence of lower velocity block on the hanging wall leads to the amplification of the ground motion at the place of the lower velocity block. Then, the fault rupture propagation is explored in presence of rock boulders and its effect on the surface peak ground acceleration. Surface faulting has been examined by keeping the boulder at different positions. Presence of boulders in the footwall and in proximity of the rupture zone increases the PGA value on the surface of hanging wall to a large extent, whereas the presence of boulder in hanging wall away from the rupture zone does not affect much on the surface ground motion. It has been seen that there is a considerable change in the rupture pattern in presence of rock boulder in the rupture zone. Recent ground-motion observations suggest that there is a considerable difference in surface-rupturing earthquakes

Abstract

Pneumoconiosis is an occupational lung disease caused by the inhalation of industrial dust. Despite the increasing safety measures and better work place environments, pneumoconiosis is deemed to be the most common occupational disease in the developing countries like India and China. Screening and assessment of this disease is done through radiological observation of chest x-rays. Several studies have shown the significant inter and intra reader observer variation in the diagnosis of this disease, showing the complexity of the task and importance of the expertise in diagnosis. The present study is aimed at understanding the perceptual and cognitive factors affecting the reading of chest x-rays of pneumoconiosis patients. Understanding these factors helps in developing better image acquisition systems, better training regimen for radiologists and development of better computer aided diagnostic (CAD) systems. We used an eye tracking experiment to study the various factors affecting the assessment of this diffused lung disease. Specifically, we aimed at understanding the role of expertize, contralateral symmetric (CS) information present in chest x-rays on the diagnosis and the eye movements of the observers. We also studied the inter and intra observer fixation consistency along with the role of anatomical and bottom up saliency features in attracting the gaze of observers of different expertize levels, to get better insights into the effect of bottom up and top down visual saliency on the eye movements of observers. The experiment is conducted in a room dedicated to eye tracking experiments. Participants consisting of novices (3), medical students (12), residents (4) and staff radiologists (4) were presented with good quality PA chest X-rays, and were asked to give profusion ratings for each of the 6 lung zones. Image set consisting of 17 normal full chest x-rays and 16 single lung images are shown to the participants in random order. Time of the diagnosis and the eye movements are also recorded using a remote head free eye tracker. Results indicated that Expertise and CS play important roles in the diagnosis of pneumoconiosis. Novices and medical students are slow and inefficient whereas, residents and staff are quick and efficient. A key finding of our study is that the presence of CS information alone does not help improve diagnosis as much as learning how to use the information. This learning appears to be gained from focused training and years of experience. Hence, good training for radiologists and careful observation of each lung zone may improve the quality of diagnostic results. For residents, the eye scanning strategies play an important role in using the CS information present in chest radiographs; however, in staff radiologists, peripheral vision or higher-level cognitive processes seems to play role in using the CS information. There is a reasonably good inter and intra observer fixation consistency suggesting the use of similar viewing strategies. Experience is helping the observers to develop new visual strategies based on the image content so that they can quickly and efficiently assess the disease level. First few fixations seem to be playing an important role in choosing the visual strategy, appropriate for the given image. Both inter-rib and rib regions are given equal importance by the observers. Despite reading of chest x-rays being highly task dependent, bottom up saliency is shown to have played an important role in attracting the fixations of the observers. This role of bottom up saliency seems to be more in lower expertize groups compared to that of higher expertize groups. Both bottom up and top down influence of visual fixations seems to change with time. The relative role of top down and bottom up influences of visual attention is still not completely understood and it remains the part of future work. Based on our experimental results, we have developed an extended saliency model by combining the bottom up saliency and the saliency of lung regions in a chest x-ray. This new saliency model performed significantly better than bottom-up saliency in predicting the gaze of the observers in our experiment. Even though, the model is a simple combination of bottom-up saliency maps and segmented lung masks, this demonstrates that even basic models using simple image features can predict the fixations of the observers to a good accuracy. Experimental analysis suggested that the factors affecting the reading of chest x-rays of pneumoconiosis are complex and varied. A good understanding of these factors definitely helps in the development of better radiological screening of pneumoconiosis through improved training and also through the use of improved CAD tools. The presented work is an attempt to get insights into what these factors are and how they modify the behavior of the observers.

Abstract

In the area of data mining, the process of frequent pattern extraction and association rule finds interesting information about the association among the items in a transactional database. The notion of support is employed to extract the frequent patterns. Several algorithms have been proposed to efficiently extract frequent patterns from the transactional databases. The frequent pattern mining often leads to the generation of huge number of frequent itemsets which might be found insignificant depending upon application or user-requirement. In this connection, the researchers have made efforts to mine the subset of interesting frequent patterns according to the needs and demands of the users. In the literature, various properties like periodicity, pattern-length, cost (utility) of a frequent pattern etc have been used to filter out the unwanted frequent patterns. Similiarly, for mining interesting association rules, several measures like 2, lift, relative-support have been proposed in the literature. In this thesis, we introduce a concept of extracting a subset of frequent patterns based on the notion of diversity. Normally, a frequent pattern may contain items which belong to different categories of a particular domain. For certain types of applications, it may be useful to distinguish between the frequent patterns with items belonging to different categories and the frequent patterns with items belonging to the same category. However, the existing approaches do not consider the notion of diversity while extracting the frequent patterns. We have conceptualized the problem of extracting diverse-frequent patterns from the transactional databases. As a part of this effort, we have proposed the interestingness measure, DiverseRank, to rank the frequent patterns based on the diversity within the items categories. Given a set of frequent patterns and a concept hierarchy, we propose an efficient approach to extract the diverse-frequent patterns. First, we propose an approach to extract diverse-frequent patterns by considering a balanced concept hierarchy. Later, we extended the approach to extract diverse-frequent patterns by considering an unbalanced concept hierarchy. We have employed an item-encoding technique to efficiently mine the complete set of diverse-frequent patterns. Experiments on the real-world and simulated data sets show that the class diverse-frequent patterns is a different type of knowledge patterns as compared to the frequent patterns.

Abstract

In this thesis, we present a methodology for coordination of multi-robot systems in an unknown environment with obstacles. The robotic systems need to coordinate and cooperate by following a strategy which helps them to move from one location to another in the environment, under the influence of one or many constraints. The multi agent systems explore the whole unknown environment during the course. The key task we have here is to allocate new points to the multi-robot systems such that maximum exploration is completed in minimum time, while maintaining the communication constraint with a moving base station the whole time. For this, we have experimented with two different frontier based exploration techniques. In the first case, we present a deployment strategy which maximizes the area coverage of the whole network while maintaining communication between each other. The method is based on the concept of artificial force fields, which is distributed, scalable and does not require prior information about the environment to be explored. This force field based method is used to control the robots motion while avoiding obstacles. Robots tend to move towards frontier points, from where they experience an attractive force, while they move away from obstacles, which exert a repulsive force. Care is also taken to ensure that no two robots move to the same location, so as to avoid common areas or sub maps during the exploration. Here, we also present an approach to deal with the deadlock and local minimum situations. Simulation results performed on different maps have shown that the robot pack is able to cover the map efficiently, while keeping the communication constraint intact. In our second technique, which is an adaptation, built to overcome the shortcomings of the first one, we present a frontier based multi-robot exploration algorithm akin to a depth first strategy that samples frontier points according to a metric function, which aims to maximize the information gain while minimizing the distance to be traveled to the frontier points. The algorithm is designed in such a way so as to accommodate the requirement of communication maintenance. Through an optimized framework, we also prove that the communication requirement between the multi-robot system is also maintained during transition from one point to another during the exploration process. Extensive simulations have been performed to show the adeptness of this method. This method is also compared to another frontier based exploration approach, which is based on population generation and utility calculation over the population. This method was extended to include the sensory visible areas and results computed. On comparison, it was found that our method fairs much better to the one based on utility function. This has been shown with the help of various graphs and simulations performed on various environments.

Abstract

Treebanks are a linguistic resource: a large database where the morphological, syntactic or semantic or both and lexical information for each sentence has been explicitly marked. The critical requirements of treebanks for various NLP activities (research and application) are well known. This also implies that treebanks need to be as error free as possible. However, manual validation of a treebank is very costly, both in terms of time and money. In this work, we try to automatically detect errors at different annotation levels ( POS, Morph, Chunk and Dependency) in Hindi Treebank after a complete manual annotation. We present different approaches to detect errors. The focus of our work has been dependency level because it marks very crucial information about a language. It is also very difficult to detect errors at this level as it requires a lot of contextual information. We have developed a validation tool which has rule based systems to detect errors at POS, Chunk, Morph and Dependency level, and a hybrid system to detect errors at Dependency level. We also present a GUI which is built on top of our validation tool. The GUI has numerous functionalities which reduces the effort of a validator and improve their efficiency. We also present a user study to show that our system reduces the validation time significantly while detecting 81.49% of the errors at the dependency level. In all we made a system which is being used for validation of current Hindi treebank under development.

Abstract

The thesis is divided into two chapters. The first chapter deals with “Effect of Thermal Perturbations and Chemical Denaturants on the Folding of Trp-cage miniprotein via Free Energy Calculations”. The second chapter deals with “Strong Dispersion Interactions between Urea and Nucleic Acid Bases in Addition to Hydrogen Bonded Interactions Assist Unfolding of RNA”. Brief introduction and the synopsis of results and discussions for each of the chapters are given below.
Chapter 1: Effect of Thermal Perturbations and Chemical Denaturants on the Folding of Trp-cage miniprotein via Free Energy Calculations
Perturbations in temperature, pressure and solvent conditions can adversely affect the stability of native folds of a protein. Thermal perturbations and chemical denaturants have been commonly used to study protein folding. Also, unfolding of the protein due to mechanical stress has been studied using atomic force microscopy (AFM) experiments in which the distance between terminal residues is typically chosen as the reaction coordinate. However, the reaction coordinate for protein folding studies may not be as simple as a distance between terminal residues. Further, the perturbation technique used adversely affects the unfolding pathway. Recent experimental studies have shown that combining various perturbation techniques facilitates in developing a better understanding of the unfolding pathway. A recent molecular dynamics study by Bung and Priyakumar on Titin I27 domain, using a combination of thermal and mechanical perturbations revealed two different competing unfolding pathways for the protein.
In this study, we use a combination of thermal, chemical, and mechanical perturbations to study the unfolding mechanism of Trp-cage miniprotein using molecular dynamics simulations. The distance between penultimate terminal residues is chosen as the reaction coordinate. We attempt to see if a simple end-end distance is a suitable reaction coordinate to study the folding/unfolding of Trp-cage miniprotein under varying temperatures and in the presence/absence of chemical denaturants. For the first time, Trp-cage miniprotein simulations are being carried out using CHARMM force field. Umbrella sampling technique was used to quantitatively compute the differences in thermodynamic quantities of the unfolding process of Trp-cage miniprotein TC5b (PDB ID: 1L2Y) due to changes in temperature, presence/absence of chemical denaturants, and mechanical stress. Urea at a concentration of 8M has been used as the chemical denaturant. WHAM was used to obtain the unbiased free energy profiles.The free energy profile can be categorized into three parts – the opening of the Trp-cage, separation of secondary structure elements and distortion of α-helix. The variation of few geometric parameters that are commonly used as order parameters conceived for Trp-cage miniprotein was analyzed with respect to the reaction coordinate used in this study. It is observed that theend-end distance may not be a suitable reaction coordinate to study the folding/unfolding of Trp-cage miniprotein. It was also observed that urea-induced denaturation of Trp-cage miniprotein is mainly through van der Waal dispersion interactions.
Chapter 2: Strong Dispersion Interactions between Urea and Nucleic Acid Bases in Addition to Hydrogen Bonded Interactions Assist Unfolding of RNA
The use of chemical denaturants to probe protein folding is commonplace and has recently been extended to understand the folding and stability of RNA. A recent molecular dynamics (MD) study has proposed that urea denatures RNA by forming stacking interactions and hydrogen bonds with nucleic acid bases. In this work, the ability of urea to form stacking interactions with one of the nucleic acid bases, guanine, has been investigated using high level ab initio quantum chemical calculations (RI-MP2 and CCSD(T)) with aug-cc-pVDZ basis set. Several highly stable guanine-urea stacks were identified whose interaction energies (up to 14 kcal/mol) are dominated by dispersion interactions; the stacks were further examined using the natural bond orbital (NBO), and atoms in molecules (AIM) analyses. It is proposed that urea molecules along with water form a cage like structure that is capable of trapping nucleic acid bases by forming both hydrogen bonded as well as dispersion interactions.

Abstract

The fourth generation mobile communication systems are on the way to revolutionize the world of telecommunications. Based on the extraordinary success of the broad band services of the 3G and the rapid increase in data traffic, it is predicted that there would be high demand for the services of the 4G. However, network operators are faced with the decline in the Average Revenue per User owing to the reduction in service costs which makes it difficult to stay profitable while enhancing system capacity. The challenge is to reduce expenditure while profitably meeting the rising demand for high speed services. Meanwhile there are concerns about the increasing energy consumption by the ICT industry. The LTE (front runner standard to 4G) seems to present a solution to both these problems with the Self Organizing Network (SON) paradigm which proposed introduction of self optimizing, configuring and healing mechanisms, aimed at reduction of operational effort, complexity and expenditure. Our research stems from the fact that sustenance of these rapidly scaling wireless systems depend on the efficient management of the limited resources owing to bandwidth, energy, spatial and other constraints. The front end of a mobile network consists of a set of base stations, each interacting with a set of users in close proximity. From a spatial tessellation perspective, it is a set of footprints (often highly overlapping) of the base stations on the network space. One may say that the effectiveness of the access part of a network depends on how well the topologies of these foot prints are managed. In the first part of our work we look at how these tessellations effect the throughput and energy consumption of the network. We propose algorithms for management of the area of influence of the base stations by dynamically adjusting their power levels according to the current user distribution to achieve better throughput and energy savings. Dynamic reconfiguration of mobile networks is gaining importance in context of new generation networks and has been independently analysed from the perspectives of throughput optimization, energy conservation and load balancing. Our proposed method takes into account more than one of these factors and shows an improvement in throughput and energy management of the access network (energy management aims at optimal usage of energy and leads to energy savings). The possibility of powering off of eNodeBs in low/moderate load conditions is investigated and simulation results are presented. Simulation results show improvement in signal quality and throughput while reducing the energy consumption by around 20% in low load conditions with dynamic configuration compared to the static case. Comparison of the results of minimizing two different cost functions with the same bi-objective but different priorities demonstrates the importance of considering coverage (over network space) and throughput together during reconfiguration. The overall energy consumed by the system during its operation depends on its ”response” to the traffic/load conditions which is dictated by the operation/management schemes that are employed. (For example, in a city, traffic in the business district may be high during the day and die out towards the night while a residential area may find its peak towards the evening.) So, we propose that a planning methodology must be ”Operationally Aware”. Operational Awareness, in this context means that the management schemes that will be employed in the operational network are taken into consideration during the process of deployment to make sure that the network obtains consistent gains through these schemes. To present this novel perspective to network planning, we define the Operationally Aware Network Planning Problem. We propose two methods (Maximal Explicit Gain Method, Integral Gain Method) with an objective of maximizing the gains (energy saving and throughput optimization) obtained by our proposed dynamic reconfiguration schemes. To show the utility of the proposed schemes, simulations were carried out. Energy savings of around 15% were obtained by reconfiguration schemes, when applied on the outputs (set of eNB network locations) of the deployment schemes. The results show that the first method maximizes the energy savings in low load conditions while the second method provides a better throughput and signal quality. Comparison of the two methods gives insights into the trade-off between energy conservation and throughput optimization in the deployment problem.

Abstract

The problem of matching small image regions or patches between images is central to many image editing and computer vision tasks. In this thesis, we propose two related solutions to the problem of fast and global patch-matching. First, we present a multi-resolution spatial pyramid based solution, which we call Pyramid Patch-Matching (PPM). It uses a simple coarse-to-fine framework powered by exhaustive search at the coarsest resolution and local directed search at finer resolutions. PPM quickly finds accurate patch correspondences between images or image regions. The search step in our algorithm is flexible to accommodate the use of other nearest-neighbor algorithms within its framework. A proposed increase K technique enables PPM to store more number of matches than required at coarse resolutions which maintains a wide search range. This improves accuracy by up-to 2%. Its effect is most significant when less number of matches are required. The early-termination technique preempts the distance calculation between patches, if the distance exceeds that of the farthest match currently stored. This speeds up the algorithm by up-to 1.7. Following the downsampling rule, the reduce patch-size technique matches smaller patches than required at coarser resolutions of the pyramid. Empowered by these techniques, PPM achieves state-of-the-art accuracy outperforming previous standards of Coherency Sensitive Hashing (CSH) [36] and PatchMatch [12] without compromising on execution-time. PPM finds up-to 4% more of the ground-truth matches and achieves lower error values compared to CSH, the current standard. Several parameters are provided to tune the search for good matches based upon the application. We perform experiments to study effects of these parameters on matching accuracy and computation time. While consistently achieving lower error values for RGB distance between matched patches, the simplicity of our algorithm also enables fast parallel implementations, providing further advantage over previous randomized, hashing or tree-based iterative approaches. On CPU cores, it achieves a nearlinear time speed-up w.r.t. the number of cores and a GPU implementation provides a further speed-up of up to 70 compared to a CPU implementation run on a quad-core machine (250 w.r.t. single core). We observe that the matching accuracy of PPM suffers from low confidence matching of patchvectors at coarse resolutions. To solve this, we propose a novel way to mix information by concatenating corresponding patch-vectors from finer resolution levels with patch-vectors of coarse levels. We call these Mixed-Resolution Vectors (MR-vectors). Unlike traditional patch-vectors that contain information from a single resolution level, MR-vectors contain more relevant information for matching. We build over our PPM algorithm by substituting MR-vectors in place of traditional patch-vectors. We call this the Mixed-Resolution Patch-Matching (MRPM) algorithm. MRPM further improves the accuracy of matches found by PPM with a marginal increase in time. It captures up-to 4% more of the groundtruth matches (8% more than CSH) and achieves near-optimal match accuracy. We also show that the MR-approach has computational benefits over an approach which uses an increased search range. We describe the effects of changing the number of resolution levels mixed and show that a balance between accuracy and time is achieved at mixing 2 levels. We perform various experiments to compare MRPM with PPM and other previous approaches, in all of which MRPM consistently performs better. Fast parallel multi-core and GPU implementations of MRPM follow from parallel implementations of PPM. We develop applications of image denoising, image summarization and auto-crop based on our MRPM algorithm. Results with better visual quality are obtained when MR-vectors are used. The computational bottleneck of these algorithms is the search for nearest neighbors of patches. We demonstrate the utility of MRPM as a fast patch-matching engine which empowers these applications. We open up new possibilities of research to explore the scope of MR-vectors which we believe has applications in several other image editing and computer vision tasks.

Abstract

The amount of information on the World Wide Web(WWW) has been increasing tremendously. It has been observed that more the available information about a given subject, the more difficult it is to locate accurate and relevant information. However, WWW is not just about textual information. The prevalence of digital cameras has brought about an exponential growth in the amount of images found on the World Wide Web. These images can be a good source of information and may prove useful for various applications. Indexing the web images and building image search engines could help users quickly find images they seek, which can then be used for many purposes. The large volume of web images has necessitated the development of efficient methods to enable indexing, searching, and retrieval of web images. The research community has responded to this challenge and we have witnessed the development of a plethora of techniques and working systems in the last two decades. Furthermore, some commercial engines have appeared, including Google image search1, Lycos2 and AltaVista photo finder3. The effectiveness of these engines is still limited. In this thesis we address the following two issues: First, predicting the terms in image alternate text using other textual descriptors. Providing search services for the web images has been difficult. Traditional image retrieval systems assign annotations to each image manually. Although it is a good methodology to retrieve images through text retrieval technologies, it is gradually becoming impossible to annotate images manually one by one due to the huge and rapid growing number of web images. Automatic Image Annotation has become an active research area since then. A common view is that semantics of web images are well correlated with their associated texts. Because of this, several popular search engines offer web image search based only on the associated texts. Alternate text(ALT tag) is considered the most important of all associated texts. ALT attribute is used to describe the contents of an image file. ALT attribute is designed to be an alternative text description for images. It represents the semantics of an image as it provides useful information to anyone using the browsers that cannot display images or image display disabled. However, a recent study has shown that around half of the images on the web have no ALT text at all. We propose an approach to predict the terms in ALT text of an image based on the term co-occurrences. We explore different approaches to the problem of predicting terms in ALT text using term co-occurrences and natural language processing techniques where the terms in noun phrases and verb phrases are given more weight, and conclude that both the term co-occurrence approach and term co-occurrence approach combined with noun phrases and verb phrases work well for the problem. However, for the prediction task, we prefer the term co-occurrence approach with out natural language processing techniques as it is language independent. We build two image annotation systems on top of the proposed approach and the proposed approach combined with natural language processing techniques, and find out that latter achieves good performance over the former. We also explore a slightly different but related problem in the context of web image retrieval: how users behave in a multilingual information access task. Search logs are good sources of information to know how the user needs are expressed. This information can be used to improve the quality of the search interface and the search experience. We analyze the search logs generated by an online game, known-item image retrieval from Flickr4, a popular image store on the web. We present our experiments to mine the search logs and extract conclusions about the behavior of users when facing a strictly multilingual information access task. We group the users based on the score, number of hints taken, and the precision to study the behavior of the most successful users, the least successful users and the users in between the two. We analyze the two types of questionnaires - Found Image Questionnaire after the user finds an image and Give up Questionnaire when the user gives up - to know the issues they faced while searching for an image. We study how the language skills effect the user behavior. The majority of Web image search is text-based and the success of such approaches often depends on reliably identifying relevant text associated with a particular image. Our findings confirm research results reported in previous studies, such as the fact that finding images is still quite challenging for users, even when the images have been tagged by a community such as Flickr. Our results show that, most of the users start with monolingual interface and soon they realize cross-lingual interface is more useful than mono-lingual interface, and the users are more comfortable to search in their mother language or the l

Abstract

Speech communication is major medium of communication among human beings. Nonverbal elements of speech help in communicating the paralinguistic information such as emotions, attitudes, intentions, etc. along with message which is conveyed by the lexical part. They play a major role in conveying the unspoken message in the speech signal. Voice quality is one such nonverbal element which helps in communicating the paralinguistic information. Voice quality (phonation type) also serves a linguistic function in various languages across the world. It also plays a role in assessment of various voice disorders. Laughter is a nonverbal vocalization which is produced and used by human beings in speech communication. It appears in natural conversation in everyday speech and provides naturalness to conversational speech. Synthesizing laughter helps in improving the expressiveness of speech synthesis. In this work, analysis and synthesis of breathy voice and laughter has been performed. Analysis has been performed based on excitation characteristics, contrary to general spectral and spectrographic methods. Features such as instantaneous fundamental frequency, strength of excitation, spectral tilt, periodic to aperiodic energy ratio and perceived loudness measure have been computed for analysis of breathy voice. Comparisons have been made between values of these parameters derived from the breathy and modal voiced speech segments. Classification experiments have been performed to discriminate breathy voice and modal voice from each other using periodic to aperiodic energy ratio and loudness measure, which proved to be discriminating the voice qualities successfully. Also, some approaches based on modifying the excitation source have been employed to synthesize breathy voice. Laugh signals have been analyzed to study the pattern and structure of the signal and the source features derived from it. The contours and range of instantaneous fundamental frequency and strength of excitation have been studied and modeled to synthesize laugh signal from a vowel segment. Other features such as presence of frication like noise within laughter, duration and intensity have also been analyzed. Perceptual significance of these features have been studied. Suitable modifications have been made in source characteristics derived from a vowel segment to synthesize a laugh signal. Subjective evaluation has been conducted to gauge the quality and the level of acceptance of the synthesized laugh signals. Scores indicate that synthesized laughter was in the acceptable range without a compromise in the quality of synthesis.