http://dspace.iiitb.ac.in:8080/handle/123456789/52 2026-07-27T22:10:50Z http://dspace.iiitb.ac.in:8080/handle/123456789/76 Title: "Digital Calibration Techniques Of Pipelined And Algorithmic Adcs" Authors: R, Chinmaye 2022-07-01T00:00:00Z http://dspace.iiitb.ac.in:8080/handle/123456789/70 Title: Novel functional availability analysis technique using system algebra for safety critical systems Authors: Nanda, Manju Abstract: ,Systems around us are often complex in design and functionality, and futuristic systems are going to be even more complex. There is a need to incorporate more formal method (FM)-based tools and techniques to fundamentally raise the bar with systems engineering processes, for lowering cost and time while increasing the safety assurance of complex systems. Such tools and techniques address problem spaces like generation of an integrated formal framework, a tool-based formal workbench, synthesis of critical functionalities, and real-life challenges. There already exist various FM-based tools and techniques being incorporated into various phases of the systems engineering process in order to address real-life system challenges. The research reported in this thesis adds a novel technique to the existing repertoire of systems engineering, to help increase the safety assurance level during the design of safety-critical systems. Modern systems in critical applications, such as net-centric warfare and aerospace cyber-physical systems, are multi-functional. The availability requirements of these complex systems are very high. An ability to predict the future functional availability of a system given its design, and to achieve an assurance of a desired level of functional ability during design, are thus of much importance for safety-critical systems. The functional availability of a system, if known early on, can be used to better understand the pros and cons of the design and to detect design anomalies, which in turn leads to improvements in the design and life-cycle processes. There is a need for such a technique to detect design anomalies early on in the engineering process, to improve the design phase. This thesis proposes a novel FM-based technique for analyzing functional availability of a system. The functional availability is determined using theSystem Algebra (SA) FM. The SA technique uses the concept of a System State Machine (SSM) to compute system states and transitions between them over the life of a system. In the SA technique, a mathematical model is generated to represent the system under analysis. The relationships between different sub-systems of a system are modeled using this mathematical model by generating an SA expression. Applying operations on the SA expressions enables understanding of the system. As per SA, a system exists in one of the three states: the safe state, the hazardous state, and the unsafe state. The related SSM concept determines and analyzes the system state and its transition from one state to another over time, influenced by the failure of various sub-systems and components. The system state at any instant is determined by the health of its components and the states of its sub-systems. The health of a component is determined by its failure rate. Over time, as components start failing, the sub-systems degrade, thus degrading the overall system due to unavailable functionality. With SSM analysis, the design can be improved for better functional availability. This technique can help designers better understand system behavior and detect design anomalies. The system state and its transition determine the control flow between system states, and related changes in system functionality. The proposed integrated design framework based on the SA technique has been automated to make the systems engineering process faster, more effective, and easier to implement. A design tool is being developed for easy plugin into any engineering framework. The design framework has been validated by applying the technique for analyzing the design of existing safety-critical systems in different domains. In addition, the efficacy of the modified design framework has been validated by implementing it on completely new safetycritical aerospace systems. The SA technique introduced in the design phase of the integrated formal framework is seen to improve the performance of the process as compared to the conventional and model-based systems engineering framework. Description: xiii, 178p. 2014-09-01T00:00:00Z http://dspace.iiitb.ac.in:8080/handle/123456789/69 Title: Semantics extraction in information spaces using co occurance analysis Authors: Mutalikdesai, Mandar R Abstract: An information space is a large collection of content generated by human actors. Examples of information spaces include the Web, digital libraries and social media. These spaces hold signi cant amounts of latent semantics, which may be relevant to various stakeholders such as market data analysts, marketing research personnel, etc. In this thesis, we address the problem of mining latent semantics from information spaces. We note that information spaces are not uniformly similar in nature. They can be classi ed into two types: repository spaces and social spaces. Examples of repository spaces are the Web and digital libraries, while examples of social spaces are the blogosphere and wikis. Content is generated in both these spaces by cognitive processes of actors, with the content manifesting as documents, web pages, blog posts, reviews, articles, tweets, etc. During the creation of such content, the actor typically embeds her individual world-views (opinions, feelings, etc.) into the content. Also, in both these spaces, there exist social interactions between the cognitive processes, which manifest as references between documents in the form of links or citations, comments to blog posts, rebuttals to criticisms, responses to reviews, etc. However, repository spaces and social spaces di er in terms of the boundary of social interaction, the scope of engagement of actors, and the localized synchrony of social interactions. While the social interactions in repository spaces can be spread across the entire repository space, the social interactions in social spaces have wellde ned boundaries within which the commonly held world-views of multiple actors can emerge in a focused manner. We call this boundary within which cognitive processes interact as a socio-cognitive process. While the entire repository represents a single socio-cognitive process, there exist multiple socio-cognitive processes within a social space. Also, in a repository space, the engagement of actors is typically limited to editing only a few documents, since they can edit only those documents that are owned by them. In social spaces, on the other hand, actors can engage in multiple socio-cognitive processes, typically even if those socio-cognitive processes are not owned by them. Another aspect in which repository spaces and social spaces differ is the localized synchrony of social interactions. As we have observed, the social interactions in a repository space are not localized. Also, these interactions between cognitive processes do not exhibit synchrony. By this, we mean that these social interactions are not in tune with each other over time within the socio-cognitive process. On the other hand, the social interactions in a social space are not only localized to a well-de ned socio-cognitive process, but also synchronous. Such social interactions largely take place within short durations of each other in a localized manner. In the rst part of this thesis, we posit that semantics are the commonly held world-views of actors, which emerge in a socio-cognitive process in both, repository spaces as well as social spaces. We rely on the co-occurrence analysis of artifacts such as concepts (e.g., named entities) and social interactions (e.g., citations) within an information space in order to mine semantics. We assert that co-occurrence analysis embodies a fundamental principle of human cognition known as the Hebbian Theory. We also assert that cooccurrence analysis is a manifestation of the principles of Ordinary Language Philosophy, which states that the meaning of a term depends upon its usage with other terms. Further, we argue that co-occurrence analysis not only helps in identifying the meaning of a concept, but also its semantic associations relative to other concepts. We test this hypothesis in both, repositories and social spaces. In the second part of this thesis, we analyze the co-occurrences of citations (or co-citations) to discover endorsed citations in a repository space. Given a document, an endorsed citation is an outgoing citation whose target document is deemed by other co-citing documents to be more relevant to the source document than the targets of other outgoing citations from the source document. We envisage the use of endorsed citations in focused resource discovery and relevance ranking in repository spaces. In the third part of this thesis, we analyze the co-occurrences of concepts (terms) in a social space to detect object-attribute relationships. Given an object (i.e. a concept), we de ne as its attributes those concepts that, besides being semantically related to the object, help in collectively describing the object uniquely. We assert that the attributes of an object tend to co-occur with the object across cognitive contexts (paragraphs, article-sections, documents, etc.) in a social space. We present two co-occurrence based hypotheses for identifying objectattribute relationships between concepts. We envisage that the discovery of the semantic attributes of an object has applications in social media analytics, e.g., (i) marketing research personnel looking to nd out how the population characterizes their product, and (ii) classi cation of concepts within an encyclopedic environment like Wikipedia. Description: viii, 150p. 2013-02-02T00:00:00Z http://dspace.iiitb.ac.in:8080/handle/123456789/68 Title: Mining Semantics from unstructured text using a cognitive model on lexical cooccurances Authors: Rachakonda, Aditya Ramana Abstract: Mining latent semantics from text corpora is an important problem with several applications, and models to explain how semantic associations get embedded into natural language are of immense interest. In this thesis, we take a cognitive modelling approach to this problem.The text corpus is viewed as a cognitive space, and each document is treated as a cognitive episode whose objective is to convey some meaning within some context. Semantic communication is proposed to take place in a 3-layer model. The topmost layer, called the analytic layer, maintains the semantic worldview of the communicator. Communication happens in the context of an episode, where semantics from the analytic layer are combined with the episodic objectives to create conceptual idea units. This happens in the second layer called the episodic layer. The last layer, called the linguistic layer, provides language specific vocabularies and inflections that convert conceptual idea units into communication units like speech utterances, gestures or written text. Mining latent semantics becomes the problem of inferring analytic layer associations by observing linguistic layer recordings. This is addressed by defining the problem in the analytic layer; proposing an episodic hypothesis on observations of episodic patterns; and extracting semantics from patterns of co-occurrences of terms based on the hypothesis. In this thesis, we define three semantic associations and by using the 3-layer cognitive model, we reliably mine them from co-occurrences observed in the English language Wikipedia. The first of these associations, called topical anchors, represents the topic of a given a short piece of text, like a sentence. We found that our algorithm could identify the topical anchor with an accuracy similar to that of a cluster labelling algorithm but instead of documents the input was just a small set of words to describe an episode. For example, given the statement, ‘Andy Murray defeated Roger Federer’, we identified that ‘Tennis’ is a term which semantically represents the topic of the statement.The second semantic association, called semantic siblings, represents terms which belong to a hypothetical set and semantically share a conceptual parent. We found that using co-occurrences and without using structural cues or domain specific cues, we could extract semantic sibling terms of a small set of terms similar to that of set expansion algorithms. For instance, given a seed set of English Premier League football teams like, {‘Manchester United’, ‘Arsenal’, ‘Chelsea’}, we identified that terms like ‘Liverpool’ and ‘New Castle United’ belongs to the same set. Finally, we propose a semantic association called topical markers. Topical markers are terms which are unique to a specific context and their presence in a sentence helps to unambiguously identify its topic. Given an arbitrary topic and a co-occurrence graph, we found that we could extract terms which are unique to the topic. We also found that the topical markers, when used as query terms in a generic search engine, resulted in pages which are unique to the topic in question. Using these semantic associations we confirm the validity of our hypotheses and in turn the validity of the cognitive model proposed in this thesis. Description: xv, 128p. 2013-12-20T00:00:00Z