Computer Science and Automation (CSA): Recent submissions
Now showing items 141-160 of 545
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Nodeterminism and communication in functional programming systems : A study in formal program development
The phenomenal advancement in VLSI technology witnessed in recent years has led to the economic feasibility of building computers which support massive parallelism in computation. Functional programming languages have great ... -
Approximate decoding over tail-biting trellises
This thesis proposes and implements soft-decision decoding algorithms on tail-biting trellises. For linear block codes, tail-biting trellises are interesting from a soft-decision decoding view-point, because of their reduced ... -
Scaling the performance of web servers using a greedy data buffering and caching strategy
Pervasive use of the web has placed extreme performance demands on its key architectural elements of which the web server is the most critical. A web server is a highly I/O intensive application, and I/O data handling ... -
Fault-tolerant distributed algorithms for reconfiguration of rings using management tokens
In this thesis, we propose two algorithms using slightly different approaches to detect failures in a ring, and to reconfigure the ring using a combination of multithreading and management tokens which circulate around the ... -
A complier writing system based on affix grammars
Compiler Generators have become well-established tools in the production of a compiler. In general, a compiler generator uses a specification of a programming language at an abstract level as input and outputs the code for ... -
Evaluating cache performance under multiprogrammed workloads
Computer system performance is critically dependent on cache performance. Cache effectiveness is determined by factors such as program locality of reference and cache organization. Different approaches to cache performance ... -
Sequential Decision Making with Risk, Offline Data and External Influence: Bandits and Reinforcement Learning
Reinforcement Learning (RL) serves as a foundational framework for addressing sequential decision-making problems under uncertainty. In recent years, extensive research in this domain has led to significant advancements ... -
A framework for timing analysis of event-driven applications
Event-driven applications, particularly those based on the publish–subscribe communication model are widely adopted to build responsive and decoupled applications in domains such as robotics, the Internet of Things ... -
Multi-timescale and Multi-agent Reinforcement Learning Algorithms
This thesis presents six novel works involving several research domains, such as reinforcement learning (RL)– both with or without function approximators including deep neural networks, multi-agent RL, stochastic optimization, ... -
CHARGE: Accelerating GNN Training via CPU Sampling in Heterogeneous CPU–GPU Environment
Graph Neural Networks (GNNs) have demonstrated exceptional performance across a wide range of applications, driving their widespread adoption. Current frameworks employ CPU and GPU resources—either in isolation or ... -
On Orbits and Border of Constant Read Circuits and Lower Bounds for Constant Depth Circuits
Two of the most common ways in which arithmetic circuits can be restricted is by requiring that they be constant read or constant depth. Constant depth circuits have received a lot of attention in the arithmetic circuit ... -
Design of AI-based Computational Framework for Accurate Detection of Polycystic Ovarian Disease and Ovarian Cancer Using Ultrasound, CT and Histopathology Images
Polycystic Ovarian Disease (PCOD) and Ovarian Cancer (OC) represent critical health challenges affecting millions of women globally. Early and accurate detection of these conditions is essential for effective clinical ... -
Controller Synthesis Techniques for Infinite-State Reactive Systems
Reactive systems are ubiquitous, with various use cases ranging from controllers for cyber-physical systems to programs that run on multipurpose computers. A system is reactive if it continually behaves in a specific manner ... -
IEDFuRL: A Black-box Fuzz Tester for IEC61850-based Intelligent Electronic Devices using Reinforcement Learning
Intelligent Electronic Devices (IEDs) are essential components of modern power grids, functioning as microprocessor-based controllers that facilitate communication, monitoring, protection, and control within Supervisory ... -
Mitigating Bias via Algorithms with Fairness Guarantees
The rapid integration of automated decision-making systems in critical domains such as resume screening, loan approval, content recommendation, and disaster containment has raised significant concerns regarding biases in ... -
Reasoning about Safety of Camera-Based Neural Network Controlled Systems
Autonomous technologies are becoming increasingly prevalent due to the numerous benefits they offer, including improved safety and security, enhanced accessibility for mobility-challenged individuals, and the ability to ... -
Algorithms for various cost criteria in Reinforcement Learning
In this thesis we will look at various Reinforcement Learning algorithms. We will look at algorithms for various cost criteria or reward objectives namely Finite Horizon, Discounted Cost, Risk-Sensitive Cost. For Finite ... -
Combinatorial Problems arising in Quantum Physics and Model counting
This thesis investigates some combinatorial problems arising in quantum physics and model counting. In particular, we develop new graph-theoretic techniques to resolve some open questions from quantum photonics. We also ... -
Feature Tracking and Visual Analysis of Temporal Scalar Fields in the Ocean
The Bay of Bengal (BoB) has maintained its salinity distribution over the years despite a continuous flow of fresh water entering it through rivers on the northern coast, which can dilute its salinity. This can be ... -
Loop Transformations for Multi-/Many-Core Architectures using Machine Learning
Loop transformation techniques such as loop tiling, loop interchange and unroll-and-jam help expose better coarse-grain and fine-grain data-level parallelisms as well as exploit data locality. These transformations are ...