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Full-Text Articles in Computer Engineering
Acm Web Conference 2023, Usha Lokala, Kaushik Roy, Utkarshani Jaimini, Amit Sheth
Acm Web Conference 2023, Usha Lokala, Kaushik Roy, Utkarshani Jaimini, Amit Sheth
Publications
Improving the performance and explanations of ML algorithms is a priority for adoption by humans in the real world. In critical domains such as healthcare, such technology has significant potential to reduce the burden on humans and considerably reduce manual assessments by providing quality assistance at scale. In today’s data-driven world, artificial intelligence (AI) systems are still experiencing issues with bias, explainability, and human-like reasoning and interpretability. Causal AI is the technique that can reason and make human-like choices making it possible to go beyond narrow Machine learning-based techniques and can be integrated into human decision-making. It also offers intrinsic …
Practical Considerations And Applications For Autonomous Robot Swarms, Rory Alan Hector
Practical Considerations And Applications For Autonomous Robot Swarms, Rory Alan Hector
LSU Doctoral Dissertations
In recent years, the study of autonomous entities such as unmanned vehicles has begun to revolutionize both military and civilian devices. One important research focus of autonomous entities has been coordination problems for autonomous robot swarms. Traditionally, robot models are used for algorithms that account for the minimum specifications needed to operate the swarm. However, these theoretical models also gloss over important practical details. Some of these details, such as time, have been considered before (as epochs of execution). In this dissertation, we examine these details in the context of several problems and introduce new performance measures to capture practical …
Relational Sequential Decision Making, Kaushik Roy
Relational Sequential Decision Making, Kaushik Roy
Publications
Markov Decision Processes(MDPs) are the standard for sequential decision making. Comprehensive theory and methods have been developed to deal with solving MDPs in the propositional setting. Real world domains however are naturally represented using objects and relationships. To this effect, relational adaptations of algorithms to solve MDPs have been proposed in recent years. This paper presents a study of these techniques both in the model based and model free setting.
Snail Algorithm For Task Allocation In Mesh Networks, Bartosz Duszel
Snail Algorithm For Task Allocation In Mesh Networks, Bartosz Duszel
UNLV Theses, Dissertations, Professional Papers, and Capstones
Topic of this master's thesis is connected with task allocation algorithms and mesh networks. Author of this work has already graduated from Wroclaw, University of Technology (Poland) where during his studies he created software simulation environment for two different task allocation algorithms for mesh networks:Adaptive ScanandFrame Sliding. Those algorithms were compared by two, main parame- ters: simulation time and average mesh fulfillment (utilization level). All simulations were done in software environment which was developed specially for that research. This application was based on few, different types of objects: task (width, height, processing time), task queue (different number of tasks), task …
Field Programmable Gate Arrays To Accelerate Sub-Surface Imaging Problems, Miriam Leeser
Field Programmable Gate Arrays To Accelerate Sub-Surface Imaging Problems, Miriam Leeser
Miriam Leeser
No abstract provided.
Fast Software Multiplication In F_2[X] For Embedded Processors, Serdar Süer Erdem
Fast Software Multiplication In F_2[X] For Embedded Processors, Serdar Süer Erdem
Turkish Journal of Electrical Engineering and Computer Sciences
We present a novel method for fast multiplication of polynomials over F_2 which can be implemented efficiently in embedded software. Fast polynomial multiplication methods are needed for the efficient implementation of some cryptographic and coding applications. The proposed method follows a strategy to reduce the memory accesses for input data and intermediate values during computation. This strategy speeds up the binary polynomial multiplication significantly on typical embedded processors with limited memory bandwidth. These multiplications are usually performed by the comb method or the Karatsuba-based methods in embedded software. The proposed method has speed and memory advantages over these methods on …
A Graph-Based Approach To Symbolic Functional Decomposition Of Finite State Machines, Piotr Szotkowski, Mariusz Rawski, Henry Selvaraj
A Graph-Based Approach To Symbolic Functional Decomposition Of Finite State Machines, Piotr Szotkowski, Mariusz Rawski, Henry Selvaraj
Electrical & Computer Engineering Faculty Research
This paper discusses the symbolic functional decomposition method for implementing finite state machines in field-programmable gate array devices. This method is a viable alternative to the presently widespread two-step approaches to the problem, which consist of separate encoding and mapping stages; the proposed method does not have a separate decomposition step instead, the state's final encoding is introduced gradually on every decomposition iteration. Along with general description of the functional symbolic decomposition method's steps, the paper discusses various algorithms implementing the method and presents an example realisation of the most interesting algorithm. In the end, the paper compares the results …
Proactive Service Migration For Long-Running Byzantine Fault-Tolerant Systems, Wenbing Zhao, H. Zhang
Proactive Service Migration For Long-Running Byzantine Fault-Tolerant Systems, Wenbing Zhao, H. Zhang
Electrical and Computer Engineering Faculty Publications
A proactive recovery scheme based on service migration for long-running Byzantine fault-tolerant systems is described. Proactive recovery is an essential method for ensuring the long-term reliability of fault-tolerant systems that are under continuous threats from malicious adversaries. The primary benefit of our proactive recovery scheme is a reduced vulnerability window under normal operation. This is achieved in two ways. First, the time-consuming reboot step is removed from the critical path of proactive recovery. Second, the response time and the service migration latency are continuously profiled and an optimal service migration interval is dynamically determined during runtime based on the observed …
Nesting System With Quantization And Knowledge Base Applied, Leszek Koszalka, Grzegorz Chmaj
Nesting System With Quantization And Knowledge Base Applied, Leszek Koszalka, Grzegorz Chmaj
Electrical & Computer Engineering Faculty Research
Nesting algorithms deal with placing two dimensional shapes on the given canvas. In this paper a binary way of solving the nesting problem is proposed. Geometric shapes are quantized into binary form, which is used to operate on them. After finishing nesting they are converted back into original geometrical form. Investigations showed, that there is a big influence of quantization accuracy for the nesting effect. However, greater accuracy results with longer time of computation. The proposed knowledge base system is able to strongly reduce the computational time.