Landing Throttleable Hybrid Rockets With Hierarchical Reinforcement Learning In A Simulated Environment,
2020
University of New Hampshire
Landing Throttleable Hybrid Rockets With Hierarchical Reinforcement Learning In A Simulated Environment, Francesco Alessandro Stefano Mikulis-Borsoi
Honors Theses and Capstones
In this paper, I develop a hierarchical Markov Decision Process (MDP) structure for completing the task of vertical rocket landing. I start by covering the background of this problem, and formally defining its constraints. In order to reduce mistakes while formulating different MDPs, I define and develop the criteria for a standardized MDP definition format. I then decompose the problem into several sub-problems of vertical landing, namely velocity control and vertical stability control. By exploiting MDP coupling and symmetrical properties, I am able to significantly reduce the size of the state space compared to a unified MDP formulation. This paper …
Accessibility Of Deepfakes,
2020
Old Dominion University
Accessibility Of Deepfakes, Andrew L. Collings
Cybersecurity Undergraduate Research Showcase
The danger posed by falsified media, commonly referred to as deepfakes, has been well researched and documented. The software Faceswap to was used to swap the faces of two politician (Joe Biden and Donald Trump). The testing was performed using an affordable consumer GPU (an AMD Radeon RX 570) over 100,000 iterations. The process and results for the two attempts with the best results (and largest differences) were recorded. The result was ultimately unconvincing, while the software was able to recreate the facial structure the lighting and skin tone did not blend at all.
Spatial Multi-Objective Land Use Optimization Toward Livability Based On Boundary-Based Genetic Algorithm: A Case Study In Singapore,
2020
Singapore Management University
Spatial Multi-Objective Land Use Optimization Toward Livability Based On Boundary-Based Genetic Algorithm: A Case Study In Singapore, Kai Cao, Muyang Liu, Shu Wang, Mengqi Liu, Wenting Zhang, Qiang Meng, Bo Huang
Research Collection School Of Computing and Information Systems
In this research, the concept of livability has been quantitatively and comprehensively reviewed and interpreted to contribute to spatial multi-objective land use optimization modelling. In addition, a multi-objective land use optimization model was constructed using goal programming and a weighted-sum approach, followed by a boundary-based genetic algorithm adapted to help address the spatial multi-objective land use optimization problem. Furthermore, the model is successfully and effectively applied to the case study in the Central Region of Queenstown Planning Area of Singapore towards livability. In the case study, the experiments based on equal weights and experiments based on different weights combination have …
Structure-Priority Image Restoration Through Genetic Algorithm Optimization,
2020
Singapore Management University
Structure-Priority Image Restoration Through Genetic Algorithm Optimization, Zhaoxia Wang, Haibo Pen, Ting Yang, Quan Wang
Research Collection School Of Computing and Information Systems
With the significant increase in the use of image information, image restoration has been gaining much attention by researchers. Restoring the structural information as well as the textural information of a damaged image to produce visually plausible restorations is a challenging task. Genetic algorithm (GA) and its variants have been applied in many fields due to their global optimization capabilities. However, the applications of GA to the image restoration domain still remain an emerging discipline. It is still challenging and difficult to restore a damaged image by leveraging GA optimization. To address this problem, this paper proposes a novel GA-based …
Maximality And Applications Of Subword-Closed Languages,
2020
University of North Florida
Maximality And Applications Of Subword-Closed Languages, Rhys Davis Jones
UNF Graduate Theses and Dissertations
Characterizing languages D that are maximal with the property that D* ⊆ S⊗ is an important problem in formal language theory with applications to coding theory and DNA codewords. Given a finite set of words of a fixed length S, the constraint, we consider its subword closure, S⊗, the set of words whose subwords of that fixed length are all in the constraint. We investigate these maximal languages and present characterizations for them. These characterizations use strongly connected components of deterministic finite automata and lead to polynomial time algorithms for generating such languages. We prove that …
An Exact Single-Agent Task Selection Algorithm For The Crowdsourced Logistics,
2020
Singapore Management University
An Exact Single-Agent Task Selection Algorithm For The Crowdsourced Logistics, Chung-Kyun Han, Shih-Fen Cheng
Research Collection School Of Computing and Information Systems
The trend of moving online in the retail industry has created great pressure for the logistics industry to catch up both in terms of volume and response time. On one hand, volume is fluctuating at greater magnitude, making peaks higher; on the other hand, customers are also expecting shorter response time. As a result, logistics service providers are pressured to expand and keep up with the demands. Expanding fleet capacity, however, is not sustainable as capacity built for the peak seasons would be mostly vacant during ordinary days. One promising solution is to engage crowdsourced workers, who are not employed …
An Intra-Severity Classification And Adaptation Technique To Improve Dysarthric Speech Recognition Accuracy,
2020
Universiti Malaya
An Intra-Severity Classification And Adaptation Technique To Improve Dysarthric Speech Recognition Accuracy, Al-Qatab Bassam Ali Qasem
Student Works (2020-2029)
Dysarthria is a motor speech impairment at the neurological and/or muscular levels that caused difficulty in pronouncing words clearly. Automatic speech recognition (ASR) system is increasingly applied as assistive technology to aid an individual with physical disability particularly the speech impaired community such as dysarthria speakers. However, the development of an effective ASR system is hindered by the data sparsity, either in the coverage of the language or the size of the existing speech databases. The speaker adaptation (SA) technique is one of the solutions to overcome the data sparsity issue of ASR for dysarthric speakers. Our proposed method introduces …
The Evolving Fuzzy Clustering Approach For Discriminating Neutron And Gamma-Ray Pulses,
2020
Universiti Malaya
The Evolving Fuzzy Clustering Approach For Discriminating Neutron And Gamma-Ray Pulses, Shirkhorshidi Ali Seyed
Student Works (2020-2029)
Having a significant amount of data is not useful unless the data can be processed for extracting knowledge and information. One of the elementary steps in crunching data is to break it down into groups. When the data is small and collected in a controlled manner, and when the training data is appropriately labelled, the trivial approach is to use supervised learning to perform the grouping. Supervised methods need training data and information about groups beforehand; however, in the current reality, with an avalanche of data, this information is not available. Nevertheless, the need for grouping data remains. Clustering, as …
Distributed Strategy For Power Re-Allocation In High Performance Applications,
2020
Old Dominion University
Distributed Strategy For Power Re-Allocation In High Performance Applications, Vaibhav Sundriyal, Masha Sosonkina
Electrical & Computer Engineering Faculty Publications
To improve the power consumption of parallel applications at the runtime, modern processors provide frequency scaling and power limiting capabilities. In this work, a runtime strategy is proposed to distribute a given power allocation among the cluster nodes assigned to the application while balancing their performance change. The strategy operates in a timeslice-based manner to estimate the current application performance and power usage per node followed by power redistribution across the nodes. Experiments, performed on four nodes (112 cores) of a modern computing platform interconnected with Infiniband showed that even a significant power budget reduction of 20% may result in …
A Review Of Emotion Sensing: Categorization Models And Algorithms,
2020
Singapore Management University
A Review Of Emotion Sensing: Categorization Models And Algorithms, Zhaoxia Wang, Seng-Beng Ho, Erik Cambria
Research Collection School Of Computing and Information Systems
Sentiment analysis consists in the identification of the sentiment polarity associated with a target object, such as a book, a movie or a phone. Sentiments reflect feelings and attitudes, while emotions provide a finer characterization of the sentiments involved. With the huge number of comments generated daily on the Internet, besides sentiment analysis, emotion identification has drawn keen interest from different researchers, businessmen and politicians for polling public opinions and attitudes. This paper reviews and discusses existing emotion categorization models for emotion analysis and proposes methods that enhance existing emotion research. We carried out emotion analysis by inviting experts from …
V-Slam And Sensor Fusion For Ground Robots,
2020
CUNY City College
V-Slam And Sensor Fusion For Ground Robots, Ejup Hoxha
Dissertations and Theses
In underground, underwater and indoor environments, a robot has to rely solely on its on-board sensors to sense and understand its surroundings. This is the main reason why SLAM gained the popularity it has today. In recent years, we have seen excellent improvement on accuracy of localization using cameras and combinations of different sensors, especially camera-IMU (VIO) fusion. Incorporating more sensors leads to improvement of accuracy,but also robustness of SLAM. However, while testing SLAM in our ground robots, we have seen a decrease in performance quality when using the same algorithms on flying vehicles.We have an additional sensor for ground …
Stochastic Orthogonalization And Its Application To Machine Learning,
2019
Southern Methodist University
Stochastic Orthogonalization And Its Application To Machine Learning, Yu Hong
Electrical Engineering Theses and Dissertations
Orthogonal transformations have driven many great achievements in signal processing. They simplify computation and stabilize convergence during parameter training. Researchers have introduced orthogonality to machine learning recently and have obtained some encouraging results. In this thesis, three new orthogonal constraint algorithms based on a stochastic version of an SVD-based cost are proposed, which are suited to training large-scale matrices in convolutional neural networks. We have observed better performance in comparison with other orthogonal algorithms for convolutional neural networks.
Adversarial Attack On Neural Machine Translation System,
2019
Indian Statistical Institute
Adversarial Attack On Neural Machine Translation System, Abijith K. P.
Master’s Dissertations
Nowadays Deep Neural Network based solutions are deployed to solve numerous tasks. Thus, it has become absolutely important to study the robustness of these systems. Machine Translation is one of the popular applications of Deep Neural Networks. This thesis studies the robustness of Neural Machine Translation systems by generating adversarial examples with the objective to fool the model. Whenever there is a change in the source, i.e. when a word in the input sentence is replaced by an unrelated word, the translation system is supposed to reflect the changes while doing translation. These unwanted invariance learned by the model is …
Developing A Computational Framework For A Construction Scheduling Decision Support Web Based Expert System,
2019
University of Southern Mississippi
Developing A Computational Framework For A Construction Scheduling Decision Support Web Based Expert System, Feroz Ahmed
Dissertations
Decision-making is one of the basic cognitive processes of human behaviors by which a preferred option or a course of action is chosen from among a set of alternatives based on certain criteria. Decision-making is the thought process of selecting a logical choice from the available options. When trying to make a good decision, all the positives and negatives of each option should be evaluated. This decision-making process is particularly challenging during the preparation of a construction schedule, where it is difficult for a human to analyze all possible outcomes of each and every situation because, construction of a project …
The Generation Of Operational Policy For Cyber-Physical Systems In Smart Homes,
2019
Missouri State University
The Generation Of Operational Policy For Cyber-Physical Systems In Smart Homes, Jared Wayne Hall
Graduate Theses/Dissertations
The term “Cyber-Physical Systems” (CPS) refers to those systems which seamlessly integrate sensing, computation, control, and networking into physical objects and infrastructure [1]. In these systems, computers and networks of physical entities interact with each other to bring new capabilities to traditional physical systems. Since its introduction, the field of Cyber-Physical Systems (CPS) has evolved with new and interesting advancements concerning its capability, adaptability, scalability, and usability [1]. One such advancement is the unification of the Internet of Things (IoT), a concept that enables real-world everyday objects to connect to the internet and interact with each other, with CPS [1]. …
Testing Isomorphism Of Graded Algebras,
2019
Colorado State University - Fort Collins
Testing Isomorphism Of Graded Algebras, Peter A. Brooksbank, James B. Wilson, Eamonn A. O'Brien
Faculty Journal Articles
We present a new algorithm to decide isomorphism between finite graded algebras. For a broad class of nilpotent Lie algebras, we demonstrate that it runs in time polynomial in the order of the input algebras. We introduce heuristics that often dramatically improve the performance of the algorithm and report on an implementation in Magma.
Harmony Search Algorithm For Time-Dependent Vehicle Routing Problem With Time Windows,
2019
Yuan-Ze University
Harmony Search Algorithm For Time-Dependent Vehicle Routing Problem With Time Windows, Yun-Chia Liang, Vanny Minanda, Aldy Gunawan, Angela Hsiang-Ling Chen
Research Collection School Of Computing and Information Systems
Vehicle Routing Problem (VRP) is a combinatorial problem where a certain set of nodes must be visited within a certain amount of time as well as the vehicle’s capacity. There are numerous variants of VRP such as VRP with time windows, where each node has opening and closing time, therefore, the visiting time must be during that interval. Another variant takes time-dependent constraint into account. This variant fits real-world scenarios, where at different period of time, the speed on the road varies depending on the traffic congestion. In this study, three objectives – total traveling time, total traveling distance, and …
Contrasting Geometric Variations Of Mathematical Models Of Self-Assembling Systems,
2019
University of Arkansas, Fayetteville
Contrasting Geometric Variations Of Mathematical Models Of Self-Assembling Systems, Michael Sharp
Graduate Theses and Dissertations
Self-assembly is the process by which complex systems are formed and behave due to the interactions of relatively simple units. In this thesis, we explore multiple augmentations of well known models of self-assembly to gain a better understanding of the roles that geometry and space play in their dynamics. We begin in the abstract Tile Assembly Model (aTAM) with some examples and a brief survey of previous results to provide a foundation. We then introduce the Geometric Thermodynamic Binding Network model, a model that focuses on the thermodynamic stability of its systems while utilizing geometrically rigid components (dissimilar to other …
Selective Discrete Particle Swarm Optimization For The Team Orienteering Problem With Time Windows And Partial Scores,
2019
Singapore Management University
Selective Discrete Particle Swarm Optimization For The Team Orienteering Problem With Time Windows And Partial Scores, Vincent F. Yu, Perwira A. A. N. Redi, Parida Jewpanya, Aldy Gunawan
Research Collection School Of Computing and Information Systems
This paper introduces the Team Orienteering Problem with Time Windows and Partial Scores (TOPTW-PS),which is an extension of the Team Orienteering Problem with Time Windows (TOPTW). In the context of theTOPTW-PS, each node is associated with a set of scores with respect to a set of attributes. The objective ofTOPTW-PS is to find a set of routes that maximizes the total score collected from a subset of attributes whenvisiting the nodes subject to the time budget and the time window at each visited node. We develop a mathematical model and propose a discrete version of the Particle Swarm Optimization (PSO), …
Iomt Malware Detection Approaches: Analysis And Research Challenges,
2019
Old Dominion University
Iomt Malware Detection Approaches: Analysis And Research Challenges, Mohammad Wazid, Ashok Kumar Das, Joel J.P.C. Rodrigues, Sachin Shetty, Youngho Park
VMASC Publications
The advancement in Information and Communications Technology (ICT) has changed the entire paradigm of computing. Because of such advancement, we have new types of computing and communication environments, for example, Internet of Things (IoT) that is a collection of smart IoT devices. The Internet of Medical Things (IoMT) is a specific type of IoT communication environment which deals with communication through the smart healthcare (medical) devices. Though IoT communication environment facilitates and supports our day-to-day activities, but at the same time it has also certain drawbacks as it suffers from several security and privacy issues, such as replay, man-in-the-middle, impersonation, …
