Digital Commons Network^™

Analysis Of Bacteriorhodopsin Suspended In A Bilayer Lipid Membrane, Moath Alhejji

Graduate Theses and Dissertations

The bacteriorhodopsin protein’s unique characteristic of proton pumping can convert light energy to electric energy. The aim of this research was to generate photocurrent using bacteriorhodopsin in a bi-layer lipid membrane. Lipid monolayer and bilayer were formed using painting and folding methods, respectively. Capacitance and resistance of the lipid membranes were measured and used to validate the best methodology. My results show that the folding method is more efficient in incorporating Bacteriorhodopsin. The photocurrent was generated by illuminating a green laser (532 nm) on the bilayer lipid membranes. The patch clamp electrophysiology technique was used to apply voltage across the …

Automated Flight Controller Adaptive Compensation For Actuator Failures In Transport Type Aircraft, Daniel James Fresella

Graduate Theses and Dissertations

Aircraft operate over a wide range of conditions including atmospheric, weight, and center ofgravity changes. This presents a substantial challenge to automatic control system designers. When these operating conditions are merged with a partial or full control surface failure, automatic flight control is near impossible with conventional controllers. Additionally, when pilots experience control failure emergencies during flight, workload and fatigue increase drastically. The continued research of automatic flight control systems that can seamlessly adapt to unmodelled failures will enable a new generation of robust aircraft control. In this paper a 9th order 6 degree of freedom aircraft model is used …

Fair And Diverse Group Formation Based On Multidimensional Features, Mohammed Saad A Alqahtani

Graduate Theses and Dissertations

The goal of group formation is to build a team to accomplish a specific task. Algorithms are being developed to improve the team's effectiveness so formed and the efficiency of the group selection process. However, there is concern that team formation algorithms could be biased against minorities due to the algorithms themselves or the data on which they are trained. Hence, it is essential to build fair team formation systems that incorporate demographic information into the process of building the group. Although there has been extensive work on modeling individuals’ expertise for expert recommendation and/or team formation, there has been …

Catalytic Activity Of Molybdenum-Dioxo Complexes, Randy Tran

Graduate Theses and Dissertations

This dissertation details the development of rationally designed dioxomolybdenum catalyst active for deoxydehydration (DODH), the net reduction of diols and polyols into alkenes and dienes. Catalyst design involved variations on dioxomolybdenum(VI) supported by a dianionic meridional pincer ligand. Rational substrate scope was explored using aliphatic diols, aromatic diols, and biomass derived diols. Various reductants were tested for ability to catalyze the reaction. The substrate specific mechanism of DODH was explored utilizing NMR and in-situ infrared spectroscopy and important rate constants and rate determining steps were found to aid in the optimization of ideal reaction conditions. Catalytic activity was observed to …

Parenting The Gifted: Caregivers’ Perspectives Of Challenges And Their Confidence To Support Their Exceptional Children, Kristi A. Mascher

Graduate Theses and Dissertations

This phenomenological study uses Bandura’s theory of self-efficacy (1977) to examine the lived experiences of eight parents of gifted children and how their experiences, both positive and negative, shape their perception of their confidence and may contribute to building future supports for gifted parents and caregivers. Qualitative data, collected through semi-structured interviews and analyzed with an interpretive/hermeneutic lens, provides seven major themes derived from the voices of parents with children of varying ages and exceptionalities. In addition, this study concludes with a discussion surrounding the additional challenges associated with parenting the exceptional, frameworks for gifted parent support systems, as well …

The Nature Of Informal Educators In Science Centers, Science Museums And Zoos: Case Studies Of Personnel, Practices, Programs, Outreach And Organization, Courtney Erickson

Graduate Theses and Dissertations

Informal Science Centers provide educational experiences for people across the country daily. While the terminology is often similar, there are differences between institutions, often determined by mission, organizational structure, and experience. The purpose of this study was to identify shared experiences and unique characteristics of eight informal science centers around the country. The significance of the study was to add to the understanding of informal science educators' responsibilities, organizational structure, decision-making process, and development. Data for the study was collected using qualitative measures through a researcher-created interview, sent to fifteen institutions, after the recommendation from two well-known informal science researchers. …

Adapting Animals: Nineteenth-Century British Literature, Science, And Media, Kristen Layne Figgins

Graduate Theses and Dissertations

In the nineteenth century, Charles Darwin and other proponents of evolutionary theory provided a theoretical framework for discussing the question of humanity’s place in the world. These nascent theories emphasized the shared animal nature of humans and the nonhuman creatures who had once occupied a distinctly lower place on the chain of being. My dissertation addresses the question of how nineteenth-century scientific attitudes about animals were reflected in the literature of the period. By examining culture-texts from the nineteenth century, it is clear that literature was an active participant in extending scientific knowledge, often by playing with the blending categorical …

The Use Of Singlebeam Echo-Sounder Depth Data To Produce Demersal Fish Distribution Models That Are Comparable To Models Produced Using Multibeam Echo-Sounder Depth, Marcela Montserrat Landero Figueroa, Miles J. G. Parsons, Benjamin J. Saunders, Ben Radford, Chandra Salgado-Kent, Iain M. Parnum

Research outputs 2014 to 2021

Seafloor characteristics can help in the prediction of fish distribution, which is required for fisheries and conservation management. Despite this, only 5%–10% of the world's seafloor has been mapped at high resolution, as it is a time-consuming and expensive process. Multibeam echo-sounders (MBES) can produce high-resolution bathymetry and a broad swath coverage of the seafloor, but require greater financial and technical resources for operation and data analysis than singlebeam echo-sounders (SBES). In contrast, SBES provide comparatively limited spatial coverage, as only a single measurement is made from directly under the vessel. Thus, producing a continuous map requires interpolation to fill …

Duty To Address Climate Change Litigation Risks For Australian Energy Companies—Policy And Governance Issues, Prafula Pearce

Research outputs 2014 to 2021

The transition from fossil fuels to renewable energy requires cooperation from all, including corporations, shareholders, and institutional investors. The purpose of this paper is to explore climate change litigation risks for Australian energy companies and investors from a policy and governance perspective. Companies are increasingly reporting their climate policies to satisfy their shareholders and investor demands. In addition, the government and judiciary are making laws and decisions to support the Paris Agreement. This paper explores whether company directors can and, in some cases, should be considering the impact of climate change litigation risks on their business, or else risk breaching …

Nano-Grating Assisted Light Absorption Enhancement For Msm-Pds Performance Improvement: An Updated Review, Narottam Das, Mohammad Nur-E-Alam, Alif Islam, Ain Zulaikha Maslihan Ain

Research outputs 2014 to 2021

The primary focus of this review article mainly emphasizes the light absorption enhancement for various nanostructured gratings assisted metal-semiconductor-metal photodetectors (MSM-PDs) that are so far proposed and developed for the improvement of light capturing performance. The MSM-PDs are considered as one of the key elements in the optical and high-speed communication systems for applications such as faster optical fiber communication systems, sensor networks, high-speed chip-to-chip interconnects, and high-speed sampling. The light absorption enhancement makes the MSM-PDs an ideal candidate due to their excellent performances in detection, especially in satisfying the high-speed or high-performance device requirements. The nano-grating assisted MSM-PDs are …

Investigating Strike-Slip Faulting Parallel To The Icelandic Plate Boundary Using Boundary Element Models, Anna E.R. Pearson, John P. Loveless

Geosciences: Faculty Publications

Most faults in Iceland strike roughly parallel to the divergent plate boundary, a part of the North American-Eurasian plate boundary, which would be expected to lead to primarily normal faulting. However, several studies have observed a significant component of rift-parallel strike-slip faulting in Iceland. To investigate these fault kinematics, we use the boundary element method to model fault slip and crustal stress patterns of the Icelandic tectonic system, including a spherical hotspot and uniaxial stress that represents rifting. On a network of faults, we estimate the slip required to relieve traction imposed by hotspot inflation and remote rifting stress and …

Genome Annotation Using Average Mutual Information, Garin P. Newcomb

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Advancements in high-throughput DNA sequencing technologies and ambitious goals for their use are resulting in the generation of a deluge of unannotated sequenced genomes. This makes computational tools that can aid in annotation increasingly valuable.

Here, we provide a detailed exploration of the utility as well as the limitations of average mutual information (AMI) in several steps of genome annotation. For a genomic sequence, AMI is a measure of the information a base contains about the base separated by a fixed lag. A profile is constructed by calculating AMI at multiple lags. In addition to traditional AMI, we employ two …

Risk-Based Machine Learning Approaches For Probabilistic Transient Stability, Umair Shahzad

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Power systems are getting more complex than ever and are consequently operating close to their limit of stability. Moreover, with the increasing demand of renewable wind generation, and the requirement to maintain a secure power system, the importance of transient stability cannot be overestimated. Considering its significance in power system security, it is important to propose a different approach for enhancing the transient stability, considering uncertainties. Current deterministic industry practices of transient stability assessment ignore the probabilistic nature of variables (fault type, fault location, fault clearing time, etc.). These approaches typically provide a conservative criterion and can result in expensive …

Order And Harmony: Kepler’S Guiding Forces, Dan Broadbent

Faculty Publications

Adapted from the article “Order and Harmony: Kepler’s Guiding Forces” included in “Towards Mysteries of the Cosmos with Johannes Kepler – on the 450th Anniversary of His Birth,” a commemorative volume published by the Obserwatorium Atronommiczne Krolowej Jadwigi Rzepienniku Biskupim (Queen Jadwiga Observatory of Rzepiennik Biskupi Poland) December 2021. Adapted with permission.

As the subject librarian for physics and astronomy at Brigham Young University, the author has had the privilege of handling some of Johannes Kepler’s original books preserved in the university’s archives. One of the most impressive materials in the archive is a large page from Mysterium Cosmographicum that …

Status Of College Libraries In Tripura, Augustine Zimik, Priyanka Laskar

Library Philosophy and Practice (e-journal)

Academic Libraries has always played a pivotal role in nurturing a resourceful human resource. The college library in particular introduces the importance of library in achieving decent grade in academic pursued. This paper is an attempt to understand the status of libraries and their services provided in college libraries of Tripura, India. Another major objective of the study is to investigate the status of college library professionals in the state of Tripura. For the study fourteen college libraries were considered for examination. A survey method was employed for the study. For primary data collection, questionnaires were distributed to concerned librarians. …

Level Of Disaster Management Preparedness By Library Staff In Academic Libraries: The Experience Of Academic Libraries In South Eastern States, Nigeria, Pauline Iroeze, Pauline Chinasa Iroeze Dr.

Library Philosophy and Practice (e-journal)

Abstract

Academic libraries in South-eastern Nigeria are still not prepared for disaster. This study sets out to assess the current status of preparedness in disaster management among academic libraries in the South east geopolitical zone of Nigeria. To obtain a base level of knowledge on disaster preparedness of current practices, a questionnaire was distributed to 380 librarians at 5 academic libraries, 356 responses were received and after sorting 337 were found to be usable. The study revolved around the current status of preparedness, on various issues including major threats that could possibly cause disaster, existence of disaster preparedness plan among …

Perspectives Of Knowledge Management Systems Implementation, De-Graft Johnson Dei

Library Philosophy and Practice (e-journal)

The implementation of systems to manage the knowledge of organizations requires robust technical and non-technical support in other to be successful. Knowledge management systems integrate people, processes, and technology. These systems result in changes in the operations and processes in organizations. The study assessed knowledge management systems from the two main perspectives (technical and non-technical) by emphasizing the technologies that drive the creation, processing, sharing, and storage of knowledge. From the nontechnological perspective, the study focussed on the interaction of people, process and that promote KM. This paved the way for the discussion of the various perspectives or procedures for …

Video Snapshot: Single Image Motion Expansion Via Invertible Motion Embedding, Qianshu Zhu, Chu Han, Guoqiang Han, Tien-Tsin Wong, Shengfeng He

Research Collection School Of Computing and Information Systems

Unlike images, finding the desired video content in a large pool of videos is not easy due to the time cost of loading and watching. Most video streaming and sharing services provide the video preview function for a better browsing experience. In this paper, we aim to generate a video preview from a single image. To this end, we propose two cascaded networks, the motion embedding network and the motion expansion network. The motion embedding network aims to embed the spatio-temporal information into an embedded image, called video snapshot. On the other end, the motion expansion network is proposed to …

Learning Large Neighborhood Search Policy For Integer Programming, Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang

Research Collection School Of Computing and Information Systems

We propose a deep reinforcement learning (RL) method to learn large neighborhood search (LNS) policy for integer programming (IP). The RL policy is trained as the destroy operator to select a subset of variables at each step, which is reoptimized by an IP solver as the repair operator. However, the combinatorial number of variable subsets prevents direct application of typical RL algorithms. To tackle this challenge, we represent all subsets by factorizing them into binary decisions on each variable. We then design a neural network to learn policies for each variable in parallel, trained by a customized actor-critic algorithm. We …

Neurolkh: Combining Deep Learning Model With Lin-Kernighan-Helsgaun Heuristic For Solving The Traveling Salesman Problem, Liang Xin, Wen Song, Zhiguang Cao, Jie Zhang

Research Collection School Of Computing and Information Systems

We present NeuroLKH, a novel algorithm that combines deep learning with the strong traditional heuristic Lin-Kernighan-Helsgaun (LKH) for solving Traveling Salesman Problem. Specifically, we train a Sparse Graph Network (SGN) with supervised learning for edge scores and unsupervised learning for node penalties, both of which are critical for improving the performance of LKH. Based on the output of SGN, NeuroLKH creates the edge candidate set and transforms edge distances to guide the searching process of LKH. Extensive experiments firmly demonstrate that, by training one model on a wide range of problem sizes, NeuroLKH significantly outperforms LKH and generalizes well to …

Learning To Iteratively Solve Routing Problems With Dual-Aspect Collaborative Transformer, Yining Ma, Jingwen Li, Zhiguang Cao, Wen Song, Le Zhang, Zhenghua Chen, Jing Tang

Research Collection School Of Computing and Information Systems

Recently, Transformer has become a prevailing deep architecture for solving vehicle routing problems (VRPs). However, it is less effective in learning improvement models for VRP because its positional encoding (PE) method is not suitable in representing VRP solutions. This paper presents a novel Dual-Aspect Collaborative Transformer (DACT) to learn embeddings for the node and positional features separately, instead of fusing them together as done in existing ones, so as to avoid potential noises and incompatible correlations. Moreover, the positional features are embedded through a novel cyclic positional encoding (CPE) method to allow Transformer to effectively capture the circularity and symmetry …

Canita: Faster Rates For Distributed Convex Optimization With Communication Compression, Zhize Li, Peter Richtarik

Research Collection School Of Computing and Information Systems

Due to the high communication cost in distributed and federated learning, methods relying on compressed communication are becoming increasingly popular. Besides, the best theoretically and practically performing gradient-type methods invariably rely on some form of acceleration/momentum to reduce the number of communications (faster convergence), e.g., Nesterov's accelerated gradient descent (Nesterov, 1983, 2004) and Adam (Kingma and Ba, 2014). In order to combine the benefits of communication compression and convergence acceleration, we propose a \emph{compressed and accelerated} gradient method based on ANITA (Li, 2021) for distributed optimization, which we call CANITA. Our CANITA achieves the \emph{first accelerated rate} $O\bigg(\sqrt{\Big(1+\sqrt{\frac{\omega^3}{n}}\Big)\frac{L}{\epsilon}} + \omega\big(\frac{1}{\epsilon}\big)^{\frac{1}{3}}\bigg)$, …

Towards Understanding Why Lookahead Generalizes Better Than Sgd And Beyond, Pan Zhou, Hanshu Yan, Xiaotong Yuan, Jiashi Feng, Shuicheng Yan

Research Collection School Of Computing and Information Systems

To train networks, lookahead algorithm [1] updates its fast weights k times via an inner-loop optimizer before updating its slow weights once by using the latest fast weights. Any optimizer, e.g. SGD, can serve as the inner-loop optimizer, and the derived lookahead generally enjoys remarkable test performance improvement over the vanilla optimizer. But theoretical understandings on the test performance improvement of lookahead remain absent yet. To solve this issue, we theoretically justify the advantages of lookahead in terms of the excess risk error which measures the test performance. Specifically, we prove that lookahead using SGD as its inner-loop optimizer can …

A Theory-Driven Self-Labeling Refinement Method For Contrastive Representation Learning, Pan Zhou, Caiming Xiong, Xiao-Tong Yuan

Research Collection School Of Computing and Information Systems

For an image query, unsupervised contrastive learning labels crops of the same image as positives, and other image crops as negatives. Although intuitive, such a native label assignment strategy cannot reveal the underlying semantic similarity between a query and its positives and negatives, and impairs performance, since some negatives are semantically similar to the query or even share the same semantic class as the query. In this work, we first prove that for contrastive learning, inaccurate label assignment heavily impairs its generalization for semantic instance discrimination, while accurate labels benefit its generalization. Inspired by this theory, we propose a novel …

Infinite Time Horizon Safety Of Bayesian Neural Networks, Mathias Lechner, Dorde Zikelic, Krishnendu Chatterjee, Thomas A. Henzinger

Research Collection School Of Computing and Information Systems

Bayesian neural networks (BNNs) place distributions over the weights of a neural network to model uncertainty in the data and the network’s prediction. We consider the problem of verifying safety when running a Bayesian neural network policy in a feedback loop with infinite time horizon systems. Compared to the existing sampling-based approaches, which are inapplicable to the infinite time horizon setting, we train a separate deterministic neural network that serves as an infinite time horizon safety certificate. In particular, we show that the certificate network guarantees the safety of the system over a subset of the BNN weight posterior’s support. …

Rmix: Learning Risk-Sensitive Policies For Cooperative Reinforcement Learning Agents, Wei Qiu, Xinrun Wang, Runsheng Yu, Xu He, Rundong Wang, Bo An, Svetlana Obraztsova, Zinovi Rabinovich

Research Collection School Of Computing and Information Systems

Current value-based multi-agent reinforcement learning methods optimize individual Q values to guide individuals' behaviours via centralized training with decentralized execution (CTDE). However, such expected, i.e., risk-neutral, Q value is not sufficient even with CTDE due to the randomness of rewards and the uncertainty in environments, which causes the failure of these methods to train coordinating agents in complex environments. To address these issues, we propose RMIX, a novel cooperative MARL method with the Conditional Value at Risk (CVaR) measure over the learned distributions of individuals' Q values. Specifically, we first learn the return distributions of individuals to analytically calculate CVaR …

Data Fusion For Trust Evaluation, Zheng Yan, Qinghua Zheng, Laurence T. Yang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Trust evaluation is a process to quantify trust by analyzing the data related to the factors that affect trust. It has been widely applied in many fields to facilitate decision making, system entity collaboration and security establishment. For example, in social networking, trust evaluation helps users make a social decision, reduce the risk of social interactions, and ensure the quality of a social networking environment. In digital communications, trust evaluation can be applied to detect malicious nodes, filter unwanted traffic and improve communication security. In e-commerce and cloud services, trust evaluation helps users selecting an appropriate product or service from …

Integration Of Information Technology Certifications Into Undergraduate Computing Curriculum, Eng Lieh Ouh, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

This innovative practice full paper describes our experiences of integrating information technology certifications into an undergraduate computing curriculum. As the technology landscape evolves, a common challenge for educators in computing programs is designing an industry-relevant curriculum. Over the years, industry practitioners have taken technology certifications to validate themselves against a base level of technical knowledge currently in demand in industry. Information technology (IT) certifications can also offer paths for academic computing programs to stay relevant to industry needs. However, identifying relevant IT certifications and integrating it into an academic curriculum requires a careful design approach as substantial efforts are needed …

Adadeep: A Usage-Driven, Automated Deep Model Compression Framework For Enabling Ubiquitous Intelligent Mobiles, Sicong Liu, Junzhao Du, Kaiming Nan, Zimu Zhou, Hui Liu, Zhangyang Wang, Yingyan Lin

Research Collection School Of Computing and Information Systems

Recent breakthroughs in deep neural networks (DNNs) have fueled a tremendously growing demand for bringing DNN-powered intelligence into mobile platforms. While the potential of deploying DNNs on resource-constrained platforms has been demonstrated by DNN compression techniques, the current practice suffers from two limitations: 1) merely stand-alone compression schemes are investigated even though each compression technique only suit for certain types of DNN layers; and 2) mostly compression techniques are optimized for DNNs’ inference accuracy, without explicitly considering other application-driven system performance (e.g., latency and energy cost) and the varying resource availability across platforms (e.g., storage and processing capability). To this …

Towards Non-Intrusive Camera-Based Heart Rate Variability Estimation In The Car Under Naturalistic Condition, Shu Liu, Kevin Koch, Zimu Zhou, Martin Maritsch, Xiaoxi He, Elgar Fleisch, Felix Wortmann

Research Collection School Of Computing and Information Systems

Driver status monitoring systems are a vital component of smart cars in the future, especially in the era when an increasing amount of time is spent in the vehicle. The heart rate (HR) is one of the most important physiological signals of driver status. To infer HR of drivers, the mainstream of existing research focused on capturing subtle heartbeat-induced vibration of the torso or leveraged photoplethysmography (PPG) that detects cardiac cycle-related blood volume changes in the microvascular. However, existing approaches rely on dedicated sensors that are expensive and cumbersome to be integrated or are vulnerable to ambient noise. Moreover, their …