Digital Commons Network^™

Vaccines And Dermatology: Expanding The Role Of Dermatology Clinics In The Name Of Public Health, Charles Dunn, Yasser Faraj, Nicole Vesely, Michael Foss, Austin Ambur, Rajiv Nathoo

GME Publications

No abstract provided.

Routes To Lower Greenhouse Gas Emissions From Freight Transportation In The City Of San José, Serena Alexander, Kyle Laveroni, Maxwell Friedman, Janani Thiagrajan

Mineta Transportation Institute

Freight represents approximately 30% of all transportation-related emissions in the U.S., but local climate action plans (CAPs) and freight plans often place limited emphasis on freight emissions reduction strategies. The objective of this report is to examine and present strategies for the City of San José, California to reduce GHG emissions from freight. The authors conducted a geospatial analysis of freight data related to San José, and an analysis of relevant literature and successful freight reduction strategies implemented globally. The report also provides key objectives and generalized strategies to reduce GHG emissions from freight as well as specific recommendations for …

Combined Impacts Of Co2 Enrichment And Water Stress On Growth And Physiology Of Plants Inoculated With An Acc Deaminase Producing Rhizobacterium, Shaijal Babu Ppoyil

Dissertations

This study assessed the water stress mitigating effects of elevated CO₂ on Chloris gayana Kunth cv. Katambora (Rhodes grass) and Medicago sativa L. cv. SuperFast (alfalfa) plants, and how the seed inoculation with one of the ACC deaminase producing plant growth promoting rhizobacterium (PGPR) supplemented the stand-alone plant drought stress mitigating effects of elevated CO₂, under different growing conditions in the United Arab Emirates (UAE). Multiple growth and physiology related variables were measured from the plants in response to different treatment combinations made of CO₂, watering treatments (WT), and PGPR, based on the research design …

Characterization Of The Long Non-Coding Rna Proins In Human Pancreatic Β-Cell, Shareena Saeed Lootah

Dissertations

It is well established that the genome is pervasively transcribed. Only 2% of those transcripts are translated into proteins, and the remaining 98% are non-translated, generating the non-coding RNAs (ncRNAs) species. A close observation of these transcripts directed the scientific community to their increasing potential functional roles in the cells. Indeed, the literature exponentially unveils this notion, with many ncRNAs showing substantial and variable biological functions. The field is in its infancy; however, efforts are accelerating to discover and define this ocean of new species.

Long non-coding RNAs (lncRNAs) are sub-species of ncRNAs with an arbitrary size of more than …

Two-Phase Matheuristic For The Vehicle Routing Problem With Reverse Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Pieter Vansteenwegen, Vincent F. Yu

Research Collection School Of Computing and Information Systems

Cross-dockingis a useful concept used by many companies to control the product flow. It enables the transshipment process of products from suppliers to customers. This research thus extends the benefit of cross-docking with reverse logistics, since return process management has become an important field in various businesses. The vehicle routing problem in a distribution network is considered to be an integrated model, namely the vehicle routing problem with reverse cross-docking (VRP-RCD). This study develops a mathematical model to minimize the costs of moving products in a four-level supply chain network that involves suppliers, cross-dock, customers, and outlets. A matheuristic based …

Learning Improvement Heuristics For Solving Routing Problems, Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang, Andrew Lim

Research Collection School Of Computing and Information Systems

Recent studies in using deep learning to solve routing problems focus on construction heuristics, the solutions of which are still far from optimality. Improvement heuristics have great potential to narrow this gap by iteratively refining a solution. However, classic improvement heuristics are all guided by hand-crafted rules which may limit their performance. In this paper, we propose a deep reinforcement learning framework to learn the improvement heuristics for routing problems. We design a self-attention based deep architecture as the policy network to guide the selection of next solution. We apply our method to two important routing problems, i.e. travelling salesman …

On The Effectiveness Of Using Graphics Interrupt As A Side Channel For User Behavior Snooping, Haoyu Ma, Jianwen Tian, Debin Gao, Chunfu Jia

Research Collection School Of Computing and Information Systems

Graphics Processing Units (GPUs) are now a key component of many devices and systems, including those in the cloud and data centers, thus are also subject to side-channel attacks. Existing side-channel attacks on GPUs typically leak information from graphics libraries like OpenGL and CUDA, which require creating contentions within the GPU resource space and are being mitigated with software patches. This paper evaluates potential side channels exposed at a lower-level interface between GPUs and CPUs, namely the graphics interrupts. These signals could indicate unique signatures of GPU workload, allowing a spy process to infer the behavior of other processes. We …

Distance Based Image Classification: A Solution To Generative Classification’S Conundrum?, Wen-Yan Lin, Siying Liu, Bing Tian Dai, Hongdong Li

Research Collection School Of Computing and Information Systems

Most classifiers rely on discriminative boundaries that separate instances of each class from everything else. We argue that discriminative boundaries are counter-intuitive as they define semantics by what-they-are-not; and should be replaced by generative classifiers which define semantics by what-they-are. Unfortunately, generative classifiers are significantly less accurate. This may be caused by the tendency of generative models to focus on easy to model semantic generative factors and ignore non-semantic factors that are important but difficult to model. We propose a new generative model in which semantic factors are accommodated by shell theory’s [25] hierarchical generative process and non-semantic factors by …

Secure Deterministic Wallet And Stealth Address: Key-Insulated And Privacy-Preserving Signature Scheme With Publicly Derived Public Key, Zhen Liu, Guomin Yang, Duncan S. Wong, Khoa Nguyen, Huaxiong Wang, Xiaorong Ke, Yining Liu

Research Collection School Of Computing and Information Systems

Deterministic Wallet (DW) and Stealth Address (SA) mechanisms have been widely adopted in the cryptocurrency community, due to their virtues on functionality and privacy protection, which come from a key derivation mechanism that allows an arbitrary number of derived keys to be generated from a master key. However, these algorithms suffer a vulnerability that, when one derived key is compromised somehow, the damage is not limited to the leaked derived key only, but to the master key and in consequence all derived keys are compromised. In this article, we introduce and formalize a new signature variant, called Key-Insulated and Privacy-Preserving …

Deep Learning-Based Text Recognition Of Agricultural Regulatory Document, Hua Leong Fwa, Farn Haur Chan

Research Collection School Of Computing and Information Systems

In this study, an OCR system based on deep learning techniques was deployed to digitize scanned agricultural regulatory documents comprising of certificates and labels. Recognition of the certificates and labels is challenging as they are scanned images of the hard copy form and the layout and size of the text as well as the languages vary between the various countries (due to diverse regulatory requirements). We evaluated and compared between various state-of-the-art deep learningbased text detection and recognition model as well as a packaged OCR library – Tesseract. We then adopted a two-stage approach comprising of text detection using Character …

Secure Hierarchical Deterministic Wallet Supporting Stealth Address, Xin Yin, Zhen Liu, Guomin Yang, Guoxing Chen, Haojin Zhu

Research Collection School Of Computing and Information Systems

Over the past decade, cryptocurrency has been undergoing a rapid development. Digital wallet, as the tool to store and manage the cryptographic keys, is the primary entrance for the public to access cryptocurrency assets. Hierarchical Deterministic Wallet (HDW), proposed in Bitcoin Improvement Proposal 32 (BIP32), has attracted much attention and been widely used in the community, due to its virtues such as easy backup/recovery, convenient cold-address management, and supporting trust-less audits and applications in hierarchical organizations. While HDW allows the wallet owner to generate and manage his keys conveniently, Stealth Address (SA) allows a payer to generate fresh address (i.e., …

Deep Learning For Coverage-Guided Fuzzing: How Far Are We?, Siqi Li, Xiaofei Xie, Yun Lin, Yuekang Li, Ruitao Feng, Xiaohong Li, Weimin Ge, Jin Song Dong

Research Collection School Of Computing and Information Systems

Fuzzing is a widely-used software vulnerability discovery technology, many of which are optimized using coverage-feedback. Recently, some techniques propose to train deep learning (DL) models to predict the branch coverage of an arbitrary input owing to its always-available gradients etc. as a guide. Those techniques have proved their success in improving coverage and discovering bugs under different experimental settings. However, DL models, usually as a magic black-box, are notoriously lack of explanation. Moreover, their performance can be sensitive to the collected runtime coverage information for training, indicating potentially unstable performance. In this work, we conduct a systematic empirical study on …

Contrastive Transformer-Based Multiple Instance Learning For Weakly Supervised Polyp Frame Detection, Tian Yu, Guansong Pang, Fengbei Liu, Yuyuan Liu, Chong Wang, Yuanhong Chen, Johan Verjans, Gustavo Carneiro

Research Collection School Of Computing and Information Systems

Current polyp detection methods from colonoscopy videos use exclusively normal (i.e., healthy) training images, which i) ignore the importance of temporal information in consecutive video frames, and ii) lack knowledge about the polyps. Consequently, they often have high detection errors, especially on challenging polyp cases (e.g., small, flat, or partially visible polyps). In this work, we formulate polyp detection as a weakly-supervised anomaly detection task that uses video-level labelled training data to detect frame-level polyps. In particular, we propose a novel convolutional transformer-based multiple instance learning method designed to identify abnormal frames (i.e., frames with polyps) from anomalous videos (i.e., …

Eeg-Video Emotion-Based Summarization: Learning With Eeg Auxiliary Signals, Wai-Cheong L. Lew, Di Wang, Kai-Keng Ang, Joo-Hwee Lim, Chai Quek, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Video summarization is the process of selecting a subset of informative keyframes to expedite storytelling with limited loss of information. In this paper, we propose an EEG-Video Emotion-based Summarization (EVES) model based on a multimodal deep reinforcement learning (DRL) architecture that leverages neural signals to learn visual interestingness to produce quantitatively and qualitatively better video summaries. As such, EVES does not learn from the expensive human annotations but the multimodal signals. Furthermore, to ensure the temporal alignment and minimize the modality gap between the visual and EEG modalities, we introduce a Time Synchronization Module (TSM) that uses an attention mechanism …

Constrained Multiagent Reinforcement Learning For Large Agent Population, Jiajing Ling, Arambam James Singh, Duc Thien Nguyen, Akshat Kumar

Research Collection School Of Computing and Information Systems

Learning control policies for a large number of agents in a decentralized setting is challenging due to partial observability, uncertainty in the environment, and scalability challenges. While several scalable multiagent RL (MARL) methods have been proposed, relatively few approaches exist for large scale constrained MARL settings. To address this, we first formulate the constrained MARL problem in a collective multiagent setting where interactions among agents are governed by the aggregate count and types of agents, and do not depend on agents’ specific identities. Second, we show that standard Lagrangian relaxation methods, which are popular for single agent RL, do not …

Toward Intention Discovery For Early Malice Detection In Bitcoin, Ling Cheng, Feida Zhu, Yong Wang, Huiwen Liu

Research Collection School Of Computing and Information Systems

Bitcoin has been subject to illicit activities more often than probably any other financial assets, due to the pseudo-anonymous nature of its transacting entities. An ideal detection model is expected to achieve all the three properties of (I) early detection, (II) good interpretability, and (III) versatility for various illicit activities. However, existing solutions cannot meet all these requirements, as most of them heavily rely on deep learning without satisfying interpretability and are only available for retrospective analysis of a specific illicit type.First, we present asset transfer paths, which aim to describe addresses' early characteristics. Next, with a decision tree based …

A Traitor-Resistant And Dynamic Anonymous Communication Service For Cloud-Based Vanets, Huiying Hou, Jianting Ning, Yunlei Zhao, Robert H. Deng

Research Collection School Of Computing and Information Systems

Cloud-based VANETs are designed to enable communication between high-speed vehicles. In such a highly dynamic environment, how to provide secure and anonymous communication service is a challenge. In this article, we affirmatively address the challenge by proposing a traitor-resistant and dynamic anonymous communication framework (TD-ACF) for cloud-based VANETs, which supports several advantageous features. In TD-ACF, each vehicle is represented by a set of attributes instead of its real identity, and the driving data is transmitted in encrypted form. Therefore, the anonymous authentication and the confidentiality of driving data are achieved in this way. Meanwhile, TD-ACF supports two practical requirements in …

Val: Volume And Access Pattern Leakage-Abuse Attack With Leaked Documents, Steven Lambregts, Huanhuan Chen, Jianting Ning, Kaitai Liang

Research Collection School Of Computing and Information Systems

Searchable Encryption schemes provide secure search over encrypted databases while allowing admitted information leakages. Generally, the leakages can be categorized into access and volume pattern. In most existing SE schemes, these leakages are caused by practical designs but are considered an acceptable price to achieve high search efficiency. Recent attacks have shown that such leakages could be easily exploited to retrieve the underlying keywords for search queries. Under the umbrella of attacking SE, we design a new Volume and Access Pattern Leakage-Abuse Attack (VAL-Attack) that improves the matching technique of LEAP (CCS ’21) and exploits both the access and volume …

Are Managed Retreat Programs Successful And Just? A Global Mapping Of Success Typologies, Justice Dimensions, And Trade-Offs, Idowu Ajibade, Meghan Sullivan, Chris Lower, Lizzie Yarina, Allie Reilly

Geography Faculty Publications and Presentations

As managed retreat programs expand across the globe, there is an urgent need to assess whether these programs are reducing exposure to climatic hazards, enhancing adaptive capacity, and improving the living conditions of communities in a just and equitable manner or are they exacerbating existing risks and vulnerabilities? Strictly speaking, are retreat programs successful? Using an expansive intersectional justice approach to examine 138 post-resettlement case studies published between 2000 and 2021 across the Global North and South, we identified five typologies of success – techno-managerial, eco-restorative, compensatory, reformative, and transformative – and their trade-offs and synergies. Our meta-analysis incorporated a …

Understanding Perspectives On Climate Hazards, Water Management, And Adaptive Transformation In An Exurban Community, Alexander Ross, Heejun Chang, Alida Cantor

Geography Faculty Publications and Presentations

Climate change and exurban development pose challenges for water resources. This paper examines the perceptions and adaptive responses to those stressors among stakeholders engaging in exurban water management. Drawing on 42 interviews with planners, water managers, and local experts, we analyze perspectives on water-related hazards in the Hood River watershed, Oregon, and identify contrasting approaches to adaptation. Interview subjects identified climate-related hazards as most significant, with relatively less – although not insignificant – concern about development. Interviewees understood the role of the Watershed Group in four different ways: resistance to change, sustaining the present system, adapting to improve resilience, or …

September 2022 News Releases, University Of Montana--Missoula. Office Of University Relations

University of Montana News Releases, 1928, 1956-present

No abstract provided.

Reimagining Community Engagement To Increase Resilience To Climate Change In El Punto Neighborhood, Salem, Massachusetts, Elizabeth Sweet, Fabián Torres-Ardila, Daniela Bravo, Leandra Jara

Gastón Institute Publications

In November 2021, the Mauricio Gastón Institute at the University of Massachusetts Boston partnered with the Woods Hole Group (WHG) to develop a community outreach strategy for the Climate Change Deep Dive Model, Alternative Analysis, and Targeted Outreach & Engagement project in the Point/Palmer Cove neighborhood (El Punto), in the city of Salem, MA. El Punto, including its residents, workers, infrastructure, and development areas, is particularly vulnerable to climate change impacts (such as sea level rise, storm surge, precipitation, and heat waves). Researchers from the Gaston institute engaged El Punto residents to:

• Increase the community’s knowledge of current and future …

Five Steps To Successfully Make Social Engagement Happen In Your Church, Sung Kun Kwon, Bordes Henry Saturne

Faculty Publications

No abstract provided.

The Molecular Basis Of Diabetic Cardiomyopath, Ahmed Salaheldin Mustafa Ali Sultan

Dissertations

Diabetes mellitus (DM) is a major and worsening global health problem. Type 2 diabetes mellitus (T2DM) accounts for more than 90% of DM and the global epidemic of obesity largely explains the dramatic increase in the incidence and prevalence of T2DM over the past 20 years. Cardiovascular complications are the major cause of morbidity and mortality in diabetic patients. The electrocardiogram (ECG) of diabetic and obese patients is frequently disturbed. The aim of this project was to characterize and clarify the molecular basis of electro-mechanical dysfunction in the hearts of type 2 diabetic and type 2 diabetic/obese rats. Experiments were …

Nurses’ Knowledge And Practice In Managing Covid-19 Patients With Cardiac Arrest At A Teaching Hospital, Li Yoong Tang

Research Publications (2021 to 2025)

The COVID-19 pandemic has posed a major threat to public health. The same goes for the healthcare providers, as they too are at great risk of being infected with the virus. COVID-19 disease may cause the patient's hemodynamically instability thus causing circulatory system collapse. Therefore, the nurses who are part of the resuscitation team should adapt themselves with knowledge and good practice on how to handle the COVID-19 patients with cardiac arrest. This study aimed to assess the nurses' knowledge and practice in managing COVID-19 patients with cardiac arrest at a teaching hospital.

Relationships Between Quality Of Work-Life, Burnout And Professional Commitment Among Nurses, Siew Li Foo

Research Publications (2021 to 2025)

Professional commitment has significant influence on nurses’ job performance and patients’ outcomes. An increasingly excessive workload seems to be an inevitable consequence of the advancement in medical technology. A worsening nurse-patient ratio and an increasing number of specific nursing tasks have a direct impact on nurses’ quality of work-life. This high workload and poor working environment can lead to poor quality of work-life and eventually, burnout which directly affect nurses’ job performance and professional commitment. This study was aimed to determine the relationships between quality of work-life, burnout and professional commitment among nurses.

The Effect Of Lockdown, Economic Stimulus Package And National Recovery Plan Announcements On The Malaysian Stock Market, Kok Jun Tan, Mohd Edil Abd Sukor

Research Publications (2021 to 2025)

This research aims to investigate the effect of lockdown, economic stimulus package and national recovery plan announcements during the Covid-19 pandemic on the Malaysian stock market. The study employs an event study methodology. A sample of 13 sectorial indexes are selected. The sample period taken for the study is from January 2, 2019 to October 29, 2021. The results of the study suggest that all events i.e., lockdown, economic stimulus packages and recovery plan announcements have significantly affect the stock market. Nevertheless, the impact varies across time periods. For example, the first three Movement Control Order (MCO) 1.0, 2.0 and …

Activity Measure For Post-Acute Care “ 6-Clicks ” Basic Mobility Scores Predict Discharge Destination After Acute Care Hospitalization In Select Patient Groups: A Retrospective, Observational Study, Burke Rehabilitation Hospital, Divya Rajaraman, Sarah Taylor, Kirollos Agayaby, Suzanne Babyar

Publications and Research

Objectives

To establish cutoff scores for the Activity Measure for Post-Acute Care “6-Clicks” standardized Basic Mobility scores (sBMSs) for predicting discharge destination after acute care hospitalization for diagnostic subgroups within an acute care population and to evaluate the need for a second score to improve predictive ability.

Design

Retrospective, observational design.

Setting

Major medical center in metropolitan area.

Participants

Electronic medical records of 1696 adult patients (>18 years) admitted to acute care from January to October 2018. Records were stratified by orthopedic, cardiac, pulmonary, stroke, and other neurological diagnoses (N=1696). Interventions: None

Main Outcome Measure

Physical therapists scored patients’ …

Factors Shaping Good And Poor Nurse-Client Relationships In Maternal And Child Care: A Qualitative Study In Rural Tanzania, Kahabi Isangula, Eunice Pallangyo, Columba Mbekenga, Eunice Ndirangu, Constance Shumba

School of Nursing & Midwifery, East Africa

Background: Evidence indicates that poor nurse‐client relationships within maternal and child health (MCH) continues to impact trust in formal healthcare systems, service uptake, continuity with care and MCH outcomes. This necessitates contextualized innovative solutions that places both nurses and clients at the forefront as agents of change in optimizing intervention designs and implementation. This study explored nurses and clients’ perspectives on the factors shaping nurse‐client relationships in MCH care to generate evidence to guide subsequent steps of human centered design (HCD) that involve designing effective strategies for improving therapeutic relationships in Shinyanga, Tanzania.

Methods: Qualitative descriptive design was …

Unit Knowledge And Practice Of Emergency Nursing Interventions At A Tertiary Public Cardiac Health Center In Uganda, Harriet Namukwaya, Cliff Asher Aliga, Grace Nakate, Judith Mutyabule

School of Nursing & Midwifery, East Africa

Background: Research suggests that many of the millions of deaths and long-term disabilities resulting from acute cardiovascular events and other emergency conditions are preventable if effective emergency care services were readily available. Effective emergency care requires trained and competent staff, including registered nurses. Most educational pathways do not adequately prepare nurses to deliver sensitive health care services for those with acute illness and injury. This includes Uganda, where few capacity-building initiatives have targeted emergency nursing care delivery, leading to knowledge and practice gaps.

Purpose: This study aimed to assess emergency nursing knowledge and clinical practice at a tertiary …