Digital Commons Network^™

New Spectral Range Generations From Laser-Plasma Interaction, Shaimaa S. Mahdi, Kadhim A. Aadim, Madyan A. Khalaf

Baghdad Science Journal

High-intensity laser-produced plasma has been extensively investigated in many studies. In this demonstration, a new spectral range was observed in the resulted spectra from the laser-plasma interaction, which opens up new discussions for new light source generation. Moreover, the characterizations of plasma have been improved through the interaction process of laser-plasma. Three types of laser were incorporated in the measurements, continuous-wave CW He-Ne laser, CW diode green laser, pulse Nd: YAG laser. As the plasma system, DC glow discharge plasma under the vacuum chamber was considered in this research. The plasma spectral peaks were evaluated, where they refer to Nitrogen …

Fabrication And Characterization Of Nanofibers Membranes Using Electrospinning Technology For Oil Removal, Amer N. Al-Naemi, Mohammed A. Abdul-Majeed, Mustafa H. Al-Furaiji, Inmar N Ghazi

Baghdad Science Journal

Oily wastewater is one of the most challenging streams to deal with especially if the oil exists in emulsified form. In this study, electrospinning method was used to prepare nanofiberous polyvinylidene fluoride (PVDF) membranes and study their performance in oil removal. Graphene particles were embedded in the electrospun PVDF membrane to enhance the efficiency of the membranes. The prepared membranes were characterized using a scanning electron microscopy (SEM) to verify the graphene stabilization on the surface of the membrane homogeneously; while FTIR was used to detect the functional groups on the membrane surface. The membrane wettability was assessed by measuring …

Checking Smart Contracts With Structural Code Embedding, Zhipeng Gao, Lingxiao Jiang, Xin Xia, David Lo, John Grundy

Research Collection School Of Computing and Information Systems

Smart contracts have been increasingly used together with blockchains to automate financial and business transactions. However, many bugs and vulnerabilities have been identified in many contracts which raises serious concerns about smart contract security, not to mention that the blockchain systems on which the smart contracts are built can be buggy. Thus, there is a significant need to better maintain smart contract code and ensure its high reliability. In this paper, we propose an automated approach to learn characteristics of smart contracts in Solidity, useful for repetitive contract code, bug detection and contract validation. Our new approach is based on …

Graph Learning Assisted Multi-Objective Integer Programming, Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang, Abhishek Gupta, Mingyan Simon Lin

Research Collection School Of Computing and Information Systems

Objective-space decomposition algorithms (ODAs) are widely studied for solvingmulti-objective integer programs. However, they often encounter difficulties inhandling scalarized problems, which could cause infeasibility or repetitive nondominatedpoints and thus induce redundant runtime. To mitigate the issue, we presenta graph neural network (GNN) based method to learn the reduction rule in the ODA.We formulate the algorithmic procedure of generic ODAs as a Markov decisionprocess, and parameterize the policy (reduction rule) with a novel two-stage GNNto fuse information from variables, constraints and especially objectives for betterstate representation. We train our model with imitation learning and deploy it ona state-of-the-art ODA. Results show that …

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 …

On Analysing Student Resilience In Higher Education Programs Using A Data-Driven Approach, Audrey Tedja Widjaja, Ee Peng Lim, Aldy Gunawan

Research Collection School Of Computing and Information Systems

Analysing student resilience is important as research has shown that resilience is related to students’ academic performance and their persistence through academic setbacks. While questionnaires can be conducted to assess student resilience directly, they suffer from human recall errors and deliberate suppression of true responses. In this paper, we propose ACREA, ACademic REsilience Analytics framework which adopts a datadriven approach to analyse student resilient behavior with the use of student-course data. ACREA defines academic setbacks experienced by students and measures how well students overcome such setbacks using a quasi-experimental design. By applying ACREA on a real world student-course dataset, we …

Degree Doesn't Matter: Identifying The Drivers Of Interaction In Software Development Ecosystem, Amrita Bhattacharjee, Subhajit Datta, Subhashis Majumder

Research Collection School Of Computing and Information Systems

Large scale software development ecosystems represent one of the most complex human enterprises. In such settings, developers are embedded in a web of shared concerns, responsibilities, and objectives at individual and collective levels. A deep understanding of the factors that influence developers to connect with one another is crucial in appreciating the challenges of such ecosystems as well as formulating strategies to overcome those challenges. We use real world data from multiple software development ecosystems to construct developer interaction networks and examine the mechanisms of such network formation using statistical models to identify developer attributes that have maximal influence on …

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 …

Imon: Appearance-Based Gaze Tracking System On Mobile Devices, Sinh Huynh, Rajesh Krishna Balan, Jeonggil Ko

Research Collection School Of Computing and Information Systems

Gaze tracking is a key building block used in many mobile applications including entertainment, personal productivity, accessibility, medical diagnosis, and visual attention monitoring. In this paper, we present iMon, an appearance-based gaze tracking system that is both designed for use on mobile phones and has significantly greater accuracy compared to prior state-of-the-art solutions. iMon achieves this by comprehensively considering the gaze estimation pipeline and then overcoming three different sources of errors. First, instead of assuming that the user's gaze is fixed to a single 2D coordinate, we construct each gaze label using a probabilistic 2D heatmap gaze representation input to …

Context-Aware Graph Convolutional Network For Dynamic Origin-Destination Prediction, Juan Nathaniel, Baihua Zheng

Research Collection School Of Computing and Information Systems

A robust Origin-Destination (OD) prediction is key to urban mobility. A good forecasting model can reduce operational risks and improve service availability, among many other upsides. Here, we examine the use of Graph Convolutional Net-work (GCN) and its hybrid Markov-Chain (GCN-MC) variant to perform a context-aware OD prediction based on a large-scale public transportation dataset in Singapore. Compared with the baseline Markov-Chain algorithm and GCN, the proposed hybrid GCN-MC model improves the prediction accuracy by 37% and 12% respectively. Lastly, the addition of temporal and historical contextual information further improves the performance of the proposed hybrid model by 4 –12%.

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 …

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. …

Institute For Global Health And Development : Issue 1 - December 2021, Institute For Global Health And Development

IGHD Newsletters

• Climate Change and Environment Sustainability
• Agriculture, Food Security, and Nutrition
• Gender Equality and Women Empowerment
• Sustainable Development Goals

Self-Supervised Learning Disentangled Group Representation As Feature, Tan Wang, Zhongqi Yue, Jianqiang Huang, Qianru Sun, Hanwang Zhang

Research Collection School Of Computing and Information Systems

A good visual representation is an inference map from observations (images) to features (vectors) that faithfully reflects the hidden modularized generative factors (semantics). In this paper, we formulate the notion of “good” representation from a group-theoretic view using Higgins’ definition of disentangled representation [38], and show that existing Self-Supervised Learning (SSL) only disentangles simple augmentation features such as rotation and colorization, thus unable to modularize the remaining semantics. To break the limitation, we propose an iterative SSL algorithm: Iterative Partition-based Invariant Risk Minimization (IP-IRM), which successfully grounds the abstract semantics and the group acting on them into concrete contrastive learning. …

The Mystery Of Covid-19 Reinfections: A Global Systematic Review And Meta-Analysis, Rubaid Azhar Dhillon, Mohammad Aadil Qamar, Jaleed Ahmed Gilani, Omar Irfan, Usama Waqar, Mir Ibrahim Sajid, Syed Faisal Mahmood

Department of Medicine

Background: As the COVID-19 pandemic rages on, reports on disparities in vaccine roll out alongside COVID-19 reinfection have been emerging. We conducted a systematic review to assess the determinants and disease spectrum of COVID-19 reinfection.
Materials and methods: A comprehensive search covering relevant databases was conducted for observational studies reporting Polymerase Chain Reaction (PCR) confirmed infection and reinfection cases. A quality assessment tool developed by the National Institute of Health (NIH) for the assessment of case series was utilized. Meta-analyses were performed using RevMan 5.3 for pooled proportions of findings in first infection and reinfection with a 95% confidence interval …

Us Consumers' Perceptions Of Raw And Cooked Broken Rice, Matthew G. Richardson, Philip Glen Crandall, Han-Seok Seo, Corliss A. O'Bryan

Food Science Faculty Publications and Presentations

Rice supplies about 20% of the calories to the world’s consumers. Milling removes the outer husk and bran, breaking about 20% of the rice kernels during the milling process that equates to almost 100,000,000 tons of rice annually. Broken rice is discounted in price by almost half or relegated to non-human consumption. This study seeks to understand why this large percentage of rice production is discounted for human consumption. Consumers who routinely consume rice evaluated raw and cooked rice with 5%, 10%, 20%, 30% and 40% levels of brokens. Sensory analysis indicated the appearance of raw rice with high levels …

Accident-Proof Headphones: An Analytical Research On How Smart Headphones Could Reduce Road Fatalities, J.K.D.R. Jayasekara, D. Dhammearatchi

Journal of Innovation in Science, Engineering and Technology

Headphones are used by most people as a source of entertainment. Many pedestrians, cyclists and joggers like to use headphones while they are on the road even though it can result in extreme sensory deprivation and distraction. The purpose of this paper is to conduct a study on how the use of headphones can reduce the standard limits of human perception. It examines how this increases the vulnerability of one facing road accidents and proposes a possible solution to overcome this issue.

Age And Roles On The Family Farm, Cassie Chambers

Humboldt Journal of Social Relations

Age is a factor that has been analyzed in the workforce for quite some time now. The aging process is universal and found in daily lives throughout the work force or labor market, but some factors of age are different in the agriculture industry. This paper aims to acknowledge and explore the aging process specifically found in the agriculture industry. The key concepts of this paper have been broken into four different topics. These topics include youth roles on the farm, mid-adult roles on the farm, older adult roles on the farm, and public policy implications dealing with the agriculture …

Mechanisms And Applications Of Improved Protein Analysis By Desorption Electrospray Ionization Mass Spectrometry (Desi-Ms), Roshan Javanshad

Dissertations

Electrospray ionization mass spectrometry (ESI-MS) is a soft ionization technique that allows detection of macromolecules, such as intact proteins, by the formation of multiply charged ions from solutions. Desorption electrospray ionization mass spectrometry (DESI-MS) is an ambient ionization technique that directly samples analyte from a surface during ESI-MS analysis. Although DESI-MS is highly accomplished at the analyses of metabolites, lipids, and other small molecules, it is far more limited when it comes to protein analysis. While most of the field in ambient ionization MS has moved towards primarily applications, our approach has been to explore the use of DESI-MS and …

Parametric Characteristics Of The B6omsi-Re, Sarahelizabeth Janemarie Baguhn

Dissertations

Orientation and mobility specialists for young children who are blind or visually impaired have relied on informal assessments or commercially available tools designed for sighted children to track developmental progress. When Bradley-Johnson (1994) literally wrote the book on assessment in blindness, the sharing and refinement of common tools led to professionals working in teams to sift and winnow the checklists, and move the best available tools into wider circulation. This has led to the evolution of the practitioner made tools becoming the published tools, although they have not yet had statistical evidence to support their efficacy. This three-paper dissertation aims …

The Role Of Youth Characteristics, Home Ecology, And Child Maltreatment In The Severity Of Problematic Sexual Behaviors And Conduct Problems, Ariel K. Berman

Dissertations

A multitude of individual, familial, and environmental variables have previously been identified as contributing to the development of problematic sexual behaviors (PSB) and general conduct problems (CP) in youth. The majority of these studies have focused either on individual youth characteristics or parenting behaviors such as child maltreatment. Although researchers examining contributions to PSB and CP generally acknowledge the importance of the impact of the home environment on youth behavior, few researchers have included family characteristics of both parents and siblings in their analyses. Additionally, some factors that have been identified as having great importance in general juvenile delinquency, such …

The Effects Of Cost, Level Of Safety, And Severity Of Injury On Manager Decisions To Implement A Safety Solution, Jonathan M. Hochmuth

Dissertations

Workplace injuries continue to be a source of substantial human and financial costs each year. Behavioral safety processes have been effective in reducing workplace injuries by increasing safety-related behaviors. In recent years, the focus in behavioral safety has shifted towards the role of managers in establishing and maintaining safe behaviors and conditions in the workplace. Understanding how managers make decisions to allocate resources is critical to improving safety. The field of behavioral economics has developed methods for studying decision-making. While there have been calls to apply these methods to occupational safety, there are only two empirical studies which have done …

Academic Resilience, Student Engagement, And Academic Achievement Among Black Male Undergraduates At Predominantly White Institutions, Henry C. Mccain Iii

Dissertations

The proportion of Black men enrolled in college is representative of the Black male population in the U.S. (Toldson, 2019). However, an investigation of the 2010 college entry cohort of Black men showed that only 34% graduate within six years (National Center for Education Statistics; NCES, 2019). The disparity in Black male graduation rate is clearer when compared to other races such as White men (61%), Hispanic men (50%), and Asian men (70%) (NCES, 2019). Within-group disparities also exist in that Black women graduate at a rate of 44% (NCES, 2019). Much of the literature on Black undergraduates has been …

Informing Cognitive Screening In The Young Adult Population, Samantha L. Mcdaniel

Dissertations

The clock drawing test (CDT) is a cognitive screening measure with sound psychometric properties which has been well researched over the past century. The CDT is a popular tool for many healthcare professionals to administer independently or as part of a more thorough cognitive evaluation. Given the drastic technological and social developments over the years since the CDT was developed as well as the persistent research focus on older adult populations, a gap in the CDT literature presented for young adults, who may have difficulty drawing an analog clock. Identifying cognitive impairment can improve health outcomes. The young adult population …

In An Era Of Soft Skills: Investigating Teamwork Skills In The Geosciences, Samuel Cornelius Nyarko

Dissertations

Geoscience employers have increasingly called for student competency in three sets of skills – technical, field and soft skills. One major soft skill identified by employers is teamwork, which is critical in laboratory and field-based activities. At the same time, educators seek to inculcate in students a stronger focus on the development of teamwork skills as they are useful for knowledge sharing and problem solving. This interconnected value of teamwork in both the workforce and academia means students’ preparation should include learning teamwork in the geoscience. However, before educators can design strategies that help students learn critical teamwork skills, we …

Gender Quotas And Women's Substantive Representation In The National And Local Governments Of The Dominican Republic, Marcial Amaury Pineda Moquete

Dissertations

Although women's political representation has increased during the first part of the twenty-first century, the number of female politicians in legislative assemblies worldwide remains low. When well-designed and enforced, gender quota laws can increase women's representation. In tum, the election of female politicians brings about better outcomes for women. Further, female politicians elected by quota are likely to feel more committed to representing women than counterparts elected without quotas. This study tests whether and how quota-elected women can represent women's interests better than men and women elected without quotas. Using the rare natural experiment of the Dominican Republic's Congress and …

Refugee Social Relations: The Development Of Social Ties Among Burmese And Congolese Refugees In West Michigan, Diane M. Roushangar

Dissertations

Refugee resettlement has been studied extensively in the academic realm. Yet, an area that is less understood is among Burmese and Congolese refugees and their adaptation processes in the United States. This study focuses on the development of social relations within these two groups as they navigate interactions within their ethnic group and with the native-born community. Examining the process of how social relations are constructed, this study reveals the nuances of how Burmese and Congolese form close social ties by focusing on four distinct social domains. Illuminating how social relations are formed and maintained within the ethnic community, church …

A Model For Evaluating Charitable Contributions In Nonprofit Organizations In Kalamazoo County, Michigan, Kristen Smith

Dissertations

Reported data suggest there has been an increase in charitable giving and the number of charitable organizations in communities nationwide over the last 20 years. It is widely believed that growth in nonprofit organizations would be a valuable asset for a community, but limited research evaluates the return on investment in these organizations. To ensure these organizations are good stewards of resources, various forms of accountability have been established, including websites like “Charity Navigator™,” which provide rankings and scores to charities nationwide. Data repositories like these make it possible to investigate variations in these organizations' funding, growth, and impact. This …

Maintenance Of Cognitive Demand During Repeated Task Enactments Using A Teaching Practice That Builds On Student Thinking, Joshua M. Ruk

Dissertations

Maintaining high levels of cognitive demand during task enactments can improve student learning in classrooms. Influences such as teachers' beliefs about their students’ abilities, and the curriculum that a teacher uses can affect the factors that contribute to the maintenance of cognitive demand. My study adds to what we know about such influences by looking at how a teaching practice that builds on student thinking affects the factors that contribute to the maintenance of cognitive demand, by asking:

1. What does the maintenance of cognitive demand look like when teachers are attempting to attend to student thinking during task enactment?
2. How …