Physical Sciences and Mathematics Commons^™

India’S First Robotic Eye For Time-Domain Astrophysics: The Growth-India Telescope, Harsh Kumar, Varun Bhalerao, G. C. Anupama, Sudhanshu Barway, Judhajeet Basu, Kunal Deshmukh, Kishalay De, Anirban Dutta, Christoffer Fremling, Hrishikesh Iyer, Adeem Jassani, Simran Joharle, Viraj Karambelkar, Maitreya Khandagale, K. Adithya Krishna, Sumeet Kulkarni, Sujay Mate, Atharva Patil, D. V. S. Phanindra

Faculty and Student Publications

We present the design and performance of the GROWTH-India telescope, a 0.7 m robotic telescope dedicated to time-domain astronomy. The telescope is equipped with a 4k back-illuminated camera that gives a 0.°82 field of view and a sensitivity of m g′ ∼ 20.5 in 5 minute exposures. Custom software handles observatory operations: attaining high on-sky observing efficiencies (≳80%) and allowing rapid response to targets of opportunity. The data processing pipelines are capable of performing point-spread function photometry as well as image subtraction for transient searches. We also present an overview of the GROWTH-India telescope’s contributions to the studies of gamma-ray …

Motion-Adjustable Neural Implicit Video Representation, Long Mai, Feng Liu

Computer Science Faculty Publications and Presentations

Implicit neural representation (INR) has been successful in representing static images. Contemporary image-based INR, with the use of Fourier-based positional encoding, can be viewed as a mapping from sinusoidal patterns with different frequencies to image content. Inspired by that view, we hypothesize that it is possible to generate temporally varying content with a single image-based INR model by displacing its input sinusoidal patterns over time. By exploiting the relation between the phase information in sinusoidal functions and their displacements, we incorporate into the conventional image-based INR model a phase-varying positional encoding module, and couple it with a phase-shift generation module …

“Pictures Are Easier To Remember Than Spellings!”: Designing And Evaluating Kidspic: A Graphical Image-Based Authentication Mechanism, Dhanush Kumar Ratakonda, Hoda Mehrpouyan, Jerry Alan Fails

Computer Science Faculty Publications and Presentations

Children encounter difficulties when they login to computers or websites because they have challenges remembering passwords. To improve children’s authentication, we conducted a series of formative studies with children (n = 8, ages 6–11) to understand their authentication practices with respect to a traditional text-based password and a new graphical picture-based password called KidsPic. The results obtained from these initial investigations, a security analysis of these authentication mechanisms, and participatory design sessions with children (ages 6–11) inspired design enhancements to KidsPic. We subsequently conducted a study comparing KidsPic to a traditional text-based authentication mechanism (n = …

Pushing Boundaries Of Co-Design By Going Online: Lessons Learned And Reflections From Three Perspectives, Jerry Alan Fails, Dhanush Kumar Ratakonda, Nitzan Koren, Salma Elsayed-Ali, Elizabeth Bonsignore, Jason Yip

Computer Science Faculty Publications and Presentations

The global COVID-19 pandemic made significant changes to our day-to-day lives, which impacted how we conduct research and design — including co-design. In this article, we present case studies from three different co-design groups that pushed the boundaries of traditional co-design, and conducted multiple co-design sessions (more than 150 total) over the last year and a half. The case studies for each team include: the transition to online co-design; the pros and cons of logistics and design tools utilized during the co-design sessions; and the advances, challenges, and surprises. We compare and contrast themes that emerged from the case studies …

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 …

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 …

Singapore Public Sector Ai Applications Emphasizing Public Engagement: Six Examples, Steven M. Miller

Research Collection School Of Computing and Information Systems

This article provides an overview of six examples of public sector AI applications in Singapore that illustrate different ways of enhancing engagement with the public. These applications demonstrate ways of enhancing engagement with the public by providing greater accessibility to government services (access anywhere, anytime) and speedier responses to public processes and feedback. Some applications make it substantially easier for members of the public to do things or make choices, while others reduce waiting time, either across an entire public infrastructure, or for an individual transaction. Some provide highly individualized coaching to guide a person through the process of doing …

Performance Evaluation Of Aggregation-Based Group Recommender Systems For Ephemeral Groups, Edgar Ceh-Varela, Huiping Cao, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

Recommender Systems (RecSys) provide suggestions in many decision-making processes. Given that groups of people can perform many real-world activities (e.g., a group of people attending a conference looking for a place to dine), the need for recommendations for groups has increased. A wide range of Group Recommender Systems (GRecSys) has been developed to aggregate individual preferences to group preferences. We analyze 175 studies related to GRecSys. Previous works evaluate their systems using different types of groups (sizes and cohesiveness), and most of such works focus on testing their systems using only one type of item, called Experience Goods (EG). As …

A Quantitative Evaluation Of Explainable Ai Methods Using The Depth Of Decision Tree, Nizar Abdulaziz Mahyoub Ahmed, Adi̇l Alpkoçak

Turkish Journal of Electrical Engineering and Computer Sciences

It is necessary to develop an explainable model to clarify how and why a medical model makes a particular decision. Local posthoc explainable AI (XAI) techniques, such as SHAP and LIME, interpret classification system predictions by displaying the most important features and rules underlying any prediction locally. Therefore, in order to compare two or more XAI methods, they must first be evaluated qualitatively or quantitatively. This paper proposes quantitative XAI evaluation metrics that are not based on biased and subjective human judgment. On the other hand, it is dependent on the depth of the decision tree (DT) to automatically and …

Track Density Imaging Using Diffusion Tensor Imaging Data From 1.5 T Mri Scanner, Fatma Betül Köşker, Kazim Zi̇ya Gümüş, Mahmut Tokmakçi, Ni̇yazi̇ Acer, Serkan Şenol, Mehmet Bi̇lgen

Turkish Journal of Electrical Engineering and Computer Sciences

Superresolution track density imaging (TDI) has recently been developed for achieving high resolution track density maps from low-resolution diffusion images acquired at 3 T. But, the utility of the approach is still unclear when applied to diffusion tensor imaging (DTI) data acquired at lower 1.5 T magnetic field strength and thus its advantages or disadvantages awaits for exploration. We implemented an algorithm to generate track density maps of human white matter using streamline tracking and tested its performance with data acquired from two healthy volunteers at 1.5 Tesla. The effects of number of diffusion directions and seed selections on the …

Perceptual Analysis Of Distance Sampling And Transmittance Estimation Techniques In Biomedical Volume Visualization, Raazia Sosan, Muhammad Mobeen Movania, Shama Siddiqui

Turkish Journal of Electrical Engineering and Computer Sciences

In volumetric path tracer, distance sampling and transmittance estimation techniques play a vital role in producing high-quality final rendered images. Previously, these techniques were implemented for production volume rendering, and were analyzed for faster convergence. In this article, we have augmented additional transmittance estimators including ratio tracking, residual ratio tracking and unbiased ray marcher in a GPU-based volumetric path tracer (Exposure Render) for biomedical datasets. We have also analyzed distance sampling methods and transmittance estimators perceptually using CIEDE2000 and Structural Similarity Index (SSIM). It was found that ratio and residual ratio tracking estimators performed close to each other and were …

A New Approach For Congestive Heart Failure And Arrhythmia Classification Using Downsampling Local Binary Patterns With Lstm, Süleyman Akdağ, Fatma Kuncan, Yilmaz Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

Electrocardiogram (ECG) is a vital diagnosis approach for the rapid explication and detection of various heart diseases, especially cardiac arrest, sinus rhythms, and heart failure. For this purpose, in this study, a different perspective based on downsampling one-dimensional-local binary pattern (1D-DS-LBP) and long short-term memory (LSTM) is presented for the categorization of Electrocardiogram (ECG) signals. A transformation method named 1DDS-LBP has been presented for Electrocardiogram signals. The 1D-DS-LBP method processes the bigness smallness relationship between neighbors. According to the proposed method, by downsampling the signal, the histograms of 1D local binary patterns (1D-LBP) calculated from the obtained signal groups are …

Two-Layered Blockchain-Based Admission Control For Secure Uav Networks, Müge Özçevi̇k

Turkish Journal of Electrical Engineering and Computer Sciences

The frequent replacement requirement of UAVs for recharging outputs an extreme number of messaging for admission control of end-users. There are many studies that try to optimize the network capacity in an energy-efficient manner. However, they do not consider the security of data and control channels, which is the urgent requirement of 5G. Blockchain handles secure systems. However, the high numbered transactions in blockchain may cause bottlenecks while considering computational delay and throughput of end-user. In UAVs, a high percentage of battery is consumed for computational tasks instead of communication tasks. Therefore, to handle security by considering the computational needs, …

A New Network-Based Community Detection Algorithm For Disjoint Communities, Peli̇n Çeti̇n, Şahi̇n Emrah Amrahov

Turkish Journal of Electrical Engineering and Computer Sciences

A community is a group of people that shares something in common. The definition of the community can be generalized as things that have common properties. By using this definition, community detection can be used to solve different problems in various areas. In this study, we propose a new network-based community detection algorithm that can work on different types of datasets. The proposed algorithm works on unweighted graphs and determines the weight by using cosine similarity. We apply a bottom-up approach and find the disjoint communities. First, we accept each node as an independent community. Then, the merging process is …

On Approximate Nash Equilibria Of The Two-Source Connection Game, Buğra Çaşkurlu, Utku Umur Açikalin, Fati̇h Erdem Kizilkaya, Özgün Eki̇ci̇

Turkish Journal of Electrical Engineering and Computer Sciences

The arbitrary-sharing connection game is prominent in the network formation game literature [1]. An undirected graph with positive edge weights is given, where the weight of an edge is the cost of building it. An edge is built if agents contribute a sufficient amount for its construction. For agent i, the goal is to contribute the least possible amount while assuring that the source node si is connected to the terminal node ti . In this paper, we study the special case of this game in which there are only two source nodes. In this setting, we prove that there …

Chemical Disease Relation Extraction Through The Combination Of Multiple Mention Levels: Relscan+, Stanley Chika Onye, Nazi̇fe Di̇mi̇li̇ler, Ari̇f Akkeleş

Turkish Journal of Electrical Engineering and Computer Sciences

Chemical-induced disease (CID) relation extraction has been pivotal in the understanding of biological processes. A CID relation between a chemical and disease entity may be extracted either from a single sentence or from two or more adjacent sentences. We use `intrasentence level' to refer to the mention of the desired entities in the same sentence and `intersentence level? to refer to the mention of these entities in two or more adjacent sentences. This study proposes a three-phase architecture for extracting CID relations from biomedical literature by considering both sentence levels and additionally the combination of these two sentence levels which …

Presenting A Method To Detect Intrusion In Iot Through Private Blockchain, Rezvan Mahmoudie, Saeed Parsa, Amir Masoud Rahmani

Turkish Journal of Electrical Engineering and Computer Sciences

Blockchain (BC) has been used as a new solution to overcome security and privacy challenges in the Internet of Things (IoT). However, recent studies have indicated that the BC has a limited scalability and is computationally costly. Also, it has significant overhead and delay in the network, which is not suitable to the nature of IoT. This article aims at implementing BC in the IoT context for smart home management, as the integration of these two technologies ensures the IoT's security and privacy. Therefore, we proposed an overlay network in private BC to optimize its compatibility with IoT by increasing …

Revisiting 228Th As A Tool For Determining Sedimentation And Mass Accumulation Rates, Joseph J. Tamborski, Pinghe Cai, Meagan Eagle, Paul Henderson, Matthew A. Charette

OES Faculty Publications

The use of ²²⁸Th has seen limited application for determining sedimentation and mass accumulation rates in coastal and marine environments. Recent analytical advances have enabled rapid, precise measurements of particle-bound ²²⁸Th using a radium delayed coincidence counting system (RaDeCC). Herein we review the ²²⁸Th cycle in the marine environment and revisit the historical use of ²²⁸Th as a tracer for determining sediment vertical accretion and mass accumulation rates in light of new measurement techniques. Case studies comparing accumulation rates from ²²⁸Th and ²¹⁰Pb are presented for a micro-tidal salt marsh and a marginal sea …

Gis Data: Queen Anne’S County, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …

Gis Data: Baltimore City, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …

Gis Data: Wicomico County, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …

Regolith And Host Rock Influences On Co2 Leakage: Active Source Seismic Profiling Across The Little Grand Wash Fault, Utah, Lee M. Liberty, Jonathan Yelton, Elin Skurtveit, Alvar Braathen, Ivar Midtkandal, James P. Evans

Geosciences Faculty Publications and Presentations

Understanding carbon dioxide (CO₂) reservoir to surface migration is crucial to successful carbon capture and sequestration approaches; especially fault/reservoir interactions under injection pressure. Through seismic imaging, we explore regolith and shallow stratigraphy across the Little Grand Wash fault. The presence of natural CO₂ seeps, travertine and tufa deposits confirm modern and ancient fault-controlled CO₂ leakage. We consider this an analogue for a long-failed sequestration site. We estimate bulk porosity and fracture density for host rock, regolith, and fault zone from petrophysical relationships. When combined with existing geochemical and geological data, we characterize a 60 m wide …

Influence Of Defects On In-Plane Dynamic Properties Of Hexagonal Ligament Chiral Structures, Ning An, Xunwen Su, Dongmei Zhu, Mileta M. Tomovic

Engineering Technology Faculty Publications

Although the six-ligament chiral structure has many unique properties, due to its special structure, the stress concentration is prone to defects. In addition, additive manufacturing is also prone to defects. This paper studies the effect of defects, which is helpful for the better application of the six-ligament chiral structure. Several new six-ligament chiral structures with random and concentrated defects were designed to explore the effects of the defects on the in-plane dynamic properties. The structures were studied with the finite element ANSYS/LSDYNA numerical simulation and experimental methods. According to the defect-free six-ligament chiral structures exhibiting different deformation modes at different …

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 …

Deep Learning Fusion Of Satellite And Social Information To Estimate Human Migratory Flows, Daniel Runfola, Heather Baier, Laura Mills, Maeve Naughton-Rockwell, Anthony Stefanidis

Arts & Sciences Articles

Human migratory decisions are driven by a wide range of factors, including economic and environmental condi-tions, conflict, and evolving social dynamics. These factors are reflected in disparate data sources, including house-hold surveys, satellite imagery, and even news and social media. Here, we present a deep learning- based data fusion technique integrating satellite and census data to estimate migratory flows from Mexico to the United States. We leverage a three-stage approach, in which we (1) construct a matrix- based representation of socioeconomic information for each municipality in Mexico, (2) implement a convolutional neural network with both satellite imagery and the constructed …

Educating Sanitation Professionals: Moving From Stem To Specialist Training In Higher Education In Malawi, Brighton A. Chunga, David Mkwambisi, Cassandra L. Workman, Francis L. De Los Reyes Iii, Rochelle H. Holm

Faculty and Staff Scholarship

Achieving the United Nations Sustainable Development Goals (SDGs) requires effective changes in multiple sectors including education, economics, and health. Malawi faces challenges in attaining the SDGs in general, and specifically in the sanitation sector. This paper aims to describe the existing landscape within public universities in Malawi to build a framework for training a cadre of locally trained experts. This is achieved by reviewing science, technology, engineering, and mathematics (STEM) degree programmes and assessing the extent of inclusion of sanitation education. The historical compartmentalization of academic programmes has resulted in few programmes to build on. Deliberate investment is needed to …

Regeneration Time: Ancient Wisdom For Planetary Wellbeing, Anne Poelina, Sandra Wooltorton, Mindy Blaise, Catrina Luz Aniere, Pierre Horwitz, Peta J. White, Stephen Muecke

Research outputs 2022 to 2026

In these regenerative times prompted by the Anthropocene, Aboriginal voices are situated to draw on ancient wisdom for local learning and to share information across the globe as ecological imperative for planetary wellbeing. In this paper, postqualitative research foregrounds the sentient nature of life as ancestral power and brings the vitality of co-becoming as our places into active engagement. It enables coloniality to surface and reveals how it sits in our places and lives, in plain sight but unnoticed because of its so-called common sense. Postqualitative research relates with ancient knowledges in foregrounding Country's animacy and presence, revealing the essence …

Sensitized Photooxidation Of Prenylated Compounds: Mechanisms Of Downstream Dark Effects And Phototoxicity Priming, Shakeela Jabeen

Dissertations, Theses, and Capstone Projects

This thesis consists of four chapters as detailed below.

Chapter 1 discusses a singlet oxygen priming mechanism. Airborne singlet oxygen derived from photosensitization of triplet dioxygen is shown to react with an alkene surfactant (8-methylnon-7-ene-1 sulfonate) leading to ‘ene’ hydroperoxides that in the dark inactivate planktonic E. coli. The ‘ene’ hydroperoxide photoproducts are not toxic on their own, but they become toxic after the bacteria are pretreated with singlet oxygen. The total quenching rate constant (k_T) of singlet oxygen of the alkene surfactant was measured to be 1.1 × 10⁶ M⁻¹ s^{− …}

Influence Level Prediction On Social Media Through Multi-Task And Sociolinguistic User Characteristics Modeling, Denys Katerenchuk

Dissertations, Theses, and Capstone Projects

Prediction of a user’s influence level on social networks has attracted a lot of attention as human interactions move online. Influential users have the ability to influence others’ behavior to achieve their own agenda. As a result, predicting users’ level of influence online can help to understand social networks, forecast trends, prevent misinformation, etc. The research on user influence in social networks has attracted much attention across multiple disciplines, from social sciences to mathematics, yet it is still not well understood. One of the difficulties is that the definition of influence is specific to a particular problem or a domain, …

Astrophysics, Cosmology And Particle Phenomenology At The Energy Frontier, Jorge Fernandez Soriano

Dissertations, Theses, and Capstone Projects

This dissertation consists of two parts, treating significantly separated fields. Each part consists on several chapters, each treating a somewhat isolated topic from the rest. In each chapter, I present some of the work developed during my passage through the graduate program, which has mostly been published elsewhere.

Part I – Cosmic Rays and Particle Physics

• Chapter 1: In this chapter we present an introduction to the topic of cosmic ray physics, with an special focus on the so-called ultra high energy cosmic rays: their potential origins, effects during their propagation between their sources and Earth, the different techniques used …