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2022

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The Path From Paramilitary To Politics: Gerry Adams, Sinn Féin, And The Good Friday Agreement: 1986-1998, Brenann Hamilton Jan 2022

The Path From Paramilitary To Politics: Gerry Adams, Sinn Féin, And The Good Friday Agreement: 1986-1998, Brenann Hamilton

Dissertations and Theses @ UNI

Although the Troubles often have been written about by historians through a nationalistic or cultural context, pitting the Irish Catholic Nationalists against the Protestant British loyalists, much of the action took place within the political sphere, as the Nationalists’ and Unionists’ representatives fought for concessions and control. Rather than focusing on the religious differences or the ethnographic backgrounds of the people living in Northern Ireland, this thesis examines through a political context how the leaders of Sinn Féin shaped popular opinion and gained support through nonviolent means. While the national identity and cultural differences between the Nationalists and Unionists inform …

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The Medieval Ideal: Utopian Medievalism In The Life, Thought, And Works Of William Morris, Benjamin Michael Kimball Jan 2022

The Medieval Ideal: Utopian Medievalism In The Life, Thought, And Works Of William Morris, Benjamin Michael Kimball

Dissertations and Theses @ UNI

Interpreting the past often reveals as much about the interpreter as it does about the subject they interpret. This was the case with William Morris and his utopian mythologization of the Middle Ages. His art, writings, politics, and philosophy are suffused with a utopian vision of the medieval past. It runs through the whole body of his work and even in affected his personal life. It became a lens through which he could understand the world around him, a source on which he could draw for his political, social, and artistic critiques of Victorian Society. Through three different vantage points, …

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Mm Percussion Recital, Tyler Darnall Jan 2022

Mm Percussion Recital, Tyler Darnall

Dissertations and Theses @ UNI

This recital abstract serves as supplemental material to the Master of Music degree recital by Tyler Darnall. The recital will take place on April 15, 2022, at 6:00 p.m. Central Standard Time in Davis Hall at the University of Northern Iowa. This recital will feature works by Jeffrey Dennis Smith, Elliott Carter, J.S. Bach, Alyssa Weinberg, Nicolas Martynciow, John Cage, and Iannis Xenakis. Aiden Endres, Nicole Loftus, Xander Webb, and Matthew Kokotivich will be collaborating with Darnall for his recital. In addition to providing musical and historical context, this document will address specific considerations regarding performance practice for each piece.

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Lexile Levels And Their Value To Public School Teachers, Kristin Schumacher Jan 2022

Lexile Levels And Their Value To Public School Teachers, Kristin Schumacher

Dissertations and Theses @ UNI

This thesis examines how teachers perceive Lexile level and its value, and whether or not their beliefs inform their practice. To address questions regarding teachers’ beliefs about Lexile level, I designed and implemented an online survey for public school teachers. My research shows that teachers have a favorable view of Lexile level, that they believe both students and parents should be informed of students’ Lexile level, that books should be labeled with Lexile level, and that asking students to read within their Lexile level range is a good practice. This survey research reveals the need to further interrogate whether or …

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The Writing Identity Of A Hip Hop Lyricist And Educator: An Autoethnography, Lamont Muhammad Jan 2022

The Writing Identity Of A Hip Hop Lyricist And Educator: An Autoethnography, Lamont Muhammad

Dissertations and Theses @ UNI

Traditional educational curricula and instruction rarely take into consideration the social and community backgrounds of historically marginalized students. It is not that students are “incapable,” however, most times they do not see themselves as “school writers” (Stormer, 2017). This autoethnographic study (Poulos, 2021) examines the topic of writers identity. My research speaks from the positionality of a Black male educator and author, Hip Hop lyricist, and curriculum writer. The dissertation study details how writing raps or lyrics contributed to the development of my writer’s identity. I explored the following research question: How did Hip Hop writing nurture my writer's identity …

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The Effects Of Mixing Multi-Component Hlw Glasses On Spinel Crystal Size, C. (Charmayne) E. Lonergan, J. Rice, C. Skidmore, M. J. Schweiger, P. Hrma Jan 2022

The Effects Of Mixing Multi-Component Hlw Glasses On Spinel Crystal Size, C. (Charmayne) E. Lonergan, J. Rice, C. Skidmore, M. J. Schweiger, P. Hrma

Materials Science and Engineering Faculty Research & Creative Works

The Hanford Waste Treatment and Immobilization Plant will vitrify radioactive waste into borosilicate glass. The high-level waste (HLW) glass formulations are constrained by processing and property requirements, including restrictions aimed at avoiding detrimental impacts of spinel crystallization in the melter. To understand the impact of glass chemistry on crystallization, two HLW glasses precipitating small (∼5 μm) spinel crystals were individually mixed and melted with a glass that precipitated large (∼45 μm) spinel crystals in ratios of 25, 50, and 75 wt.%. The size of spinel crystals in the mixed glasses varied from 5 to 20 μm. Small crystal size was …

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Pulsed-Active Microwave Thermography, Logan M. Wilcox, Mathias Bonmarin, Kristen M. Donnell Jan 2022

Pulsed-Active Microwave Thermography, Logan M. Wilcox, Mathias Bonmarin, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Active microwave thermography (AMT) is a thermographic nondestructive testing and evaluation technique that utilizes an electromagnetic-based excitation with a subsequent infrared measurement of the surface thermal profile of the material or structure of interest. AMT has been successfully applied to several aerospace and civil infrastructure applications. This work seeks to expand the performance of AMT by incorporating a signal processing technique common to traditional (flash-lamp) thermography, referred to as pulsed thermography (PT). PT operates on the premise of a pulsed excitation, as opposed to a constant or step excitation (ST) over a given time-period that is typical to traditional active …

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3d-Printed Gelatin-Alginate Hydrogel Dressings For Burn Wound Healing: A Comprehensive Study, Fateme Fayyazbakhsh, Michael J. Khayat, Ming-Chuan Leu Jan 2022

3d-Printed Gelatin-Alginate Hydrogel Dressings For Burn Wound Healing: A Comprehensive Study, Fateme Fayyazbakhsh, Michael J. Khayat, Ming-Chuan Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Burn Wound Treatment is Still a Clinical Challenge Due to the Severity of Tissue Damage and Dehydration. among Various Wound Dressings, Hydrogel Materials Have Gained Significant Attention for Burn Wound Treatment in Clinical Practice Due to their Soothing and Moisturizing Activity. in This Study, 3D-Printed Dressings Were Fabricated using Clinically Relevant Hydrogels for Deep Partial-Thickness Burn (PTB) Wounds. Different Ratios of Gelatin and Alginate Mixture Were 3D-Printed and Examined in Terms of Rheological Behavior, Shear Thinning Behavior, Mechanical Properties, Degradation Rate, and Hydration Activity to Tune the Hydrogel Composition for Best Functionality. the Cell-Laden Dressings Were Bioprinted to Evaluate the …

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Monetization For Content Generation And User Engagement On Social Media Platforms: Evidence From Paid Q&A, Jonathan Hua Ye, Cecil Eng Huang Chua Jan 2022

Monetization For Content Generation And User Engagement On Social Media Platforms: Evidence From Paid Q&A, Jonathan Hua Ye, Cecil Eng Huang Chua

Business and Information Technology Faculty Research & Creative Works

Social media platforms want to increase their valuation in terms of total content quantity and user engagement. Monetization is often used to induce user content generation. However, research documents that while monetization increases the quantity of specific kinds of content, it does not necessarily increase the total content quantity or user engagement (i.e., platform value). Furthermore, the impact of monetization may depend on the social status of content creators. This article investigates paid question and answer (paid Q&A). Based on expectancy theory and relevant research, this article hypothesizes the effects of introducing paid Q&A on both total content quantity and …

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Are Socially Responsible Exchange-Traded Funds Paying Off In Performance?, Ya Dai, Liang Guo, Steve Liu, Hongxian Zhang Jan 2022

Are Socially Responsible Exchange-Traded Funds Paying Off In Performance?, Ya Dai, Liang Guo, Steve Liu, Hongxian Zhang

Business and Information Technology Faculty Research & Creative Works

This study examines the Socially Responsible (SR) exchange-traded funds (ETFs) by comparing their risk-adjusted performance with a matched group of conventional ETFs in the U.S. equity market. In contrast to prior studies that focus on actively managed mutual funds, we find that the risk-adjusted returns of SR ETFs are significantly lower than those of conventional ETFs during the 2005–2020 period. Such underperformance is only observed in non-crisis periods but not in economic crisis periods (i.e., the 2020 pandemic recession and 2008 financial turmoil). We attribute the observed underperformance of SR ETFs during the non-crisis periods to their limited diversification of …

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The Impact Of Perceived Manipulation, Motives, And Ethicality In Cause-Related Marketing: A Crm+ Model, Nathan W. Twyman, Sarah M. Stanley, Cassandra C. Elrod, Tamara M. Masters Jan 2022

The Impact Of Perceived Manipulation, Motives, And Ethicality In Cause-Related Marketing: A Crm+ Model, Nathan W. Twyman, Sarah M. Stanley, Cassandra C. Elrod, Tamara M. Masters

Business and Information Technology Faculty Research & Creative Works

We Developed a CRM+ Model using Experimentation and Structural Equation Modeling Analysis. CRM+ Demonstrates Previously Unexplored Interrelationships among Consumer-Perceived Manipulation, Brand Motives, Perceived Ethicality of the Cause-Related Marketing, and Brand Attitude. CRM+ Reveals that Perceived Ethicality of the CRM Has a Significant Positive Effect on Brand Attitude, Though It is Not as Pronounced as the Effect of Perceived Altruistic Motives. Egoistic Motives Decrease Ethicality Perceptions But Has No Direct Effect on Brand Attitude. Altruistic Motive Perceptions Diminish Egoistic Motive Perceptions. CRM+ Suggests Marketing Managers Should Prioritize Emphasizing Altruistic Motives and Ethicality of the Partnership over Downplaying Egoistic Motives.

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Information Systems Analysis And Design: Past Revolutions, Present Challenges, And Future Research Directions, Keng Siau, Carson Woo, Veda C. Storey, Roger H.L. Chiang, Cecil Eng Huang Chua, Jon W. Beard Jan 2022

Information Systems Analysis And Design: Past Revolutions, Present Challenges, And Future Research Directions, Keng Siau, Carson Woo, Veda C. Storey, Roger H.L. Chiang, Cecil Eng Huang Chua, Jon W. Beard

Business and Information Technology Faculty Research & Creative Works

Systems Analysis and Design (SAND) is Undoubtedly a Pillar in the Field of Information Systems (IS). Some Researchers Have Even Claimed that SAND is the Field that Defines the Information Systems Discipline and is the Core of Information Systems. the Past Decades Have Seen the Development of Structured SAND Methodologies and Object-Oriented Methodologies. in the Early 1990s, Key Players in the Field Collaborated to Develop the Unified Modeling Language and the Unified Process. Agile Approaches Followed, as Did Other Dynamic Methods. These Approaches Remain Heavily Employed in the Development of Contemporary Information Systems. at the Same Time, New Approaches Such …

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A Novel Echo State Network Autoencoder For Anomaly Detection In Industrial Iot Systems, Fabrizio De Vita, Giorgio Nocera, Dario Bruneo, Sajal K. Das Jan 2022

A Novel Echo State Network Autoencoder For Anomaly Detection In Industrial Iot Systems, Fabrizio De Vita, Giorgio Nocera, Dario Bruneo, Sajal K. Das

Computer Science Faculty Research & Creative Works

The Industrial Internet of Things (IIoT) technology had a very strong impact on the realization of smart frameworks for detecting anomalous behaviors that could be potentially dangerous to a system. In this regard, most of the existing solutions involve the use of Artificial Intelligence (AI) models running on Edge devices, such as Intelligent Cyber Physical Systems (ICPS) typically equipped with sensing and actuating capabilities. However, the hardware restrictions of these devices make the implementation of an effective anomaly detection algorithm quite challenging. Considering an industrial scenario, where signals in the form of multivariate time-series should be analyzed to perform a …

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Noise Resilient Learning For Attack Detection In Smart Grid Pmu Infrastructure, Prithwiraj Roy, Shameek Bhattacharjee, Sahar Abedzadeh, Sajal K. Das Jan 2022

Noise Resilient Learning For Attack Detection In Smart Grid Pmu Infrastructure, Prithwiraj Roy, Shameek Bhattacharjee, Sahar Abedzadeh, Sajal K. Das

Computer Science Faculty Research & Creative Works

Falsified data from compromised Phasor Measurement Units (PMUs) in a smart grid induce Energy Management Systems (EMS) to have an inaccurate estimation of the state of the grid, disrupting various operations of the power grid. Moreover, the PMUs deployed at the distribution layer of a smart grid show dynamic fluctuations in their data streams, which make it extremely challenging to design effective learning frameworks for anomaly-based attack detection. In this paper, we propose a noise resilient learning framework for anomaly-based attack detection specifically for distribution layer PMU infrastructure, that show real time indicators of data falsifications attacks while offsetting the …

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Cansafe: An Mtd Based Approach For Providing Resiliency Against Dos Attack Within In-Vehicle Networks, Ayan Roy, Sanjay Kumar Madria Jan 2022

Cansafe: An Mtd Based Approach For Providing Resiliency Against Dos Attack Within In-Vehicle Networks, Ayan Roy, Sanjay Kumar Madria

Computer Science Faculty Research & Creative Works

Trending towards autonomous transportation systems, modern vehicles are equipped with hundreds of sensors and actuators that increase the intelligence of the vehicles with a higher level of autonomy, as well as facilitate increased communication with entities outside the in-vehicle network. However, increase in a contact point with the outside world has exposed the controller area network (CAN) of a vehicle to remote security vulnerabilities. In particular, an attacker can inject fake high priority messages within the CAN through the contact points, while preventing legitimate messages from controlling the CAN (Denial-of-Service (DoS) attack). In this paper, we propose a Moving Target …

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Distributed Decision Making For V2v Charge Sharing In Intelligent Transportation Systems, Punyasha Chatterjee, Pratham Majumder, Arpita Debnath, Sajal K. Das Jan 2022

Distributed Decision Making For V2v Charge Sharing In Intelligent Transportation Systems, Punyasha Chatterjee, Pratham Majumder, Arpita Debnath, Sajal K. Das

Computer Science Faculty Research & Creative Works

Electric vehicles (EVs) have emerged in the intelligent transportation system (ITS) to meet the increasing environmental concerns. To facilitate on-demand requirement of EV charging, vehicle-to-vehicle (V2V) charge transfer can be employed. However, most of the existing approaches to V2V charge sharing are centralized or semi-centralized, incurring huge message overhead, long waiting time, and infrastructural cost. In this paper, we propose novel distributed heuristic algorithms for V2V charge sharing based on the multi-criteria decision-making policy. The problem is mapped to an alias classical problem (i.e., optimum matching in weighted bipartite graphs), where the goal is to maximize the matching cardinality while …

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Rssafe: Personalized Driver Behavior Prediction For Safe Driving, Bhumika, Debasis Das, Sajal K. Das Jan 2022

Rssafe: Personalized Driver Behavior Prediction For Safe Driving, Bhumika, Debasis Das, Sajal K. Das

Computer Science Faculty Research & Creative Works

While the increased demand for taxi services like Uber, Lyft, Hailo, Ola, Grab, Cabify etc. provides livelihood to many drivers, the desire to raise income forces the drivers to work very hard without rest. However, continuous journeys not only affect their health, but also lead to abnormal driving behavior such as rash driving, swerving, sideslipping, sudden brakes, or weaving, leading to accidents in the worst cases. Motivated by the severity of rising accidents and health issues among drivers, this paper proposes a recommendation system, called RsSafe, for the safety of drivers. Aiming to improve the driving quality and the driver's …

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An Icn-Based Secure Task Cooperation Scheme In Challenging Wireless Edge Networks, Ningchun Liu, Shuai Gao, Teng Liang, Xindi Hou, Sajal K. Das Jan 2022

An Icn-Based Secure Task Cooperation Scheme In Challenging Wireless Edge Networks, Ningchun Liu, Shuai Gao, Teng Liang, Xindi Hou, Sajal K. Das

Computer Science Faculty Research & Creative Works

Task cooperation is an effective way to execute a complex task in challenging wireless edge networks. Existing TCP/IP-based solutions encounter the problem of low network resource utilization and the heavy dependency of infrastructure connections. Information-centric networking (ICN) is a promising architecture to address these issues. In existing ICN-based task cooperation schemes, the data reuse feature of ICN improves the utilization of network resources, which also brings potential security threats to the reused data. To guarantee the security of data reuse in task cooperation without affecting the data reuse feature, we propose an ICN-based secure task cooperation scheme. In our scheme, …

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Toward Feature-Preserving Vector Field Compression, Xin Liang, Sheng Di, Franck Cappello, Mukund Raj, Chunhui Liu, Kenji Ono, Zizhong Chen, Tom Peterka, Hanqi Guo Jan 2022

Toward Feature-Preserving Vector Field Compression, Xin Liang, Sheng Di, Franck Cappello, Mukund Raj, Chunhui Liu, Kenji Ono, Zizhong Chen, Tom Peterka, Hanqi Guo

Computer Science Faculty Research & Creative Works

The objective of this work is to develop error-bounded lossy compression methods to preserve topological features in 2D and 3D vector fields. Specifically, we explore the preservation of critical points in piecewise linear and bilinear vector fields. We define the preservation of critical points as, without any false positive, false negative, or false type in the decompressed data, (1) keeping each critical point in its original cell and (2) retaining the type of each critical point (e.g., saddle and attracting node). The key to our method is to adapt a vertex-wise error bound for each grid point and to compress …

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Delivery With Uavs: A Simulated Dataset Via Ats, Giulio Rigoni, Cristina M. Pinotti, Bhumika, Debasis Das, Sajal K. Das Jan 2022

Delivery With Uavs: A Simulated Dataset Via Ats, Giulio Rigoni, Cristina M. Pinotti, Bhumika, Debasis Das, Sajal K. Das

Computer Science Faculty Research & Creative Works

We consider a delivery food service operated by Unmanned Aerial Vehicles (UAVs). Due to the absence of a dataset on UAVs deliveries in the literature, and since it is not possible to perform real tests, we create a dataset using an open-Air Traffic Simulator (ATS). Precisely, we converted a set of food deliveries operated by wheeled vehicles, proposed in the literature [1], into a set of simulated UAVs deliveries. For each delivery, we ran a UAV flight from the source to the destination. The results showed that, as expected, the UAV's course is shorter than the vehicle trajectory on the …

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Targeted Content-Sharing In A Multi-Group Dtn Application Using Attribute-Based Encryption, Xiaofei Cao, Shudip Datta, Ram Charan Bolla, Sanjay Kumar Madria Jan 2022

Targeted Content-Sharing In A Multi-Group Dtn Application Using Attribute-Based Encryption, Xiaofei Cao, Shudip Datta, Ram Charan Bolla, Sanjay Kumar Madria

Computer Science Faculty Research & Creative Works

In a battlefield, multiple groups operate with different missions, but their missions and groups can dynamically change based on the evolving situation. Due to the unavailability of network infrastructure after deployment, group members form a Delay Tolerant Network (DTN) which is prone to security attacks. Hence, based on the mission attributes, group memberships, nodes' interests, and data tags determination, targeted contents need to be distributed in a secure fashion to different users. Though existing Attributes Based Encryption (ABE) can provide security of information, revoking a member from a group is always an issue in DTN as the Attribute Authority (AA) …

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Active Learning Augmented Folded Gaussian Model For Anomaly Detection In Smart Transportation, Venkata Praveen Kumar Madhavarapu, Prithwiraj Roy, Shameek Bhattacharjee, Sajal K. Das Jan 2022

Active Learning Augmented Folded Gaussian Model For Anomaly Detection In Smart Transportation, Venkata Praveen Kumar Madhavarapu, Prithwiraj Roy, Shameek Bhattacharjee, Sajal K. Das

Computer Science Faculty Research & Creative Works

Smart transportation networks have become instrumental in smart city applications with the potential to enhance road safety, improve the traffic management system and driving experience. A Traffic Message Channel (TMC) is an IoT device that records the data collected from the vehicles and forwards it to the Roadside Units (RSUs). This data is further processed and shared with the vehicles to inquire the fastest route and incidents that can cause significant delays. The failure of the TMC sensors can have adverse effects on the transportation network. In this paper, we propose a Gaussian distribution-based trust scoring model to identify anomalous …

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Improving Age Of Information With Interference Problem In Long-Range Wide Area Networks, Preti Kumari, Hari Prabhat Gupta, Tanima Dutta, Sajal K. Das Jan 2022

Improving Age Of Information With Interference Problem In Long-Range Wide Area Networks, Preti Kumari, Hari Prabhat Gupta, Tanima Dutta, Sajal K. Das

Computer Science Faculty Research & Creative Works

Low Power Wide Area Networks (LPWAN) offer a promising wireless communications technology for Internet of Things (IoT) applications. Among various existing LPWAN technologies, Long-Range WAN (LoRaWAN) consumes minimal power and provides virtual channels for communication through spreading factors. However, LoRaWAN suffers from the interference problem among nodes connected to a gateway that uses the same spreading factor. Such interference increases data communication time, thus reducing data freshness and suitability of LoRaWAN for delay-sensitive applications. To minimize the interference problem, an optimal allocation of the spreading factor is requisite for determining the time duration of data transmission. This paper proposes a …

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Mobility Management In Industrial Iot Environments, Marco Pettorali, Francesca Righetti, Carlo Vallati, Sajal K. Das, Giuseppe Anastasi Jan 2022

Mobility Management In Industrial Iot Environments, Marco Pettorali, Francesca Righetti, Carlo Vallati, Sajal K. Das, Giuseppe Anastasi

Computer Science Faculty Research & Creative Works

The Internet Engineering Task Force (IETF) has defined the 6TiSCH architecture to enable the Industrial Inter-net of Things (IIoT). Unfortunately, 6TiSCH does not provide mechanisms to manage node mobility, while many industrial applications involve mobile devices (e.g., mobile robots or wearable devices carried by workers). In this paper, we consider the Synchronized Single-hop Multiple Gateway framework to manage mobility in 6TiSCH networks. For this framework, we address the problem of positioning Border Routers in a deployment area, which is similar to the "Art Gallery"problem, proposing an efficient deployment policy for Border Routers based on geometrical rules. Moreover, we define a …

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Mdz: An Efficient Error-Bounded Lossy Compressor For Molecular Dynamics, Kai Zhao, Sheng Di, Danny Perez, Xin Liang, Zizhong Chen, Franck Cappello Jan 2022

Mdz: An Efficient Error-Bounded Lossy Compressor For Molecular Dynamics, Kai Zhao, Sheng Di, Danny Perez, Xin Liang, Zizhong Chen, Franck Cappello

Computer Science Faculty Research & Creative Works

Molecular dynamics (MD) has been widely used in today's scientific research across multiple domains including materials science, biochemistry, biophysics, and structural biology. MD simulations can produce extremely large amounts of data in that each simulation could involve a large number of atoms (up to trillions) for a large number of timesteps (up to hundreds of millions). In this paper, we perform an in-depth analysis of a number of MD simulation datasets and then develop an efficient error-bounded lossy compressor that can significantly improve the compression ratios. The contributions are fourfold. (1) We characterize a number of MD datasets and summarize …

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Spade: Multi-Stage Spam Account Detection For Online Social Networks, Federico Concone, Giuseppe Lo Re, Marco Morana, Sajal K. Das Jan 2022

Spade: Multi-Stage Spam Account Detection For Online Social Networks, Federico Concone, Giuseppe Lo Re, Marco Morana, Sajal K. Das

Computer Science Faculty Research & Creative Works

In recent years, Online Social Networks (OSNs) have radically changed the way people communicate. The most widely used platforms, such as Facebook, Youtube, and Instagram, claim more than one billion monthly active users each. Beyond these, news-oriented micro-blogging services, e.g., Twitter, are daily accessed by more than 120 million users sharing contents from all over the world. Unfortunately, legitimate users of the OSNs are mixed with malicious ones, which are interested in spreading unwanted, misleading, harmful, or discriminatory content. Spam detection in OSNs is generally approached by considering the characteristics of the account under analysis, its connection with the rest …

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Locality-Aware Qubit Routing For The Grid Architecture, Avah Banerjee, Xin Liang, R. Tohid Jan 2022

Locality-Aware Qubit Routing For The Grid Architecture, Avah Banerjee, Xin Liang, R. Tohid

Computer Science Faculty Research & Creative Works

Due to the short decohorence time of qubits available in the NISQ-era, it is essential to pack (minimize the size and or the depth of) a logical quantum circuit as efficiently as possible given a sparsely coupled physical architecture. In this work we introduce a locality-aware qubit routing algorithm based on a graph theoretic framework. Our algorithm is designed for the grid and certain 'grid-like' architectures. We experimentally show the competitiveness of algorithm by comparing it against the approximate token swapping algorithm, which is used as a primitive in many state-of-the-art quantum trans pilers. Our algorithm produces circuits of comparable …

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Privacy-Preserving Data Falsification Detection In Smart Grids Using Elliptic Curve Cryptography And Homomorphic Encryption, Sanskruti Joshi, Ruixiao Li, Shameek Bhattacharjee, Sajal K. Das, Hayato Yamana Jan 2022

Privacy-Preserving Data Falsification Detection In Smart Grids Using Elliptic Curve Cryptography And Homomorphic Encryption, Sanskruti Joshi, Ruixiao Li, Shameek Bhattacharjee, Sajal K. Das, Hayato Yamana

Computer Science Faculty Research & Creative Works

In an advanced metering infrastructure (AMI), the electric utility collects power consumption data from smart meters to improve energy optimization and provides detailed information on power consumption to electric utility customers. However, AMI is vulnerable to data falsification attacks, which organized adversaries can launch. Such attacks can be detected by analyzing customers' fine-grained power consumption data; however, analyzing customers' private data violates the customers' privacy. Although homomorphic encryption-based schemes have been proposed to tackle the problem, the disadvantage is a long execution time. This paper proposes a new privacy-preserving data falsification detection scheme to shorten the execution time. We adopt …

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Look-Up Table Based Fhe System For Privacy Preserving Anomaly Detection In Smart Grids, Ruixiao Li, Shameek Bhattacharjee, Sajal K. Das, Hayato Yamana Jan 2022

Look-Up Table Based Fhe System For Privacy Preserving Anomaly Detection In Smart Grids, Ruixiao Li, Shameek Bhattacharjee, Sajal K. Das, Hayato Yamana

Computer Science Faculty Research & Creative Works

In advanced metering infrastructure (AMI), the customers' power consumption data is considered private but needs to be revealed to data-driven attack detection frameworks. In this paper, we present a system for privacy-preserving anomaly-based data falsification attack detection over fully homomorphic encrypted (FHE) data, which enables computations required for the attack detection over encrypted individual customer smart meter's data. Specifically, we propose a homomorphic look-up table (LUT) based FHE approach that supports privacy preserving anomaly detection between the utility, customer, and multiple partied providing security services. In the LUTs, the data pairs of input and output values for each function required …

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Message From The Bits 2022 Workshop Co-Chairs, Sajal K. Das, Hayato Yamana, Keiichi Yasumoto, Shameek Bhattacharjee Jan 2022

Message From The Bits 2022 Workshop Co-Chairs, Sajal K. Das, Hayato Yamana, Keiichi Yasumoto, Shameek Bhattacharjee

Computer Science Faculty Research & Creative Works

No abstract provided.

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