Digital Commons Network^™

Cyber-Agricultural Systems For Crop Breeding And Sustainable Production, Soumik Sarkar, Baskar Ganapathysubramanian, Arti Singh, Fateme Fotouhi, Soumyashree Kar, Koushik Nagasubramanian, Girish Chowdhary, Sajal K. Das, George Kantor, Adarsh Krishnamurthy, Nirav Merchant, Asheesh K. Singh

Computer Science Faculty Research & Creative Works

The Cyber-Agricultural System (CAS) Represents an overarching Framework of Agriculture that Leverages Recent Advances in Ubiquitous Sensing, Artificial Intelligence, Smart Actuators, and Scalable Cyberinfrastructure (CI) in Both Breeding and Production Agriculture. We Discuss the Recent Progress and Perspective of the Three Fundamental Components of CAS – Sensing, Modeling, and Actuation – and the Emerging Concept of Agricultural Digital Twins (DTs). We Also Discuss How Scalable CI is Becoming a Key Enabler of Smart Agriculture. in This Review We Shed Light on the Significance of CAS in Revolutionizing Crop Breeding and Production by Enhancing Efficiency, Productivity, Sustainability, and Resilience to Changing …

Q-Learning For Sum-Throughput Optimization In Wireless Visible-Light Uav Networks, Yuwei Long, Nan Cen

Computer Science Faculty Research & Creative Works

Unmanned Aerial Vehicles (UAVs) Have Been Adopted as Aerial Base Stations (ABSs) to Provide Wireless Connectivity to Ground Users in Events of Increased Network Demand, and Points-Of-Failure Infrastructure (Such as in Disasters). However, with the Existing Crowded Radio Frequency (RF) Spectrum, UAV ABSs Cannot Provide High-Data-Rate Communication Required in 5G and beyond. to Address This Challenge, Visible Light Communication (VLC) is Proposed to Be Equipped on UAVs to Take Advantage of the Flexible and On-Demand Deployment Feature of the UAV, and the High-Data-Rate Communication of the VLC. However, VLC Has Strong Alignment Requirements between Transceivers, Therefore, How to Determine the …

Lightesd: Fully-Automated And Lightweight Anomaly Detection Framework For Edge Computing, Ronit Das, Tie (Tony) T. Luo

Computer Science Faculty Research & Creative Works

Anomaly Detection is Widely Used in a Broad Range of Domains from Cybersecurity to Manufacturing, Finance, and So On. Deep Learning based Anomaly Detection Has Recently Drawn Much Attention Because of its Superior Capability of Recognizing Complex Data Patterns and Identifying Outliers Accurately. However, Deep Learning Models Are Typically Iteratively Optimized in a Central Server with Input Data Gathered from Edge Devices, and Such Data Transfer between Edge Devices and the Central Server Impose Substantial overhead on the Network and Incur Additional Latency and Energy Consumption. to overcome This Problem, We Propose a Fully Automated, Lightweight, Statistical Learning based Anomaly …

Smartlens: Robust Detection Of Rogue Device Via Frequency Domain Features In Lora-Enabled Iiot, Subir Halder, Amrita Ghosal, Thomas Newe, Sajal K. Das

Computer Science Faculty Research & Creative Works

A challenging problem in Long Range (LoRa) communications enabled Industrial Internet of Things (IIoT) is the detection of rogue devices, which attempt to impersonate real devices by spoofing their authentic identifications in order to steal information and gain access to the system. Although machine learning (ML) offers a promising approach to detecting rogue devices, existing ML models rely on domain knowledge yet exhibit low detection accuracy and vulnerability against adversarial attacks. This paper proposes SmartLens, a novel real-time frequency domain feature based rogue device detection system, using a lightweight statistical ML algorithm and Mahalanobis distance to achieve high accuracy and …

A Distributed Algorithm For Identifying Strongly Connected Components On Incremental Graphs, S. Srinivasan, A. Khanda, S. Srinivasan, A. Pandey, S. (Sajal) K. Das, S. Bhowmick, B. Norris

Computer Science Faculty Research & Creative Works

Incremental graphs that change over time capture the changing relationships of different entities. Given that many real-world networks are extremely large, it is often necessary to partition the network over many distributed systems and solve a complex graph problem over the partitioned network. This paper presents a distributed algorithm for identifying strongly connected components (SCC) on incremental graphs. We propose a two-phase asynchronous algorithm that involves storing the intermediate results between each iteration of dynamic updates in a novel meta-graph storage format for efficient recomputation of the SCC for successive iterations. To the best of our knowledge, this is the …

Strategic Information Design In Selfish Routing With Quantum Response Travelers, Sainath Sanga, Venkata Sriram Siddhardh Nadendla, Mukund Telukunta, Sajal K. Das

Computer Science Faculty Research & Creative Works

Selfish routing begets inefficiency in multi-agent transportation systems, leading to significant economic losses in our society. Although several powerful techniques (e. g., marginal cost pricing) have been proposed to mitigate price-of-anarchy (a measure of inefficiency), social welfare maximization still remains a huge challenge in selfish routing, especially when travelers deviate from maximizing their own expected utilities. This paper proposes a novel informational intervention to improve the efficiency of selfish routing, especially in the presence of quantal response travelers. Specifically, modeling the interaction between the system and travelers as a Stackelberg game, and develop a novel approximate algorithm, called LoRI (which …

Optimizing Federated Learning In Leo Satellite Constellations Via Intra-Plane Model Propagation And Sink Satellite Scheduling, Mohamed Elmahallawy, Tie (Tony) T. Luo

Computer Science Faculty Research & Creative Works

The advances in satellite technology developments have recently seen a large number of small satellites being launched into space on Low Earth orbit (LEO) to collect massive data such as Earth observational imagery. The traditional way which downloads such data to a ground station (GS) to train a machine learning (ML) model is not desirable due to the bandwidth limitation and intermittent connectivity between LEO satellites and the GS. Satellite edge computing (SEC), on the other hand, allows each satellite to train an ML model onboard and uploads only the model to the GS which appears to be a promising …

Rate-Monotonic Scheduler For Lora-Based Smart Space Monitoring System, Preti Kumari, Hari Prabhat Gupta, Sajal K. Das, Rahul Bansal

Computer Science Faculty Research & Creative Works

Smart spaces system equipped with sensors to collect data that can be used to generate insights about its environmental conditions. Those collected data is then transmitted to the applications to enhance the comfort, quality of life, and security of the space. Long Range (LoRa) technology provides long distance coverage and consumes low energy which makes it suitable for smart space application. There are six virtual channels to transmit data in LoRa, however network faces the interference problem when nodes transmitted data at the same time. The interference problem makes LoRa less suitable for time-critical applications. To mitigate the interference problem, …

Identifying Design-Build Decision-Making Factors And Providing Future Research Guidelines: Social Network And Association Rule Analysis, Ramy Khalef, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

There is a dire need to rebuild existing infrastructure with strategic and efficient methods. Design-build (DB) becomes a potential solution that provides fast-tracked delivery as a more time and cost-efficient project delivery method. Past research studied factors influencing DB but without providing a holistic analytic approach. This paper fills this knowledge gap. First, a systematic literature review is performed using the preferred reporting items for systematic reviews and meta-analyses techniques, and a set of factors affecting DB projects are then identified and clustered, using k-means clustering, based on the whole literature discussions. Second, a graph theory approach, social network analysis …

Supply Chain Insights From Social Media Users’ Responses To Panic Buying During Covid-19: The Herd Mentality, Violetta Wilk, Saiyidi Mat Roni, Ferry Jie

Research outputs 2022 to 2026

Purpose:

This study applied the herd mentality theory to explore local and global social media users’ responses to panic buying across the USA, UK and Australia during the COVID-19 crisis to understand the implications on operations and supply chains.

Design/methodology/approach:

A total of 208,806 social media user-generated content (UGC) pieces were collected from Twitter in three countries – the USA, UK and Australia. The analysis of this big qualitative data was performed using machine learning–based software – Leximancer.

Findings:

Positive and negative sentiment towards panic buying during the COVID-19 crisis was observed in the UGC. No significant differences in social …

Determinants Of Intention To Use E-Wallet: Personal Innovativeness And Propensity To Trust As Moderators, Madugoda Gunaratnege Senali, Mohammad Iranmanesh, Fatin Nadzirah Ismail, Noor Fareen Abdul Rahim, Mana Khoshkam, Maryam Mirzaei

Research outputs 2022 to 2026

This study aims to investigate the determinants of intention to use e-wallets. Drawing on the technology acceptance model (TAM), the conceptual framework was developed. The study extends the TAM in the context of e-wallets, by testing the influences of product-related factors namely perceived compatibility, perceived risk, and perceived emotions and investigating the moderating impacts of personal innovativeness and propensity to trust. To conduct an empirical study, the data were collected from Malaysian individuals with no experience with e-wallets using an online survey. Data from 374 participants were obtained and analyzed using the partial least squares technique. The results showed that …

Spatial Heterogeneity In Sediment And Carbon Accretion Rates Within A Seagrass Meadow Correlated With The Hydrodynamic Intensity, Jiarui Lei, Rachel Schaefer, Phil Colarusso, Alyssa Novak, Juliet C. Simpson, Pere Masqué, Heidi Nepf

Research outputs 2022 to 2026

The majority of the carbon stored in seagrass sediments originates outside the meadow, such that the carbon storage capacity within a meadow is strongly dependent on hydrodynamic conditions that favor deposition and retention of fine organic matter within the meadow. By extension, if hydrodynamic conditions vary across a meadow, they may give rise to spatial gradients in carbon. This study considered whether the spatial gradients in sediment and carbon accretion rates correlated with the spatial variation in hydrodynamic intensity within a single meadow. Field measurements were conducted in three depth zones across a Zostera marina L. (eelgrass) meadow in Nahant …

Judging Better Together: Understanding The Psychology Of Group Decision-Making On Panel Courts And Tribunals, Brian M. Barry Dr

Articles

While the psychological phenomena that affect group decisionmaking have been thoroughly investigated for decades, how these phenomena apply to decision-making by judges on panel courts is under-examined. This article examines the main psychological phenomena of group decision-making, both positive and negative, and considers their implications for panel courts and other groups of professional legal decision-makers such as adjudicators serving on tribunals. This article argues that experimental studies on judges and adjudicators testing the effects of these phenomena would improve understanding of legal decision-making by these groups and could help to devise ways to improve their decision-making processes to reach higher …

The Distribution Of Justices' Votes And Countering National Disunity, Nicholas L. Georgakopoulos

FIU Law Review

The estimation of the distribution that matches the voting of the justices of the Supreme Court shows that voting is correlated and reveals three phenomena: an outlier distribution produced by one composition of the Court, the surprising frequency of unanimous decisions, and the intensity with which the Court avoids 4–4 decisions. The intensity with which the Court avoids 4–4 splits and the strength of the drive to produce unanimous decisions seem sensitive to national disunity. At times of greater disunity, 1965 to 1975 and 2001 to 2020, the Court avoids 4–4 splits more intensely and has a greater fraction of …

Early Detection Of Sars-Cov-2 Variants Through Dynamic Co-Mutation Network Surveillance, Paul W. Bible, Qiang Huang, Huining Qiu, Yong Huang, Fangfang Zheng, Jing Gu, Jian Sun, Yuantao Hao, Yu Liu

Computer Science Faculty publications

Background: Precise public health and clinical interventions for the COVID-19 pandemic has spurred a global rush on SARS-CoV-2 variant tracking, but current approaches to variant tracking are challenged by the flood of viral genome sequences leading to a loss of timeliness, accuracy, and reliability. Here, we devised a new co-mutation network framework, aiming to tackle these difficulties in variant surveillance.

Methods: To avoid simultaneous input and modeling of the whole large-scale data, we dynamically investigate the nucleotide covarying pattern of weekly sequences. The community detection algorithm is applied to a co-occurring genomic alteration network constructed from mutation corpora of weekly …

School Library Advocacy: Enhancing Opportunities For All Learners, Elizabeth A. Burns

STEMPS Faculty Publications

There is a lack of consistency in how school librarians understand and engage in advocacy for their programs and the profession (Burns, 2015; Lance & Kachel, 2018). It is important that school librarians demonstrate the positive impact they contribute to improving instruction for student learners and advancing access so that all learners have equal opportunities. The school library and school librarian should be available to each student (Kachel, 2021). The School Library Manifesto (2021) includes language to support a strong school library with a qualified school librarian. Advocacy goals can be highlighted throughout this critical set of school library guidelines. …

How It Course Improves Digital Competencies: An Experimental Study In Science Education, Mustafa Tevfik Hebebci, Helen Crompton

STEMPS Faculty Publications

The rising significance of technology in society has caused a surge in the requirement of individuals possessing digital competencies. In the current era, digital skills are progressively vital for both personal and occupational growth. Governments have acknowledged the value of digital competencies and have incorporated them as part of fundamental proficiencies in numerous countries. Pre-service teachers have a paramount role in molding forthcoming generations, highlighting their necessity to possess robust digital competencies. This research centers on how an "Information Technologies in Science Education" course influences the digital competency progression in pre-service teachers. The study deployed a pre-test post-test experimental design …

Improving Reliability In Assessing Integrative Learning Using Rubrics: Does Group Norming Help?, Lanah Stafford, Erin Cousins, Linda Bol, Megan Mize

STEMPS Faculty Publications

Integrative learning is an important outcome for graduates of higher education. Therefore, it should be well-defined and assessed reliably. The American Association of Colleges & Universities has developed a rubric to define and assess integrative learning, but it has low reliability. This pilot study examines whether this rubric's reliability can be improved by training users on how to use the rubric in a group setting rather than individually. Twelve faculty were trained to score undergraduate ePortfolios using the Integrative and Applied Learning VALUE Rubric. Half of the faculty were trained in an individual setting and half in a group setting …

Dementia And Cognitive Impairment In French-Speaking Sub-Saharan Africa: A Comprehensive Review On Moving Out Of The Shadows Of Neglect, Cyrille D. Nkouonlack, Wepnyu Y. Njamnshi, Samuel A. Angwafor, Joseph N. Siewe Fodjo, Michel K. Mengnjo, Leonard Ngarka, Maggy Mbede, Leonard N. Nfor, Carlson Abomate, Gladys E. Maestre

School of Medicine Publications

Dementia is a global public health problem with increasing prevalence and incidence worldwide. The African continent is expected to bear the biggest brunt of the burden of dementia by 2050 because of the rapid demographic changes, including rapid population growth, an increase in life expectancy, and ageing. However, French-speaking Sub-Saharan African (FS-SSA) countries are underrepresented in research on dementia in Africa. While the reasons are diverse and complex, linguistic and cultural barriers to research, disproportionately affect these countries and may be significant factors. Any efforts, therefore, to redress the burden of dementia in Africa must consider the specific demographic, cultural, …

Maximizing Technology Acceptance Model In Accessing The Attitude Of Rural Farmers Using Ict Tools In Farming To Enhance Productivity, Francis Yao Anyan Dr., Michael Oppong Mr., Stephanie O. Ansah Mrs., Millicent Yengkangyi Ms., Akosua Boatemaa Adarkwa Mrs

Library Philosophy and Practice (e-journal)

The study was conducted using a multi-stage sampling technique involving simple random sampling, a probability sampling method, purposive sampling, and snowball sampling, which are non-probability methods. Two regions, namely, the Greater Accra and Eastern were purposively selected for the study. In the Greater Accra Region, Ada East District was selected while in the Eastern Region Asuogyaman District. In Greater Accra, the study was conducted in six farming villages namely: Big Ada, Dogo, Kasseh, Addokope, Korlekope, and Bedeku. In Eastern regions, the study was conducted in Asogyaman, where Tortibo, Sappor, Yenease, Adina Donor, and Ankyease. A snowball strategy was relied on …

Hardin-Wilkes Family Papers - Accession 221, Hardin Family, Wilkes Family

Manuscript Collection

The Hardin–Wilkes Family Papers consist of correspondence, financial records, ledgers, newspaper clippings, photographs, and printed materials documenting the Hardin and Wilkes families of Chester County, South Carolina. The collection spans from 1833 to 1973, with the bulk of the material dating from the mid-nineteenth through the early twentieth centuries. The papers provide insight into family life, local business activity, and regional history in and around Chester, South Carolina.

A significant portion of the collection consists of correspondence among members of the Hardin and Wilkes families. Of particular note are the letters of Captain Obadiah Hardin (1827–1862), an officer in Company …

Assessment Of The Imerg Early-Run Precipitation Estimates Over South American Country Of Chile, Luciana Das Dores De Jesus Da Silva, Mohammed Mahoud, Lisdelys González-Rodríguez, Safa Mohammed, Lien Rodríguez-López, Mauricio Ivan Aguayo Arias

Articles

Accurate rainfall measurement is a challenge, especially in regions with diverse climates and complex topography. Thus, knowledge of precipitation patterns requires observational networks with a very high spatial and temporal resolution, which is very difficult to construct in remote areas with complex geological features such as desert areas and mountains, particularly in countries with high topographical variability such as Chile. This study evaluated the performance of the near-real-time Integrated Multi-satellite Retrievals for GPM (IMERG) Early product throughout Chile, a country located in South America between 16°S–66°S latitude. The accuracy of the IMERG Early was assessed at different special and temporal …

A Lak Of Direction Misalignment Between The Goals Of Learning Analytics And Its Research Scholarship, Benjamin A. Motz, Yoav Bergner, Christopher A. Brooks, Anna Gladden, Geraldine Gray, Charles Lang, Warren Li, Fernando Marmolejo-Ramos, Joshua D. Quick

Articles

Learning analytics defines itself with a focus on data from learners and learning environments, with corresponding goals of understanding and optimizing student learning. In this regard, learning analytics research, ideally, should be characterized by studies that make use of data from learners engaged in education systems, should measure student learning, and should make efforts to intervene and improve these learning environments.

Pattern And Polarization Diversity Multisector Annular Antenna For Iot Applications, Abel Zandamela, Nicola Marchetti, Max Ammann, Adam Narbudowicz

Articles

This work proposes a small pattern and polarization diversity multisector annular antenna with electrical size and profile of ka = 1.2 and 0.018λ, respectively. The antenna is planar and comprises annular sectors that are fed using different ports to enable digital beamforming techniques, with efficiency and gain of up to 78% and 4.62 dBi, respectively. The cavity model analysis is used to describe the design concept and the antenna diversity. The proposed method can produce different polarization states (e.g., linearly and circularly polarized patterns) and pattern diversity characteristics covering the elevation plane. Owing to its small electrical size, low-profile and …

Applying Machine Learning To Assess The Morphology Of Sculpted Teeth, Fang-Yu Fan, Wei-Chun Lin, Huei-Yu Huang, Yung-Kang Shen, Yung-Chun Chang, Heng-Yu Li, Muhammad Ruslin, Sheng-Yang Lee

Journal of Dental Sciences

Abstract Background/purpose Producing tooth crowns through dental technology is a basic function of dentistry. The morphology of tooth crowns is the most important parameter for evaluating its acceptability. The procedures were divided into four steps: tooth collection, scanning skills, use of mathematical methods and software, and machine learning calculation. Materials and methods Dental plaster rods were prepared. The effective data collected were to classify 121 teeth (15th tooth position), 342 teeth (16th tooth position), 69 teeth (21st tooth position), and 89 teeth (43rd tooth position), for a total of 621 teeth. The procedures are divided into four steps: tooth collection, …

Nmr Study Of Co2 Capture By Butylamine And Oligopeptide Kdde In Aqueous Solution: Capture Efficiency And Gibbs Free Energy Of The Capture Reaction As A Function Of Ph**, Kaidi Yang, Joseph Schell, Fabio Gallazzi, Wei Wycoff, Rainer Glaser

Chemistry Faculty Research & Creative Works

We Have Been Interested in the Development of Rubisco-Based Biomimetic Systems for Reversible CO₂ Capture from Air. Our Design of the Chemical CO₂ Capture and Release (CCR) System is Informed by the Understanding of the Binding of the Activator CO₂ (^ACO₂) in Rubisco (Ribulose-1,5-Bisphosphate Carboxylase/oxygenase). the Active Site Consists of the Tetrapeptide Sequence Lys-Asp-Asp-Glu (Or KDDE) and the Lys Sidechain Amine is Responsible for the CO₂ Capture Reaction. We Are Studying the Structural Chemistry and the Thermodynamics of CO₂ Capture based on the Tetrapeptide CH₃CO−KDDE−NH₂ ("KDDE") in Aqueous …

Nanostructured Ternary Nickel-Based Mixed Anionic (Telluro)-Selenide As A Superior Catalyst For Oxygen Evolution Reaction, Ibrahim Munkaila Abdullahi, Siby Thomas, Alessio Gagliardi, Mohsen Asle Zaeem, Manashi Nath

Chemistry Faculty Research & Creative Works

Developing Protocols for Designing High-Efficiency, Durable, Cost-Effective Electrocatalysts for Oxygen Evolution Reaction (OER) Necessitates Deeper Understanding of Structure–property Correlation as a Function of Composition. Herein, It Has Been Demonstrated that Incorporating Tellurium into Binary Nickel Chalcogenide (NiSe) and Creating a Mixed Anionic Phase Perturbs its Electronic Structure and Significantly Enhances the OER Activity. a Series of Nanostructured Nickel Chalcogenides Comprising a Layer-By-Layer Morphology Along with Mixed Anionic Ternary Phase Are Grown in Situ on Nickel Foam with Varying Morphological Textures using Simple Hydrothermal Synthesis Route. Comprehensive X-Ray Diffraction, X-Ray Photoelectron Spectroscopy, and in Situ Raman Spectroscopy Analysis Confirms the Formation …

Epitaxial Electrodeposition Of Ordered Inorganic Materials, Jay A. Switzer, Avishek Banik

Chemistry Faculty Research & Creative Works

Conspectus The quality of technological materials generally improves as the crystallographic order is increased. This is particularly true in semiconductor materials, as evidenced by the huge impact that bulk single crystals of silicon have had on electronics. Another approach to producing highly ordered materials is the epitaxial growth of crystals on a single-crystal surface that determines their orientation. Epitaxy can be used to produce films and nanostructures of materials with a level of perfection that approaches that of single crystals. It may be used to produce materials that cannot be grown as large single crystals due to either economic or …

Insights To Surfactant Huff-Puff Design In Carbonate Reservoirs Based On Machine Learning Modeling, Ya Yao, Yue Qiu, Yue Cui, Mingzhen Wei, Baojun Bai

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Surfactants could react with adsorbates on carbonate rock surface to alter wettability from oil-wetness to water-wetness, which is effective to enhance oil recovery. Surfactant huff-puff treatment is mostly applied for this purpose and the resulting surfactant performance is the outcome of complex interfacial processes. Currently, the effect of important parameters on surfactant performance is not completely reported and the contribution of each parameter to surfactant performance is hard to be quantified. Traditional methods to optimize surfactant performance are time-consuming and show strong dependency on extensive experiments. in this paper, we address these problems from machine learning (ML) perspectives. Several ML …

Ongoing Fragmentation Of The Subducting Cocos Slab, Central America, Tu Xue, Diandian Peng, Kelly H. Liu, Jonathan Obrist-Farner, Marek Locmelis, Stephen S. Gao, Lijun Liu

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Fundamental to plate tectonics is the subduction of cold and mechanically strong oceanic plates. While the subducted plates are conventionally regarded to be impermeable to mantle flow and separate the mantle wedge and the sub slab region, isolated openings have been proposed. by combining new shear wave splitting measurements with results from geodynamic modeling and recent seismic tomography and geochemical observations, we show that the upper ~200 km of the Cocos slab in northern Central America is intensively fractured. the slab there is strong enough to produce typical arc volcanoes and Benioff Zone earthquakes but allows mantle flow to traverse …