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Articles 3691 - 3720 of 64979
Full-Text Articles in Entire DC Network
Educational Efficacy Of Private Well-Testing Workshops And The Surveillance Of Private Drinking Water Quality In Connecticut, Alec Janis, Michael Dietz, Meredith Metcalf
Educational Efficacy Of Private Well-Testing Workshops And The Surveillance Of Private Drinking Water Quality In Connecticut, Alec Janis, Michael Dietz, Meredith Metcalf
Journal of Human Sciences and Extension
More than 820,000 Connecticut residents rely on groundwater from private wells, yet minimal regulations address well water quality. Extension programs across the United States have begun to provide private drinking water education and testing assistance to address this public health gap. Few studies have analyzed the efficacy of these programs.
We delivered four workshops across Connecticut, from November 2022 to November 2023, where participants were given an educational presentation on private drinking water and an opportunity to test their well-water quality at a subsidized cost. After participating in the workshops, participants believed they were more confident to begin annual testing, …
Enhancing Fishnet For Wireless Network Simulation, Cameron J. Mcclure-Coleman
Enhancing Fishnet For Wireless Network Simulation, Cameron J. Mcclure-Coleman
Computer Science and Software Engineering
This report documents the senior project focused on enhancing the Fishnet network simulation library used in Cal Poly’s CPE 464 (Introduction to Computer Networks) course. The primary goal was to implement features for simulating wireless networks and introducing discrete-event simulation (DES) capabilities to increase computational efficiency. These enhancements aim to better support the curriculum transition as Cal Poly switches from quarters to semesters. The project successfully established foundational components for wireless network simulation, including node positioning in three-dimensional space, signal propagation modeling, multiple interface nodes, and wireless collision domains. While the complete implementation of discrete-event simulation and YAML configuration features …
Pm2.5 Forecasting At U.S. Embassies And Consulates Worldwide Using Nasa Model Powered By Machine Learning, Junhyeon Seo, Alqamah Sayeed, Seohui Park, John Kerekes, Stephanie Christel, Mary Tran, Pawan Gupta
Pm2.5 Forecasting At U.S. Embassies And Consulates Worldwide Using Nasa Model Powered By Machine Learning, Junhyeon Seo, Alqamah Sayeed, Seohui Park, John Kerekes, Stephanie Christel, Mary Tran, Pawan Gupta
Articles
Air quality forecasting is crucial for public health, especially in rural, suburban, and developing areas lacking reliable monitoring data. Hybrid monitoring (surface, satellite, and models) offers a scalable, cost‐ effective solution for tracking pollution and trends. This work presents a machine learning model that integrates ground measurements with global model outputs assimilating satellite observations to forecast air quality. Ground measurements of fine particulate matter (PM2.5) from over 60 U.S. embassies and consulates were used to calibrate global model outputs for local air quality forecasting. Multi‐channel input data was prepared using the Goddard Earth Observing System forward processing for meteorology and …
Toward Integrated Urban Observatories: Synthesizing Remote And Social Sensing In Urban Science, Danlin Yu
Toward Integrated Urban Observatories: Synthesizing Remote And Social Sensing In Urban Science, Danlin Yu
Department of Earth and Environmental Studies Faculty Scholarship and Creative Works
Urbanization is reshaping landscapes and posing unprecedented sustainability challenges, necessitating more integrative approaches to urban observation. This review synthesizes recent advancements in traditional remote sensing and emerging social sensing technologies, emphasizing their convergence within urban science. A systematic thematic analysis of 667 peer-reviewed articles highlights the methodological progress, practical applications, and theoretical innovations arising from this integration. Traditional remote sensing effectively captures urban physical features but lacks insights into human behaviors. Conversely, social sensing, leveraging digital traces from social media and mobile data, introduces essential human-centered dimensions into urban monitoring. The fusion of these complementary paradigms through advanced data analytics …
2025 June - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University
2025 June - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University
Tennessee Climate Office Monthly Reports
Hi All,
The main story of June 2025 was the first major heat wave of the year that sent temperatures into the mid-to-upper 90’s and heat index values over 100°F for most locations in the state from June 22nd to 28th. This included the first day of the year with a high over 90°F for many parts of the state. The National Weather Service offices covering Tennessee issued heat advisories for most counties in the state for at least 1 day during this period and several areas of West and Middle Tennessee had multiple days in a row with these …
Forging The Future, Kenneth Benoit
Forging The Future, Kenneth Benoit
Asian Management Insights
How AI is rewriting the rules of knowledge, expertise, and practice.
"Maine Office Of Behavioral Health’S Section 17 Self-Direction Pilot Program: Executive Summary", Rachel M. Gallo Mph, Sarah Goan, Emma Schwartz
"Maine Office Of Behavioral Health’S Section 17 Self-Direction Pilot Program: Executive Summary", Rachel M. Gallo Mph, Sarah Goan, Emma Schwartz
Publications
The Self-Directed Care (SDC) pilot program in Maine tested a service delivery model that allows individuals with mental health needs to manage a personal budget, supported by a trained broker to purchase goods and services that best support their recovery goals. Funded through the American Rescue Plan Act, the Maine Office of Behavioral Health implemented the nine-month pilot in three counties, partnering with Alpha One, Maine’s Center for Independent Living, to provide reloadable debit cards for participant purchases. The program aimed to promote autonomy, satisfaction, and stability among adults receiving Section 17 Medicaid services while informing decisions about the model’s …
"Maine Office Of Behavioral Health’S Section 17 Self-Direction Pilot Program: Evaluation Report", Rachel M. Gallo Mph, Sarah Goan, Emma Schwartz, Aaron Rose
"Maine Office Of Behavioral Health’S Section 17 Self-Direction Pilot Program: Evaluation Report", Rachel M. Gallo Mph, Sarah Goan, Emma Schwartz, Aaron Rose
Publications
Maine’s Office of Behavioral Health conducted a nine-month pilot of Self-Directed Care to support adults with serious mental illness in Cumberland, Hancock, and Washington Counties. The program allowed eligible participants receiving MaineCare Section 17 services to manage a personal budget, guided by trained Support Brokers from Alpha One, to purchase goods and services that would advance their recovery goals. The pilot aimed to increase participant choice, autonomy, and flexibility in managing their mental health needs. Support Brokers worked closely with participants and Case Managers to develop and approve individualized purchase plans, monitor expenditures, and ensure alignment with treatment objectives. A …
Babies, Babes, And Bayes: Modeling Mother-Infant Feedings With Bayesian Multilevel Hidden Markov Models, Zachary G. Felix
Babies, Babes, And Bayes: Modeling Mother-Infant Feedings With Bayesian Multilevel Hidden Markov Models, Zachary G. Felix
Master's Theses
Understanding the interaction between mother and baby during feeding is critical for the long-term development health of the baby. Overfeeding can lead to later obesity, while underfeeding can lead to malnutrition. In a recent study, the behaviors exhibited by mother-infant dyads across multiple ages of infants have been observed and coded according to the Baby Behaviors when Satiated (BABES) coding scheme. However, creating models using the data obtained from this coding is no simple task since the data coding is continuous, multivariate, and longitudinal in nature. The specific model utilized for these data is a hidden Markov model, since there …
The Influence Of Black Soldier Fly Residue On Watermelon Growth And The Properties Of A Coarse-Textured Ultisol, Benedict Onyebuchi Unagwu, Chidiebere Fransica Odu, Chinedu Felix Amuji, Michael Onyedika Eze, Nancy Ekene Ebido, Chidike Ude Abara, Chioma Rosita Igboka, Uchechukwu Paschal Chukwudi
The Influence Of Black Soldier Fly Residue On Watermelon Growth And The Properties Of A Coarse-Textured Ultisol, Benedict Onyebuchi Unagwu, Chidiebere Fransica Odu, Chinedu Felix Amuji, Michael Onyedika Eze, Nancy Ekene Ebido, Chidike Ude Abara, Chioma Rosita Igboka, Uchechukwu Paschal Chukwudi
Chemistry Faculty Research & Creative Works
Improving the fertility status of nutrient-depleted soils is critical to achieving food security. The negative effects of chemical fertilizers on soils necessitate the global quest for eco-friendly, effective, and sustainable alternatives. This work assessed the effect of black soldier fly (BSF) residue application on soil properties and watermelon growth. The study was set up in a completely randomized design with six replications. The treatments were BSF1 (BSF applied at 10 t ha−1), BSF2 (20 t ha−1), BSF3 (30 t ha−1), and control. The plant data collected in this study were vine length, leaf width, …
Designing A Model To Empower Rural Communities For Self-Sufficiency In Zanjan Province, Iran, Azra Ganjkhanloo, Alireza Poursaeed, Roya Eshraghi Samani, Marjan Vahedi
Designing A Model To Empower Rural Communities For Self-Sufficiency In Zanjan Province, Iran, Azra Ganjkhanloo, Alireza Poursaeed, Roya Eshraghi Samani, Marjan Vahedi
The Philippine Agricultural Scientist
In this research, empowerment is conceptualized as the process through which rural villagers organize themselves to enhance their self-sufficiency, assert their right to independent decision-making, gain control over resources, and address and overcome poverty. This study aimed to develop an empowerment model for rural communities in Zanjan Province, Iran, focusing on achieving self-sufficiency and assessing the model using structural equation modeling. The study compared the main components of the model using the post-event technique and validated the variables of self-sufficiency in rural communities through a descriptive-correlational design and structural equation modeling. The sample comprised 384 villagers selected via stratified random …
Unveiling The Vital Role Of Blue Carbon In Mangroves: Understanding Environmental Influences, Jahnelle Howe
Unveiling The Vital Role Of Blue Carbon In Mangroves: Understanding Environmental Influences, Jahnelle Howe
Dissertations, Theses, and Capstone Projects
Mangrove ecosystems provide essential ecological services, including carbon sequestration, coastal protection, and heavy metal retention. However, their resilience and functionality are increasingly influenced by hurricanes, climate variability, and anthropogenic contamination. This dissertation integrates three research efforts examining mangrove canopy dynamics, carbon storage, and heavy metal contamination in two Puerto Rican mangrove systems: La Parguera and Laguna Grande.
Using remote sensing techniques (LiDAR and NDVI analysis), we assessed the impact of Hurricane Maria (Category 4, 2017) on mangrove canopy structure and vegetation health. Results revealed significant canopy height loss, with greater damage at Laguna Grande, where pre-storm canopy height and human …
Unpacking The Orders, Leonard J. Santos
Unpacking The Orders, Leonard J. Santos
Dissertations, Theses, and Capstone Projects
At the end of the first week of his presidency this year in 2025, Donald Trump signed a total of thirty-six executive orders. After only one month, that number had gone up to seventy-six. He is currently on track to sign the highest number of executive orders in his first year in office of any president in the last 50 years, and potentially even the last 100 years if he keeps moving at this rate. In the first 90 days of his term, Donald Trump has signed 159 executive orders, more than any other president in the history of the …
Sla Evaluation And Composition In Reconfigurable Cloud-Based Services, Michael Iannelli
Sla Evaluation And Composition In Reconfigurable Cloud-Based Services, Michael Iannelli
Dissertations, Theses, and Capstone Projects
Given the business model of offering data and computing services in a cloud setting, a major question arises: How do the services of one cloud provider compare to those of others? With the ubiquitous use of smartphones and tablets, the ability of a cloud provider to support QoS and client mobility becomes paramount. This research proposes a methodology for evaluating service-level agreements (SLAs) between cloud providers and their consumers, with a particular focus on dynamic SLA composition to adapt to changes in the application requirements and the external environment—such as traffic surges, security threats, or evolving business models.
In one …
Tailoring Evaluations Of Chronic Rhinosinusitis: Understanding Sleep And Its Effect On Memory Through Actigraphy, Donyea Moore, Rachel Nolte, Yitong Pepper Huang, Shreya Maharana, Pavan Nataraj, Bichun Ouyang, Mahboobeh Mahdavinia
Tailoring Evaluations Of Chronic Rhinosinusitis: Understanding Sleep And Its Effect On Memory Through Actigraphy, Donyea Moore, Rachel Nolte, Yitong Pepper Huang, Shreya Maharana, Pavan Nataraj, Bichun Ouyang, Mahboobeh Mahdavinia
Mathematics Sciences: Faculty Publications
Background/Objectives: Chronic rhinosinusitis (CRS) is a persistent inflammatory condition of the sinonasal mucosa lasting for at least three months. For patients, CRS-related sleep disturbances can significantly disrupt circadian rhythms, leading to further health complications such as cognitive impairment. Despite the well-documented sleep disturbances associated with CRS, there is limited research on objective assessment methods. Additionally, the severity of these issues can vary among patients. This study aims to assess sleep quality and timing in CRS patients and investigate their impact on cognition, providing guidance for personalized and tailored assessment and management of CRS. Methods: Our case–control study compares sleep patterns …
Computerized Diagnostic Decision Support Systems-Isabel Pro Versus Chatgpt-4 Part Ii, Joe M Bridges, Xiaoqian Jiang, Michael Ige, Oluwatoniloba Toyobo
Computerized Diagnostic Decision Support Systems-Isabel Pro Versus Chatgpt-4 Part Ii, Joe M Bridges, Xiaoqian Jiang, Michael Ige, Oluwatoniloba Toyobo
Faculty, Staff and Student Publications
Objective: Does a Tree-of-Thought prompt and reconsideration of Isabel Pro's differential improve ChatGPT-4's accuracy; does increasing expert panel size improve ChatGPT-4's accuracy; does ChatGPT-4 produce consistent outputs in sequential requests; what is the frequency of fabricated references?
Materials and methods: Isabel Pro, a computerized diagnostic decision support system, and ChatGPT-4, a large language model. Using 201 cases from the New England Journal of Medicine, each system produced a differential diagnosis ranked by likelihood. Statistics were Mean Reciprocal Rank, Recall at Rank, Average Rank, Number of Correct Diagnoses, and Rank Improvement. For reproducibility, the study compared the initial expert panel run …
Arkansas Corn And Grain Sorghum Research Studies 2024, Jason Kelley, Travis Faske
Arkansas Corn And Grain Sorghum Research Studies 2024, Jason Kelley, Travis Faske
Arkansas Agricultural Experiment Station Research Series
The 2024 edition of the Arkansas Corn and Grain Sorghum Research Studies Series includes research results on topics pertaining to corn and grain sorghum production, including weed, disease, nematode, and insect management; economics; irrigation; agronomics; soil fertility; drone use; and research verification program results.
Our objective is to capture and broadly distribute the results of research projects funded by the Arkansas Corn and Grain Sorghum Board. The intended audience includes producers and their advisors, current investigators, and future researchers. The Series serves as a citable archive of research results.
The reports inform and guide our long-term recommendations, but should not …
Graduate School Blog - June 2025, Cynthia Haynes
Graduate School Blog - June 2025, Cynthia Haynes
UofM Grad School Blog
The June 2025 edition of the UofM Graduate School Blog helps prospective and current students make informed financial decisions with Part 1 of the Graduate School Cost Guide, breaking down tuition structures such as per-credit hour versus flat-rate models, highlighting UofM’s tuition cap for in-state students, and explaining key university fees and cost differences between online and on-campus formats. The blog also features Brianna Reilly, a Doctor of Musical Arts graduate from New York, who shares how a graduate assistantship and her passion for music education led her to continue at UofM through the pandemic. Additional resources include an …
Revised Draft Final Bpsou Unreclaimed Sites: Ur-05 Remedial Action Work Plan (Rawp), Pioneer Technical Services, Inc.
Revised Draft Final Bpsou Unreclaimed Sites: Ur-05 Remedial Action Work Plan (Rawp), Pioneer Technical Services, Inc.
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Topodino: Self-Supervised Topological Representation Learning For Neuronal Morphologies, Yasser Binbisher
Topodino: Self-Supervised Topological Representation Learning For Neuronal Morphologies, Yasser Binbisher
Master's Theses
Neuronal cell types are categorized by transcriptomic identity, yet their morphological heterogeneity defies this classification. In response, researchers have adopted unsupervised graph representation learning as a tool to reveal morphological variation within single-class transcriptomic types. However, the complex geometry of neuronal morphology—especially long axons and dense dendrites—challenges graph neural networks, which struggle with message propagation across extended structures. To mitigate this, current approaches enforce sub-sampling on neuronal graphs and omit axons entirely, sacrificing critical biological features for computational efficiency. To overcome this trade-off, this thesis introduces TopoDINO, a self-supervised, topology-aware representation learning model designed to preserve the full hierarchical organization …
State And Transition Models For Mulga Rangelands Of Western Australia, Alison O'Donnell, Anna E. Richards, Suzanne Prober, Peter-Jon A. Waddell, Sarah Luxton, Ian Watson, Brett Abbott, Philip Thomas, Joshua E. Foster
State And Transition Models For Mulga Rangelands Of Western Australia, Alison O'Donnell, Anna E. Richards, Suzanne Prober, Peter-Jon A. Waddell, Sarah Luxton, Ian Watson, Brett Abbott, Philip Thomas, Joshua E. Foster
Natural resources published reports
This report details a collaborative project between the Western Australian Department of Primary Industries and Regional Development and CSIRO that focused on developing State and Transition Models (STMs) for mulga rangelands in Western Australia. The overarching aim of the project was to improve the common understanding of the characteristics and dynamics of mulga rangeland ecosystems and the expected impacts of management. Specifically, the project aimed to collate expert knowledge and monitoring information using a nationally consistent framework to develop quantitative and dynamic STMs. The geographic scope of the project covers the extensive mulga rangelands of Western Australia, particularly the Gascoyne …
Glacial Lakes Segmentation Using Multispectral Remote Sensing Data And Deep Learning Models, Debankan Das
Glacial Lakes Segmentation Using Multispectral Remote Sensing Data And Deep Learning Models, Debankan Das
Master’s Dissertations
The identification and delineation of glacial lakes through segmentation is crucial for tracking glacial changes and evaluating potential dangers from sudden flood events (GLOFs). These floods can severely impact populated areas and man-made structures downstream. Recent advances in high-quality satellite imagery have sparked increased attention toward using advanced machine learning methods, particularly deep learning, to enable precise and automated glacial lake detection. In this study, we explore the effectiveness of deep learning-based pointwise semantic segmentation for glacial lake mapping using multisource remote sensing imagery, including both optical and synthetic aperture radar (SAR) data. We experiment with a novel stack combination …
Long-Range Transport Of Canadian Wildfire Smoke: Public Health And Earth System Impacts, Erica L. Simon
Long-Range Transport Of Canadian Wildfire Smoke: Public Health And Earth System Impacts, Erica L. Simon
Environmental Studies Senior Theses
In the summer of 2023, Canada experienced an unprecedented wildfire season with total burned area reaching 15 million hectares, doubling the previous record. Notably, smoke plumes from Eastern Canada were transported to the Northeast United States, resulting in record-breaking measures of poor air quality in early June 2023. This thesis employs a multi-method analysis to understand the June 2023 Quebec wildfires, focusing on atmospheric science, public health effects in New York City, and albedo changes on the Greenland ice sheet. Through this analysis, I find record-high monthly mean aerosol optical depth values in June 2023 in three regions– the Northeast …
Catalyzed Chemical Recycling Of Poly(Ethylene Terephthalate) For Enhanced Sustainability, Gilberto J. Hernandez-Leypon Jr.
Catalyzed Chemical Recycling Of Poly(Ethylene Terephthalate) For Enhanced Sustainability, Gilberto J. Hernandez-Leypon Jr.
Master's Theses
Plastics are ubiquitous in the production of consumer and industrial products; their chemical stability, low cost of production, and performance versatility make them the best option for many industries. Their inherent benefits, specifically durability, is the basis for the negative environmental impact of polymers. Improper containment of endof-life polymer products causes unintentional migration into the environment. The monomers for many common polymer types are also fossil fuel based further increasing the environmental impact of the plastic lifecycle. Recycling is a possible method of closing the loop of the plastic lifecycle. Currently most recycling is physical, thermally reprocessing used plastics into …
Advancing Fake News Detection With Graph Neural Network And Deep Learning, Haji Gul, Feras Al-Obeidat, Muhammad Wasim, Adnan Amin, Fernando Moreira
Advancing Fake News Detection With Graph Neural Network And Deep Learning, Haji Gul, Feras Al-Obeidat, Muhammad Wasim, Adnan Amin, Fernando Moreira
All Works
In the modern era of digital technology, the rapid distribution of news via social media platforms substantially contributes to the propagation of false information, presenting challenges in upholding the accuracy and reliability of information. This study presents an updated approach that utilizes graph neural networks (GNNs) alongside with advanced deep learning techniques to improve the identification of false information. In contrast to traditional approaches that primarily rely on analyzing text and assessing the credibility of sources, our methodology utilizes the structural information of news propagation networks. This allows for a detailed comprehension of the interconnections and patterns that are indicative …
A Novel Fractional Order Model For Analyzing Counterterrorism Operations And Mitigating Extremism, Mutaz Mohammad, Isa Abdullahi Baba, Evren Hincal, Fathalla A. Rihan
A Novel Fractional Order Model For Analyzing Counterterrorism Operations And Mitigating Extremism, Mutaz Mohammad, Isa Abdullahi Baba, Evren Hincal, Fathalla A. Rihan
All Works
This study examines the profound impact of terrorism on individuals and society by developing a fractional-order mathematical model to analyze and enhance counterterrorism efforts. The model accounts for the persistent and complex nature of extremist behavior, particularly emphasizing the importance of preventing violent extremism before it escalates into terrorism. Real-world data on terrorist activities in Nigeria – specifically from the Boko Haram insurgency – was used to calibrate and validate the model, ensuring its relevance and accuracy. The model reveals that the basic reproduction number (R0) plays a decisive role in determining the long-term success of counterterrorism strategies. Numerical simulations …
Transforming The Future Of Health: Building Learning Health Systems Across The Globe, Sandra Yankah, Robert Saunders, Mark L. Tykocinski, Claudia Salzberg, Jonathan Gonzalez-Smith, Rachel Bonesteel, Cameron Joyce, Charles Kahn, Mark Mcclellan, Eyal Zimlichman
Transforming The Future Of Health: Building Learning Health Systems Across The Globe, Sandra Yankah, Robert Saunders, Mark L. Tykocinski, Claudia Salzberg, Jonathan Gonzalez-Smith, Rachel Bonesteel, Cameron Joyce, Charles Kahn, Mark Mcclellan, Eyal Zimlichman
Department of Pathology, Anatomy, and Cell Biology Faculty Papers
Health care has faced disruptions over the past 5 years, including a global pandemic, supply chain interruptions, workforce shifts, and the introduction of new artificial intelligence (AI) tools. Health care organizations continue to leverage the learning health system (LHS) concept to adapt to these challenges through iterative feedback loops. The Future of Health (FOH), an international community of over 50 senior health leaders that focuses on shared challenges across international health systems, collaborated with the Duke-Margolis Institute for Health Policy in a consensus-building process with FOH members to identify opportunities for action in an LHS. Key areas for action identified …
Final Silver Bow Creek Conservation Area (Sbcca) Butte Reduction Works (Brw) Air Monitoring For Interim Demolition Activities – Phase I Data Summary Report (Dsr), Pioneer Technical Services, Inc.
Final Silver Bow Creek Conservation Area (Sbcca) Butte Reduction Works (Brw) Air Monitoring For Interim Demolition Activities – Phase I Data Summary Report (Dsr), Pioneer Technical Services, Inc.
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Ideal Query Expansion Using Reinforcement Learning, Madhuchchhanda Das
Ideal Query Expansion Using Reinforcement Learning, Madhuchchhanda Das
Master’s Dissertations
Information retrieval (IR) systems often struggle with short, ambiguous, or underspecified queries, leading to suboptimal document retrieval. Traditional query reformulation methods, such as those based on the Rocchio algorithm, rely on heuristic term selection and relevance feedback but typically apply fixed or manually tuned weights to expanded terms. This limits their adaptability and generalization across diverse query-document contexts. In this thesis, we propose a novel reinforcement learning (RL)-based framework to dynamically optimize term weighting in reformulated queries. We model the problem as a Markov Decision Process (MDP), where each state represents a query as a vector of term weights. An …
Cutting Through The Infodemic Efficiently: News Claims Surveillance And Llm-Based Lightweight Fact Verification, Xuan Zhang
Dissertations and Theses Collection (Open Access)
In the context of the current infodemic, the rapid spread of misinformation poses a severe threat to social stability and public health. Recently, the rise of deep learning technologies has offered the potential for accelerating the development of automated misinformation detection and verification. However, current technological capabilities and computational resources often prove inadequate for the exhaustive scrutiny required, rendering the enhancement of processing efficiency a critical imperative. Given the vast amount of data on the internet, current technology and computational power often fall short in timely and accurate scrutiny of each piece of information, making the improvement of processing efficiency …