Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- University of Nebraska - Lincoln (25791)
- Western Michigan University (20684)
- University of Kentucky (14838)
- TÜBİTAK (10730)
- Singapore Management University (9399)
-
- Utah State University (7957)
- Old Dominion University (7361)
- Missouri University of Science and Technology (7311)
- Portland State University (4206)
- University of South Florida (4144)
- Wright State University (3961)
- University of Nevada, Las Vegas (3930)
- China Simulation Federation (3924)
- City University of New York (CUNY) (3756)
- Louisiana State University (3676)
- Brigham Young University (3436)
- University of Texas Rio Grande Valley (3168)
- University of Arkansas, Fayetteville (3137)
- Chulalongkorn University (3121)
- Air Force Institute of Technology (3078)
- Department of Primary Industries and Regional Development, Western Australia (2929)
- Purdue University (2869)
- Claremont Colleges (2865)
- California Polytechnic State University, San Luis Obispo (2725)
- University of Texas at El Paso (2636)
- Montana Tech Library (2422)
- University of South Carolina (2411)
- Chinese Chemical Society | Xiamen University (2395)
- Technological University Dublin (2383)
- Wayne State University (2316)
- Keyword
-
- Machine learning (2208)
- Western Australia (1955)
- Climate change (1686)
- Mathematics (1412)
- Deep learning (1191)
-
- Sustainability (1184)
- Chemistry (1131)
- Artificial intelligence (1117)
- Machine Learning (1100)
- Physics (1035)
- Groundwater (979)
- Geology (975)
- Water quality (905)
- Computer Science (827)
- United States (810)
- Simulation (789)
- Nebraska (774)
- Education (743)
- Remote sensing (719)
- Climate (705)
- Agriculture (704)
- Grains and field crops (698)
- Water (698)
- Security (688)
- Statistics (688)
- Optimization (667)
- Conservation (648)
- Environment (626)
- Humans (602)
- Algorithms (585)
- Publication Year
-
- 2026 (9036)
- 2025 (12189)
- 2024 (14121)
- 2023 (14122)
- 2022 (18217)
-
- 2021 (27756)
- 2020 (14806)
- 2019 (13032)
- 2018 (11790)
- 2017 (11102)
- 2016 (10866)
- 2015 (9578)
- 2014 (9800)
- 2013 (8927)
- 2012 (8515)
- 2011 (7769)
- 2010 (6945)
- 2009 (6353)
- 2008 (5871)
- 2007 (5729)
- 2006 (4906)
- 2005 (4759)
- 2004 (3873)
- 2003 (3370)
- 2002 (3128)
- 2001 (2764)
- 2000 (2647)
- 1999 (2348)
- 1998 (2338)
- 1997 (2184)
- Publication
-
- Legacy Scout Tickets from Pure Oil Company (11044)
- IGC Proceedings (1977-2023) (9261)
- Theses and Dissertations (8799)
- Research Collection School Of Computing and Information Systems (8556)
- Thin Sections (6677)
-
- Faculty Publications (4090)
- Journal of System Simulation (3924)
- Electronic Theses and Dissertations (3529)
- Nebraska Tractor Tests (3402)
- Turkish Journal of Electrical Engineering and Computer Sciences (3106)
- Turkish Journal of Chemistry (2730)
- Turkish Journal of Mathematics (2595)
- Journal of Electrochemistry (2395)
- Physics Faculty Publications (2178)
- Masters Theses (2077)
- Dissertations (2036)
- Physics Faculty Research & Creative Works (1959)
- Silver Bow Creek/Butte Area Superfund Site (1896)
- Chulalongkorn University Theses and Dissertations (Chula ETD) (1876)
- USF Tampa Graduate Theses and Dissertations (1834)
- Coal Geology & Exploration (1822)
- School of Natural Resources: Faculty Publications (1735)
- Department of Computer Science Technical Reports (1721)
- United States Department of Agriculture Wildlife Services: Staff Publications (1625)
- All Graduate Theses and Dissertations, Spring 1920 to Summer 2023 (1434)
- Publications and Research (1413)
- LSU Doctoral Dissertations (1402)
- Publications (1383)
- Turkish Journal of Physics (1382)
- Open Access Theses & Dissertations (1380)
- Publication Type
Articles 2731 - 2760 of 294649
Full-Text Articles in Entire DC Network
Alcohol-Based Microextraction Of Rhodamine 6g From Soft Drink, Food, And Cosmetic Samples, Mustafa Soylak, Esra Yamaner, Özgür Özalp
Alcohol-Based Microextraction Of Rhodamine 6g From Soft Drink, Food, And Cosmetic Samples, Mustafa Soylak, Esra Yamaner, Özgür Özalp
Turkish Journal of Chemistry
By using alcohol-based solvent extraction without tetrahydrofuran, a liquid–liquid microextraction technique was developed for the separation–enrichment of trace levels of Rhodamine 6G from complex matrices, including soft drinks, food, cosmetics, hygiene products, and natural waters. Numerous experimental parameters were tuned, including pH, alcohol volume, ultrasonication time, and sample and eluent volume. The enrichment factor (EF), limit of detection (LOD), and limit of quantification (LOQ) were used to assess the analytical performance of the suggested approach. The LOD and LOQ were 6.92 ng mL−1 and 23 ng mL−1, respectively, and the EF was 14. Through the use of the standard addition …
A Nonenzymatic Electrochemical Glucose Sensor Depending On A Ninps/Co3o4/Functionalized Graphene Oxide-Modified Working Electrode, Sümeyra Pekmez, Muhammet Güler
A Nonenzymatic Electrochemical Glucose Sensor Depending On A Ninps/Co3o4/Functionalized Graphene Oxide-Modified Working Electrode, Sümeyra Pekmez, Muhammet Güler
Turkish Journal of Chemistry
In the present research, the aim was to develop a novel electrochemical enzyme-free glucose sensor dependent upon a nickel nanoparticles (NiNPs)/cobalt (II, III) oxide (Co3O4)/carboxylated graphene oxide (GO-COOH)-modified glassy carbon (GC) electrode. The electrocatalytic performance of the electrode was tested using various electrochemical methods such as amperometry and cyclic voltammetry (CV). The NiNPs@Co3O4/GO-COOH/GC electrode showed noticeably superior electrocatalytic behavior for glucose oxidation in 0.1 M NaOH media, ascribed to the good synergistic impact between NiNPs, Co3O4, and GO-COOH. The amperometric response of the NiNPs@Co3O4/GO-COOH/GC electrode to glucose exhibited two linear determination ranges at +0.55 V potential. The first one was …
Synthesis Of Two Hofmann-Type-Like Clathrates, Characterizations, And Investigation Of Their Structures, Spectroscopic And Theoretical Properties, Zari̇fe Si̇bel Şahi̇n, Zeki̇ Kartal
Synthesis Of Two Hofmann-Type-Like Clathrates, Characterizations, And Investigation Of Their Structures, Spectroscopic And Theoretical Properties, Zari̇fe Si̇bel Şahi̇n, Zeki̇ Kartal
Turkish Journal of Chemistry
This study concerns two Hofmann-type-like clathrates using 4-aminopyridine (4AP) as ligands and the transition metal atoms copper (Cu) and zinc (Zn). These clathrates have the structural features of heteronuclear tetracyanonickelate(II) and contain H2O and 4AP molecules as guest molecules, respectively. These two clathrates were characterized by infrared spectroscopy (IR), elemental analysis, and single crystal X-ray diffraction (SC-XRD) techniques. Based on elemental and spectral data, the structural formulae describing these clathrates were found to be [Cu(II)(4AP)4Ni(μ-CN)2(CN)2]·H2O (1) and [Zn(II)(4AP)4Ni(μ-CN)2(CN)2]·(4AP) (2). In addition, the values of some optical, electronic, and thermochemical properties of the two obtained clathrates calculated with the Gaussian 03 …
2026 June 18 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University
2026 June 18 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University
Tennessee Climate Office Weekly Drought Summaries
No abstract provided.
Efficient Multimodal Foundation Model Tuning For Hallucination Mitigation, Fei Zhao
Efficient Multimodal Foundation Model Tuning For Hallucination Mitigation, Fei Zhao
ETDs from 2020-2029
Over the past few years, multimodal foundation models have achieved remarkable progress in perception and understanding. However, two challenges limit their reliability: (1) dependence on offline training, which in most real-world settings requires large volumes of labeled data and, as a result, hinders the model’s ability to adapt to new data or domains; (2) weak cross-modal grounding, which often leads to hallucinated content generation, producing descriptions that are linguistically fluent but inconsistent with the input visual evidence. This dissertation frames hallucination mitigation as an outcome of transitioning from fixed learning (static, offline fine-tuning) to adaptive, feedback-driven lifelong learning. By incorporating …
Learnable Structured Attention For Student-Aware Knowledge Distillation In Dense Prediction, Chen Liu
Learnable Structured Attention For Student-Aware Knowledge Distillation In Dense Prediction, Chen Liu
ETDs from 2020-2029
Dense prediction tasks, including object detection and semantic segmentation, require models to produce structured predictions and are widely used in real-world vision applications. Although deep networks have achieved strong performance on these tasks, their high computational cost limits deployment on resource-constrained systems such as autonomous-driving vehicles. Knowledge distillation (KD) addresses this issue by transferring knowledge from a large teacher model to a compact student model. However, existing distillation methods for dense prediction face greater challenges than those for classification due to the more complex task requirements. To overcome the challenges, this thesis presents a unified study of adaptive distillation for …
From Cork To Coasting: A Multi-Stage Ode Model Of Water-Rocket Flight, Viktoria Savatorova, Patryk Kustra, Ethan Dyer, Connor Carlson, Aleksei Talonov
From Cork To Coasting: A Multi-Stage Ode Model Of Water-Rocket Flight, Viktoria Savatorova, Patryk Kustra, Ethan Dyer, Connor Carlson, Aleksei Talonov
CODEE Journal
Water rockets provide an affordable and engaging context for exploring applications of differential equations. Motivated by outreach activities conducted with undergraduate students, we develop a four-stage mathematical model of vertical water-rocket flight that is suitable for use in an ODE or mathematical modeling course. The model includes the cork-release phase, water-thrust propulsion, air-thrust propulsion with compressible and potentially choked flow, and the final ballistic stage with quadratic drag. While retaining key physical features, the model can be formulated as a system of ordinary differential equations that can be integrated numerically using tools familiar to students. We compare model predictions with …
A Modular Saponin Adjuvant Platform: Development, Structure–Activity Relationships, And Applications, Di Bai
A Modular Saponin Adjuvant Platform: Development, Structure–Activity Relationships, And Applications, Di Bai
ETDs from 2020-2029
ABSTRACT Saponin-based vaccine adjuvants have attracted considerable attention owing to the clinical success of QS-21, a potent immunostimulant capable of inducing balanced humoral and cellular immune responses, yet its widespread application is limited by supply constraints, chemical instability, and dose-dependent toxicity. To address these challenges, we previously developed two semisynthetic saponin adjuvants, VSA-1 and VSA-2, derived from abundant Momordica saponins through a single-step modification, which exhibit QS-21–comparable immunopotentiating activity with improved accessibility and stability. Here, we first performed a systematic structure–activity relationship (SAR) study of the VSA series using MS I as the lead scaffold. Modulation of the side-chain length …
Investigation Of Air Emissions With A Local Composites Industry, Chris White
Investigation Of Air Emissions With A Local Composites Industry, Chris White
ETDs from 2020-2029
Workers at an office space raised complaints about a sweet-smelling odor directly outside their building. After an initial assessment of the surrounding businesses and their processes, it was determined that the workers were most likely exposed to styrene emissions from a nearby composites company. This investigation utilizes multiple weeks of direct readings with a photoionization device and active environmental sampling with a charcoal tube and pump to confirm the styrene exposure hypothesis. Weather trends were also recorded to determine correlation between weather and exposure to the sweet-smelling chemical. The direct readings found an exposure maximum of less than 2 ppm …
Statistical Methods For Mendelian Randomization Under Nonlinearity And Non-Normality, Mary Appah
Statistical Methods For Mendelian Randomization Under Nonlinearity And Non-Normality, Mary Appah
ETDs from 2020-2029
Instrumental variable (IV) methods are widely used for estimating causal effects in observational studies where unmeasured confounding may bias traditional regression estimates. The core idea is to use a variable referred to as an instrument that is associated with the exposure of interest, independent of unmeasured confounders, and influences the outcome only through the exposure. While originally developed in econometrics, IV methods have been increasingly adopted in epidemiology and genetic research under the framework of Mendelian Randomization (MR), where genetic variants, most commonly single nucleotide polymorphisms (SNPs), serve as instruments. MR provides a powerful tool for investigating causal relationships between …
Active Learning Of Constraint Boundaries Using Expected Magnitude Of Incorrectness And Neural Networks, Atticus Beachy, Ramana V. Grandhi
Active Learning Of Constraint Boundaries Using Expected Magnitude Of Incorrectness And Neural Networks, Atticus Beachy, Ramana V. Grandhi
Faculty Publications
This research proposes an acquisition function for constraint boundary identification, with applications to hypersonic air vehicles. Hypersonic vehicles endure extreme thermal loads caused by aerodynamic heating, resulting in a strong coupling between structural performance and aerothermodynamics. However, modeling coupled system behaviors requires simultaneous consideration of both aerodynamic and structural design variables, increasing the dimensionality of the design trade space and the difficulty of accurately modeling the constraints. Several active learning schemes have been proposed to accelerate identification of the composite feasible region that satisfies all constraints. Some of these require integrating the surrogate model over the entire design space with …
Physically Mixed Graphene Aerogel:Carbon Black (Ga:Cb)-Supported Pt Or Hydrothermally Synthesized Ga-Pt/Cb Hybrid Electrocatalysts For Pem Fuel Cells, Emi̇ne Teke Öner, Meli̇s Irmak Aydin, Merve Ni̇da Dursunoğlu, Ayşe Bayrakçeken
Physically Mixed Graphene Aerogel:Carbon Black (Ga:Cb)-Supported Pt Or Hydrothermally Synthesized Ga-Pt/Cb Hybrid Electrocatalysts For Pem Fuel Cells, Emi̇ne Teke Öner, Meli̇s Irmak Aydin, Merve Ni̇da Dursunoğlu, Ayşe Bayrakçeken
Turkish Journal of Chemistry
Graphene aerogels (GAs), having the superior properties of graphene and aerogel structures, are promising support materials for Pt nanoparticles to be used as electrocatalysts for PEM fuel cells. In this study, two routes were followed to synthesize GA-based electrocatalysts. In the first route, after GA synthesis it was physically mixed with carbon black (CB) by changing the mass ratios from 0% to 100% with 25% increments and then decorated with Pt nanoparticles via microwave irradiation, resulting in Pt/GA:CB electrocatalysts. In the second route, firstly, Pt/CB electrocatalyst was synthesized and then GA was hydrothermally added to the Pt/CB by changing the …
Amending Planting Media With Typha-Derived Biochar For Sustainable Horticulture, Elissa Touma
Amending Planting Media With Typha-Derived Biochar For Sustainable Horticulture, Elissa Touma
USF Tampa Graduate Theses and Dissertations
Constructed wetlands are widely used to improve water quality by removing excess nutrients from wastewater and stormwater. Nutrients are stored within wetland vegetation, particularly in fast-growing plants such as Typha. Harvesting vegetation provides an opportunity to permanently remove these nutrients while generating biomass suitable for beneficial reuse. Converting harvested biomass into value-added products such as compost and biochar can support nutrient recovery and sustainable biomass management. In addition, increasing concerns regarding the environmental impacts of peat extraction have created interest in renewable alternatives for horticultural growing media. Therefore, the objective of this study was to evaluate the potential of harvested …
Modeling And Mitigating Stale Hardcoded Secrets In Version Control History, Katarina Valentine Capalbo
Modeling And Mitigating Stale Hardcoded Secrets In Version Control History, Katarina Valentine Capalbo
USF Tampa Graduate Theses and Dissertations
Hardcoded secret vulnerabilities remain a growing and persistent problem that can be difficult to mitigate once exposed. While there has been significant research and advancements in identifying and preventing hardcoded secrets, less attention has been given to understanding the risks of leaving these secrets behind in version control history, as well as analyzing the sanitization of hardcoded secrets. These challenges present a growing gap between the risk and ability to mitigate and sanitize existing secret exposures. This thesis begins to address this gap by formalizing a threat model for hardcoded secrets that persist in Git version control history after the …
The Colorado River Water Supply Crisis In A Few Graphs: Part 1, Jack Schmidt, Anne Castle, Eric Kuhn, Kathryn Sorensen, Katherine Tara
The Colorado River Water Supply Crisis In A Few Graphs: Part 1, Jack Schmidt, Anne Castle, Eric Kuhn, Kathryn Sorensen, Katherine Tara
The Traveling Wilburys of the Colorado River
In 2026 and for only the third time in the 21st century, there was no accumulation, and no recovery, of total Basin live storage6 during the snowmelt season. Nor was there any accumulation or recovery of total live storage in Lake Powell and Lake Mead during the 2026 snowmelt season. Total Basin live storage (hereafter, total Basin storage) is all the water available in the Colorado River Basin’s reservoir “savings account” and stored in reservoirs within the watershed.7 On June 1, total Basin storage was 22.94 million acre feet (maf), only 1.62 maf above the previous minimum of March 20238 …
Gwtc-4.0: Methods For Identifying And Characterizing Gravitational-Wave Transients, A. G. Abac, I. Abouelfettouh, Teviet Creighton, Mario C. Diaz, Raul Alberto Espinosa Perez, J. Lawrence, Francisco Llamas Villarreal, Soma Mukherjee, Volker Quetschke, Wenhui Wang
Gwtc-4.0: Methods For Identifying And Characterizing Gravitational-Wave Transients, A. G. Abac, I. Abouelfettouh, Teviet Creighton, Mario C. Diaz, Raul Alberto Espinosa Perez, J. Lawrence, Francisco Llamas Villarreal, Soma Mukherjee, Volker Quetschke, Wenhui Wang
Physics & Astronomy Faculty Publications
The Gravitational-Wave Transient Catalog (GWTC) is a collection of candidate gravitational-wave transient signals identified and characterized by the LIGO–Virgo–KAGRA Collaboration. Producing the contents of the GWTC from detector data requires complex analysis methods. These comprise techniques to model the signal; identify the transients in the data; evaluate the quality of the data and mitigate possible instrumental issues; infer the parameters of each transient; compare the data with the waveform models for compact binary coalescences; and handle the large amount of results associated with all of these different analyses. In this paper, we describe the methods employed to produce the catalog’s …
Development Of An Adaptive Pelican Crossing Model Using Fuzzy Logic In Mixed Traffic Conditions, Manazil Adam, Andyka Kusuma, R. Jachrizal Sumabrata
Development Of An Adaptive Pelican Crossing Model Using Fuzzy Logic In Mixed Traffic Conditions, Manazil Adam, Andyka Kusuma, R. Jachrizal Sumabrata
Smart City
Traffic management at at-grade pedestrian crossing facilities (pelican crossings) in highly populated areas, such as the Universitas Indonesia Station, faces significant inefficiency challenges. During peak hours, the fixed-time system is frequently disabled and replaced with subjective manual control by security personnel, thereby triggering irregular stop-and-go cycles and a high accumulation of vehicle delays. This study aims to develop a hybrid adaptive control model integrating Computer Vision, Genetic Algorithm (GA), and Fuzzy Logic to optimize intersection performance under mixed traffic conditions. The research methodology begins with the extraction of traffic and pedestrian characteristic data, calculated manually through recorded field observations. This …
Spatial Tax Intelligence: Implementing Integrated Spatial Decision Support Systems For Smart Urban Governance, Wildan R. Irfana, Haldis A. Bahar, Muhammad H. Candra
Spatial Tax Intelligence: Implementing Integrated Spatial Decision Support Systems For Smart Urban Governance, Wildan R. Irfana, Haldis A. Bahar, Muhammad H. Candra
Smart City
The transition toward smart governance requires local governments to adopt data-driven policy approaches, particularly in managing urban tax capacity. However, tax administration in many developing regions remains predominantly tabular and administrative, limiting the ability to capture the spatial dynamics of economic activities. This reveals a critical knowledge gap, as integrated frameworks combining spatial and tax data to identify geographic disparities in tax performance remain limited. Consequently, areas with high economic activity but low tax compliance, referred to as tax blind spots, often remain undetected. This study aims to analyze the effectiveness of integrating spatial and tax data in identifying spatial-tax …
Kernelizing Protein Interaction Languages: Spectral Approximations And Random Fourier Features, Aishik Ghosh
Kernelizing Protein Interaction Languages: Spectral Approximations And Random Fourier Features, Aishik Ghosh
Master’s Dissertations
Protein-peptide interactions play an important role in many biological phenomena, spanning adaptive immunity to disease pathology. In the Sliding Window Interaction Grammar (SWING) framework, interactions are represented as sequences of biochemical tokens embedded using Doc2Vec, allowing robust generalisation to unobserved MHC alleles. However, classification remains limited to a single Euclidean feature space that is incapable of resolving binding landscapes. This dissertation develops SWING for four distinct kernel types: Gaussian, Laplacian, anisotropic (ARD), and the Spectral Mixture (SM) kernel, each approximated using scalable Random Fourier Features. The SM kernel incorporates prior knowledge about secondary structure into its spectral density as biological …
Main-Chain Ion-Pair Polybenzimidazole Membranes Enabling Reduced-Temperature Ht-Pemfc Operation (Down To 120°C), Brian C. Benicewicz, Huina Lin
Main-Chain Ion-Pair Polybenzimidazole Membranes Enabling Reduced-Temperature Ht-Pemfc Operation (Down To 120°C), Brian C. Benicewicz, Huina Lin
Faculty Publications
Proton exchange membrane (PEM) fuel cells are promising for clean and efficient energy conversion across diverse applications. High-temperature PEM fuel cells (HT-PEMFCs) using phosphoric acid (PA)-doped polybenzimidazole (PBI) can operate up to 200°C, but at lower temperatures, water-induced PA loss often leads to performance degradation and reduced durability. In this work, we present a new class of main-chain ion-pair PBI membranes by integrating the imidazolium-biphosphate ion-pair units directly into the PBI backbone. This design results in membranes with high acid content, stronger acid-polymer interactions and stabilized acid retention. In single-cell tests, the Im+-PBI15-3 wt.% exhibits peak power densities of 0.79 …
State Government, The Forgotten Cyber Actor, Joshua D. Strubel
State Government, The Forgotten Cyber Actor, Joshua D. Strubel
Doctoral Dissertations and Projects
Cyber incidents are among the most pervasive threats facing the United States, with the FBI recording over 859,000 reported attacks and an estimated $16.6 billion in losses in 2024 alone. Despite widespread recognition that effective cyber defense requires a whole-nation approach, the existing research literature overwhelmingly focuses on federal policy, leaving state governments as largely overlooked actors. This study addresses that gap by examining the research question: How does state cybersecurity policy affect malicious cyber actors' frequency of operations? Drawing on multilinear regression analysis augmented by Random Forest machine learning models, this study evaluates the relationship between state-level cyber deterrence …
The Effect Of Project-Based Learning Model On Entrepreneurship (Pjbl-E) With A Deep Learning Approach On Students' Problem-Solving And Cognitive Skills, Ricce Oktasari, Irwandi Irwandi, Siti Darwa Suryani
The Effect Of Project-Based Learning Model On Entrepreneurship (Pjbl-E) With A Deep Learning Approach On Students' Problem-Solving And Cognitive Skills, Ricce Oktasari, Irwandi Irwandi, Siti Darwa Suryani
Jurnal Pendidikan Sains
This study aims to examine the effect of the Entrepreneurship-based Project Based Learning (PjBL-E) model integrated with a pedagogical Deep Learning approach on students’ problem-solving skills and cognitive learning outcomes in biology learning. The novelty of this study lies in the integration of entrepreneurship values and pedagogical deep learning principles into Project Based Learning to create contextual and meaningful learning experiences. Entrepreneurship integration encourages students to develop innovative products, identify real-world problems, and apply biological concepts in practical and socio-economic contexts. Meanwhile, the pedagogical Deep Learning approach promotes reflective thinking, conceptual understanding, critical analysis, and the ability to connect theory …
You Mean What? Commognitive Conflict In Resolving Contextual Logarithm Problems, Endrayana Putut Laksminto Emanuel, Fatkul Anam, Radhitya Duta Pradana, Anik Kirana, Sikky El Walida
You Mean What? Commognitive Conflict In Resolving Contextual Logarithm Problems, Endrayana Putut Laksminto Emanuel, Fatkul Anam, Radhitya Duta Pradana, Anik Kirana, Sikky El Walida
Jurnal Pendidikan Sains
Students’ approaches to solving contextual mathematics problems involving logarithms vary significantly due to differences in their prior mathematical understanding. These differences may trigger commognitive conflict during the interpretation and reasoning processes when students attempt to construct mathematical meaning from contextual situations. This qualitative study aimed to explore how commognitive conflict emerges as a mechanism of mathematical interpretation in students’ discourse while solving logarithmic contextual problems. Twenty students participated in the study and were grouped based on their performance. One student was selected as the main research subject for an in-depth analysis. The findings reveal that commognitive conflict appeared in two …
Student Worksheets Based On The Local Wisdom Of Besilek Serawai For Sixth-Grade Elementary Science Learning, Mice Agustin, Tomi Hidayat, Irwandi Irwandi
Student Worksheets Based On The Local Wisdom Of Besilek Serawai For Sixth-Grade Elementary Science Learning, Mice Agustin, Tomi Hidayat, Irwandi Irwandi
Jurnal Pendidikan Sains
This study aims to develop a Student Worksheet (Lembar Kerja Peserta Didik [LKPD]) based on the local wisdom of Besilek Serawai for sixth-grade elementary science education and to evaluate its validity. The study employed the ADDIE development model, consisting of five stages: Analyze, Design, Develop, Implement, and Evaluate. The developed LKPD integrates Besilek Serawai, a traditional martial art of the Seluma community, with the concept of the human locomotor system in science instruction. The worksheet was validated by two subject-matter experts and two media experts. Material validation yielded an average score of 4.26, equivalent to a validity percentage of 85.2%, …
High-Throughput Optical Analysis To Inform Design Of Electrochemical Biosensors, Nathan J. Ricks, Michael A. Pence, Monica Brachi, Shelley D. Minteer
High-Throughput Optical Analysis To Inform Design Of Electrochemical Biosensors, Nathan J. Ricks, Michael A. Pence, Monica Brachi, Shelley D. Minteer
Chemistry Faculty Research & Creative Works
Electrochemical biosensors are central to wearable diagnostics, point-of-care testing, and continuous health monitoring due to their low power requirements, compatibility with miniaturized electronics, and proven clinical impact. Despite these advantages, the development of new electrochemical biosensors remains slow, constrained by limited throughput, complex electrode–biomolecule interfaces, and challenges associated with selectivity and performance in chemically complex environments. This perspective outlines how the next generation of electrochemical biosensors can be enabled by decoupling high-throughput front-end discovery and optimization from electrochemical readouts using nonelectrochemical surrogate assays. Optical, affinity, and cell-sorting platforms, including SELEX, fluorescence-activated cell sorting, and chemically coupled fluorescence assays, allow orders-of-magnitude …
Learning In Infants Using Intrinsically Motivated Goal Conditioned Reinforcement Learning, T I Darsan
Learning In Infants Using Intrinsically Motivated Goal Conditioned Reinforcement Learning, T I Darsan
Master’s Dissertations
Traditional artificial intelligence models learn by passively digesting large datasets. In contrast, human infants discover skills by actively interacting with their bodies and environments without explicit external rewards. This thesis introduces the Composer Architecture, a machine learning framework designed to mimic this autonomous, open-ended development. The Composer architecture operates in a multi-stage loop, the latent model using Contrastive Learning Through Time (CLTT) to compress high-dimensional raw data from visual, proprioceptive, and touch sensors into a low-dimensional space. To preserve data relationships and prevent topological collapse, a Softmax activation forces these latent representations to lie smoothly on a probability simplex. A …
Design And Evaluation Of A Code-Switching-Aware Multilingual Conversational Ai System Using Advanced Rag Architectures, Ashutosh Juvale
Design And Evaluation Of A Code-Switching-Aware Multilingual Conversational Ai System Using Advanced Rag Architectures, Ashutosh Juvale
Master’s Dissertations
Conversational artificial intelligence has become the primary interface through which hundreds of millions of users in India seek information and customer support. Yet the way these users actually write and speak is fundamentally at odds with the monolingual assumptions baked into most retrieval and generation systems: they code-switch, fluidly mixing one or more of the twenty-two scheduled languages of India with English, frequently typing Indic words in the Roman script ("mera refund kab tak aayega"). Standard Retrieval-Augmented Generation (RAG) pipelines silently fail on such input — the retriever returns off-topic passages because the query and the knowledge base live in …
An Efficient Hierarchical Deployment Of Sensors For K-Coverage In Planner Wireless Sensor Network, Abhay Raj Singh
An Efficient Hierarchical Deployment Of Sensors For K-Coverage In Planner Wireless Sensor Network, Abhay Raj Singh
Master’s Dissertations
Ensuring reliable sensing coverage is a fundamental challenge in wireless sensor networks (WSNs), particularly when multiple sensors are monitoring each location to provide robustness against node failures. In this work, we address the problem of deterministic k-coverage in planar WSN by proposing a hierarchical triangular lattice-based deployment strategy that organizes sensor locations across di↵erent refinement levels and guarantees coverage of every point in the sensing domain by at least k sensors. Each lattice is three-colorable, and selective activation of color classes ensures adjustable coverage guarantees. We prove that activating a single color class at refinement level t guarantees at least …
Telluric Correction Of M-Dwarf Stars Using Machine Learning, Sayak Rana
Telluric Correction Of M-Dwarf Stars Using Machine Learning, Sayak Rana
Master’s Dissertations
The study of M-dwarf stars is of prime scientific interest to us because of their closer habitable zones and the favorable conditions they offer for exoplanet detection. However, telluric contamination of the ground-based spectra results in sharp absorption lines, which makes their study cumbersome. Removing this contamination is necessary for estimating key stellar parameters. The central contribution is a one-dimensional Convolutional Neural Network (CNN) that retrieves the four atmospheric parameters governing telluric absorption: pressure, temperature, humidity, and airmass. These predicted parameters are passed to Telfit which produces an estimated telluric spectrum. The observed spectrum is then divided by this estimated …
Data-Driven Electrochemistry Reveals The Impact Of Hydrophobicity On Aptamer Cross-Reactivity, Emily Carroll, Michael A. Pence, Elizabeth Winterholler, Taylor D. Sparks, Shelley D. Minteer
Data-Driven Electrochemistry Reveals The Impact Of Hydrophobicity On Aptamer Cross-Reactivity, Emily Carroll, Michael A. Pence, Elizabeth Winterholler, Taylor D. Sparks, Shelley D. Minteer
Chemistry Faculty Research & Creative Works
Electrochemical aptamer-based (E-AB) biosensors offer a promising platform for reagentless detection of molecular targets, yet aptamer recognition can be limited by cross-reactivity, particularly for hydrophobic analytes such as steroid hormones. To investigate how cross-reactivity influences E-AB sensor performance, we use automation and machine learning to screen a library of possible interferent molecules against a steroid-binding aptamer, with progesterone serving as a physiologically relevant test case. Here, we develop a label-free E-AB sensor for progesterone detection using a methylene blue-modified aptamer anchored with a hexanethiol linker. We then used an automated electrochemistry platform to perform reproducible and high-throughput characterization of our …