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Weak Identification Of Long Memory With Implications For Volatility Modeling;, Jia Li, Peter C. B. Phillips, Shuping Shi, Jun Yu Oct 2025

Weak Identification Of Long Memory With Implications For Volatility Modeling;, Jia Li, Peter C. B. Phillips, Shuping Shi, Jun Yu

Research Collection School Of Economics

This paper explores implications of weak identification in common ‘long memory’ and recent ‘rough’ approaches to modeling volatility dynamics of financial assets. We unveil an asymptotic near-observational equivalence between a long memory model with weak autoregressive dynamics and a rough model with a near-unit autoregressive root. Standard methods struggle to distinguish them, and conventional asymptotics are invalid. We propose an identification-robust approach to construct confidence sets that reveal the uncertainty and aid inference. Empirical studies based on realized volatility and trading volume often fail to statistically reject either model, thereby providing evidence of their potential coexistence.

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The Degree Of Digital Fluency Availability Among Middle School English Teachers In Bisha City, Sharifah Al-Shahrani, Ahmad Al- Daleel Oct 2025

The Degree Of Digital Fluency Availability Among Middle School English Teachers In Bisha City, Sharifah Al-Shahrani, Ahmad Al- Daleel

Journal of Educational and Psychological Studies

The aim of this study was to assess the dimensions of digital fluency (technical, cognitive, social, and security/privacy) among middle school English teachers in Bisha Governorate, Saudi Arabia. The study included 157 teachers selected using a simple random sampling method. The researchers employed a descriptive survey approach and used a questionnaire as the research instrument. The study results showed that the level of availability of the dimensions of digital fluency among middle school English teachers in Bisha Governorate varied: the social dimension ranked first with a mean score of 4.35, indicating a very high level of availability; followed by the …

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Frameworks And Life Cycle Assessment For Reinforced Concrete Bridges For Sustainability In Transportation, Yu-Fu Ko, Jessica Gonzalez Oct 2025

Frameworks And Life Cycle Assessment For Reinforced Concrete Bridges For Sustainability In Transportation, Yu-Fu Ko, Jessica Gonzalez

Mineta Transportation Institute

Bridge structures are critical components of California’s transportation network, with reinforced concrete (RC) bridges being among the most widely used. Extending the lifespan of these structures can lead to significant reductions in environmental impacts. However, California’s frequent seismic activity has repeatedly exposed the vulnerability of existing RC bridges, highlighting the urgent need for seismic retrofitting and maintenance to improve infrastructure resilience against earthquakes and to increase sustainability. This research used detailed computer simulations known as nonlinear finite element models, which are highly detailed computer models, incorporating section damage indices to predict damage and assess structural deficiencies in RC bridges during …

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Wildfire Emergency Response And Evacuation Framework Using Drones: Phase I, Hovannes Kulhandjian Oct 2025

Wildfire Emergency Response And Evacuation Framework Using Drones: Phase I, Hovannes Kulhandjian

Mineta Transportation Institute

Wildfires are escalating in frequency and severity due to climate change, posing increasing threats to human life, infrastructure,and ecosystems. Traditional wildfire management systems struggle to respond effectively to rapidly evolving fire conditions. This research presents a novel, AI-powered Wildfire Emergency Response and Evacuation Framework that integrates autonomous unmanned aerial vehicles (UAVs, AKA “drones”), multi-sensor data fusion, and machine learning (ML) for real-time fire detection, evacuation planning, and search and rescue (SAR) operations. Central to the system is the Dynamic Wildfire Response Algorithm (DWRA), a hybrid decision-making framework combining AI-driven techniques including reinforcement learning (RL), genetic algorithms (GA), and deep learning …

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Revised Draft Final 2022 Unreclaimed Sites Sampling: Ur-20 Site Evaluation Summary Report, Pioneer Technical Services, Inc. Oct 2025

Revised Draft Final 2022 Unreclaimed Sites Sampling: Ur-20 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Draft Final Butte Priority Soils Operable Unit (Bpsou) Insufficiently Reclaimed Sites Remedial Action Work Plan (Rawp): Bres No. 104 (Colorado Dump) North Slope, Pioneer Technical Services, Inc. Oct 2025

Draft Final Butte Priority Soils Operable Unit (Bpsou) Insufficiently Reclaimed Sites Remedial Action Work Plan (Rawp): Bres No. 104 (Colorado Dump) North Slope, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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African American Female College Students’ Experiences At Predominately White Institutions, Sh'nita Louise Mitchell Oct 2025

African American Female College Students’ Experiences At Predominately White Institutions, Sh'nita Louise Mitchell

Electronic Theses and Dissertations

African American women who attend predominantly White institutions (PWIs) have historically encountered systemic challenges that include racial isolation, microaggressions, a lack of cultural understanding, and insufficient institutional support. These barriers often impact their sense of belonging, academic persistence, and overall success. I aimed to explore the lived experiences of African American women who graduated from PWIs to understand how these women navigate institutional structures and sustain their academic journeys. I aimed to examine the unique challenges and supports experienced by African American women, and to identify factors that contribute to or hinder their persistence and success at their PWI. The …

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Beyond Leadership Turnover: Examining The Relationship Between Principal Supervisor Coaching And Student Academic Performance, Margo L. Nottingham Oct 2025

Beyond Leadership Turnover: Examining The Relationship Between Principal Supervisor Coaching And Student Academic Performance, Margo L. Nottingham

Electronic Theses and Dissertations

Schools that maintain stable leadership report increased student achievement outcomes. The problem is that over 21% of U.S. principals leave their positions in the first year in high-poverty contexts. Principals leave their roles due to high job demands, inadequate support, and limited professional development, leading to decreased performance and poor school culture. The problem examined in this study was the lack of evidence on whether coaching principal supervisors contributed to improved student achievement outcomes. The study aimed to determine whether coaching principal supervisors through a regional service center was associated with higher student achievement in low-performing elementary and middle schools. …

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A Comprehensive Review Of Financial Knowledge Graphs, Jeyaraman Brindha Priyadarshini, Bing Tian Dai, Yuan Fang Oct 2025

A Comprehensive Review Of Financial Knowledge Graphs, Jeyaraman Brindha Priyadarshini, Bing Tian Dai, Yuan Fang

Research Collection School Of Computing and Information Systems

Knowledge Graphs (KGs) are increasingly used in finance to manage complex, interconnected data and support advanced analytics. This survey provides an overview of how KGs are applied across various financial areas, such as fraud detection, credit risk assessment, anti-money laundering, and regulatory compliance. We examine key techniques for building and using KGs in finance, including graph construction, embedding methods, and machine learning models. The survey also discusses challenges specific to finance, like handling private data, ensuring interpretability, and managing real-time data. Additionally, we explore the emerging combination of KGs with large language models and generative AI, which offers new possibilities …

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Rethinking Teaching Evaluation Reports: Designing Ai-Transformed Student Feedback For Instructor Engagement, Ruoxi Shang, Keri Mallari, Au Wei Bin Yeong, Ken Yasuhara, Anthony Tang, Gary Hsieh Oct 2025

Rethinking Teaching Evaluation Reports: Designing Ai-Transformed Student Feedback For Instructor Engagement, Ruoxi Shang, Keri Mallari, Au Wei Bin Yeong, Ken Yasuhara, Anthony Tang, Gary Hsieh

Research Collection School Of Computing and Information Systems

Student feedback is critical for improving teaching, yet instructors often avoid reading evaluations due to emotional burden and information overload. We present a systematic exploration of how language models can distill and transform student evaluations into adaptive, actionable insights. Through a systematic design space exploration combining 4 feedback strategies (removing harmful content, paraphrasing criticism, sandwiching negatives, adding constructive suggestions) with 4 presentation formats (themes, cards, letters, chatbots), we created six AI-augmented prototypes of teaching evaluations. Interviews with 16 post-secondary instructors revealed that effective use of AI in feedback processing should: (1) support action formation through focused views and divergent thinking, …

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Polymind: Parallel Visual Diagramming With Large Language Models To Support Prewriting Through Microtasks, Qian Wan, Jiannan Li, Huanchen Wang, Zhicong Lu Oct 2025

Polymind: Parallel Visual Diagramming With Large Language Models To Support Prewriting Through Microtasks, Qian Wan, Jiannan Li, Huanchen Wang, Zhicong Lu

Research Collection School Of Computing and Information Systems

Prewriting is the process of generating and organising ideas before a first draft. It consists of a combination of informal, iterative, and semi-structured strategies such as visual diagramming, which poses a challenge for collaborating with large language models (LLMs) in a turn-taking conversational manner. We present Polymind, a visual diagramming tool that leverages multiple LLM-powered agents to support prewriting. The system features a parallel collaboration workflow in place of the turn-taking conversational interactions. It defines multiple ''microtasks'' to simulate group collaboration scenarios such as collaborative writing and group brainstorming. Instead of repetitively prompting a chatbot for various purposes, Polymind enables …

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Information Provision And Search Frictions: Evidence From The Taxi Industry In Singapore, Sumit Agarwal, Shih-Fen Cheng, Jussi Keppo, Long Wang, Yang Yang Oct 2025

Information Provision And Search Frictions: Evidence From The Taxi Industry In Singapore, Sumit Agarwal, Shih-Fen Cheng, Jussi Keppo, Long Wang, Yang Yang

Research Collection School Of Computing and Information Systems

Search frictions and misallocation are common in decentralized transportation markets. Using novel trip-level data of taxis in Singapore, this paper examines the impactof real-time demand information at airport terminals on search frictions. The information reduces taxi supply misallocation, increasing deadheading speed by 16.3% and decreasing deadheading time by 10.77%, benefiting both passengers and drivers. It raises daily earnings by $3.70 USD and adds 6.2 minutes of operational time per airport-trip taxi. Spatial spillovers are primarily observed among drivers in adjacentdistricts. Taxis from the Budget Terminal and drivers with fewer prior airport pickups benefit more from this information.

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Conditional Attribute-Based Pre: Definition And Construction From Lwe, Lisha Yao, Jian Weng, Pengfei Wu, Guofeng Tang, Guomin Yang, Haiyang Xue, Robert H. Deng Oct 2025

Conditional Attribute-Based Pre: Definition And Construction From Lwe, Lisha Yao, Jian Weng, Pengfei Wu, Guofeng Tang, Guomin Yang, Haiyang Xue, Robert H. Deng

Research Collection School Of Computing and Information Systems

Attribute-based proxy re-encryption (AB-PRE) is a crucial variant of proxy re-encryption. It allows a proxy with a re-encryption key to transform a delegator’s ciphertext associated with an access policy into another ciphertext associated with a new access policy, enabling delegatees with matching attributes to decrypt the transformed ciphertext. However, a key limitation of AB-PRE is that the delegator cannot control which ciphertexts are transformed. As a result, the proxy, once given the re-encryption key, indiscriminately transforms all ciphertexts, effectively switching their underlying policies—an issue known as the all-or-nothing problem. It limits the system’s flexibility and practicality in real-world use cases.In …

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Stable Score Distillation, Haiming Zhu, Yangyang Xu, Chenshu Xu, Tingrui Shen, Wenxi Liu, Yong Du, Jun Yu, Shengfeng He Oct 2025

Stable Score Distillation, Haiming Zhu, Yangyang Xu, Chenshu Xu, Tingrui Shen, Wenxi Liu, Yong Du, Jun Yu, Shengfeng He

Research Collection School Of Computing and Information Systems

Text-guided image and 3D editing have advanced with diffusion-based models, yet methods like Delta Denoising Score often struggle with stability, spatial control, and editing strength. These limitations stem from reliance on complex auxiliary structures, which introduce conflicting optimization signals and restrict precise, localized edits. We introduce Stable Score Distillation (SSD), a streamlined framework that enhances stability and alignment in the editing process by anchoring a single classifier to the source prompt. Specifically, SSD utilizes Classifier-Free Guidance (CFG) equation to achieve cross-prompt alignment, and introduces a constant term null-text branch to stabilize the optimization process. This approach preserves the original content's …

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Stroke2sketch: Harnessing Stroke Attributes For Training-Free Sketch Generation, Rui Yang, Huining Li, Yiyi Long, Xiaojun Wu, Shengfeng He Oct 2025

Stroke2sketch: Harnessing Stroke Attributes For Training-Free Sketch Generation, Rui Yang, Huining Li, Yiyi Long, Xiaojun Wu, Shengfeng He

Research Collection School Of Computing and Information Systems

Generating sketches guided by reference styles requires precise transfer of stroke attributes, such as line thickness, deformation, and texture sparsity, while preserving semantic structure and content fidelity. To this end, we propose Stroke2Sketch, a novel training-free framework that introduces cross-image stroke attention, a mechanism embedded within self-attention layers to establish fine-grained semantic correspondences and enable accurate stroke attribute transfer. This allows our method to adaptively integrate reference stroke characteristics into content images while maintaining structural integrity. Additionally, we develop adaptive contrast enhancement and semanticfocused attention to reinforce content preservation and foreground emphasis. Stroke2Sketch effectively synthesizes stylistically faithful sketches that closely …

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Tactile Data Comics: Combining Step-By-Step Presentation Of Tactile Graphics With Verbal Narration For The Blind And Visually Impaired, Yang Jiao, Ruoting Sun, Rong Luo, Xiwen Yao, Xinran She, Kotaro Hara, Yuewen Zhang, Xinyi Fu Oct 2025

Tactile Data Comics: Combining Step-By-Step Presentation Of Tactile Graphics With Verbal Narration For The Blind And Visually Impaired, Yang Jiao, Ruoting Sun, Rong Luo, Xiwen Yao, Xinran She, Kotaro Hara, Yuewen Zhang, Xinyi Fu

Research Collection School Of Computing and Information Systems

Tactile graphics on a refreshable display have proven effective in enabling visually impaired people to comprehend pictorial content. To further evaluate the effectiveness of refreshable tactile displays in blind education, we designed tactile data comics, a method that combines step-by-step presentation of tactile graphics with verbal narration. We conducted a user study with sixteen visually impaired students to compare tactile data comics against verbal-only and static tactile graphics. Our findings show that tactile data comics significantly improve participants’ comprehension and engagement during the learning experience. These empirical results suggest that the integration of refreshable tactile displays and tactile data comics …

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2025 October, Morehead State University. Office Of Communications & Marketing. Oct 2025

2025 October, Morehead State University. Office Of Communications & Marketing.

Morehead State Press Release Archive, 1961 to the Present

Press releases for October of 2025.

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Tess Light Curves And Period Changes In Low-Mass Eclipsing Binary Bb Persei, Marek Wolf, Petr Zasche, Miloslav Zejda, Martin Mašek, Andrej Mudray, Hana Kučáková, Waldemar Ogłoza, Jaroslav Merc, Jan Kára, Vojtěch Dienstbier Oct 2025

Tess Light Curves And Period Changes In Low-Mass Eclipsing Binary Bb Persei, Marek Wolf, Petr Zasche, Miloslav Zejda, Martin Mašek, Andrej Mudray, Hana Kučáková, Waldemar Ogłoza, Jaroslav Merc, Jan Kára, Vojtěch Dienstbier

Physics & Astronomy Faculty Publications

We present a detailed analysis of the low-mass detached eclipsing binary system BB Persei, which contains two K-type stars in a circular orbit with a short period of 0.4856 d. We used light curves from the Transiting Exoplanet Survey Satellite (Tess), which observed BB Per in five sectors, to determine its photometric properties and a precise orbital ephemeris. The solution of the Tess light curve in Phoebe results in a detached configuration, where the temperature of the primary component was fixed to T 1 = 5 300 K according to Lamost, which gives us T 2 = 5 050 ± …

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Six New Doubly Eclipsing Quadruples In A 2+2 Architecture, Petr Zasche, Hana Kučáková, Jan Kára, Jaroslav Merc, Z. Henzl, Martin Mašek, L. Červinka, Vojtěch Dienstbier Oct 2025

Six New Doubly Eclipsing Quadruples In A 2+2 Architecture, Petr Zasche, Hana Kučáková, Jan Kára, Jaroslav Merc, Z. Henzl, Martin Mašek, L. Červinka, Vojtěch Dienstbier

Physics & Astronomy Faculty Publications

The study presents a confirmation of six quadruples with two sets of eclipses that have the 2+2 architecture. These so-called doubly eclipsing systems still present a quite rare group of stars. We collected all available photometric data and carried out a detailed analysis of them. In addition to the precise TESS photometry used to model the light curves for both inner eclipsing binaries, photometric survey data were also used, and more than 100 nights of our own dedicated observations were carried out. These were mainly used for the detection of the long-term evolution of orbital periods. Thanks to these data, …

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Topoimages: Incorporating Local Topology Encoding Into Deep Learning Models For Medical Image Classification, Pengfei Gu, Hongxiao Wang, Yejia Zhang, Huimin Li, Chaoli Wang, Danny Z. Chen Oct 2025

Topoimages: Incorporating Local Topology Encoding Into Deep Learning Models For Medical Image Classification, Pengfei Gu, Hongxiao Wang, Yejia Zhang, Huimin Li, Chaoli Wang, Danny Z. Chen

Computer Science Faculty Publications

Topological structures in image data, such as connected components and loops, play a crucial role in understanding image content (e.g., biomedical objects). Despite remarkable successes of numerous image processing methods that rely on appearance information, these methods often lack sensitivity to topological structures when used in general deep learning (DL) frameworks. In this paper, we introduce a new general approach, called TopoImages (for Topology Images), which computes a new representation of input images by encoding local topology of patches. In TopoImages, we leverage persistent homology (PH) to encode geometric and topological features inherent in image patches. Our main objective is …

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Cookingdiffusion: Cooking Procedural Image Generation With Stable Diffusion, Yuan Wang, Bin Zhu, Yanbin Hao, Chong-Wah Ngo, Yi Tan, Xiang Wang Oct 2025

Cookingdiffusion: Cooking Procedural Image Generation With Stable Diffusion, Yuan Wang, Bin Zhu, Yanbin Hao, Chong-Wah Ngo, Yi Tan, Xiang Wang

Research Collection School Of Computing and Information Systems

Recent advancements in text-to-image generation models have excelled in creating diverse and realistic images. This success extends to food imagery, where various conditional inputs like cooking styles, ingredients, and recipes are utilized. However, a yet-unexplored challenge is generating a sequence of procedural images based on cooking steps from a recipe. This could enhance the cooking experience with visual guidance and possibly lead to an intelligent cooking simulation system. To fill this gap, we introduce a novel task called cooking procedural image generation. This task is inherently demanding, as it strives to create photo-realistic images that align with cooking steps while …

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Omnivton: Training-Free Universal Virtual Try-On, Zhaotong Yang, Yuhui Li, Shengfeng He, Xinzhe Li, Yangyang Xu, Junyu Dong, Yong Du Oct 2025

Omnivton: Training-Free Universal Virtual Try-On, Zhaotong Yang, Yuhui Li, Shengfeng He, Xinzhe Li, Yangyang Xu, Junyu Dong, Yong Du

Research Collection School Of Computing and Information Systems

Image-based Virtual Try-On (VTON) techniques rely on either supervised in-shop approaches, which ensure high fidelity but struggle with cross-domain generalization, or unsupervised in-the-wild methods, which improve adaptability but remain constrained by data biases and limited universality. A unified, training-free solution that works across both scenarios remains an open challenge. We propose OmniVTON, the first training-free universal VTON framework that decouples garment and pose conditioning to achieve both texture fidelity and pose consistency across diverse settings. To preserve garment details, we introduce a garment prior generation mechanism that aligns clothing with the body, followed by continuous boundary stitching technique to achieve …

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Fcad: Feature-Coupled Anisotropic Diffusion For Continuous Graph Learning, Amitoz Azad, Zhiyuan Zhang Oct 2025

Fcad: Feature-Coupled Anisotropic Diffusion For Continuous Graph Learning, Amitoz Azad, Zhiyuan Zhang

Research Collection School Of Computing and Information Systems

In this work, we propose a novel continuous graph neural network called FCAD (Feature-Coupled Anisotropic Diffusion) for the task of node classification on graphs. Our approach is motivated by the success of feature-coupled anisotropic diffusion PDEs in multivalued image restoration. Our method introduces a total variation regularization-inspired anisotropic term to control diffusion between nodes and incorporates a learnable parameterization for feature coupling during the diffusion process. Our model performs competitively against several GNN baselines for both heterophilous and homophilous graphs, demonstrating notable benefits for heterophilous graphs due to the learnable feature coupling.

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Lsfdnet: A Single-Stage Fusion And Detection Network For Ships Using Swir And Lwir, Yanyin Guo, Runxuan An, Junwei Li, Zhiyuan Zhang Oct 2025

Lsfdnet: A Single-Stage Fusion And Detection Network For Ships Using Swir And Lwir, Yanyin Guo, Runxuan An, Junwei Li, Zhiyuan Zhang

Research Collection School Of Computing and Information Systems

Traditional ship detection methods primarily rely on single-modal approaches, such as visible or infrared images, which limit their application in complex scenarios involving varying lighting conditions and heavy fog. To address this issue, we explore the advantages of short-wave infrared (SWIR) and long-wave infrared (LWIR) in ship detection and propose a novel single-stage image fusion detection algorithm called LSFDNet. This algorithm leverages feature interaction between the image fusion and object detection subtask networks, achieving remarkable detection performance and generating visually impressive fused images. To further improve the saliency of objects in the fused images and improve the performance of the …

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Diffusionmat: Alpha Matting As Deterministic Sequential Refinement Learning, Yangyang Xu, Shengfeng He, Wenqi Shao, Yong Du, Kwan-Yee K. Wong, Yu Qiao, Jun Yu, Ping Luo Oct 2025

Diffusionmat: Alpha Matting As Deterministic Sequential Refinement Learning, Yangyang Xu, Shengfeng He, Wenqi Shao, Yong Du, Kwan-Yee K. Wong, Yu Qiao, Jun Yu, Ping Luo

Research Collection School Of Computing and Information Systems

In this paper, we introduce DiffusionMat, a novel image matting framework that employs a diffusion model for the transition from coarse to refined alpha mattes. Diverging from conventional methods that utilize trimaps merely as loose guidance for alpha matte prediction, our approach treats image matting as a deterministic sequential refinement learning process. This process begins with the addition of noise to trimaps and iteratively denoises them using a pre-trained diffusion model, which incrementally guides the prediction towards a clean alpha matte. The key innovation of our framework is a correction module that adjusts the output at each denoising step, ensuring …

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Fine-Grained Abnormality Prompt Learning For Zero-Shot Anomaly Detection, Jiawen Zhu, Yew‑Soon Ong, Chunhua Shen, Guansong Pang Oct 2025

Fine-Grained Abnormality Prompt Learning For Zero-Shot Anomaly Detection, Jiawen Zhu, Yew‑Soon Ong, Chunhua Shen, Guansong Pang

Research Collection School Of Computing and Information Systems

Current zero-shot anomaly detection (ZSAD) methods show remarkable success in prompting large pre-trained visionlanguage models to detect anomalies in a target dataset without using any dataset-specific training or demonstration. However, these methods often focus on crafting/learning prompts that capture only coarse-grained semantics of abnormality, e.g., high-level semantics like ‘damaged’, ‘imperfect’, or ‘defective’ objects. They therefore have limited capability in recognizing diverse abnormality details that deviate from these general abnormal patterns in various ways. To address this limitation, we propose FAPrompt, a novel framework designed to learn Fine-grained Abnormality Prompts for accurate ZSAD. To this end, a novel Compound Abnormality Prompt …

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Impact Of Original Versus Reposted Social Endorsements On Content Consumption: The Moderating Role Of Endorsers’ Network Characteristics, Anqi Zhao, Qian Tang Oct 2025

Impact Of Original Versus Reposted Social Endorsements On Content Consumption: The Moderating Role Of Endorsers’ Network Characteristics, Anqi Zhao, Qian Tang

Research Collection School Of Computing and Information Systems

Social endorsements broadcast endorsers’ positive attitudes toward content or products, especially to their social ties. Original endorsements created by endorsers can be propagated further as reposted endorsements. Both are important marketing tools to increase content consumption, yet their differences are unclear. This study compares the impacts of original and reposted endorsements on content consumption and their contingencies on the endorsers’ network characteristics. Using data on social endorsements of YouTube videos on Twitter, we find that original endorsements (i.e., original tweets) significantly boost content consumption, and the effect is positively moderated by the endorsers’ network size but not their tie strength. …

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Using Some Artificial Intelligence Algorithms To Estimate The Parametric Regression Function For Spatially Dependent Data Of Water Pollution Of The Euphrates River, Ons Edin Musa, Sabah Manfi Redha Oct 2025

Using Some Artificial Intelligence Algorithms To Estimate The Parametric Regression Function For Spatially Dependent Data Of Water Pollution Of The Euphrates River, Ons Edin Musa, Sabah Manfi Redha

Journal of Economics and Administrative Sciences

These models account for the spatial effects resulting from the proximity of events. A compromise exists in the mathematical accuracy of model parameters when spatial correlations are present in the data of the phenomenon. Data reliant on spatial correlations are crucial in statistical modelling, especially in environmental science, economics, epidemiology, and various other disciplines. This study employs and compares three artificial intelligence approaches—the genetic algorithm (GA), the TABU search algorithm (TSA), and the binary firefly algorithm (Binary FFA)—to determine which is the most efficient for estimating the parametric regression function for spatially dependent data. The Mean Absolute Percentage Error numbers …

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Layer By Layer: Elevating Mathematics Learning With 3d Printing, Jia He, Eryn Michelle Maher, Heidi Eisenreich, Ha Nguyen Oct 2025

Layer By Layer: Elevating Mathematics Learning With 3d Printing, Jia He, Eryn Michelle Maher, Heidi Eisenreich, Ha Nguyen

Proceedings of the Annual Meeting of the Georgia Association of Mathematics Teacher Educators

This article explores how 3D printing, particularly through the free and widely used slicing program Cura, can support the Concrete-Representational-Abstract (CRA) instructional model in alignment with Georgia Department of Education (GaDOE) mathematics standards. Through the CRA lens, students engage with tangible models, modify drawings and diagrams, and connect these experiences to symbols and formulas through a cyclical process. Cura’s design and printing processes invite authentic mathematical reasoning about geometry, measurement, and proportionality. Real-world constraints, such as infill density and support structures, create opportunities for students to explore relationships among shape, size, and resource optimization. By sharing approachable examples and classroom …

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Information-Bottleneck Driven Binary Neural Network For Change Detection, Kaijie Yin, Zhiyuan Zhang, Shu Kong, Tian Gao, Cheng-Zhong Xu, Hui Kong Oct 2025

Information-Bottleneck Driven Binary Neural Network For Change Detection, Kaijie Yin, Zhiyuan Zhang, Shu Kong, Tian Gao, Cheng-Zhong Xu, Hui Kong

Research Collection School Of Computing and Information Systems

In this paper, we propose Binarized Change Detection (BiCD), the first binary neural network (BNN) designed specifically for change detection. Conventional network binarization approaches, which directly quantize both weights and activations in change detection models, severely limit the network's ability to represent input data and distinguish between changed and unchanged regions. This results in significantly lower detection accuracy compared to real-valued networks. To overcome these challenges, BiCD enhances both the representational power and feature separability of BNNs, improving detection performance. Specifically, we introduce an auxiliary objective based on the Information Bottleneck (IB) principle, guiding the encoder to retain essential input …

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