Digital Commons Network^™

From Feedback To Insight: Using Hierarchical Clustering Analysis To Identify And Analyze Feedback Dimensions In Online Courses, Reagan R. Siggard

All Graduate Theses and Dissertations, Fall 2023 to Present

The demand for online courses continues to increase, as do the critiques of their effectiveness. Studies have found that peer interactions positively impact the online course experience and that peers can offer feedback to each other at the instructor's level with proper guidance. To help understand this feedback, researchers have identified feedback dimensions. Most feedback dimensions have been created through inductive coding, not exploratory data analysis approaches. This study sought to identify those feedback dimensions that perhaps had been missed or were highly associated with those already existing in the literature, hoping to inform research and practice to improve the …

Utilizing Diatoms In Wastewater Treatment For Pollutant Removal, Ceaira D. Howard

All Graduate Theses and Dissertations, Fall 2023 to Present

Wastewater treatment systems are increasingly challenged by a complex mix of pollutants including excess nutrients, organic dyes, and persistent chemicals like per- and polyfluoroalkyl substances (PFAS). Conventional treatment technologies often struggle to effectively and affordably remove these contaminants. This study explores the use of two diatom species, Phaeodactylum tricornutum and Navicula cryptocephala var. veneta, both single-celled microalgae with silica-based cell walls, as an environmentally sustainable approach to tertiary wastewater treatment. Diatoms offer dual functionality through surface adsorption properties and metabolic flexibilities, making them promising candidates for integrated treatment strategies.

To test the trophic flexibilities of diatoms, P. tricornutum was …

A Software Framework For Translating Onnx Models Onto The Lace-C3a Hardware, Shawn Jones

All Graduate Theses and Dissertations, Fall 2023 to Present

Modern computers are powerful, but they are not always efficient enough for small, low power systems like those used on satellites and scientific instruments. To solve this problem, engineers often turn to FPGAs—reconfigurable computer chips that can be customized to run specific tasks much faster and with far less energy than ordinary processors. However, finding the best possible design for an FPGA program is extremely difficult because there are millions of ways a design could be built, and only a small fraction of them actually perform well.

This thesis presents SNOW, a new framework that helps automate the search for …

Lace Network Firmware: A Polarfire Fpga Network For Data Routing And Command Interfacing In Space Applications, Kade C. Howes

All Graduate Theses and Dissertations, Fall 2023 to Present

Modern small spacecraft rely on powerful yet efficient onboard compute devices to process data from sensors in real-time due to tight power and volume constraints. This work explores a new compute device system built from PolarFire Field-Programmable Gate Arrays (FPGAs), which are power-efficient, reprogrammable chips well-suited for space applications. The system connects via a central controller FPGA with one or multiple companion processing FPGAs, allowing sensor data to be quickly received and shared across the network. Standardized data formats and interfaces increase compatibility with spacecraft computers. By simplifying data handling and using high-speed communication links, this architecture makes it easier …

An Investigation Of Paleoclimate Through A Sedimentological Lens In The Gulf Of Mexico And Western North Pacific, Sarah Monica

Dissertations

This dissertation explores the use of sediment cores as proxy data for the reconstruction of paleoclimatic and environmental conditions. Human-caused climate change is leading to dramatic shifts in the global climate. As the instrumental record of climate is relatively short compared to the amount of time Earth has experienced weather, this work aims to extend our knowledge of climate beyond the instrumental record, thereby improving our holistic understanding of the climate system. In Chapter one, sediment cores from the central Texas inner shelf are used to produce a record of intense tropical cyclone (TC) activity over a ~4500-year period. X-Ray …

Evaluation Of The Suitability Of Tomato (Solanum Lycopersicum L.) Accessions Grown In A Vertical Container System, Darel Kenth S. Antesco, Lourdes Edano Ma., Renerio Gentallan Jr, Roselyn F. Paelmo, Annalissa L. Aquino

The Philippine Agricultural Scientist

Growing tomatoes in vertical container systems such as hanging pots presents a promising production system for urban gardening. However, horticultural selections of tomato with traits suited for this system are still limited. The success of different genotypes grown in this system depends on the combination of morphological characters, including plant form, vegetative growth, and root development, as well as yield. This study assessed the morphological characters of 10 tomato accessions to identify those with ideal traits for this system. Results showed that some accessions possess unique traits that enhance their performance in hanging pots. Among the 10 accessions, T2 from …

From Fruit To Nut: Revisiting Pili Nut (Canarium Ovatum Engl.) Production Capacities And Value-Adding Activities In Sorsogon, Philippines, Joey Richard V. Dio, Ryan V. Dio, Dulce Corazon F. Lacson

The Philippine Agricultural Scientist

The value chain of agricultural products significantly influences their profitability and socio-economic contribution. This study developed a descriptive model of the pili (Canarium ovatum Engl.) nut value chain in Sorsogon, the primary producer in the Philippines, and the only province with large-scale commercial operations. Using a descriptive research approach, data were collected through purposive interviews with 15 key informants—farmers, processors, and traders—guided by Porter’s value-chain framework. Results indicate that Sorsogon produces about 3 times the quantity required daily (< 2,233 kg) by Bicol-based processors, leading to underutilization and post-harvest losses attributed to limited storage facilities and market linkages. The processing stage, which converts pili fruits into nuts and kernels, demonstrates the highest operational efficiency, while the trading stage remains constrained by limited market access. Stakeholders often perform overlapping functions, and traditional sun-drying methods remain common. Furthermore, an aging farming population, limited succession planning, and inconsistent implementation of food safety standards continue to pose challenges to industry growth. These inefficiencies result in reduced profitability and restrict expansion. Strengthening the value chain through improved processing systems, broader market integration, and streamlined production activities is necessary to enhance economic returns and support the sustainable growth of Sorsogon’s pili nut industry.

Gastropod Assemblage And Biofilm Abundance On Rocky Shores Of Southern Antique, Panay, Philippines, Mia Jane D. Geneblaza, Karen A. Villarta-Lane

The Philippine Agricultural Scientist

The gastropod assemblage and biofilm abundance, measured as chlorophyll a levels, were examined at 3 rocky shore sites in southern Antique, Panay, Philippines, in February 2024 to address significant gaps in current knowledge and help better understand the ecological dynamics of rocky intertidal zones. A total of 14 families comprising 22 genera and 31 species were identified from the area. The family Littorinidae was the most speciesrich, comprising 9 species. Among these, the scabra periwinkle Littoraria scabra (Philippi 1846) was the most abundant, comprising on average 50.17% of the total abundance across sites. Other identified gastropod families included Muricidae (5 …

Non-Target Organisms And Terrestrial Arthropod Biodiversity In The Corn Agroecosystem: Bt Corn Beyond Acb Pest Management [Review Article], Ireneo L. Lit Jr., Merdelyn T. Caasi-Lit, Kristine O. Abenis

The Philippine Agricultural Scientist

Assessments of risks of modern biotechnology products to non-target organisms (NTOs) are required before a product can be registered and allowed for commercial production. For Bt-engineered plants, data from such studies become part of environmental risk or impact assessments that are reviewed before a hybrid can be registered and allowed for commercial planting. The approaches and methods vary among countries and researchers. Consequently, the choice of species and groups of organisms or guilds that are monitored or studied may range from narrow to broad and encompassing. The inevitability of adverse changes in agroecosystems, including those that involve the corn crop, …

Age-Dependent Reproductive Fitness And Behavioral Dynamics Of The Asian Corn Borer, Ostrinia Furnacalis (Guenée) (Lepidoptera:Crambidae), Marcela M. Navasero, Randolph N. Candano, Maricon Dp Javier, Jethro M. Navasero, Wilson N. De Panis

The Philippine Agricultural Scientist

This study evaluated the effects of parental age of the Asian corn borer (ACB), Ostrinia furnacalis (Guenée), on fecundity, egg hatchability, adult longevity, and the duration of pre-oviposition, oviposition, and post-oviposition periods using arranged mating pairs aged 1 to 5 days old. Mating behavior was also observed and documented. The highest fecundity, measured by the number of egg masses and total eggs produced, was recorded in pairings of 1-day-old males and females, indicating a positive effect of young parental age. In contrast, pairings involving 5-day-old males and females resulted in the lowest egg production, demonstrating an inverse relationship between parental …

Oviposition Preference And Behavior Of The Asian Corn Borer, Ostrinia Furnacalis (Guenée) (Lepidoptera: Crambidae), On Corn And Non-Corn Plants Under Semi-Field And Mini-Screen Cage Conditions, Merdelyn T. Caasi-Lit, Jessica B. Baroga-Barbecho, John David C. Cortez, Edwin A. Benigno

The Philippine Agricultural Scientist

Oviposition site selection in Ostrinia furnacalis is a hierarchical, multi-stage process influenced by plant phenology and spatial context. Oviposition preferences under mini-screen cage (Sampaloc) and semi-field (BL2) conditions were evaluated to determine the effects of field size, corn developmental stage, and the presence of non-corn plants on egg deposition patterns. Females deposited significantly more egg masses on 40 DAP (pre-reproductive) corn than on early vegetative-stage plants [Sampaloc: n=437 (40 DAP), n=88 (30 DAP); BL2: n=98 (40 DAP), n=84 (30 DAP)], demonstrating a strong phenological preference, particularly in Sampaloc. The presence of non-corn plants has a negligible …

Characterization Of Adult Emergence Pattern And Eclosion Behavior Of The Asian Corn Borer, [Ostrinia Furnacalis (Guenée)] (Lepidoptera: Crambidae), Under Laboratory And Field Conditions In The Philippines, Marcela M. Navasero, Gelyn D. Sapin, Merdelyn T. Caasi-Lit, Wilson N. De Panis, Randolph N. Candano, Maricon Dp Javier, Jethro M. Navasero, Meijei T. Bangangao

The Philippine Agricultural Scientist

This study focuses on understanding the emergence pattern of Asian Corn Borer (ACB), Ostrinia furnacalis (Guenee), in the Philippines vital in crafting integrated pest management schemes, including insect resistance management against pesticides and Bt protein. Although ACB adults are known to be nocturnal and primarily emerge at night, identifying critical windows of emergence for targeted management actions is essential. In the experiments conducted, the scotophase period is the preferred time for adult emergence under laboratory conditions with 248 adults (80.52%) and 60 adults (19.48%) in the photophase period. A similar trend was also observed under field cage conditions with ACB …

The Effect Of Corn Event Mir162 And The Triple Stacked Hybrid, Bt11 X Mir162 X Ga21, On Key Non-Target Organisms Of Corn, Ireneo L. Lit Jr., Merdelyn T. Caasi-Lit, Kristine O. Abenis, Edwin A. Benigno

The Philippine Agricultural Scientist

Assessments of environmental risks, especially to non-target organisms, are required before genetically modified plants are approved for commercial production. Incorporated genes or traits, whether as single events or stacked or combined with other traits, are treated separately. In compliance with Philippine regulations, confined field trials were conducted to evaluate possible effects of corn event Maximus MIR162 and triple stacked corn hybrid Bt11 x MIR162 x GA21 on non-target arthropods from August 2011 to January 2012 in Laoac, Pangasinan, and Tampakan, South Cotabato. Visual counts and opportunistic sampling, sweep net sampling, pitfall traps, and sticky traps were used at each sampling …

Hardening The Economical Acquisition Of Intersection Data To Improve System Integrity, Anuska Das, Walt Fehr, Andrew Balmos, Mark Goodfriend, Yaguang Zhang, Richard O. Ajagu, James V. Krogmeier, Samuel Labi

Center for Connected and Automated Transportation

Modern traffic management systems increasingly depend on real-time Signal Phase and Timing (SPaT) data generated by Traffic Signal Controllers (TSCs) to support safety, mobility, and emerging connected-vehicle applications. The applications of SPaT outputs require timely and reliable access to such data from the traffic signal controllers. However, these controllers are safety-critical infrastructure and exposing them to external networks introduces significant cybersecurity and operational risks. Thus, there is a need for mechanisms that provide secure, low-latency access to SPaT data without compromising controller integrity. The information flow methods that are used traditionally for connected and automated vehicle (CAV) environments have several …

The Relationship Between Forgiveness And Religiosity In Counseling In The Saudi Population, Salman Alqahtani

Electronic Theses and Dissertations

Forgiveness is an important psychological process associated with religiosity, with both having been shown to support mental health and promote personal growth. Forgiveness remains understudied in Arab and Islamic societies, specifically in Saudi Arabia, where religiosity is an important cultural value. The purpose of this study was to gain a better understanding of the relationship between forgiveness and religiosity among Saudi college students in a faith-oriented and collectivistic society. Data were collected from 106 Saudi college students using the Arabic variation of the Forgiveness and Reconciliation Inventory (A-FRI) and the Arabic Inventory of Religiosity (AIR). Results showed a statistically significant …

Investigating The Origins Of Symbiosis Using A Novel Mycorrhizal Interaction In Pasque Flowers (Pulsatilla Patens), Savannah Lane Draud

Electronic Theses and Dissertations

Mycorrhizal fungi form mutualistic symbioses with most land plants, occurring primarily as arbuscular mycorrhizal (AM) fungi or ectomycorrhizal (ECM) fungi. Pulsatilla patens, an herbaceous perennial widely distributed across Eurasia and North America, belongs to a plant family historically known only to form AM associations. However, recent discoveries of ECM P. patens individuals in northeastern Poland raise questions about the mycorrhizal status and evolutionary trajectory of this species. Because ECM formation in this lineage is likely evolutionarily recent, P. patens offers a valuable system for investigating the ecological and historical factors that facilitate the emergence of ECM symbiosis.

Chapter 1 assessed …

Numerical Studies Of Entanglement Entropy In The Fredkin Spin Chain, Joshua Tyler Moore

Electronic Theses and Dissertations

In this dissertation, we present work on the entanglement properties of the Fredkin spin chain, a spin one-half chain with local three-body interactions. We focus on the development and use of Monte Carlo techniques to measure the entanglement entropy for bipartitions of the Fredkin spin chain.

In the first chapter, we formally develop an extension to existing Monte Carlo techniques to allow for the calculation of higher-order Rényi entanglement entropies using the replica trick. The method clarifies how multiple systems can be simulated in parallel to calculate the Rényi entanglement entropy at any order.

In the next chapter, we apply …

News From Hope College, Volume 57.2: Winter 2025, Hope College

News from Hope College

No abstract provided.

The Effect Of Simulation On Nurses’ Confidence With Providing Post-Fetal Death Support To Bereaved Parents, Monique Scholine, Shannon Zalewski, Erin M. Franklin, Sandria Jamieson, Janelle Diaz, Donna Davis, Kristi Vargo, Nicole Adokou, Kettia Antoine, Natalie Bermudez

Nursing & Health Sciences Research Journal

Introduction: Fetal death (FD) affects one in 10 women worldwide and is associated with negative sequelae such as complicated grief. The negative effects of FD may potentially be mitigated through provision of bereavement support (BS) by trained healthcare workers.

Purpose: The purpose of this study was to explore the effect of simulation on registered nurses’ (RN) confidence in providing BS following FD.

Methods: This was a quasi-experimental study conducted within a South Florida community hospital. Nurses were recruited via email/flyers. Participation in the study entailed attending a post-FD simulation session, and completion of the Perinatal Bereavement Care Confidence Scale (PBCCS) …

Advancements In Sinkhole Remediation: Field Data-Driven Sinkhole Grout Volume Prediction Model Via Machine Learning-Based Regression Analysis, Bubryur Kim, Yuvaraj Natarajan, K. R. Sri Preethaa, V. Danushkumar, Ryan Shamet, Jiannan Chen, Rui Xie, Timothy Copeland, Boo Hyun Nam, Jinwoo An

Civil Engineering Faculty Publications

Sinkhole formation poses a significant geohazard in karst regions, where unpredictable subsurface erosion often necessitates costly grouting for stabilization. Accurate estimation of grout volume remains a persistent challenge due to spatial variability, site-specific conditions, and the limitations of traditional empirical methods. This study introduces a novel machine learning-based regression model for grout volume prediction that integrates cone penetration test (CPT)-derived Sinkhole Resistance Ratio (SRR) values, spatial correlations between CPT and grouting points (GPs), and field-recorded grout volumes from six sinkhole sites in Florida. Three data transformation methods, the Proximal Allocation Method (PAM), the Equitable Distribution Method (EDM), and the Threshold-based …

Upright-Net+: Enhanced Learning Of Upright Orientation For 3d Point Clouds, Xufang Pang, Feng Li, Hongjie Zhuang, Ning Ding, Xiaopin Zhong, Shengfeng He, Wenxi Liu, Bo Jiang

Research Collection School Of Computing and Information Systems

Automatic 3D shape analysis is heavily influenced by the pose of input 3D models, as the continuous nature of pose space introduces complexities that usually exceed the encoding capacities of standard deep learning frameworks. To tackle this challenge, we present Upright-Net+, an enhancement of our previous model, Upright-Net, specifically developed for estimating upright orientation in 3D point clouds. Our approach is grounded in the design principle that ”form ever follows function,” treating the natural base of an object as a functional structure that stabilizes it in its typical pose, influenced by physical laws and geometric properties. We reformulate the continuous …

Safe-Sora: Safe Text-To-Video Generation Via Graphical Watermarking, Zihan Su, Xuerui Qiu, Hongbin Xu, Tangyu Jiang, Jun-Hao Zhuang, Chun Yuan, Ming Li, Shengfeng He, Fei Yu

Research Collection School Of Computing and Information Systems

The explosive growth of generative video models has amplified the demand for reliable copyright preservation of AI-generated content. Despite its popularity in image synthesis, invisible generative watermarking remains largely underexplored in video generation. To address this gap, we propose Safe-Sora, the first framework to embed graphical watermarks directly into the video generation process. Motivated by the observation that watermarking performance is closely tied to the visual similarity between the watermark and cover content, we introduce a hierarchical coarse-to-fine adaptive matching mechanism. Specifically, the watermark image is divided into patches, each assigned to the most visually similar video frame, and further …

Iostom: Offline Imitation Learning From Observations Via State Transition Occupancy Matching, Quang Anh Pham, Brahmanage Janaka Chathuranga Thilakarathna, Tien Mai, Akshat Kumar

Research Collection School Of Computing and Information Systems

Offline Learning from Observations (LfO) focuses on enabling agents to imitate expert behavior using datasets that contain only expert state trajectories and separate transition data with suboptimal actions. This setting is both practical and critical in real-world scenarios where direct environment interaction or access to expert action labels is costly, risky, or infeasible. Most existing LfO methods attempt to solve this problem through state or state-action occupancy matching. They typically rely on pretraining a discriminator to differentiate between expert and non-expert states, which could introduce errors and instability—especially when the discriminator is poorly trained. While recent discriminator-free methods have emerged, …

Cssa-Fusion: Channel Selective And Spatial Alignment Infrared-Visible Image Fusion, Zhen Li, Zhi Zeng, Zhongrui Xiao, Ming Wen, Zhiyuan Zhang, Yibin Tian

Research Collection School Of Computing and Information Systems

Infrared-visible image fusion aims to integrate complementary information from two modalities to generate images with enriched semantic content. However, existing methods often neglect two critical aspects: the design of a local–global feature enhancement architecture and spatial alignment. To address these challenges, we propose Channel Selective and Spatial Alignment Fusion (CSSA-Fusion), a novel framework composed of two synergistic modules. The first is a selective channel and redundancy suppression module, which introduces a dual-branch selective channel attention mechanism to jointly capture local saliency and global channel importance for enhanced feature representation, and an informativeness–redundancy separation strategy to suppress redundant information while preserving …

The Rise Of Parameter Specialization For Knowledge Storage In Large Language Models, Yihuai Hong, Yiran Zhao, Wei Tang, Yang Deng, Yu Rong, Wenxuan Zhang

Research Collection School Of Computing and Information Systems

Over time, a growing wave of large language models from various series has been introduced to the community. Researchers are striving to maximize the performance of language models with constrained parameter sizes. However, from a microscopic perspective, there has been limited research on how to better store knowledge in model parameters, particularly within MLPs, to enable more effective utilization of this knowledge by the model. In this work, we analyze twenty publicly available open-source large language models to investigate the relationship between their strong performance and the way knowledge is stored in their corresponding MLP parameters. Our findings reveal that …

Contx: Scene Context Prediction Via Context Bank And Layout Perception, Jingxin Liang, Yangyang Xu, Haorui Song, Yuan Lu, Yuhui Deng, Yiyi Long, Yan Huang, Shengxin Liu, Jianbo Jiao, Shengfeng He

Research Collection School Of Computing and Information Systems

Scene context prediction, which seeks to infer unknown contextual information from isolated object properties, currently faces limitations due to predominant reliance on pixel-wise supervision that overlooks real-world context priors. To address this, we present ContX, a context-prior-driven, coarse-to-fine model. ContX distinctively integrates explicit linguistic-contextual knowledge in two key ways. First, it proposes a linguistic guided context bank, leveraging linguistic-statistical contextual data to guide the rationality of segmentation shapes and foster meaningful inter-class contextual interactions. Second, ContX augments contextual comprehension by correlating layouts with linguistic descriptions, enhancing layout perception through a multi-modal strategy. Comprehensive experiments demonstrate ContX's superiority and versatility, outperforming …

Pilot-C: Physics-Informed Low-Distortion Optimal Trajectory Compression, Kefei Wu, Baihua Zheng, Weiwei Sun

Research Collection School Of Computing and Information Systems

Location-aware devices continuously generate massive volumes of trajectory data, creating demand for efficient compression. Line simplification is a common solution but typically assumes 2D trajectories and ignores time synchronization and motion continuity. We propose PILOT-C, a novel trajectory compression framework that integrates frequency-domain physics modeling with error-bounded optimization. Unlike existing line simplification methods, PILOT-C supports trajectories in arbitrary dimensions, including 3D, by compressing each spatial axis independently. Evaluated on four real-world datasets, PILOT-C achieves superior performance across multiple dimensions. In terms of compression ratio, PILOT-C outperforms CISED-W, the current state-of-the-art SED-based line simplification algorithm, by an average of 19.2%. For …

Catalytic Synthesis Of Iron-Doped Graphitic Aerogels From Poly(Phloroglucinol-Terephthalaldehyde – Urethane) Precursors, Stephen Yaw Owusu, Rushi U. Soni, Chariklia Sotiriou-Leventis

Chemistry Faculty Research & Creative Works

We report a new class of graphitic carbon aerogel precursors based on iron oxide-doped poly(phloroglucinol-terephthalaldehyde–urethane) (T-POL/PU-FeOx) networks. The hybrid polymeric network incorporates a rigid aromatic triisocyanate, tris(4-isocyanatophenyl)methane, which reacts in situ with the hydroxyl groups of phloroglucinol to form a polyurethane-containing framework. Monolithic aerogels derived from this system undergo catalytic graphitization at significantly reduced temperatures (800–1500 °C) compared to conventional graphitization (2500–3300 °C). An oxidative ring fusion aromatization step (240 °C, air) prior to pyrolysis enhanced the degree of graphitization. The resulting graphitic aerogels were characterized by XRD, Raman spectroscopy, TGA, TEM, SEM, XPS, and N₂ sorption porosimetry. Compared to …

General Test-Time Backdoor Detection In Split Neural Network-Based Vertical Federated Learning, Shunjie Yuan, Xinghua Li, Xuelin Cao, Haiyan Zhang, Robert H. Deng

Research Collection School Of Computing and Information Systems

As a new distributed machine learning framework, vertical federated learning (VFL) has been widely applied in the industry. However, recent studies have demonstrated that VFL faces serious challenges from backdoor attacks, which significantly hinder its further development. Although a few studies have focused on defending against VFL backdoor attacks, these defenses either do not consider the latest attack methods or show limited effectiveness. Moreover, most existing backdoor defense efforts primarily focus on backdoor attacks in horizontal federated learning (HFL) and centralized learning. Due to the unique architecture of VFL models, these methods cannot be directly applied to backdoor defense in …

Kpiroot+: An Efficient Integrated Framework For Anomaly Detection And Root Cause Analysis In Large-Scale Cloud Systems, Wenwei Gu, Renyi Zhong, Guangba Yu, Xinying Sun, Jinyang Liu, Yintong Huo, Zhuangbin Chen, Jianping Zhang, Jiazhen Gu, Yongqiang Yang, Michael R. Lyu

Research Collection School Of Computing and Information Systems

To ensure the reliability of cloud systems, their runtime status reflecting the service quality is periodically monitored with monitoring metrics, i.e., KPIs (key performance indicators). When performance issues happen, root cause localization pinpoints the specific KPIs that are responsible for the degradation of overall service quality, facilitating prompt problem diagnosis and resolution. To this end, existing methods generally locate root-cause KPIs by identifying the KPIs that exhibit a similar anomalous trend to the overall service performance. While straightforward, solely relying on the similarity calculation may be ineffective when dealing with cloud systems with complicated interdependent services. Recent deep learning-based methods …