Digital Commons Network^™

Assessing Factors Of Adherence And Efficacy: A Randomized Controlled Trial Of A Fully Automated Self-Help A-Ebt Website, Leila K. Capel, Emily M. Bowers, Mckenzie R. Becker, Marisa P. Davis, Michael E. Levin, Michael P. Twohig

Psychology Faculty Publications

Treatment for trichotillomania is notably limited, preventing suffering individuals from having access to treatment. To address this need, researchers have developed and tested asynchronous online interventions for adults with trichotillomania. A factor that may impact the efficacy of these programs is the use of phone check-ins (or similar coaching support) to improve treatment adherence in website treatment delivery. In the current study we evaluated the role of check-ins on treatment adherence and efficacy of a website delivering acceptance and commitment therapy-enhanced behavior therapy (A-EBT). A sample of 101 adults with trichotillomania were randomly assigned to an A-EBT web-based intervention with …

A Content Analysis Of Counseling Psychology Literature: Resilience Against Oppression Among People Of Color, David C. Stanley Jr., Rawan H. Atari-Khan

Psychology Faculty Research and Publications

The researchers analyzed articles from two flagship counseling psychology journals (i.e., Journal of Counseling Psychology and The Counseling Psychologist) to examine current understandings of resilience. There were 54 articles included in the final analysis that spanned the years 1997–2022. The researchers conducted a content analysis to identify, analyze, and report patterns across counseling psychology journals with regard to how resilience has been defined, the racial/ethnic groups that were of focus, and the forms of oppression that were studied or addressed. Five themes were generated that are a direct representation of the topics within previous literature on resilience in the field …

Evaluating The Efficacy Of And Preference For Interactive Computer Training With Student-Generated Examples, Sylvia C. Aquino, Stephanie Hood, Tara A. Fahmie, Richard Tanis

Psychology Faculty Research and Publications

Designing effective and preferred teaching practices for undergraduate students are common goals in behavior analytic training programs. A preliminary study by Nava et al. (2019) showed that undergraduate students generally rated peer-generated examples of the principles of behavior analysis as more preferred, relatable, and culturally responsive than traditional textbook examples. However, peer-generated examples did not result in any improvement in performance on concept knowledge assessments. The current study extended the study by Nava et al. by embedding peer-generated examples within interactive computer training (ICT) to provide opportunities for active responding, prompt fading, automated feedback, and practice with examples and nonexamples. …

Rules, Privacy, And Ethics: Challenges In Creating Author Name Change Guidelines, Angela Yon, Emily Baldoni, Eric Willey

Faculty and Staff Publications – Milner Library

People change their names for a variety of reasons, including, but not limited to, gender transition, change in marital status, and religious conversion. Guidance on the metadata management of author name changes for the myriad resources in a library’s discovery system is elusive and absent. Executing metadata for name changes creates many challenges in a rapidly advancing infrastructure of emerging discovery technologies, aggregators with shared metadata in multiple schemas, and numerous formats in varied platforms. Moreover, it is difficult to find a balanced approach to ethically apply evolving cataloging and name authority control rules to suit the linked data environment. …

Evaluating The Impact Of Spot Position Errors On Dose Distribution: A Comparison Between Spot-Scanning Arc Therapy (Sparc) And Intensity-Modulated Proton Therapy (Impt), Peilin Liu, Lewei Zhao, Gang Liu, Xiaoda Cong, Xiaoqiang Li, Xuanfeng Ding

Conference Presentation Abstracts

Purpose: To quantitatively investigate the impact of spot position error (PE) on the dose distribution in (Spot-scanning arc therapy) SPArc plans versus Intensity-Modulated Proton Therapy (IMPT).

Methods:

Four representative disease sites, including brain, lung, liver, and prostate cancers, were retrospectively selected. Spot position errors were simulated during dynamic SPArc treatment delivery. Two types of errors were generated, including randomized error and systematic error. For each random error scenario, they were further examined across four sub-scenarios (25%, 50%, 75%, and 100% of spots affected) at 1 mm and 2 mm deviations.The randomized errors used two categories with and without Gaussian distribution …

Response To Letter To The Editor Concerning The Article "The Clinical And Economic Impact Of Extended Battery Longevity Of A Substernal Extravascular Implantable Cardioverter Defibrillator"., Bradley P Knight, Nicolas Clémenty, Anish Amin, Ulrika Maria Birgersdotter-Green, Henri Roukoz, Reece Holbrook, Jaimie Manlucu

Heart and Vascular Articles

No abstract provided.

Impact Of Functional Recovery On Patients Having Heart Surgery., Richard J Snow, Lauren Mckown, Geoffrey Blossom, Karen Vogel, Amy Creighton, Jason Shriver, Linda Will, Katie Lentz, Elizabeth Snow, Teresa Caulin-Glaser

Heart and Vascular Articles

OBJECTIVE: To describe the results of a program developed to manage institutional postacute care (IPAC) (postacute skilled nursing, inpatient rehabilitation facility, and long-term acute care) in a CMS Bundled Payments for Care Improvement (BPCI) project for coronary artery bypass graft (CABG) surgery.

STUDY DESIGN: We compared pre- and postutilization patterns during a 3-year period by evaluating risk-adjusted national, state, and other BPCI participant comparisons using a difference-in-differences (DID) analysis in a large urban community tertiary center with a CABG surgery program. Included in the analysis were all Medicare patients receiving CABG surgery at the institution (n = 504), across the …

Exploring Ngc 2287: An Investigation Of Open Cluster Membership, Rotation, And A Curiously Bifurcated Main Sequence, Benjamin J. Ramsey

Theses

The study of stellar clusters is integral to our understanding of many areas of astrophysics because of the role they play as astrophysical benchmarks. Thanks to shared characteristics (in particular, age and chemical composition) of their members, open star clusters represent essential subjects to address contemporary problems in stellar structure, formation, and evolution. The rich open cluster NGC 2287 (the Little Beehive) is young (age~200 Myr), relatively nearby (D~735 pc), and suffers little intervening extinction, making it ripe for further study. The cluster is particularly noteworthy for displaying a rotationally bifurcated upper main sequence. We are investigating the membership and …

Accreditation Update, Georgia Southern University

Institutional Assessment & Accreditation

No abstract provided.

The George-Anne Daily, Georgia Southern University

George-Anne Media Group: Newsletters & Magazines

No abstract provided.

Video Editing For Video Retrieval, Bin Zhu, Kevin Flanagan, Adriano Fragomeni, Michael Wray, Dima Damen

Research Collection School Of Computing and Information Systems

Though pre-training vision-language models have demonstrated significant benefits in boosting video-text retrieval performance from large-scale web videos, fine-tuning still plays a critical role with manually annotated clips with start and end times, which requires considerable human effort. To address this issue, we explore an alternative cheaper source of annotations, single timestamps, for video-text retrieval. We initialise clips from timestamps in a heuristic way to warm up a retrieval model. Then a video clip editing method is proposed to refine the initial rough boundaries to improve retrieval performance. A student-teacher network is introduced for video clip editing: the teacher model is …

Stagedvulbert: Multi-Granular Vulnerability Detection With A Novel Pre-Trained Code Model, Yuan Jiang, Yujian Zhang, Xiaohong Su, Christoph Treude, Tiantian Wang

Research Collection School Of Computing and Information Systems

The emergence of pre-trained model-based vulnerability detection methods has significantly advanced the field of automated vulnerability detection. However, these methods still face several challenges, such as difficulty in learning effective feature representations of statements for fine-grained predictions and struggling to process overly long code sequences. To address these issues, this study introduces StagedVulBERT, a novel vulnerability detection framework that leverages a pre-trained code language model and employs a coarse-to-fine strategy. The key innovation and contribution of our research lies in the development of the CodeBERT-HLS component within our framework, specialized in hierarchical, layered, and semantic encoding. This component is designed …

Kpiroot: Efficient Monitoring Metric-Based Root Cause Localization In Large-Scale Cloud Systems, Wenwei Gu, 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 run-time 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 …

Ocapo: Fine-Grained Occupancy-Aware, Empirically-Driven Pdc Control In Open-Plan, Shared Workspaces, Ravi Anuradha, Dulaj Sanjaya Weerakoon, Archan Misra

Research Collection School Of Computing and Information Systems

Passive Displacement Cooling (PDC) is a relatively recent technology gaining attention as a means of significantly reducing building energy consumption overheads, especially in tropical climates. PDC eliminates the use of mechanical fans, instead using chilled-water heat exchangers to perform convective cooling. In this paper, we identify and characterize the impact of several key parameters affecting occupant comfort in a 1000m2 open-floor area (consisting of multiple zones) of a ZEB (Zero Energy Building) deployed with PDC units and tackle the problem of setting the temperature setpoint of the PDC units to assure occupant thermal comfort and yet conserve energy. We tackle …

Retrofitting A Legacy Cutlery Washing Machine Using Computer Vision, Hua Leong Fwa

Research Collection School Of Computing and Information Systems

Industry 4.0, the digitalization of manufacturing promises to lead to lowered cost, efficient processes and even discovery of new business models. However, many of the enterprises have huge investments in legacy machines which are not 'smart'. In this study, we thus designed a cost-efficient solution to retrofit a legacy conveyor belt-based cutlery washing machine with a commodity web camera. We then applied computer vision (using both traditional image processing and deep learning techniques) to infer the speed and utilization of the machine. We detailed the algorithms that we designed for computing both speed andutilization. With the existing operational constraints of …

History Happenings, Georgia Southern University

History: News & Publications

• Savannah Events and Statesboro Events
• History Chats by Makenzie Lewis
• Faculty Activities
• Student Activities
• Event Spotlight
• Alumni News and Activities

Evaluation Of The Proposed Strategy For The Iraqi Media Network For The Period (2024-2028), Field Research, Aous Mahmood Ibrahim, Yousif Aftan Abdullah, Muhammad Umar

Journal of Economics and Administrative Sciences

The current research aims to study a crucial phase of strategic management, which is strategic evaluation, to assess the proposed strategy through data analysis, ensuring its implementation with minimal deviation from the planned course. The research focuses on studying and evaluating the proposed strategy for the Iraqi media network for the years 2024-2028, examining its effectiveness and alignment with the state's directions. This involves understanding the realism of strategic visions, plans, and programs and building a suitable conceptualization. The research takes into consideration the environmental conditions and relies on scientific principles and steps to formulate a comprehensive and realistic strategy. …

Foss: Towards Fine-Grained Unknown Class Detection Against The Open-Set Attack Spectrum With Variable Legitimate Traffic, Ziming Zhao, Zhaoxuan Li, Xiaofei Xie, Jiongchi Yu, Fan Zhang, Rui Zhang, Binbin Chen, Xiangyang Luo, Ming Hu, Wenrui Ma

Research Collection School Of Computing and Information Systems

Anomaly-based network intrusion detection systems (NIDSs) are essential for ensuring cybersecurity. However, the security communities realize some limitations when they put most existing proposals into practice. The challenges are mainly concerned with (i) fine-grained unknown attack detection and (ii) ever-changing legitimate traffic adaptation. To tackle these problem, we present three key design norms. The core idea is to construct a model to split the data distribution hyperplane and leverage the concept of isolation, as well as advance the incremental model update. We utilize the isolation tree as the backbone to design our model, named FOSS, to echo back three norms. …

Themis: Automatic And Efficient Deep Learning System Testing With Strong Fault Detection Capability, Dong Huang, Tsz On Li, Xiaofei Xie, Heming Cui

Research Collection School Of Computing and Information Systems

Deep Learning Systems (DLSs) have been widely applied in safety-critical tasks such as autopilot. However, when a perturbed input is fed into a DLS for inference, the DLS often has incorrect outputs (i.e., faults). DLS testing techniques (e.g., DeepXplore) detect such faults by generating perturbed inputs to explore data flows that induce faults. Since a DLS often has infinitely many data flows, existing techniques require developers to manually specify a set of activation values in a DLS’s neurons for exploring fault-inducing data flows. Unfortunately, recent studies show that such manual effort is tedious and can detect only a tiny proportion …

Exploring Conversations Between A Practitioner And A Person With Dementia, Kotaro Hara, Rosiana Natalie, Wei Soon Cheong, Jingjing Gu, Qianli Xu

Research Collection School Of Computing and Information Systems

In social service centers, practitioners engage in conversations with clients with dementia to facilitate their daily activities and provide support when they are distressed. However, the nature of the care demands the practitioner’s active engagement, which becomes difficult to deliver as the number of people who need care expands. Researchers have been investigating the efficacy of developing agents that assume conversational tasks to alleviate this work. To contribute to the future design of agents for caregiving, we collected and analyzed ten conversations between clients with mild dementia and practitioners who provide care. Our analyses of turn-taking dynamics and dialogue acts …

Efficient Cascaded Multiscale Adaptive Network For Image Restoration, Yichen Zhou, Pan Zhou, Teck Khim Ng

Research Collection School Of Computing and Information Systems

Image restoration, encompassing tasks such as deblurring, denoising, and super-resolution, remains a pivotal area in computer vision. However, efficiently addressing the spatially varying artifacts of various low-quality images with local adaptiveness and handling their degradations at different scales poses significant challenges. To efficiently tackle these issues, we propose the novel Efficient Cascaded Multiscale Adaptive (ECMA) Network. ECMA employs Local Adaptive Module, LAM, which dynamically adjusts convolution kernels across local image regions to efficiently handle varying artifacts. Thus, LAM addresses the local adaptiveness challenge more efficiently than costlier mechanisms like self-attention, due to its less computationally intensive convolutions. To construct a …

Graph Continual Learning With Debiased Lossless Memory Replay, Chaoxi Niu, Guansong Pang, Ling Chen

Research Collection School Of Computing and Information Systems

Real-life graph data often expands continually, rendering the learning of graph neural networks (GNNs) on static graph data impractical. Graph continual learning (GCL) tackles this problem by continually adapting GNNs to the expanded graph of the current task while maintaining the performance over the graph of previous tasks. Memory replay-based methods, which aim to replay data of previous tasks when learning new tasks, have been explored as one principled approach to mitigate the forgetting of the knowledge learned from the previous tasks. In this paper we extend this methodology with a novel framework, called Debiased Lossless Memory replay (DeLoMe). Unlike …

The Relationship Of Acculturation With The Health Numeracy And Associated Health Behaviors Of Filipino-Americans, Ashwini Wagle, J. Cuaresma, Giselle A.P. Pignotti

Faculty Research, Scholarly, and Creative Activity

Describe relationships between acculturation level and the following variables - dietary acculturation and intake, health numeracy, physical activity, and anthropometric measurements - among Filipino-American men and women.

Towards An Extended Resource Theory Of Marital Power: Parental Education And Household Decision-Making In Rural China, Cheng Cheng, Yu Xie

Research Collection School of Social Sciences

Existing literature on the resource theory of marital power has focused on the relative resources of spouses and overlooked the resource contributions of spouses’ extended families. We propose an extended resource theory that considers how the comparative resources of a couple’s natal families are directly associated with marital power, net of the comparative resources of the couple. Using data from the China Panel Family Studies, we examine how the relative education of a couple’s respective parents affects the wife’s decision-making power, net of the relative education of the couple. Results suggest that the higher the wife’s parental education relative to …

Does Relationship Conflict Reduce Novel Idea Communication Through Perceived Leader Openness? Power Distance Orientation As A Moderator, Ming-Hong Tsai

Research Collection School of Social Sciences

Purpose: This paper aims to investigate why followers have low perceptions of leader openness and thus feel reluctant to communicate novel ideas by examining leader–follower relationship conflict (i.e. interpersonal incompatibility) and a follower’s power distance orientation (i.e. an acceptance of uneven power distribution in organizations) as antecedents. Design/methodology/approach: The research administrators conducted a three-wave work behavior survey in Study 1, a laboratory experiment in Study 2, and an online experiment in Study 3. Findings: The results demonstrated that leader–follower relationship conflict reduced followers’ perceptions of leader openness. However, the negative impact of relationship conflict became non-significant when followers have high …

What Is Beyond Measurement For Social Cohesion?, Qian Hui Tricia Tok, Orlando Woods, Lily Kong

Research Collection College of Integrative Studies

“What gets measured gets managed” has long been a mantra to rally improvement throughout various domains of life. Perhaps this is also the case for existing work on social cohesion, whereby much of its conceptual and operational elements have received interest in both academic and policy research aiming for practical improvement with regard to the cohesiveness of communities and societies. We contend, however, that not everything that matters for social cohesion may be measurable, and not everything that has been measured for social cohesion may matter. This is not to suggest that not measuring any indicators is better than measuring …

Enhancing Recipe Retrieval With Foundation Models: A Data Augmentation Perspective, Fangzhou Song, Bin Zhu, Yanbin Hao, Shuo Wang

Research Collection School Of Computing and Information Systems

Learning recipe and food image representation in common embedding space is non-trivial but crucial for cross-modal recipe retrieval. In this paper, we propose a new perspective for this problem by utilizing foundation models for data augmentation. Leveraging on the remarkable capabilities of foundation models (i.e., Llama2 and SAM), we propose to augment recipe and food image by extracting alignable information related to the counterpart. Specifically, Llama2 is employed to generate a textual description from the recipe, aiming to capture the visual cues of a food image, and SAM is used to produce image segments that correspond to key ingredients in …

Beat-It : Beat-Synchronized Multi-Condition 3d Dance Generation, Zikai Huang, Xuemiao Xu, Cheng Xu, Huaidong Zhang, Chenxi Zheng, Jing Qin, Shengfeng He

Research Collection School Of Computing and Information Systems

Dance, as an art form, fundamentally hinges on the precise synchronization with musical beats. However, achieving aesthetically pleasing dance sequences from music is challenging, with existing methods often falling short in controllability and beat alignment. To address these shortcomings, this paper introduces Beat-It, a novel framework for beat-specific, key pose-guided dance generation. Unlike prior approaches, Beat-It uniquely integrates explicit beat awareness and key pose guidance, effectively resolving two main issues: the misalignment of generated dance motions with musical beats, and the inability to map key poses to specific beats, critical for practical choreography. Our approach disentangles beat conditions from music …

D2sr: Decentralized Detection, De-Synchronization, And Recovery Of Lidar Interference, Darshana Rathnayake, Hemanth Sabbella, Meera Radhakrishnan, Archan Misra

Research Collection School Of Computing and Information Systems

We address the challenge of multi-LiDAR interference, an issue of growing importance as LiDAR sensors are embedded in a growing set of pervasive devices. We introduce a novel approach named D2SR, enabling decentralized interference detection, mitigation, and recovery without explicit coordination among nearby LiDAR devices. D2SR comprises three stages: (a) Detection, which identifies interfered frames, (b) Mitigation, which performs time-shifting of a LiDAR’s active period to reduce interference, and (c) Recovery, which corrects or reconstructs the depth values in interfered regions of a depth frame. Key contributions include a lightweight interference detection algorithm achieving an F1-score of 92%, a simple …

Nigerian Software Engineer Or American Data Scientist? Github Profile Recruitment Bias In Large Language Models, Takashi Nakano, Kazumasa Shimari, Raula Gaikovina Kula, Christoph Treude, Marc Cheong, Kenichi Matsumoto

Research Collection School Of Computing and Information Systems

Large Language Models (LLMs) have taken the world by storm, demonstrating their ability not only to automate tedious tasks, but also to show some degree of proficiency in completing software engineering tasks. A key concern with LLMs is their “black-box” nature, which obscures their internal workings and could lead to societal biases in their outputs. In the software engineering context, in this early results paper, we empirically explore how well LLMs can automate recruitment tasks for a geographically diverse software team. We use OpenAI's ChatGPT to conduct an initial set of experiments using GitHub User Profiles from four regions to …