Digital Commons Network^™

Diffusion Model For Human Motion Generation With Fine-Grained Text And Spatial Control Signals, Binze Jiang, Wenfeng Song, Xia Hou, Shuai Li

Journal of System Simulation

Abstract: To improve the accuracy, controllability, and realism of text-driven human motion generation, a novel method is proposed that integrates fine-grained textual semantics with spatial control signals. Within the diffusion model framework, both global text tokens and body-part-level local tokens are introduced. These are encoded using CLIP to obtain corresponding features, which are then fed into the motion diffusion model to enable fine control over different body parts. Spatial guidance is used to dynamically adjust joint positions during the diffusion denoising process, ensuring that the generated motion adheres to spatial constraints. Realism guidance is incorporated to enhance the naturalness and …

Virtual Reality Rehabilitation Training System Based On Multimodal Brain-Computer Interface, Jing Qu, Kaining Fang, Shantong Zhu, Lingguo Bu

Journal of System Simulation

Abstract: The aging population has led to an increasing demand for rehabilitation for cognitive and motor functions. In response to the lack of interest in traditional rehabilitation and the absence of objective physiological assessment in existing virtual reality (VR) rehabilitation systems, a VR rehabilitation training system based on multimodal brain computer interface is developed by integrating VR interaction, near-infrared brain functional imaging, and motion capture technology. An immersive cognitive-motor integrated training environment was constructed to guide users in completing upper limb tasks. By recruiting subjects and synchronously collecting brain network data and Kinect upper limb motion parameters, multimodal assessment …

Defect Detection Method Based On Hierarchical Microscopic Feature Modeling And Simulation, Jing Zou, Xu Tan, Junji Mao, Haidong Gao, Jianrong Tan

Journal of System Simulation

Abstract: To address the challenge of detecting small and low-contrast defects in complex microscopic images, a defect method technology based on hierarchical microscopic feature modeling and simulation is proposed. The method is built on the RT-DETR (real-time detection transformer)framework to construct the HM-RTDETR (hierarchical microscopic RT-DETR) model. It maintains the global feature modeling ability of the Transformer and introduces a Dense O2O-Mosaic, a high-density one-to-one Mosaic augmentation strategy, to increase supervision density for small samples. A depthwise separable convolution (DWConv) module is used to enhance local detail extraction in microscopic textures, and a learnable PatchExpand module is applied …

Material Reconstruction From Single Image Combining Neural Networks With Singular Value Decomposition, Zhiqiang Li, Xukun Shen, Yong Hu, Xueyang Zhou, Yifan Chen

Journal of System Simulation

Abstract: The tabulated BRDFs (bidirectional reflectance distribution function) can realistically reproduce the surface appearance of objects. However, due to their high-dimensional characteristics and the fact that a single planar image contains limited reflectance information and small differences, methods for estimating tabulated BRDFs typically require complex equipment or the capture of multiple images. To address this issue, a method is proposed for reconstructing material properties from a single image by combining neural networks with singular value decomposition. The singular value decomposition is introduced to compress the material into a lower-dimensional space. The task of solving the tabulated BRDFs is simplified to …

Full-Body Co-Speech Gesture Generation Based On Spatial-Temporal Enhanced Generation Model, Shuozhe Zhang, Wenfeng Song, Xia Hou, Shuai Li

Journal of System Simulation

Abstract: Full-body co-speech gesture generation significantly enhances the interactivity of virtual digital humans, requiring generated gestures to not only align accurately with speech but also demonstrate realistic full-body dynamics. To address limitations of existing methods—Transformer-based approaches often overlook temporal features of action sequences, while diffusion model-based ones inadequately capture spatial correlations between body parts, a full-body action generation method integrating diffusion models, Mamba, and attention mechanisms is proposed. We introduce the spatial self-attention-temporal state space model (STMamba Layer) as the core of denoising network to extract
inter-part spatial features and intra-part temporal features, thus enhancing action quality and diversity. …

Vrbt: Vr Badminton Training With Multitask Injury Alerts Based On Lightweight 3d Skeletal Reconstruction, Yuning Zhu, Meng Yang, Tianyue Chen, Weiliang Meng

Journal of System Simulation

Abstract: To overcome the limitations of traditional badminton training, a VR training method that integrates multiple models for collaborative simulation is proposed. A "perception-decision- interaction" framework is developed within Unity, featuring diverse training modules powered by a physics engine for realistic trajectory simulation. The system employs a lightweight MHFormer for 3D pose estimation and a novel multi-task model (enhanced injury prediction system, EIPS) that combines random forest and XGBoost to jointly assess injury risk. This approach offers a solution for balancing real-time performance with accuracy in skeleton reconstruction and enables personalized training through dynamic risk assessment.

Addressing The Void Of Ai Policies In Education For Students With Specific Learning Disabilities, Mikyung Shin, Fatmana Deniz, Latesha Watson, Cynthia Dieterich, Kathy B. Ewoldt, Friggita Johnson, Jennifer E. Kong, Sung Hee Lee, April Whitehurst

Education Faculty Articles and Research

The purpose of this study was to identify the current state of artificial intelligence (AI) policies in U.S. education and propose actionable recommendations through large language model–based topic modeling and Delphi surveys. Out of 12 policy documents released between 2015 and 2025, only two documents (National Center for Learning Disabilities, 2024; W.A. v. Clarksville/Montgomery County School System, 2024) specifically addressed learning disabilities. Policy documents addressing topics such as AI-driven risk assessment, data protection, legal risk management, and ethical guidelines covering other disabilities and general AI in education policy were provided as baselines that could be discussed and validated through …

Inverse Kinematics 3d Human Modeling Simulation Based On Multi-View Vision, Guoyu Fang, Yanze Li, Kai Chen, Xiaodong Zhao, Zizhuo Hu, Mingshi Yang, Wanqing Wu, Zichen Wang, Wenkai Guo

Journal of System Simulation

Abstract: In autonomous driving simulation and industrial virtual reality simulation, there is a high demand for accuracy and robustness in 3D human body modeling. However, current joint-based human modeling approaches suffer from issues such as continuous modeling jitter, local distortion, and poor adaptability to occlusion, which degrade model quality and limit the development of practical applications such as intelligent driving and digital factories. To address these challenges, this paper proposes a multi-view vision-based inverse kinematics 3D human modeling method using a vector quantized variational autoencoder(IK-VQ-VAE). By integrating joint training with an automatic variational gradient descent approach, the proposed method achieves …

Pdr-Stgcn: An Enhanced Stgcn With Multi-Scale Periodic Fusion And A Dynamic Relational Graph For Traffic Forecasting, Jie Hu, Bingbing Tang, Langsha Zhu, Yiting Li, Jianjun Hu, Guanci Yang

Faculty Publications

Accurate traffic flow prediction is a core component of intelligent transportation systems, supporting proactive traffic management, resource optimization, and sustainable urban mobility. However, urban traffic networks exhibit heterogeneous multi-scale periodic patterns and time-varying spatial interactions among road segments, which are not sufficiently captured by many existing spatio-temporal forecasting models. To address this limitation, this paper proposes PDR-STGCN (Periodicity-Aware Dynamic Relational Spatio-Temporal Graph Convolutional Network), an enhanced STGCN framework that jointly models multi-scale periodicity and dynamically evolving spatial dependencies for traffic flow prediction. Specifically, a periodicity-aware embedding module is designed to capture heterogeneous temporal cycles (e.g., daily and weekly patterns) and …

Virtual-Real Fusion Simulation Technology And Application Research For Industrial Control Systems Cybersecurity Of Process Manufacturing, Xinwei Wang, Jinjiang Wang, Zheng Wang, Laibin Zhang

Journal of System Simulation

Abstract: Aiming at the problem that the industrial control system in the process manufacturing industry lacks an effective attack and defense drill platform when facing network attacks, it is difficult to truly simulate the attack situation, verify the protective measures, and accurately evaluate the impact of attacks on the physical system, an industrial control cybersecurity simulation technology based on virtual-real fusion is proposed to build an efficient attack and defense drill range. The industrial control cybersecurity simulation architecture based on virtual-real fusion is designed, and the consistency analysis of virtual-real fusion data is carried out. At the same time, …

Spatio-Temporal Swin Transformer-Based Flow-Solid Coupling Interaction Sequence Image Prediction Network, Changjun Zou, Zhiyu Ge, Chenxi Zhong

Journal of System Simulation

Abstract: To address limitations in modeling long-term dependencies and multi-scale features in fluidstructure interaction scenarios, a spatiotemporal deep learning model (SwinLSTM) integrating ConvLSTM and Swin Transformer is proposed. The model employs a gated spatiotemporal attention mechanism that dynamically embeds Swin Transformer's window-based multi-head self-attention into ConvLSTM's output gate, enabling adaptive temporal-spatial feature coupling, and designs a multi-level ConvLSTM framework to hierarchically capture complex spatiotemporal correlations. Experiments on a self-built fluid-interaction dataset show that our method achieves the highest PSNR and leading SSIM scores, with superior performance in preserving vortex details and boundary consistency. This work provides an efficient solution …

Research On Real-Time Animatable Human Avatar Generation Via 3d Gaussian Splatting, Yuyou Zhong, Xukun Shen, Yong Hu

Journal of System Simulation

Abstract: Real-time animatable 3D human avatar generation technology hold significant application value in fields such as virtual reality and remote collaboration. To address the limitations of existing methods in detail modeling, real-time performance, and robustness under novel pose driving, an efficient human avatar generation and driving method based on 3D Gaussian splatting (3DGS) is proposed. This method integrates optimized parametric human reconstruction, tri-plane feature encoding, and dynamic offset prediction to achieve efficient modeling from monocular video input. By introducing a skeleton binding and visibility analysis strategy, while designing a multi-scale regularization loss to address the overfitting problem. Simulation experiments demonstrate …

Military Metaverse: Conceptual Connotation, Construction And Application Framework, Key Issues, Dayong Liu, Zhiming Dong, Jiancheng Gao

Journal of System Simulation

Abstract: Based on the analysis of the concept of the metaverse, the military metaverse concept model is established and compared with virtual-real fusion systems such as the digital twin battlefield, analyzing its core characteristics and construction significance. To accelerate the construction of the military metaverse, an overall logical architecture for the construction and application of the military metaverse is designed, the concept of military metaverse primitives is proposed, and the technical architecture is designed. The main application directions of the military metaverse are analyzed, and the construction stage division and overall thinking are provided. The key issues in construction and …

Pl-Mamba: A 3d Point Cloud Semantic Segmentation Network Based On Bimodal Fusion, He Zhu, Feng Zhou, Mengxiao Zhu, Ju Dai

Journal of System Simulation

Abstract: To enhance the semantic discrimination capability in point cloud semantic segmentation, a 3D point cloud semantic segmentation network named PL-Mamba is proposed, which is centered on the fusion of point cloud (P) and language (L) dual modalities. This method takes PointMamba as the backbone network, leveraging its excellent long-sequence modeling and global perception capabilities. It introduces a language prompt mechanism and uses a pretrained language model BERT to encode the context of category labels, obtaining semantically rich text features. The text information serves as a language guided token and is deeply integrated with point cloud features through cross modal …

Dehpr: A Diffusion-Based End-To-End Hand Pose Reconstruction Network, Guoqiong Liao, Longjie Huang, Qingxin Li, Jiajun Zhang, Kefan Chen

Journal of System Simulation

Abstract: Traditional methods such as convolutional neural networks (CNNs) and Transformers suffer from strong dependence on large-scale annotated data and limited generalization capability when dealing with hand pose reconstruction in complex scenarios. To address these issues, a diffusion-based end-to-end hand pose reconstruction network (DEHPR) is proposed. This method employs a diffusion model to directly generate and refine 3D predictions, thereby reducing spatial uncertainties inherent in 2D-to-3D modeling paradigms. By incorporating an end-to-end framework that reprojects multiple 3D candidate predictions to select optimal joint positions, the approach ultimately produces accurate hand pose estimations. Comprehensive evaluations conducted on HO3D V2, DexYCB, …

Cross-Domain Crowd Counting Model Based On Frequency Domain Enhancement, De Zhang, Zishan Liang, Ningning Liu

Journal of System Simulation

Abstract: Crowd counting takes video surveillance data as input and can be applied to the construction of city digital twin platforms, virtual city modeling and smart city management, etc. However, when there are data domain differences between the application scenario and training scenario, counting performance often significantly decreases. A cross-domain crowd counting model based on frequency domain enhancement is proposed. To alleviate the distribution differences between domains, a frequency domain feature enhancement module and a domain invariant frequency domain adapter module are constructed: the former uses discrete cosine transform to extract key statistical features to enhance spatial representation ability, while …

Fatigue Crack Length Estimation Using Acoustic Emissions Technique-Based Convolutional Neural Networks, Asaad Migot, Ahmed Saaudi, Roshan Joseph, Victor Giurgiutiu

Faculty Publications

Fatigue crack propagation is a critical failure mechanism in engineering structures, requiring meticulous monitoring for timely maintenance. This research introduces a deep learning framework for estimating fatigue fracture length in metallic plates through acoustic emission (AE) signals. AE waveforms recorded during crack growth are transformed into time-frequency images using the Choi–Williams distribution. First, a clustering system is developed to analyze the distribution of the AE image-based dataset. This system employs a CNN-based model to extract features from the input images. The AE dataset is then divided into three categories according to fatigue lengths using the K-means algorithm. Principal Component Analysis …

The Impact Of Congenital Heart Disease On The Timing Of Alzheimer's Disease In Down Syndrome., Julianne G. Clina, Brian C. Helsel, Sigan L. Hartley, David A. White, Victoria L. Fleming-Batayneh, Benjamin Handen, Bradley Christian, Elizabeth Head, Mark Mapstone, Christy L. Hom, Beau Ances, Jeffrey Burns, H Diana Rosas, Florence Lai, Sharon Krinsky Mchale, Joseph H. Lee, Frederick A. Schmitt, Jordan Harp, Ira T. Lott, Shahid Zaman, Lauren T. Ptomey, Alzheimer Biomarker Consortium–Down Syndrome (Abc‐Ds) Investigators

Manuscripts, Articles, Book Chapters and Other Papers

INTRODUCTION: The incidence of Alzheimer's disease (AD) in Down syndrome (DS) exceeds 90%. Approximately 50% of people with DS have congenital heart disease (CHD). Having CHD increases risk for early-onset AD in populations without DS, but it is unclear if CHD influences AD in DS.

METHODS: Data from the Alzheimer Biomarker Consortium-Down Syndrome (ABC-DS) were used. Participants with CHD (n = 82, mean age = 39.9 ± 8.5 years, 97.6% White race) were age- and sex-matched to participants without CHD (n = 82, mean age = 40.5 ± 8.1 years, 98.8% White race). Cognitive assessments and Centiloid load …

Model Kurva Pertumbuhan Pra Sapih Dari Sapi Madura Betina Dan Jantan, Karnaen

Jurnal Ilmu Ternak Universitas Padjadjaran

Kurva pertumbuhan merupakan pencerminan kemampuan suatu individu untuk menampilkan potensi genetic dan perkembangan bagian-bagian tubuh mencapai dewasa. Penelitian mengenai model kurva pertumbuhan sapi Madura betina dan jantan dari lahir sampai umur 6 bulan telah dilaksanakan di kabupaten Bangkalan. Tujuan penelitian ini adalah untuk mengetahui kurva pertumbuhan sapi madura periode pra sapih. Penelitian ini menggunakan metode observasi dengan sample acak sebanyak 57 ekor sapi. Data yang diperoleh dianalisis regresi. Hasil analisis menunjukkan bahwa model kurva pertumbuhan sapi madura betina dan jantan dari lahir sampai 6 bulan mengikuti model persamaan regresi alometrik dengan koefisien determinan R² = 0,9950 dan R^{2 …}

Model Matematika Kurva Produksi Telur Ayam Broiler Breeder Parent Stock, A. Anang, H. Indrijani, T.A. Sundara

Jurnal Ilmu Ternak Universitas Padjadjaran

Produksi telur membentuk suatu kurva dengan model matematika tertentu. Penelitian ini bertujuan untuk mendapatkan model matematika terbaik untuk menggambarkan  kurva produksi telur ayam broiler breeder parent stock Cobb 500 umur 24-45 minggu. Model matematika yang diuji dalam penelitian ini ada empat, yaitu model Mc Millan, model Yang, model Logistik, dan model Adams-Bell. Model Adams-Bell dengan rumus  memiliki kecocokan yang  paling baik dengan koefisien determinasi (R²) = 0,9998, koefisien korelasi (r) = 0,999, dan galat baku (SE) = 1,060. Dengan menggunakan model Adams-Bell ini, dapat dibuat suatu dugaan kurva produksi telur broiler breeder parent stock umur 24-45 minggu.

Kata …

Mathematical Models To Describe Egg Production In Laying Hens (Review) (Model Matematik Untuk Menggambarkan Kurva Produksi Telur Pada Ayam Petelur (Review)), A. Anang, H. Indrijani

Jurnal Ilmu Ternak Universitas Padjadjaran

Makalah ini bertujuan untuk me-review model matematik yang dapat mendeskripsikan kurva produksi telur pada ayam petelur. Kurva produksi telur umumnya sama, baik untuk bangsa ataupun strain, yaitu meningkat pada awal masa bertelur untuk mencapai puncaknya pada umur tertentu dan akan menurun secara gradual sampai akhir periode bertelur. Banyak model matematik kurva produksi telur yang sudah dipublikasikan, dan pada umumnya model-model tersebut sudah cukup bila digunakan untuk menduga produksi telur saja, tapi jika untuk keperluan pemuliaan ternak, perlu dikembangkan model yang bisa menduga produksi pada populasi yang kecil. Jika karakteristik kematangan seksual turut dipertimbangkan, maka model Yang lebih menguntungkan jika dibandingkan …

Acknowledgement Of Reviewers

Journal of Sustainable Mining

No abstract provided.

A Critical Appraisal On The Injury Susceptibility Of Underground Metalliferous Mine Workers: Application Of Logistic Regression Model, Sudip Das, Falguni Sarkar, P.S. Paul, B.K. Pal

Journal of Sustainable Mining

The aim of this study is to analyze the occupational injury data of Indian underground metalliferous mines for scrutinizing the injury proneness of different groups of mine workers. In this context, injury records from 2011 to 2022 were obtained from underground metalliferous mines situated at Eastern part of India. The data were characterized and segregated based on different individual and workplace level variables. The workplace injury is categorized as ‘no injury’ and ‘all injury’. Subsequently, Frequency and Classification Based analysis (FCBA), Standardized Injury Rate (SIR) analysis and Logistic Regression Model (LRM) analysis were performed sequentially (FCBA-SIR-LRM) to predict the susceptibility …

Modulation Of Hypothalamic–Limbic Circuits Regulating Appetite In Response To Health Lifestyle In Obese Adults, Nour Shakir Rezaieg, Muthanna M. Awad

Karbala International Journal of Modern Science

Background: Overeating leads to obesity a low-grade inflammatory disease. In this context, aguati-related neuropeptide (AgRP) and ghrelin are pivotal players in appetite regulation, while chemerin is an adipose tissue-secreted adipokine that contributes to low-grade inflammation associated with obesity. Objective: This study used a healthy lifestyle program designed for each obese participant to identify diet-related neuro-hormonal changes in appetite regulation. Design, Setting, and Participants: This a longitudinal quasi-experimental controlled study was conducted from 1^st December 2024, to 30^th July 2025, at University of Anbar. The sample included 100 participants, 50 obese (weight between 100–140 kg) and 50 healthy participants …

Evaluation Of Mcf-7 Breast Cancer Cell Cytotoxic And Antioxidant Activities Of Peptide Fractions From Symbiotic Bacteria Of Jellyfish Catostylus Sp., Eka Sry Wahyuni, Ahyar Ahmad, Muhammad Nasrum Massi, Sofa Fajriah, Randi Rimpung, Muh. Akbar Ardiputra, Harningsih Karim, Irda Handayani

Karbala International Journal of Modern Science

Marine-derived symbiotic microorganisms are recognized as a promising source of bioactive compounds with potential therapeutic applications, yet research on jellyfish-associated bacteria remains limited. This study examines the bioactivity of peptide fractions derived from symbiotic bacteria isolated from the jellyfish Catostylus sp., collected from the coastal waters of South Sulawesi, Indonesia, with a focus on their anticancer and antioxidant properties. Following sample collection, the symbiont bacteria were isolated, enzymatically hydrolyzed, and purified before their biological activity was evaluated. Preliminary cytotoxicity screening using the brine shrimp lethality assay revealed that the extracellular peptide fraction (5–10 kDa) and intracellular peptide fraction (3–5 kDa) …

California Couple Adds $3 Million To Scholarship Fund, Tina H. Hahn

University of Mississippi News

OXFORD, Miss. – Bill and Melanie Roper, of La Jolla, California, are deepening their commitment to University of Mississippi students by adding $3 million to the Bill and Melanie Roper Scholarship Endowment, which began with a $2 million gift in 2022.

First Arkansas Records Of The True Bugs Lasiochilus Hirtellus (Hemiptera: Heteroptera: Lasiochilidae) And Physopleurella Mundula (Anthocoridae)., S. W. Chordas Iii, R. Tumlison

Journal of the Arkansas Academy of Science

We report 2 uncommon species of true bugs (Hemiptera: Heteroptera), Lasiochilus hirtellus (Lasiochilidae) and Physopleurella mundula (Anthocoridae), for the first time from Arkansas. This includes the first report of the family Lasiochilidae for Arkansas. Both species were captured in UV light traps set in Clark County. We discuss identification, provide digital images of the voucher specimens and include updated distribution maps (north of Mexico) for both species. With the addition of these 2 species, there are now a total of 7 anthocorid species, among the 3 bug families Lasiochilidae, Anthocoridae and Lytocoridae, known for Arkansas.

Affective Interdependence And Welfare, Aviad Heifetz, Enrico Minelli, Heracles M. Polemarchakis

Cowles Foundation Discussion Papers

Purely affective interaction allows the welfare of an individual to depend only the individual’s own action and on the profile of welfare levels of others. Under an assumption on the structure of mutual affection that we interpret as non-reinforcing mutual affection, we show that equilibria of affective interaction are Pareto optimal. Moreover, if purely affective interaction induces a standard game, then an equilibrium profile of actions is a Nash equilibrium of the induced game, and this Nash equilibrium and Pareto optimal profile of strategies is locally dominant.

Risks And Possibilities: The Poetry Of A. R. Ammons, Peter Stevens

Ontario Review

PETER STEVENS, whose Pavase sequence appeared in Ontario Review #2, is former poetry editor of Canadian Forum and the author of numerous articles, poems, and reviews. His most recent book is And the Dying Sky Like Blood, a cycle of poems for Norman Bethune. He teaches at the University of Windsor.

Multimedia-Based Interventions To Improve Science Learning Outcomes For Deaf Students At Wangsel Institute For The Deaf., Cheten Tshering Mr., Tshering Wangchuk

Journal of Science Education for Students with Disabilities

Efforts have been made to ensure inclusive learning opportunities for all students, including those from diverse backgrounds. One key strategy to enhance children’s learning and academic performance involves the thoughtful selection and application of instructional tools tailored to meet learners' specific needs. This study examines the impact of multimedia-based instruction on science achievement among deaf students at Wangsel Institute for the Deaf in Bhutan. Using a quasi-experimental design, the research compared pretest and post-test results between a control group and an experimental group. Data analysis included descriptive statistics (t-test) and ANCOVA. The findings indicated a statistically significant differences (p = …