Digital Commons Network^™

Evaluating The Efficacy Of Aerobic Exercise As Therapy For Depression And Anxiety In Women With Pcos: A Systematic Review, Lorna Evelyn Mansell, Caitlin Fox-Harding, Robert U. Newton, Pedro Lopez Da Cruz, Sara Bayes, Favil Singh

Research outputs 2022 to 2026

Objective This systematic review aims to evaluate the effectiveness of exercise interventions in alleviating depression and anxiety symptoms in women with polycystic ovary syndrome (PCOS). Data sources PubMed, CINAHL, Cochrane Library, SportDiscus, EMBASE and Web of Science databases were searched from their inception to July 2025. Eligibility criteria for selecting studies Randomised controlled trials were eligible if they examined the effects of exercise lasting ≥4 weeks on validated measures of depression and/or anxiety in women aged 18–45 with PCOS diagnosed using the Rotterdam criteria. Publications not written in English were excluded. Data extraction and synthesis Two reviewers independently extracted data …

Imu-Driven Watch Face With Performance-Optimized Graphics, Gabriela Namie, Teddy Guerrero, Seth Benson, Courtney Cox, Tyler Gough, Mike Humphrey

Defensive Publications Series

A smartwatch interface displays dynamic, three-dimensional-like animations which are directly responsive to the user's wrist movements. The system uses data from the watch's Inertial Measurement Unit (IMU) to drive the animation of on-screen graphical elements in real-time. The method includes code-based techniques for simulating visual effects like gradients and for managing element animation to maintain fluid performance (e.g., 30 frames per second) to overcome hardware limitations related to rendering complex graphics and a high number of elements.

Conscious Ai Thought Origination In Llm, Shreyas Kc, Yu Gu

Defensive Publications Series

The present disclosure relates to the field of Artificial Intelligence (AI), and more specifically to conscious AI systems integrated with Large Language Models (LLMs) for autonomous ideation and decision-making. The present disclosure introduces a consciousness layer to a fine-tuned LLM, enabling the model to continuously generate candidate topics, rank them using a weighted scoring algorithm, and select the highest-priority topic for ideation. The consciousness layer captures and stores intermediate outcomes, embeddings, agent actions, and metadata, which are vectorized and re-injected into the LLM’s context to maintain continuity. This loop operates without external prompting, emulating humans like spontaneous thought and topic …

Warehouse Operational Administration In The Context Of Increasing The Effectiveness And Efficiency Of The Audio Business Unit Warehouse Of Pt Xyz, Annisa Dwi Novianti, Mohammad Ridha

Jurnal Vokasi Indonesia

                                                      ABSTRACT

This study analyzes the critical role of warehouse operational administration as a determinant of effectiveness and efficiency within the supply chain, focusing on the Audio Business Unit of PT XYZ. It posits that robust administrative processes are fundamental to optimizing warehouse performance, which in turn supports broader business unit objectives. Using a qualitative case study approach, this research conducted an in-depth investigation from September 1^st to October 31^st, 2025, employing data triangulation through direct observation, semi-structured interviews, and documents analysis. The findings confirm that the established operational administration system significantly contributes to enhancing warehouse effectiveness measured …

Estimation Of Net Premium For Flight Delay Insurance Using The Aggregate Loss Model: A Case Study Of Indonesia Otas, Azka Nurul Husna, Yulial Hikmah, Ira Rosianal Hikmah

Jurnal Vokasi Indonesia

Air transportation, as one of the most chosen transportation modes, is frequently susceptible to delays. Flight Delay Insurance offers a vital solution to mitigate the financial losses associated with this risk. Premium pricing is a key factor influencing the decision to purchase this insurance, particularly on Online Travel Agent (OTA) platforms where product offerings are often highly comparable. The aggregate loss method is employed herein to ascertain the net premium (or pure premium) price. The loss severity component (X) is modeled using an empirical distribution, while the loss frequency component (N) is modeled using a Negative Binomial distribution with parameters …

Investigation Of Maneuvering Coefficients For The Darpa Suboff Aff1 Model Via Computational Fluid Dynamics, Haydar Palavar

Seatific Journal

Due to their military applications, submarines are expected to possess certain operational capabilities. Among these, maneuverability stands out as a critical feature, and the investigation and prediction of this capability in the early design stages is of particular importance. In this context, the present study aims to determine the maneuvering coefficients of the DARPA Suboff form’s bare hull model (AFF1) by employing the static drift method. Computational Fluid Dynamics (CFD) simulations were conducted in STAR-CCM+, and the results were validated against experimental data available in the literature. As a result of the hydrodynamic effects investigated under various speeds and drift …

Bridging Physics And Data: Hybrid Modelling Of Nox And Soot Emissions In Alternative-Fuel Diesel Engine, Fatih Okumuş

Seatific Journal

In this study, a basic machine learning approach based on fuel type for estimating NOx and soot emissions in diesel engines was comparatively evaluated against a physics-based model incorporating physical indicators related to the combustion process. Experimental data were obtained from a single-cylinder, four-stroke diesel engine under single and dual fuel conditions using diesel, biodiesel, and ammonia. Quantities derived from the in-cylinder pressure signal, including IMEP, maximum pressure rise rate, maximum pressure, the crankshaft angle corresponding to maximum pressure, the CA10–CA90 combustion interval, ignition delay and total combustion duration, were integrated into the model as quantitative indicators representing the engine’s …

Benchmarking Reference Bulk Carriers With The Best International Shipping Results Regarding Carbon Intensity Indices, Alper Seyhan, Coşkan Sevgili, Murat Bayraktar, Onur Yüksel

Seatific Journal

The growing urgency of maritime decarbonization and the efforts toward achieving it are a critical subject of academic debate. This research provides a comprehensive empirical analysis of the operational carbon intensity of a Capesize bulk carrier having 176,859 deadweight tonnage using a full year of noon report data. In addition, a forward-looking scenario analysis was conducted to compare the vessel’s performance under alternative fuel options including liquefied natural gas, and Methanol. The findings were then compared with maritime sector data from the period 2008 to 2018. The primary findings confirm the ship’s exceptional efficiency in load-dependent metrics, with its Energy …

Single-Objective Psa Framework For Longitudinal Girder Scantlings With Full-Ship And Ultimate Strength Verification For A 500-Tonne Catamaran, Sang Eui Lee

Seatific Journal

Hull structures must withstand design loads throughout their expected lifetime. Industry practice often uses a comparative approach, which works for designs similar to proven ships with good service records. However, it can leave some members overly heavy while others barely meet strength criteria, and errors may remain hidden until construction. To prevent such issues at the initial design stage, scantlings should be optimised and reviewed numerically. To address these limitations in the initial design stage, this study aims to develop and demonstrate a practical numerical framework for optimising hull scantlings by integrating a fully automated single-objective optimisation procedure with direct …

Evaluasi Nilai Nutrisi Tongkol Jagung Hasil Bioproses Kapang Neurospora Sitophila Dengan Suplementasi Sulpur Dan Nitrogen, Nurafni Noverina, Tina Harlina, Dinda Yolandasari, Annisa Septianie

Jurnal Ilmu Ternak Universitas Padjadjaran

Penelitian bertujuan untuk mengetahui nilai nutrisi tongkol jagung hasil bioproses menggunakan kapang Neurospora sitophila dengan suplementasi sulpur dan nitrogen. Penelitian dilakukan menggunakan metode eksperimen dengan Rancangan Acak Lengkap Pola Faktorial 4 x 4. Faktor pertama adalah taraf suplementasi 0,02 %, 0,04 %, 0,06 % dan 0,08 % sulpur (S), faktor kedua adalah taraf suplementasi 1,00 %, 1,50 %, 2,00 % dan 2,50 % nitrogen (N), tiap perlakuan diulang sebanyak 3 (tiga) kali. Peubah yang diamati untuk melihat respon terhadap perlakuan yang diberikan adalah kandungan protein kasar, protein murni, Non Protein Nitrogen (NPN), lemak kasar, serat kasar, dan Bahan …

3d Object Tracking Registration Based On Improved Rbot Method, Jiarui Zhou, Haihua Cui, Pengcheng Li, Shihao Gu, Huipu Hao, Xifu Zhao, Anan Zhao, Tao Jiang

Journal of System Simulation

Abstract: To address the limitations of region-based object tracking (RBOT) in handling isotropic objects and scenarios with similar foreground-background colors, an improved method integrating edge features is proposed. The approach employs edge detection to extract object contours and designs a region segmentation strategy incorporated into an energy function framework to optimize internal line and edge consistency, thereby enhancing adaptability in dynamic environments and improving pose estimation accuracy. Validation through augmented reality assembly experiments on an aero-engine demonstrates that the proposed method effectively reduces rotational and translational errors, achieving initialization deviations of less than 1.5° and 0.5%, respectively. For static …

3d Reconstruction For Stadium Cad Drawings Based On Graphic Element Arrangement Pattern Analysis, Shang Ma, Mengyu Zhang, Lan Zhang, Gang Yang

Journal of System Simulation

Abstract: To address the issue of the time-consuming and labor-intensive manual conversion of two-dimensional CAD design drawings of buildings into three-dimensional models, and leveraging the characteristic that stadiums contain a large number of repetitively and regularly arranged objects, this study proposes a similar graphical element detection algorithm. This algorithm detects similarities between graphical elements by constructing their bounding boxes and calculating the L2-Norm distance, identifying all graphical elements of the same type within the CAD drawing. Furthermore, a transformation sequence detection algorithm is proposed. Based on the geometric transformation relationships between graphical elements, a geometric transformation space is defined. By …

Visual Relocalization Method Combining Region Classification And Local Feature Enhancement, Yining Wang, Yanli Liu, Guanyu Xing

Journal of System Simulation

Abstract: Visual relocalization tasks have important application value in fields such as digital twin and augmented reality. The current mainstream methods still face challenges such as mismatch between coordinate regression scale and receptive field and insufficient attention to local information. A visual relocalization method that combines region classification and local feature enhancement is proposed. The coordinate regression problem in large space is transformed into a multi-region classification problem and a coordinate regression problem inside a small scene, which significantly reduces the uncertainty of coordinate regression and makes the network globally have a large receptive field. A conditioning layer using deep …

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 …

A Noncovalent Click-To-Release Strategy To Control Bond Cleavage And Prodrug Activation, Xuancheng Fu, Bowen Xu, Suman Maity, Michelle Wu, Luke G. Westbrook, James H. Henderson, Yaoying Wu, Katie A. Edwards, Atanu Acharya, Xiaoran Hu

Pharmacy Faculty Scholarship

Click-to-release chemistry enables bioorthogonal bond cleavage and controlled release via a click-type ligation reaction serving as both the trigger and means of localization. Extending this concept beyond covalent ligation reactions, we introduce a noncovalent click-to-release strategy based on cucurbit[7]uril-adamantane (CB-Ad) association. The CB host molecule forms a pre-assembled host-guest complex with a self-immolative guest (SIG) SIG1, where the masked SIG remains inert. Introduction of a high-affinity guest Ad initiates the CB-Ad noncovalent click reaction, displacing SIG1 and triggering its self-immolation and cargo release. As a proof-of-concept, we used a prototype prodrug SIG2 to demonstrate our strategy's potential for controlled therapeutic …

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 …