Artificial Intelligence and Robotics Commons^™

Heartdj - Music Recommendation And Generation Through Biofeedback From Heart Rate Variability, Egemen Şahin

Dartmouth College Master’s Theses

This study investigates the integration of real-time physiological data with AI-generated music to enhance emotional well-being, stress regulation, and focus, using Heart Rate Variability (HRV) as a biomarker of autonomic function. Conducted in two phases—Stable Audio Open (SAO) and Suno (SUNO)—the research evaluates biofeedback-driven music interventions across varying daily music-listening habits.

In the SAO phase, short AI-generated instrumental tracks were compared with Spotify recommendations and guided meditation. Modest HRV improvements were observed in biofeedback conditions, but participants noted emotional limitations, citing short track lengths and abrupt transitions.

The SUNO phase addressed these limitations with longer, more complex AI-generated compositions combined …

A Robust Framework For Graph Construction In Vision Graph Neural Networks, Ismael Elsharkawi

Theses and Dissertations

In Computer Vision, the method of representing an image has a profound effect on the performance of a model. Traditionally speaking, an image is treated as a grid of pixels and can be processed via Convolution Neural Net- works (CNN). An image can also be treated as a sequence of patches. Vision Transformers and MLP-Mixers (Multi-Layer Perceptron Mixers) are two types of models that process an image as a sequence. A more generic representation than grids and sequences would be graphs. That is why Vision Graph Neural Network (ViG) construct a graph for an image and process the image as …

Deep Learning-Based Auto-Segmentation For Liver Yttrium-90 Selective Internal Radiation Therapy, Jun Li, Wookjin Choi, Rani Anne

Department of Radiation Oncology Faculty Papers

The aim was to evaluate a deep learning-based auto-segmentation method for liver delineation in Y-90 selective internal radiation therapy (SIRT). A deep learning (DL)-based liver segmentation model using the U-Net3D architecture was built. Auto-segmentation of the liver was tested in CT images of SIRT patients. DL auto-segmented liver contours were evaluated against physician manually-delineated contours. Dice similarity coefficient (DSC) and mean distance to agreement (MDA) were calculated. The DL-model-generated contours were compared with the contours generated using an Atlas-based method. Ratio of volume (RV, the ratio of DL-model auto-segmented liver volume to manually-delineated liver volume), and ratio of activity (RA, …

Playing The Digital Dialectic Game: Writing Pedagogy With Generative Ai, Rebekah Shultz Colby

University Writing Program: Faculty Scholarship

This article explores teaching writing with generative AI as critical play where students and teachers engage in an ethically dialectical and aleatory game with generative AI. I qualitatively surveyed 24 writing teachers about how they teach writing with generative AI as well as its advantages and disadvantages. I discovered that teachers used generative AI to teach about the ethics of generative AI's design and rhetorical use to avoid plagiarism. Teachers also critically played with generative AI to teach the writing process of invention, drafting, revision, and editing. Specifically, the critical, dialectical interplay of human and machine invents in aleatory and …

Unveiling The Potential Of Generative Artificial Intelligence: A Multidimensional Journey Into The Future, Keng Boon Ooi, Alex Koohang, Eugene Cheng Xi Aw, Tat Huei Cham, Cihan Cobanoglu, Charles Dennis, Yogesh K. Dwivedi, Jun Jie Hew, Heather Linton Kelly, Laurie Hughes, Chieh Yu Lin, Anubhav Mishra, Ian Phau, Ramakrishnan Raman, Marianna Sigala, Yun Chia Tang, Lai Wan Wong, Garry Wei Han Tan

Research outputs 2022 to 2026

Purpose: The launch of ChatGPT has brought the large language model (LLM)-based generative artificial intelligence (GAI) into the spotlight, triggering the interests of various stakeholders to seize the possible opportunities implicated by it. Nevertheless, there are also challenges that the stakeholders should observe when they are considering the potential of GAI. Given this backdrop, this study presents the viewpoints gathered from various subject experts on six identified areas. Design/methodology/approach: Through an expert-based approach, this paper gathers the viewpoints of various subject experts on the identified areas of tourism and hospitality, marketing, retailing, service operations, manufacturing and healthcare. Findings: The subject …

Incorporating Visual Information Into Natural Language Processing, Maxwell Mbabilla Aladago

Dartmouth College Ph.D Dissertations

Natural language describes entities in the world, some real and some abstract. It is also common practice to complement human learning of natural language with visual cues. This is evident in the heavily graphical nature of children’s literature which underscores the importance of visual cues in language acquisition. Similarly, the notion of “visual learners” is well recognized, reflecting the understanding that visual signals such as illustrations, gestures, and depictions effectively supplement language. In machine learning, two primary paradigms have emerged for training systems involving natural language. The first paradigm encompasses setups where pre-training and downstream tasks are exclusively in natural …

The Year Of Ai: Raising Campus Awareness Through Art, Exhibits, And Community Engagement, Essraa Nawar

Library Articles and Research

This poster highlights the Leatherby Libraries’ leadership in advancing AI literacy through creative, inclusive, and interdisciplinary approaches. As part of Chapman University’s “Year of AI,” the library launched initiatives such as Beyond the Lens and AI: The Next Chapter, blending art, ethics, and education to inspire campus-wide engagement. Through collaboration with IS&T, Town & Gown, and academic departments, the library positioned itself as a hub for ethical dialogue and innovation. The poster shares replicable models for how libraries can foster AI awareness through community partnerships, exhibitions, and experiential learning.

Sequential Convex Programming Using Safe Flight Corridor For Trajectory Planning Of Uavs, Zhu Wang, Zhenpeng Zhang, Mengtong Zhang, Guangtong Xu

Journal of System Simulation

Abstract: To address the issues of sensitivity to initial values and weak convergence of sequential convex programming(SCP) based time-optimal trajectory planning for UAVs, a SCP method using safety flight corridor, denoted as SFC-SCP(safe flight corridor-sequential convex programming) is proposed. According to the obstacle avoidance path obtained from the front-end path planning, a safe flight corridor is constructed by forming a convex polygon safe flight area without obstacles for each trajectory point. The non-convex obstacle avoidance constraint is converted into linear inequality constraints to improve convergence ability. The rear-end SCP method is used to transform the nonlinear trajectory optimization problem under …

Research And Realization Of Immersive Skeleton Simulation System, Zining Wang, Shijiang Luo, Weiya Chen, Hanbin Luo

Journal of System Simulation

Abstract: Skeleton, as one of the sliding sports in Winter Olympic Games, has the characteristics of high speed, complexity and danger. In order to reduce the risk of accidents during sliding, a series of immersive skeleton simulation system is constructed utilizing virtual reality. Based on the point cloud data obtained by laser scanning, the existing track is modeled to build a virtual track stadium and skeleton sliding model in Unreal Engine 4. The data collected by motion capture devices is employed to estimate the centroid of the person and enable glide control input. The simulated skeleton posture is captured and …

Research On Modeling And Simulation Of Collective Mechanical Props Performance Behavior, Lian He, Kexiang Huang, Dapeng Yan, Ruida Tang, Gangyi Ding

Journal of System Simulation

Abstract: In stage performances, the increasing number of mechanical props poses significant challenges to their control and design. Each creative modification requires a complete rehearsal, resulting in low efficiency and sensitivity to creative changes. To address these issues, a model for the collective performance behavior of mechanical props is proposed. It utilizes centroid growth and 3D linear interpolation to generate spatial states and optimizes them in the temporal dimension using gradient descent. Through the construction of 3D simulation experiments, the planning and optimization of collective mechanical prop performance behavior in the model are analyzed. Similarity evaluation is used to compare …

Task Reallocation Method For Unmanned Swarm Under Adversarial Conditions, Lun Zhang, Mei Yang, Tuo Zhao, Shuiku Zhang, Jian Huang

Journal of System Simulation

Abstract: Heterogeneous unmanned swarms have important potential applications in future wars. However, during the high-intensity confrontation in the battlefield, how to efficiently and quickly redistribute the tasks carried by the damaged agents so that the swarms could successfully complete the mission is a difficult problem that must be addressed in the combat application of unmanned swarms. This paper proposes a task reallocation method named improved CNP-HA (contract net protocol-Hungarian algorithm). Through the allocation mechanism and the bidding mechanism, the method realizes the task reallocation of damaged agents with lower communication cost and faster speed comparing with baseline methods. In the …

Multi-Uav Deployment And Collaborative Offloading For Large-Scale Iot Systems, Zhiqin Huang, Tianying Lu, Zheyi Chen

Journal of System Simulation

Abstract: In large-scale internet-of-things (IoT) systems, unmanned aerial vehicles (UAV) enabled mobile edge computing (MEC) can alleviate the performance constraints on end IoT devices. However, due to the uneven distribution of IoT devices and inefficient problem-solving, how to efficiently perform computation offloading in large-scale IoT systems is a major challenge. Existing solutions generally cannot fit into dynamic multi-UAV scenarios, causing inefficient resource utilization and excessive response delay. To address these important challenges, this paper proposes a novel multi-UAV deployment and collaborative offloading (MUCO) method for large-scale IoT systems. A UAV deployment scheme based on constrained K-Means clustering is designed to …

Moving Target Velocity Measurement Method Based On Multi-View Observation Optimization Of Uav Image, Yuxin Wu, Zhilong Zhang, Aoxu Liu, Jiangwei Zou, Chuwei Li

Journal of System Simulation

Abstract: Measuring the position and velocity of moving targets is an important requirement for drone video analysis. In this paper, a moving target localization and velocity estimation algorithm based on least square optimization of UAV multi-view observation images is proposed: the video and corresponding pose parameters obtained by the airborne optoelectronic system are used to establish a line-of-sight model at multiple observation times, it is unified to the WGS-84 coordinate system by coordinate transformation, the position and velocity of the moving target are estimated based on the least squares algorithm. This algorithm does not require laser ranging information between the …

Decision Modeling And Solution Based On Game Adversarial Complex Systems, Jiachen Jiang, Zhengxuan Jia, Zhao Xu, Tingyu Lin, Pengpeng Zhao, Yiming Ou

Journal of System Simulation

Abstract: In view of the complex situation of the current game which will be large-scale, high-intensity, not omniscient, and strong confrontation, and in response to the lack of flexibility and long iteration cycles in traditional game decision-making, the model of the unmanned complex game system is built according to the background of the unmanned red and blue game. Based on deep reinforcement learning technology, intelligent decision-making algorithms are studied in the background of unmanned red and blue games. With the help of deep neural networks and Bellman's optimal principle, the search of the huge solution space is more efficient, and …

Dynamic Scene Point Cloud Mapping Method Based On Lidar-Imu, Weigang Li, Lei Gan, Yongqiang Wang

Journal of System Simulation

Abstract: In order to address the issue of decreased mapping accuracy and precision caused by dynamic object interference during the construction of point cloud maps in dynamic scenarios such as urban roads, this study proposes a method for building dynamic scene point cloud maps based on LiDAR and inertial measurement unit (IMU). The method incorporates several key steps. An index-based Octree voxel structure is utilized to enhance the incremental update and nearest neighbor search efficiency of the local perception map (LP-Map). The point cloud is processed using ground segmentation, clustering, and dynamic score calculation methods to enable real-time identification of …

A Visual Servo Precision Assembly Method For Riveting Parts Based On Adaptive Extended Kalman Filtering, Zonggang Li, Yanbo Li, Jianjun Jiao, Yajiang Du

Journal of System Simulation

Abstract: Aiming at the problems of multiple peg-in-hole riveting parts in industrial production due to the large number of rivets, small gap between rivets and rivet holes, and irregular rivet distribution, resulting in complex assembly process constraints, high assembly accuracy requirements, and difficulty in realizing intelligent riveting process to improve assembly efficiency, a visual servo accurate assembly method of riveting parts based on adaptive extended Kalman filter is proposed. In order to realize the high-precision positioning of riveted parts assembly, on the basis of the traditional extended Kalman filtering, an adaptive noise estimator is introduced to eliminate the influence of …

Performance Evaluation Technology For Low Earth Orbit Satellite Internet, Xiaofeng Wang, Yi Zhang, Guoxiu Zhang

Journal of System Simulation

Abstract: Performance evaluation can provide strong support for new technology verification of low earth orbit(LEO) satellite internet. Aiming at the characteristics of flexible networking and large spacetime scale of satellite internet, a performance evaluation architecture of satellite internet is designed. Aiming at the characteristics of various performance elements, a performance evaluation index system is designed under the premise of multi-dimensional comprehensive consideration. Aiming at the problem of frequent switching of satellite-ground links caused by high-speed movement, an algorithm for satelliteground link switching is proposed, which provides support for subsequent collection work. Aiming at the multi-dimensional problem of indicators, a multi-mode …

Simulation Research On Multi-Aircraft Conflict Resolution Based On Improved Chaotic Ant Colony Algorithm, Liang Tong, Jie Yang, Xusheng Gan, Di Shen, Wenda Yang, Daxiong Chen

Journal of System Simulation

Abstract: A chaotic ant colony algorithm based on dynamic volatility factor is proposed to solve the problem of multi-aircraft conflict resolution during free flight of fighter jets. The mathematical modelling is conducted on the conflict resolution problem of multiple fighter jets in the air. Based on the performance characteristics of fighter jets, fighter protection zone models, flight conflict models, and resolution models are established respectively. The chaotic ant colony algorithm is improved by using Logistic mapping and Henon mapping to optimize the pheromone update formula in the ant colony algorithm, and setting a dynamic factor for the pheromone volatilization factor …

Research On Mixed-Model Assembly Line Balancing Optimization Based On Hybrid Genetic Tabu Search Algorithm, Ke Wang, Sijia Guan, Xiyan Yin, Xixing Li, Hongtao Tang

Journal of System Simulation

Abstract: Aiming at the problem of unbalanced running load caused by idle or blocked workstations in the assembly line of mixed-flow hydraulic pump, a hybrid genetic tabu search algorithm solution and computer simulation verification method are proposed. A hybrid genetic tabu search algorithm with strong local search capability is designed with the optimization objectives of minimizing the production beats of the mixed-flow assembly line, the operational loads distributed among different workstations and the operational load smoothing indices of different products within the same workstation. The algorithm incorporates multi-fragment crossover and fragmentation of feasible solutions through Hamming distance mutation operations. The …

Research And Implementation Of Digital Twin System For Mine Drainage Monitoring, Qinghui Wu, Yaqing Bao, Zhongxin Zhao, Xu Huang, Yuchen Wei

Journal of System Simulation

Abstract: The conventional mine drainage monitoring system faces problems such as poor visualization, insufficient linkage, and monotonous real-time monitoring methods for mine drainage in dynamic environments. Combining digital twin technology, a digital twin system for mine drainage monitoring has been developed. Through the construction of digital space, virtual real interaction layer structure framework, and three-dimensional visualization system data architecture, combined with fluid mechanics, using Unity3D development engine and five dimensional model ideas, a three-dimensional visualization system architecture for mine drainage is constructed, achieving various application functions such as real-time monitoring, fault warning, and virtual real mixed control. The feasibility of …