Computer Sciences Commons^™

Translation Of: Dupin'sche Hyperflächen In E^4, Manuscripta Math By Ulrich Pinkall, Thomas E. Cecil

Mathematics and Computer Science Department Faculty Scholarship

This is an English translation of the article "Dupin'sche Hyperflächen in E⁴" by Ulrich Pinkall, which was originally published in manuscripta math. 51 (1985), 89-119.

A note from Thomas E. Cecil, translator: This is an unofficial translation of the original paper which was written in German. All references should be made to the original paper.

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 …

Pilot Study: Initial Investigation Suggests Differences In Emt-Associated Gene Expression In Breast Tumor Regions, Kylie L. King, Hamed Abdollahi, Zoe Dinkel, Alannah Akins, Homayoun Valafar, Heather Dunn

Faculty Publications

Triple negative breast cancer (TNBC) is the most aggressive subtype and disproportionately affects African American women. The development of breast cancer is highly associated with interactions between tumor cells and the extracellular matrix (ECM), and recent research suggests that cellular components of the ECM vary between racial groups. This pilot study aimed to evaluate gene expression in TNBC samples from patients who identified as African American and Caucasian using traditional statistical methods and emerging Machine Learning (ML) approaches. ML enables the analysis of complex datasets and the extraction of useful information from small datasets. We selected four regions of interest …

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 …

Electronic Component Authenticity Identification System And Related Methods, Yunghsiao Chung, Feng Yu, Stephen Edward Saddow, Junjie Xiong

Computer Science Faculty Research & Creative Works

A method and a system for identifying authenticity of an electronic component is disclosed. The method may include obtaining chip data of an electronic component; extracting feature information of the chip data for reducing noise of the chip data; providing the feature information of the chip data to a trained deep learning model; and providing a user with an authenticity indication for the electronic component based on an output of the deep learning model. Other aspects, embodiments, and features are also claimed and described.

An Effective Secure Multi-Objective Task Scheduling Algorithm In Multi-Cloud Environment, V K S K Sai Vadapalli, Ramesh Babu Gurujukota, Phaneendra Varma Chintalapati, Satyanarayana Murty, G. Sai Chaitanya Kumar, Satish Kumar Kode

Karbala International Journal of Modern Science

In cloud environments, task scheduling is essential for improving performance. Nevertheless, the existence of several heterogeneous clouds makes scheduling extremely difficult, requiring increasingly advanced algorithms to manage these environments' diversity and dynamic nature. To solve this, numerous authors have created a variety of task schedulers utilizing heuristic and metaheuristic techniques. Nevertheless, it remains dynamic and challenging because task scheduling is an NP-hard issue. Furthermore, in many complicated situations, it is still problematic to guarantee security throughout the task’s execution. Therefore, this paper introduces a multi-objective security-aware task scheduler using the Crayfish Mud Ring Optimization Algorithm for a multi-cloud environment. This …

In Memoriam - Nora Sabelli: Master Orchestrator Of Grant Programs And Mentor For Advancing The Interdisciplinary Learning Sciences Field, Eric Hamilton, Jeremy Roschelle, Roy Pea, Barbara Means, Louis Gomez, Kim Gomez, Nancy Butler Songer

Education Division Scholarship

On Friday, September 6, 2024, the learning sciences field lost a giant in Dr. Nora Sabelli, 87 years old, a personal mentor to many researchers and an inspiration to so many learning scientists and STEM leaders. Nora’s first professional career was as a computational chemist, and later she became a passionate leader in research for improving STEM education. Nora’s time as a senior program officer at the National Science Foundation’s (NSF) Education and Human Resources (EHR) directorate was legendary; she was a force of nature who reshaped funding priorities for stronger science and a stronger connection of science to education …

Bridging The Gap: Understanding And Mitigating Csrf Threats In Service Worker Environments, Sivakanesan Dhanushkanda, Mustafa A. Ibrahim

Graduate Student Government Association Research Conference

Progressive Web Applications (PWAs) are gaining popularity due to their rich features. Service Workers (SWs), one of its integral components, make this possible by providing users with offline functionality, improved performance, and effective caching techniques. SWs act as proxies positioned between the client browser and the web server, capable of intercepting requests and responses. Recent research has revealed that, despite being designed with security in mind, there are ways to circumvent these security precautions and launch various attacks.

Sensitive functions in JavaScript are functions that can introduce security vulnerabilities if not properly coded or validated. These functions can manipulate the …

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, …

Exploring School Teachers' Cyber Security Awareness, Experiences, And Practices In The Digital Age, R Ravichandran, Sonam Singh, P Sasikala

Journal of Cybersecurity Education, Research and Practice

This study investigates the awareness and practices of cyber security among school teachers, exploring their understanding of cyber threats, online behaviours, and response mechanisms to cyber incidents. A structured questionnaire was administered to gather data on demographic information, cyber security training, online practices, and experiences with cybercrime. The findings reveal varying levels of awareness among teachers, with many reporting limited knowledge of prevalent cyber threats such as phishing and identity theft. Despite the increasing reliance on digital tools for teaching, a significant number of respondents indicated a lack of formal training in cyber security. The study highlights the necessity for …

Display System Interface Using Visually-Evoked Cortical Potentials, Michael E. Miller, Brett J. Borghetti, Kellie D. Kennedy, Chad L. Stephens, Alan T. Pope

AFIT Patents

A brain-computer interface system includes a video processor for producing a display signal, a temporal controller for producing a plurality of repetitive visual stimulus (RVS) signals with different respective temporal aspects, a display device that receives the display signal and displays a corresponding image on a plurality of different display regions and receives the RVS signals and displays corresponding RVS in respective ones of the display regions, an electroencephalographic (EEG) sensor for sensing a visually-evoked cortical potential (VECP) signal in a user with eyes fixated on a viewed one of the display regions, and a VECP processor for processing the …

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 …

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 …

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 …

Identifying Cyberbullying Roles In Social Media, Manuel Sandoval, Mohammed Abuhamad, Patrick Furman, Mujtaba Nazari, Deborah Hall, Yasin N. Silva

Computer Science: Faculty Publications and Other Works

Social media has revolutionized communication, allowing people worldwide to connect and interact instantly. However, it has also led to increases in cyberbullying, which poses a significant threat to children and adolescents globally, affecting their mental health and well-being. It is critical to accurately detect the roles of individuals involved in cyberbullying incidents to effectively address the issue on a large scale. This study explores the use of machine learning models to detect the roles involved in cyberbullying interactions. After examining the AMiCA dataset and addressing class imbalance issues, we evaluate the performance of various models built with four underlying LLMs …

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.

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 …

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 …

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 …

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 The Digital Twin Architecture And Application Of Cnc System, Xiyang Zhang, Xusheng Lin, Rui Zhou, Yi Hu

Journal of System Simulation

Abstract: In response to the intelligent and digital requirements for virtual debugging, performance evaluation, and machining quality optimization of CNC systems in the field of production and manufacturing, a five dimensional digital twin system of CNC systems combining virtual and real is constructed based on digital twin technology. And combined with relevant new generation information technology, the digital twin system is modeled in multiple fields, including information models, mechanism models, and digital threads, to achieve comprehensive simulation and analysis of physical entities and processing processes. The study also verifies the feasibility of data transmission between CNC systems and digital twin …

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 …

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 …

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 …

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 …

Design And Function Analysis Of New Steering System For Autonomous Vehicle, Peng Ji, Jinpeng Zhao, Limin Jiang

Journal of System Simulation

Abstract: For the current requirements of regulations and technical maturity, the steering system for autonomous vehicles must have the driver takeover function, explore the permanent magnet coupling device embedded in the steering system, and design a new steering system, which can realize the switch between automatic driving mode and driver takeover mode. The overall design of the new steering system is carried out. The system can realize the functions of steering wheel silence, road sense simulation, overload protection and mechanical steering redundancy, and realize the redundant design of steering system without adding additional hardware. The key component of the system, …

Global Selection And Local Differentiation Fusion For Vehicle Re-Identification, Shengjun Xu, Mengqian Zhang, Bohan Zhan, Guanghui Liu, Yuebo Meng

Journal of System Simulation

Abstract: To address the interference issues of different perspectives, complex backgrounds, and lighting intensity in vehicle re-identification caused by cross lens multi view differences, a vehicle reidentification network integrating global selection and local differentiation is proposed. Based on Resnet50 backbone network, a three-branch complementary network integrating global and local features is designed. The global branch is used to learn overall appearance information of the vehicle, while the local branch captures differential details of the vehicle. Based on attention mechanism, a context feature selection module (CFSM) is proposed to effectively separate vehicle information from complex background information, and a detail feature …

Vehicle Routing Problem With Drones Considering Zoned Distribution Of Epidemic Prevention Materials, Huawei Ma, Boying Yan

Journal of System Simulation

Abstract: To address the shortcomings of current contactless delivery methods in the collaborative distribution of epidemic prevention supplies, we introduce a specialized model called the vehicle routing problem with drones considering zoned distribution (VRPD-ZD). In order to solve the problem, a linear programming model is established with the shortest delivery time as the optimization objective, and a two-stage heuristic algorithm is proposed. The initial solution is generated by greedy algorithm in the first stage. In the second stage, we develop a Tabu search algorithm with genetic algorithm (TSGA) hybrid. This enhanced algorithm integrates a taboo list and employs advanced chromosome …

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 …

Novel Multi-Gait Strategy For Stable And Efficient Quadruped Robot Locomotion, Daoxun Zhang, Xieyuanli Chen, Zhengyu Zhong, Ming Xu, Zhiqiang Zheng, Huimin Lu

Journal of System Simulation

Abstract: Inspired by the natural gait transition mechanism of quadruped animals, a multi-gait motion strategy is proposed to realize the stable and efficient motion of quadruped robots on different terrains in response to the trade-off between motion energy efficiency and motion stability. The gait is defined based on the duty cycle parameters and phase bias to form the switching basis. Secondly, the affine transformation of gait parameters and the finite state machine are introduced to establish the switching sequence, which realizes the timely gait switching. The speed-gait mapping is designed based on the cost of transport (CoT) and the stability …