Handling Constrained Multi-Objective Optimization Problems Based On Relationship Between Pareto Fronts,
2024
School of Computer Science, China University of Geosciences, Wuhan 430074, China
Handling Constrained Multi-Objective Optimization Problems Based On Relationship Between Pareto Fronts, Yubo Wang, Chengyu Hu, Wenyin Gong
Journal of System Simulation
Abstract: To address the challenges of balancing the constraint satisfaction and objective function optimization, and dealing with the complex feasible regions in constrained multi-objective optimization problems(CMOPs), a classification-based search approach is proposed based on different Pareto front relationships. A dual-population dual-phase framework is proposed in which an auxiliary population Pa and a main population Pm are evolved and the evolution process is divided into a learning phase and a search phase. During the learning phase, Pa explores unconstrained Pareto front (UPF) and Pm explores constrained Pareto front(CPF), through which the relationship between UPF and CPF is determined. After completing the …
Element Grouping Faceted Fully Connected Network Based On Ris,
2024
Graduate School, Space Engineering University, Beijing 101416, China
Element Grouping Faceted Fully Connected Network Based On Ris, Shunhu Hou, Shengliang Fang, Qingyao Zeng, Mengtao Wang
Journal of System Simulation
Abstract: In view of the over-fitting problem that caused by multiple parameters and high memory usage of the full connection layer of neural network in training, a RIS-based element grouping areal fully connected neural network (RGFCNN) is proposed for the first time based on the structural characteristics of reconfigurable intelligence surface (RIS). Based on the structural characteristics of RIS, the network is optimized on traditional FCNN. A novel transmission surface attention mechanism is designed for the effective feature extraction of data. Compared with the traditional FCNNs, the proposed network does not arrange the data in one-dimensional manner. Instead, a element …
Research On Theoretical Framework Of Simulative Experiment Evalution For Intelligent Unmanned Swarm Cooperation,
2024
China Academy of Electronics and Information Technology, CETC, Beijing 100041, China
Research On Theoretical Framework Of Simulative Experiment Evalution For Intelligent Unmanned Swarm Cooperation, Jipeng Wang, Xing Zhang, Hao Wu, Yu Gu, Huijie Yang
Journal of System Simulation
Abstract: As a typical representative of intelligent equipment, the technology, equipment and combat applications of intelligent unmanned swarm are being promoted globally. However, the research on experimental theory of unmanned swarm lags behind the technology and equipment in general. The emergence of swarm ability and complexity of confrontation of unmanned swarm, the nonrepeatability and non-generalization of swam experiment take great challenge to the basic theory and methods of unmanned swarm. The four experimental models including intelligent technology, intelligent equipment, intelligent swarm, and intelligent sos(system of systems) experiment from the perspective of system engineering and the whole life cycle of equipment …
Research On Dynamic Scene Slam Based On Improved Object Detection,
2024
School of Internet of Things Engineering , Jiangnan University , Wuxi 214100, China
Research On Dynamic Scene Slam Based On Improved Object Detection, Lanxi Shi, Wenxu Yan, Hongyu Ni, Feng Zhao
Journal of System Simulation
Abstract: Aiming at the epipolar constraint matching problem of monocular SLAM in dynamic scenes a dynamic feature point selection method based on object detection is proposed, in which the dynamic feature points in the front-end image frame of SLAM system is eliminated during feature extraction to improve the localization accuracy of SLAM. An improved target detection network is proposed to construct a loss function to describe the bounding box by using the overlap area, distance similarity and cosine similarity, which can achieve the accurate localization of target objects and obtain the range of object feature points in the current image …
Study On Forest Fire Visual Analysis Method For Extinguishing Command In Virtual Environment,
2024
School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China; Engineering Research Center for Forestry-oriented Intelligent Information Processing of National Forestry and Grassland Administration, Beijing 100083, China
Study On Forest Fire Visual Analysis Method For Extinguishing Command In Virtual Environment, Benrun Zhang, Weiqun Cao
Journal of System Simulation
Abstract: Aiming at the demand of forest fire fighting command, the information required for the command, such as geographical environment, meteorological conditions, forest resources and forest fire behavior are comprehensively analyzed, and the data visualization visual analysis method in the virtual forest fire environment is designed and realized. Wang Zhengfei-3D mixed cellular automata model is used to simulate the process of forest fire spread and the difference time method is adopted to predict the forest fire spreading behavior. The change of environmental data in different interest domains is captured in real time, and the multi-view panel and overlay layers are …
Asl-Catboost Method For Wind Turbine Fault Detection Integrated With Digital Twin,
2024
School of Information Science and Technology, Qingdao University of Science and Technology, Qingdao 266061, China
Asl-Catboost Method For Wind Turbine Fault Detection Integrated With Digital Twin, Hongtao Liang, Lingchao Kong, Guozhu Liu, Wenxuan Dong, Xiangyi Liu
Journal of System Simulation
Abstract: In view of the low visibility of the current wind farm status monitoring and insufficient realtime operation and maintenance, based on the concept of digital twin five-dimensional model, the framework of wind farm digital twin five-dimensional model is constructed. Aiming at the insufficient fault detection capability of traditional algorithms and unbalanced positive and negative samples in fan fault data set, the improved ASL-CatBoost algorithm is proposed to achieve the accurate detection of fan fault status. Based on the digital twinning platform, combined with MATLAB/Simulink, the simulation mathematical model of doubly-fed wind turbine under the condition of blade mass imbalance …
Using Ai Chatbots As Ideation Machines,
2024
Lipscomb University
Using Ai Chatbots As Ideation Machines, Brett Hawley, Naomi Hollans
Student Works
The team analyzed 3 popular chatbots and found that none of them could consistently produce idea-centered essay help responses. The team approached them with 3 separate prompts, one from each of three academic subjects. The team analyzed how each chatbot adapted to the addition of personal information from the “student” and to the phrase, “what are some ideas that could help me get started?” The goal with each interaction was to receive a response in which the chatbot did not produce any pre-written content. Overall, the team’s research did not suggest that AI is fully reliable as an ideation tool.
Comprehensive Question And Answer Generation With Llama 2,
2024
Southern Adventist University
Comprehensive Question And Answer Generation With Llama 2, Matous Hybl
MS in Computer Science Theses
Since the introduction of transformers, large language models have proven capable in many natural language processing fields. However, existing systems still face challenges in generating high-quality extractive questions. Base models and public chatbots fall short if the question source or quantity are critical. Our contribution is a question and answer generator for generating comprehensive, extractive questions and answers. This approach includes fine-tuning a LLaMA 2 base model for answer extraction (AE) and question generation (QG). We evaluate the resulting system using common automated metrics and a manual evaluation. We find that our system is comparable to the latest research and …
The Security Of Deep Neural Networks,
2024
Norfolk State University
The Security Of Deep Neural Networks, Jalaya Allen
Cybersecurity Undergraduate Research Showcase
Our society has transitioned from our primitive lifestyle to soon, an increasingly automatic one. That idea is further exemplified as we shift into an AI era, better known as Artificial intelligence. Artificial Intelligence is classified as computer systems that can perform tasks that typically require human intelligence. However, a common thought or question that most might have is, how is this done? How does AI process information the way we want it to and have access to so much information? AI is trained by systems called AI models. These modeling programs are trained on data to recognize patterns or make …
High-Resolution And Quality Settings With Latent Consistency Models,
2024
Old Dominion University
High-Resolution And Quality Settings With Latent Consistency Models, Steven Chen, Junrui Zhang, Rui Ning
Cybersecurity Undergraduate Research Showcase
Diffusion Models have become powerful generative models which is capable of synthesizing high-quality images across various domains. This paper explores Stable Diffusion and mostly focuses on Latent Diffusion Models. Latent Consistency Models can enhance the inference with minimal iterations. It demonstrates the performance in image in-painting and class-conditional synthesis tasks. Throughout the experiment different datasets and parameter configurations, the paper highlights the image quality, processing time, and parameter. It also discussed the future directions including adding trigger-based implementation and emotional-based themes to replace the prompt.
Citdet,
2024
University of Texas at Arlington
Citdet, Jordan A. James, Heather K. Manching, Matthew R. Mattia, Kim D. Bowman, Amanda M. Hulse-Kemp, William J. Beksi
Computer Science and Engineering Datasets - Archive
The CitDet dataset is composed of images captured at the USDA Agricultural Research Service Subtropical Insects and Horticulture Research Unit in Fort Pierce, FL, USA. Data was collected between October 2021 and October 2022. 579 images were captured from different sections of the orchard using the open-source application Field Book on Android tablets. While collecting images, we faced the camera in a portrait orientation directly centered on the tree of interest. All images were taken at the edge of the soil in the tree row to simulate a ground-based robot imaging the tree while moving between two rows of trees. …
Mathematically Rigorous Deep Learning Paradigms For Data-Driven Scientific Modeling,
2024
University of New Mexico
Mathematically Rigorous Deep Learning Paradigms For Data-Driven Scientific Modeling, Owen Nicholas Davis
Mathematics & Statistics ETDs
This dissertation explores the crucial role of data-driven modeling in science and engineering, with a focus on developing surrogate models to accelerate large-scale computational tasks, aiding in both outer-loop functions like uncertainty quantification and expensive inner-loop tasks within broader computational frameworks. Challenges arise with increased problem dimension and sparse, noisy training data, particularly significant when constructing surrogates for very expensive computational models where acquiring sufficient high-fidelity training data is unfeasible. In such scenarios, training surrogates from an ensemble of multifidelity information sources of varying accuracy and cost becomes essential. We emphasize neural network-based modeling paradigms, which are flexible in integrating …
Immersive Japanese Language Learning Web Application Using Spaced Repetition, Active Recall, And An Artificial Intelligent Conversational Chat Agent Both In Voice And In Text,
2024
Southern Adventist University
Immersive Japanese Language Learning Web Application Using Spaced Repetition, Active Recall, And An Artificial Intelligent Conversational Chat Agent Both In Voice And In Text, Marc Butler
MS in Computer Science Project Reports
In the last two decades various human language learning applications, spaced repetition software, online dictionaries, and artificial intelligent chat agents have been developed. However, there is no solution to cohesively combine these technologies into a comprehensive language learning application including skills such as speaking, typing, listening, and reading. Our contribution is to provide an immersive language learning web application to the end user which combines spaced repetition, a study technique used to review information at systematic intervals, and active recall, the process of purposely retrieving information from memory during a review session, with an artificial intelligent conversational chat agent both …
The Borderline Between Beneficial And Dishonest Ai: A Technical Report,
2024
Lipscomb University
The Borderline Between Beneficial And Dishonest Ai: A Technical Report, Seth Richards, Katherine Shell, Seth Wright
Student Works
Artificial Intelligence (AI) has been used since 1950 but it was largely overlooked by the public until 2022. Current discussions about AI center around academic integrity. This report seeks to understand if AI can be handled, used, or accepted in Lipscomb’s academic environment as a beneficial aid to writing and research, without actively doing these tasks for an individual. Generative AI is a neural network, which enables it to receive input, gather information from a database of existing content, and create new content [2]. Due to the nature of generative AI, its beneficial contributions to academia are extremely limited.
Individualized Learning As An Ai Tool: A Technical Report,
2024
Lipscomb University
Individualized Learning As An Ai Tool: A Technical Report, Petsimnan Blessing Dayit, Kasen Holt, Nuala Roper
Student Works
The purpose of the report’s research is to test and analyze whether Artificial Intelligence (AI) platforms can be used as beneficial tools for individualized learning at Lipscomb University without violating the Academic Integrity Policy. The methods section evaluates AI on the scopes of accuracy, analytical thinking, and adaptability. The results demonstrated how each platform responded to the prompts within the lines of the scope. The answers they gave were accurate, detailed, and contained various adaptations to make explanations clearer for the user. The team concluded that AI can be used at Lipscomb as a beneficial tool for students in their …
Artificial Sociality,
2024
University of Turin, Italy
Artificial Sociality, Simone Natale, Iliana Depounti
Human-Machine Communication
This article proposes the notion of Artificial Sociality to describe communicative AI technologies that create the impression of social behavior. Existing tools that activate Artificial Sociality include, among others, Large Language Models (LLMs) such as ChatGPT, voice assistants, virtual influencers, socialbots and companion chatbots such as Replika. The article highlights three key issues that are likely to shape present and future debates about these technologies, as well as design practices and regulation efforts: the modelling of human sociality that foregrounds it, the problem of deception and the issue of control from the part of the users. Ethical, social and cultural …
Context-Aware Affective Behavior Modeling And Analytics,
2024
University of South Florida
Context-Aware Affective Behavior Modeling And Analytics, Md Taufeeq Uddin
USF Tampa Graduate Theses and Dissertations
Affective computing (AC) is a sub-domain of AI that has the potential to assist people by assessing mental states and making appropriate recommendations to patients, loved ones, caregivers, and domain experts. Humans usually produce an enormous amount of data (such as face videos) every day. One of the major challenges for affective computer vision is to efficiently deal with high volumes of data to facilitate automated model development. To cope with this challenge, we developed computer vision algorithms that measure the expressivity of the human face from video data. More precisely, the developed algorithms can map complex affect information from …
A Smart Resume Builder Tool Using Generative Ai,
2024
Fort Hays State University
A Smart Resume Builder Tool Using Generative Ai, Ivan A. Velo Castaneda, Anas Hourani, Magdalene Moy
SACAD: Scholarly Activities
Crafting a standout resume is crucial in today’s competitive job market. Not only does it create a strong first impression on employers but it also it opens the doors for endless job opportunities. Despite existing resume assistance for FHSU students on the Career Services page, there's a lack of tools for generating or streamlining the resume writing process. To address this issue, an efficient resume builder utilizing OpenAI’s GPT-3.5 model was developed specifically for FHSU students. Its key features include intuitive template selection, dynamic AI-generated content for tailored resumes, multi-format output supporting PDF and Word formats, and a user-friendly experience …
No Generation Without Representation: Solving Ai Art Attribution With Sno-E,
2024
Stephen F Austin State University
No Generation Without Representation: Solving Ai Art Attribution With Sno-E, Sadie Campbell
Undergraduate Research Conference
Artificial intelligence has sparked a new-age debate about its ethical implications, specifically in the world of art. The Signature Neural Operative- Environment (SNO-E) is a multidisciplinary solution that draws on computer science, statistics, and art. It addresses the issue of proper attribution for Al-generated artworks through a Convolution Neural Network that adopts signature checks to cite artists whose works are sampled by Al. This novel approach ensures proper recognition and compensation for artists in the Al-generated era.
Gender Detection In Facial Images: A Comprehensive Cnn Analysis,
2024
Fort Hays State University
Gender Detection In Facial Images: A Comprehensive Cnn Analysis, Jose N T Ambrosio, Anas Hourani, Magdalene Moy
SACAD: Scholarly Activities
This research investigates the construction of a robust gender detection system using facial features and Convolutional Neural Networks (CNNs), exploring the impact of different layer configurations on accuracy and computational efficiency. With a validation accuracy of 91%, findings illuminate the nuanced relationship between precision and computational resources, enriching discussions on facial recognition technologies.
