Artificial Intelligence and Robotics Commons^™

Ai’S Carbon Shadow: An Exploration Of The Energy Dilemma And Earth’S Future, Olga Roussos

Student Publications and Presentations

As artificial intelligence continues to advance, more processing power and energy usage are required. This increase in energy consumption by AI leads to increased carbon emissions in the atmosphere as well as rapid resource depletion. The effects of AI’s growing energy consumption can have severe negative impacts on global climate, biodiversity, sustainability, and other aspects of the environment. This research aims to highlight the volume of energy that artificial intelligence uses, the expected environmental effects of artificial intelligence’s expansion, as well as the potential innovative solutions and sustainable practices that can be implemented to decrease energy usage and preserve the …

A Research Proposal Investigating The Geopolitical And Economic Impact Resulting From The Development Of Artificial General Intelligence (Agi), Tobia Donadon, Kristen Migliano

Student Publications and Presentations

Artificial General Intelligence (AGI) represents the next step in the development of AI, a huge step in the quest for artificial intelligence. AGI aims to create machines capable of understanding, learning, and applying knowledge across various tasks, much like humans.

This research proposal focuses on advancements and potential effects, with an objective to bridge the gap between narrow AI applications and the broader cognitive capabilities of AGI. This study explores the transformative potential of AGI while addressing the societal impacts. The research looks into the relationship between the development of AGI and geopolitical affairs.

Drawing on recent discoveries in mathematical …

Jsper (Just Stablediffusion Plus Easy Retraining), Adam Rusterholz, Meghan Finn, Zach Zolliecoffer, Zach Judy

ATU Scholars Symposium

JSPER is an an AI art generation Web Application that is both flexible and accessible. Our goal is to enable anyone to create and use their own customized art models, regardless of technical skill level. These models can be trained on almost anything, from a person, to an animal, to a specific object, or even style. The user only has to upload a handful of images of their subject. Then, training settings get optimized at the push of a button to match the type of subject the user is training. After training, their customized model can be used to generate …

Optimizing Campus Chat-Bot Experience Using Puaa: Integrating Large Language Model (Llm) Into University Ai Assistants, Sijan Panday, Zurab Sabakhtarishvili, Clayton Jensen

ATU Scholars Symposium

The advent of large language models (LLMs) such as Chat-GPT and Bard marks a significant milestone in knowledge acquisition, offering a streamlined alternative to the traditionally labor-intensive process of navigating through multiple checkpoints on the web. This emerging trend in LLMs renders the prevalent rule-based chatbots, commonly utilized by universities, increasingly outdated and subpar. This research project proposes integrating LLM technology into university websites, specifically targeting the needs of students seeking information about their institutions by introducing PUAA (Personal University AI Assistant). Our approach involves using the Retrieval-Augmented Generation (RAG) framework, leveraging the capabilities of the LlamaIndex in conjunction with …

Techniques To Detect Fake Profiles On Social Media Using The New Age Algorithms – A Survey, A K M Rubaiyat Reza Habib, Edidiong Elijah Akpan

ATU Scholars Symposium

This research explores the growing issue of fake accounts in Online Social Networks [OSNs]. While platforms like Twitter, Instagram, and Facebook foster connections, their lax authentication measures have attracted many scammers and cybercriminals. Fake profiles conduct malicious activities, such as phishing, spreading misinformation, and inciting social discord. The consequences range from cyberbullying to deceptive commercial practices. Detecting fake profiles manually is often challenging and causes considerable stress and trust issues for the users. Typically, a social media user scrutinizes various elements like the profile picture, bio, and shared posts to identify fake profiles. These evaluations sometimes lead users to conclude …

Anomaly Detection With Spiking Neural Networks (Snn), Shruti Bhandari, Vyshnavi Gogineni

ATU Scholars Symposium

Abstract:

Anomaly detection, the identification of rare or unusual patterns that deviate from normal behavior, is a fundamental task with wide-ranging applications across various domains. Traditional machine learning techniques often struggle to effectively capture the complex temporal dynamics present in real-world data streams. Spiking Neural Networks (SNNs), inspired by the spiking nature of biological neurons, offer a promising approach by inherently modeling temporal information through precise spike timing. In this study, we investigate the use of Spiking Neural Networks (SNNs) for detecting anomalies or unusual patterns in data. We propose an SNN model that can learn what constitutes normal …

Innovating Inventory And Alert Systems With Object Tracking, Juan Harmse, Esther Peden

Campus Research Month

Security system users require safeguarding inventory from potential theft while reducing manual tracking of physical objects. Our contribution harnesses the power of artificial intelligence and computer vision with YOLO to automate the process of tracking inventory items. The system sends alerts to the inventory manager when it detects particular events. Our approach was evaluated with KernProf profiling, interference, and orientation tests. The results were overall positive in these testing areas.

The Vulnerabilities Of Artificial Intelligence Models And Potential Defenses, Felix Iov

Cybersecurity Undergraduate Research Showcase

The rapid integration of artificial intelligence (AI) into various commercial products has raised concerns about the security risks posed by adversarial attacks. These attacks manipulate input data to disrupt the functioning of AI models, potentially leading to severe consequences such as self-driving car crashes, financial losses, or data breaches. We will explore neural networks, their weaknesses, and potential defenses. We will discuss adversarial attacks including data poisoning, backdoor attacks, evasion attacks, and prompt injection. Then, we will explore defense strategies such as data protection, input sanitization, and adversarial training. By understanding how adversarial attacks work and the defenses against them, …

Intelligent Optimization Method Of Cloud Manufacturing Swarm Based On Incomplete Information Game, Kunpeng Zhang, Yan Wang, Zhicheng Ji

Journal of System Simulation

Abstract: In the process of cloud manufacturing, the incomplete information status and the mutual competition and restriction relationship between cloud platform operator and demander lead to the difficult choice of manufacturing services. A cloud manufacturing swarm intelligent optimization method based on incomplete information game model is proposed. A static game model based on incomplete information is established for the interest competition between demand-side and cloud platform, with the goal of rationally pursuing the maximization of their own revenue function. The competition rules between demand-side and cloud platform are proposed, which are introduced into nature through Harsanyi transformation and converted into …

Hyper-Heuristic Approach With K-Means Clustering For Inter-Cell Scheduling, Yanlin Zhao, Yunna Tian

Journal of System Simulation

Abstract: According to the actual production situation of China's manufacturing industry, a hyperheuristic algorithm based on K-means clustering is proposed for inter-cell scheduling problem of flexible job-shop. K-means clustering is applied to group entities with similar attributes into the corresponding work cluster decision blocks, and the ant colony algorithm is used to select heuristic rules for each decision block. The optimal scheduling solutions are generated by using corresponding heuristic rules for scheduling of entities in each decision block. Computational results show that, the computational granularity is properly increased by the form of decision blocks, and the computational efficiency of the …

Distributed Energy Management Strategy Of Microgrid Based On Master-Slave Game, Miaomiao Ma, Hao Wang, Lipeng Dong, Xiangjie Liu

Journal of System Simulation

Abstract: Under the operation mode of power market, based on two-layer master-slave game, a distributed energy management strategy for the microgrid is proposed to tackle the conflict between the overall optimal operation of renewable microgrid and the maximum profit of each investor. To fully consider the balance between energy supply and demand, the concept of power trading agent is introduced, and an integrated demand response strategy based on consumer satisfaction and adjustable load is proposed on the user side. Considering the initiative and decision-making ability of power supply and load, the decision-making game model is established with power trading agent …

Optimization Of Urban Traffic Microsimulation Model For Carbon Emission Reduction, Bo Liu, Jianxin Lin, Yini Liu, Dong Zhang

Journal of System Simulation

Abstract: To assess the environmental benefits of transportation management or control strategies, a method to effectively integrate the micro-traffic simulation model and the micro-vehicle emission model is proposed. VISSIM platform is used to build a case micro traffic simulation model. K-means clustering method is used to divide the driving behavior into 4 types based on the acceleration and deceleration characteristics of different speed intervals of the trajectory data, and the global parameters of the simulation model are calibrated based on the driving characteristics, which quantitatively describe the total sensitivity of the parameters and the sensitivity of the interactions between the …

Modeling And Analysis Of Hybrid Traffic Flow Considering Actual Behavior Of Platoon, Xi Wang, Xiujian Yang, Xiaohan Jia, Shenyi Wang

Journal of System Simulation

Abstract: To explore the effect of actual behavior of autonomous vehicular platoon on traffic flow, aiming at the hybrid traffic flow mixed with predecessor following(PF) platoon which is modeled according to the actual control strategy, a hybrid traffic flow model is established based on cellular automata(CA) modeling method. Simulation analysis shows that the effect of platoon characteristics such as time headway, market penetration, platoon size, and control gains on hybrid traffic flow presents coupling and nonlinear properties. The spatiotemporal behavior of hybrid traffic flow with different platoon characteristics is generally much different. Reducing time headway or increasing platoon market penetration …

Dynamic Path Planning For Mobile Robot Based On Rrt* And Dynamic Window Approach, Rui Zhang, Li Zhou, Zhengyang Liu

Journal of System Simulation

Abstract: A dynamic path planning method combining RRT* and dynamic window approach(DWA) is proposed to realize the obstacle avoidance of mobile robot in complex environment of dynamic obstacles. Improved RRT* algorithm is used to generate the global optimal safe path based on the known environment information. By eliminating the dangerous nodes generated by RRT* algorithm, the security of global path is ensured. Greedy algorithm is used to remove the redundant nodes in the path to reduce the length of global path. DWA is used to track along the global optimal path planned by the improved RRT* algorithm. When static obstacles …

Collaborative Navigation Method For 5g Cluster Uav Based On Configuration Optimization, Chao Gao, Zheng Huang, Xuan Zhao, Hongxing Wang, Tao Long

Journal of System Simulation

Abstract: The existing range based cooperative navigation methods for clustered UAVs generally ignore the impact of space configuration on positioning and energy determination, which makes it difficult to obtain the accurate navigation and positioning results. In view of this, a collaborative navigation method is proposed for 5G clustered UAVs based on spatial configuration optimization. The relative ranging error model of UAVs based on 5G signals in complex environments is constructed, and the optimization strategy for collaborative navigation nodes is established based on the minimum geometric division of precision(GDOP) criterion to achieve the real-time optimization of collaborative navigation spatial configuration; A …

A Multi-Uav Collaborative Priority Coverage Search Algorithm, Xiang Yu, Qianrui Deng, Sirui Duan, Chen Jiang

Journal of System Simulation

Abstract: For the challenges such as large disaster area, uneven distribution of key areas and limited rescue time in emergency rescue, a multi-UAV collaborative priority coverage search algorithm is proposed. The search area is rasterized, and each grid is probabilistically labeled according to the disaster prediction information. The search area is divided into sub-regions of similar size and equal number of UAVs by K-means++ algorithm, and the search starting point of each sub-region is determined based on the clustering center, so that the multiple UAVs can carry out the partition cooperative search of the whole area. The score of each …

Incremental Image Dehazing Algorithm Based On Multiple Transfer Attention, Jinyang Wei, Keping Wang, Yi Yang, Shumin Fei

Journal of System Simulation

Abstract: In order to improve the processing ability of the depth-neural network dehazing algorithm to the supplementary data set, and to make the network differently process the image features of different importance to improve the dehazing ability of the network, an incremental dehazing algorithm based on multiple migration of attention is proposed. The teacher's attention generation network in the form of Encoder-Decoder extracts the multiple attention of labels and haze, which is used it as the label of the characteristic migration media network to constrain the network training to form the migration media attention as close as possible to the …

Path Planning Rapid Algorithm Based On Modified Rrt* For Unmanned Surface Vessel, Zhaozhen Jiang, Wenlong Wang, Wenqi Sun

Journal of System Simulation

Abstract: Aiming at the weak purposiveness of rapidly exploring random tree algorithm in USV path planning, a modified rapid algorithm is proposed. The artificial potential field method is improved and the force analysis in four directions is added to comprehensively calculate the resultant force on USV. The calculation method of steering angle is redefined to avoid entering the local optimal trap and can reach the target point smoothly to obtain an initial path. The initial path is used to set the random point sampling area of rapidly exploring random tree algorithm. By reducing the probability of random points generated in …

Research On Cross-Domain Unmanned Swarm Cooperative Anti-Submarine Search Method, Ning Wang, Xiaolong Liang, Jiaqiang Zhang, Yueqi Hou, Aiwu Yang

Journal of System Simulation

Abstract: For the maritime ASW search, a cross-domain unmanned swarm cooperative search method is proposed in which USVs are used as the communication relay of UAVs. The digital grid map is used to characterize the mission area and the kinematic model of cross-domain platform is constructed. The cooperative method of cross-domain unmanned systems is proposed, and the distributed information fusion mechanism of unmanned systems is designed. The search objective function for heterogeneous platforms is designed to guide the unmanned systems to make real-time decisions in search task. The simulation results show that the proposed method can be effective to the …

Simulation Verification And Decision-Making Key Technologies Of Unmanned Swarm Game Confrontation: A Survey, Xiaolong Liang, Aiwu Yang, Jiaqiang Zhang, Yueqi Hou, Ning Wang, Xiao Huang, Junbin Gong

Journal of System Simulation

Abstract: Unmanned swarm game confrontation is a new combat mode and plays a crucial role in intelligent warfare. Its core is the autonomous generation of a series of game confrontation decision sequences to "empower" the swarm. The progress of system simulation verification for the unmanned swarm game confrontation is analyzed. The key technologies of the autonomous decision-making are discussed from three aspects, technology based on expert systems and game theory, technology based on swarm intelligence and optimization theory, and technology based on neural networks and reinforcement learning. The key technology research conducted by the author's team on the autonomous decisionmaking …

Research On Integration Of Virtual-Real Hybrid Simulation Experiment Environment For Unmanned Swarm, Huijie Yang, Taoshun Xiao, Chen Wu, Lingfeng Guo

Journal of System Simulation

Abstract: Constructing the experiment environment and researching the core technology, key equipment and operation theory is the key step for the development of unmanned swarm. Based on the requirement of hybrid simulation environment for unmanned swarm, the elements of the experiment environment are analyzed, and the architecture is proposed, which is composed of common infrastructure, general experiment services, special experiment tools, security and support tool. The key experiment environment integration technology is studied from the aspects of experiment network, model data and experiment application. The feasibility of the method to construct the virtual-real hybrid simulation environment is verified by an …

Mixed-Variable Particle Swarm Optimization Algorithm Based On Competitive Coevolution, Hu Zhang, Heng Zhang, Zilu Huang, Zhe Wang, Qingpo Fu, Jin Peng, Feng Wang

Journal of System Simulation

Abstract: For the current algorithm, it is difficult to obtain the available solution due to the irregularity of problem decision space caused by the numerous mixed variable optimization problems during real industrial applications. The coevolution strategy is introduced and a mixed variable particle swarm optimization algorithm(CCPSO) based on competitive coevolution is proposed. The search direction adjustment mechanism based on tolerance is designed to judge the evolution state of particles, adaptively adjust the search direction of particles, avoid falling into local optimum, and balance the convergence and diversity of the population. The learning object generation mechanism is adopted for each particle …

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, 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, 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, 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, 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, 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, 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, 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 …