Artificial Intelligence and Robotics Commons^™

Multi-View Human Action Recognition Based On Deep Neural Network, Zhao Ying, Lu Yao, Zhang Jian, Qidi Liang, Long Wei

Journal of System Simulation

Abstract: A novel deep neural network named CNN+CA(Convolutional Neural Network plus Context Attention) model is constructed and a new recognition algorithm based on sequence matching is presented to improve the recognition accuracy of MVHAR (Multi-view Human Action Recognition). A CNN(Convolutional Neural Network) is designed to automatically learn multi-view fusion features; the CA (Context Attention) module is introduced to selectively focus on the parts of the features that are relevant for the recognition task; the proposed recognition algorithm based on sequence matching is used to realize MVHAR. The experimental results on the IXMAS dataset and the i3DPost dataset …

Design And Simulation For Compensatory Controller Of Aircraft Rudder Electro-Hydraulic Loading System, Xiaolin Liu, Jingyi Wu

Journal of System Simulation

Abstract: The electro-hydraulic loading system of aircraft rudder is a torque servo system which is a special equipment for testing the performance of rudder. In order to reduce the influence of surplus force in loading system, a control method for PID controller tuned in real time by radial basis function neural network based on particle swarm optimization is proposed. The characteristics of global and hyper parameter optimization of particle swarm optimization are used to improve the control effect of the controller. The learning coefficient based on annealing is used to accelerate the network convergence speed. Simulation results show that, compared …

An Artificial Emotion Model For The Mutual Mapping Between Discrete State And Dimensional Space, Zhihang Tian, Xiaming Chen, Dazhi Jiang

Journal of System Simulation

Abstract: Emotional intelligence is an important component and development direction of machine intelligence. The purpose of artificial emotion model is to construct emotion models for machines to develope systematic ability of emotion understanding and expression. However, the existing methods are still insufficient in artificial emotion modeling ability. Aiming at the key factor of personalization in the construction of artificial emotion model, this paper proposes a method of mutual mapping between discrete emotion state and dimension space state, and constructs a machine personalized artificial emotion model based on Big Five personality model and emotion state transfer model. The relevant experimental results …

System Reliability Modeling In Competitive Failure Considering Zoned Shock Effect, Qiguo Hu, Gao Zhan

Journal of System Simulation

Abstract: Shocks have certain effects on system reliability, and how to quantify the degree of shock loads becomes the key of system reliability analysis. The reliability modeling problem of system suffered from different shock strength is researched based on degradation process competing with sudden failure. Shock process is descripted by extreme shock and two types of degradation processes are descripted by Wiener process under the condition of shifting failure threshold. Aiming at different intensity shocks on the system, the different shock load suffered by zoned shock effect is partitioned, the distribution function of the two types of failure processes is …

Time-Varying Ocean Channel Modeling Method, Yuehua Pei, Su Wei, Jincheng Tao, Xialin Jiang

Journal of System Simulation

Abstract: For the ocean channel with extremely complicated situation, an underwater acoustic channel modeling algorithm which can reflect the sparsity, time-varying and space-varying characteristics is proposed. Based on the prior information obtained from the sea trials in a specific sea area, the statistical characteristics of the channel impulses response structure with time and space are obtained. According to the obtained channel sparsities and non-zero position vectors’ statistics, a time-varying underwater acoustic channel model match the real environment is generated. Based on the measured data of marine communication in specific sea area, the simulation results show that the proposed …

Bilingual Harmony Micro-Simulation Model And Computational Experiment, Shouming Zhang, Zhiping Wang, Guihong Bi, Zhenghua Zeng

Journal of System Simulation

Abstract: Under the background of urbanization, the weak connection of social networks has increased, which has challenged the protection of vulnerable languages. A new social network with remote weak connection is constructed based on the improved modeling method of agent social circle network; in addition to considering the influence of language status and the language population ratio on the language evolution mechanism of different populations, a new mechanism is introduced for the influence of bilinguals on the transition from monolingual to bilingual, and the influence of language attitudes and network connections on language choice behaviors; an improved agent language level …

Explicit Model Predictive Control For Intelligent Vehicle Lateral Trajectory Tracking, Leng Yao, Shuen Zhao

Journal of System Simulation

Abstract: To ensure the accuracy, driving stability and online real-time of intelligent vehicle tracking control, an explicit model predictive tracking control method is designed. The cost functions and constraints for tracking accuracy and driving stability in the prediction time domain are proposed. The tracking control problem is transformed into the optimization of the active steering angle with dynamic disturbances. To improve the real-time performance, the traditional model predictive control system is transformed into an equivalent explicit polyhedral piece-wise affine (PPWA) system, and the active steering angle of front wheel is gained by the explicit law on parameter partition. Carsim and …

Simulation And Experimental Verification Of Precision Grinding Of Micro-Groove Structure, Haoyang Cao

Journal of System Simulation

Abstract: In order to study the influence of micro-groove structure precision grinding, based on grinding wheel dressing and grinding kinematics, a grinding simulation model for the micro-groove structural surface is established. The influence of dressing, grinding parameters and pitch length on the profile of micro-groove structure was analyzed systematically, the grinding conditions for forming complete or interfering micro-groove profile are described, the profile and size of micro-groove are predicted, and the grinding test is carried out on carbon steel. The test results are consistent with the trend of the simulation model. The profile and size of the micro-groove …

Multi-Objective Optimization Of Multi-Task Parallel Motorcycle Suspension System Parameters, Xiansheng Ran, Yang Jing, Luo Ling, Chen Kai

Journal of System Simulation

Abstract: Aiming at the comprehensive problem of wobble of front suspension system and weave of rear suspension system of large displacement motorcycle at medium and high speed, a multi-objective optimization scheme based on sensitivity analysis and approximate modeling is proposed. The motorcycle model is established and the dynamics simulation is carried out. The lateral acceleration of front wheel's centroid position, the yaw rate and roll rate of whole vehicle's centroid position, which characterize the wobble and weave are the targets. The sensitivity analysis of suspension system parameters and the approximate modeling are carried out. Based on the analysis results, …

Research On Variable Swept Wing Mode Of Missile Based On Flutter Characteristics, Gao Yang, Yanbin Li, Wang Ying, Zhang Ze, Lü Rui

Journal of System Simulation

Abstract: The variable sweep angle of missile wing is an important variant missile design scheme. In the process of variant design, the aerodynamic and flutter characteristics of missile will be significantly different by using different variable sweep methods. Referring to the shape characteristics of Tomahawk missile, the geometric model of variable sweep wing missile is established. The flutter characteristics of variable sweep wing missile under different variable sweep angle modes are calculated and analyzed by fluid structure coupling method, and the selection scheme of variable sweep wing mode based on flutter characteristics is explored. The results show that the …

Examining The Effect Of Explanation On Satisfaction And Trust In Ai Diagnostic Systems, Lamia Alam, Shane Mueller

Michigan Tech Publications, Part 1

Background: Artificial Intelligence has the potential to revolutionize healthcare, and it is increasingly being deployed to support and assist medical diagnosis. One potential application of AI is as the first point of contact for patients, replacing initial diagnoses prior to sending a patient to a specialist, allowing health care professionals to focus on more challenging and critical aspects of treatment. But for AI systems to succeed in this role, it will not be enough for them to merely provide accurate diagnoses and predictions. In addition, it will need to provide explanations (both to physicians and patients) about why the diagnoses …

Lexical Complexity Prediction With Assembly Models, Aadil Islam

Dartmouth College Undergraduate Theses

Tuning the complexity of one's writing is essential to presenting ideas in a logical, intuitive manner to audiences. This paper describes a system submitted by team BigGreen to LCP 2021 for predicting the lexical complexity of English words in a given context. We assemble a feature engineering-based model and a deep neural network model with an underlying Transformer architecture based on BERT. While BERT itself performs competitively, our feature engineering-based model helps in extreme cases, eg. separating instances of easy and neutral difficulty. Our handcrafted features comprise a breadth of lexical, semantic, syntactic, and novel phonetic measures. Visualizations of BERT …

Fine-Grained Detection Of Hate Speech Using Bertoxic, Yakoob Khan

Dartmouth College Undergraduate Theses

This thesis describes our approach towards the fine-grained detection of hate speech using deep learning. We leverage the transformer encoder architecture to propose BERToxic, a system that fine-tunes a pre-trained BERT model to locate toxic text spans in a given text and utilizes additional post-processing steps to refine the prediction boundaries. The post-processing steps involve (1) labeling character offsets between consecutive toxic tokens as toxic and (2) assigning a toxic label to words that have at least one token labeled as toxic. Through experiments, we show that these two post-processing steps improve the performance of our model by 4.16% on …

Exploring The Long Tail, Joseph H. Hajjar

Dartmouth College Undergraduate Theses

The migration of datasets online has created a near-infinite inventory for big name retailers such as Amazon and Netflix, giving rise to recommendation systems to assist users in navigating the massive catalog. This has also allowed for the possibility of retailers storing much less popular, uncommon items which would not appear in a more traditional brick-and-mortar setting due to the cost of storage. Nevertheless, previous work has highlighted the profit potential which lies in the so-called "long tail'' of niche, unpopular items. Unfortunately, due to the limited amount of data in this subset of the inventory, recommendation systems often struggle …

Object Manipulation With Modular Planar Tensegrity Robots, Maxine Perroni-Scharf

Dartmouth College Undergraduate Theses

This thesis explores the creation of a novel two-dimensional tensegrity-based mod- ular system. When individual planar modules are linked together, they form a larger tensegrity robot that can be used to achieve non-prehensile manipulation. The first half of this dissertation focuses on the study of preexisting types of tensegrity mod- ules and proposes different possible structures and arrangements of modules. The second half describes the construction and actuation of a modular 2D robot com- posed of planar three-bar tensegrity structures. We conclude that tensegrity modules are suitably adapted to object manipulation and propose a future extension of the modular 2D …

Investigating Daily Fantasy Baseball: An Approach To Automated Lineup Generation, Ryan Smith

Master's Theses

A recent trend among sports fans along both sides of the letterman jacket is that of Daily Fantasy Sports (DFS). The DFS industry has been under legal scrutiny recently, due to the view that daily sports data is too random to make its prediction skillful. Therefore, a common view is that it constitutes online gambling. This thesis proves that DFS, as it pertains to Baseball, is significantly more predictable than random chance, and thus does not constitute gambling.

We propose a system which generates daily lists of lineups for Fanduel Daily Fantasy Baseball contests. The system consists of two components: …

Constraint Answer Set Programming As A Tool To Improve Legislative Drafting, Jason Morris

Centre for Computational Law (2022-2025)

Rules as Code" in this paper is used to refer to a proposed methodology of legislative and regulatory drafting.1 That legislation can be represented in declarative code for automation has long been recognized [6], as has the opportunity for improving the quality of legal drafting with the techniques of formal representation.

Exploring The Use Of Social Media To Infer Relationships Between Demographics, Psychographics And Vaccine Hesitancy, Abhimanyu Kapur

Computer Science Senior Theses

The growing popularity of social media as a platform to obtain information and share one's opinions on various topics makes it a rich source of information for research. In this study, we aimed to develop a framework to infer relationships between demographic and psychographic characteristics of a user and their opinion on a specific narrative - in this case, their stance on taking the COVID-19 vaccine. Twitter was the chosen platform due to the large USA user base and easily available data. Demographic traits included Race, Age, Gender, and Human-vs-Organization Status. Psychographic traits included the Big Five personality traits (Conscientiousness, …

Teaching Law And Artificial Intelligence, Brendan Johnson, Francis X. Shen

Minnesota Journal of Law, Science & Technology

No abstract provided.

Learn Biologically Meaningful Representation With Transfer Learning, Di He

Dissertations, Theses, and Capstone Projects

Machine learning has made significant contributions to bioinformatics and computational biol­ogy. In particular, supervised learning approaches have been widely used in solving problems such as bio­marker identification, drug response prediction, and so on. However, because of the limited availability of comprehensively labeled and clean data, constructing predictive models in super­ vised settings is not always desirable or possible, especially when using data­hunger, red­hot learning paradigms such as deep learning methods. Hence, there are urgent needs to develop new approaches that could leverage more readily available unlabeled data in driving successful machine learning ap­ plications in this area.

In my dissertation, …