Artificial Intelligence and Robotics Commons^™

A Route Recovery Mechanism Using Hybrid Anti-Interference Method, Ziwen Sun, Yanqi Zhang, Yimin Xu

Journal of System Simulation

Abstract: Aiming at the jamming attacks in the industrial wireless sensor networks, a route recovery mechanism based on the WirelessHART graph routing is proposed. The jamming attack detection method is used to obtain the node and area being attacked by the jamming attack, the uncoordinated frequency hopping spread spectrum is used to generate the frequency hopping sequence of the node of being attacked by the jamming attack and that of the surrounding nodes, so that the traditional frequency hopping spread spectrum is performed on the nodes. Detects again, and combines the routing cost and the WirelessHART graph routing …

Non-Contact Object Size Acquisition Based On Visual-Inertial Sensor Fusion, Kang Lai, Yingmei Wei, Jiang Jie, Yuxiang Xie

Journal of System Simulation

Abstract: In consideration of the visual data and the data from the inertial measurement unit (IMU) having the different characteristics, the 6D pose of the visual sensor is recovered from the captured video by using the vision-based 3D reconstruction techniques, the obtained pose information and inertial measurements is fused via the spatial-temporal alignment, and based on the determined scale of the visual 3D reconstruction the non-contact measurement of a scene is performed. The proposed approach achieves a relative measurement error of about 3% in the non-contact object size estimation experiment. As it does not require the additional calibration object …

Optimization Design And Locomotion Characteristics Analysis Of Wheeled Traction Robot, Wu Wei, Li Bo, Nana Liu, Guangzhi Ma

Journal of System Simulation

Abstract: To evaluate quantitatively the dynamic locomotion characteristics and obstacle performance of the wheeled traction robot in horizontal well with single pipe diameter, the mechanical model of the crawling module of the wheeled traction robot is established and the structural and size parameters are optimized. The ADAMS model of the current robot is presented, and the Simulink models of three parts of the driving module, supporting mechanism and traction resistance are built. A specified method of the ADAMS/Simulink joint simulation modeling is proposed to analyze the locomotion characteristics and obstacle performance of the wheeled traction robot. The simulation results …

Prediction Of Flight Taxi-Out Time In A Busy Airport Based On Lwsvr, Zhiwei Xing, Songyue Jiang, Luo Qian, Luo Xiao

Journal of System Simulation

Abstract: Aiming at improving the accuracy of predicting the flight taxi-out time in a busy airport, based on the local regression and weighted support vector regression, a prediction model of the locally weighted support vector regression is proposed. The model uses the K nearest neighbor method to reduce the capacity of the training sample set and build a predictive model for each predicted sample. The bandwidth parameter of the Gaussian weighting function is optimized with the Mahalanobis distance between the forecast sample and training samples, and the weighting coefficients are obtained. Combining the airport departure flight data in simulation analysis, …

Two-Stage Dynamic Emergency And Disaster Resistance Operation Strategy For Active Distribution Network, Zhang Wei, Li Quan, Yuqiu Zhou, Yuhang Luo, Peifeng Xi

Journal of System Simulation

Abstract: The persistence and gradual change of the typhoons and other dynamic disasters, increase the complexity of the fault recovery process. In order to quickly restore the power to the active distribution network, a two-stage dynamic emergency operational strategy is proposed and the corresponding overall optimization model is established. The strategy includes the resource allocation plan, island partition scheme and cooperative scheme of the emergency repair and restoration. In the first stage, the pre-disaster resource allocation plan is made according to the travel time and attribute matching situation between the disaster-stricken areas and the repair resources. In the second stage, …

Simulation Research On Effectiveness Of Reward And Punishment Strategy In Open-Pit Mines, Xingxin Nie, Cunrui Bai

Journal of System Simulation

Abstract: Mining safety accidents occur frequently, and one of the main causes is the miners' Intentional Unsafe Behavior (IUB), and therefore implementing the reward and punishment strategy on it is the key coping strategy. In order to study how the reward and punishment strategy acts on the Intentional Unsafe Behavior (IUB) of the miners and how effective the strategy is, based on the Behavioral Economics + IUB Diffusion Theory, combined with the Multi-Agent model to analyze the influencing factors of the miners' IUB, and based on the work situation adaptability function and the unsafe behavior adaptability function, the simulation model …

Model And Simulation Of Interactive Dissemination Of Multiple Public Opinion Information Under Government Intervention, Zhiying Wang, Weikang Wang, Chaolong Yue

Journal of System Simulation

Abstract: In order to identify the interactive dissemination rules of the multiple public opinion information (POI) in major emergencies and make the intervention decisions more pertinently, an intervention model of interactive dissemination is proposed. The model integrates the characteristics of the unequal competition of multiple POI, expands the existing intervention model of the single POI dissemination, and could analyze the intervention measures from the global perspective of the interactive dissemination. Case analysis and simulation results show that the proposed model could well simulate the evolution of the interactive transmission of the multiple POI. Although the strong POI is more harmful …

Understanding Impact Of Twitter Feed On Bitcoin Price And Trading Patterns, Ashrit Deebadi

Master's Projects

‘‘Cryptocurrency trading was one of the most exciting jobs of 2017’’. ‘‘Bit- coin’’,‘‘Blockchain’’, ‘‘Bitcoin Trading’’ were the most searched words in Google during 2017. High return on investment has attracted many people towards this crypto market. Existing research has shown that the trading price is completely based on speculation, and its trading volume is highly impacted by news media. This paper discusses the existing work to evaluate the sentiment and price of the cryptocurrency, the issues with the current trading models. It builds possible solutions to understand better the semantic orientation of text by comparing different machine learning techniques and …

A Real-Time Internet Of Things (Iot) Based Affective Framework For Monitoring Emotions In Infants, Alhagie Sallah

Electrical Engineering Theses

An increase in the number of working parents has led to a higher demand for remotely monitoring activities of babies through baby monitors. The baby monitors vary from simple audio and video monitoring frameworks to advance applications where we can integrate sensors for tracking vital signs such as heart rate, respiratory rate monitoring. The Internet of Things (IoT) is a network of devices where each device can is recognizable in the network. The IoT node is a sensor or device, which primarily functions as a data acquisition unit. The data acquired through the IoT nodes are wirelessly transmitted to the …

Continuous Authentication System And Method Based On Bioaura, Arsalan Mosenia, Susmita Sur-Kolay, Anand Raghunathan, Niraj K. Jha

Patents

A user authentication system for an electronic device for use with a plurality of wireless wearable medical sensors (WMSs) and a wireless base station that receives a biomedical data stream (bio-stream) from each WMS. The system includes a BioAura engine located on a server, the server has a wireless transmitter/receiver with receive buffers that store the plurality of bio-streams, the bio-stream from a single WMS lacks the discriminatory power to identify the user, the BioAura engine has a look-up stage and a classifier, the classifier generates an authentication output based on the plurality of bio-streams, the authentication output authenticates the …

Raspberry Pi Ai Assistant, Cole Tharaldson

Student Academic Conference

Artificial Intelligence (AI) assistants are nearly everywhere you look in today’s society. With the use of a Raspberry Pi computer and the Google Application Programming Interface (API), an AI assistant can be created. Much like Google Home, this AI assistant can help people with everyday tasks, such as handling requests, controlling smart devices, answering questions, or even telling jokes.

Predictive Modeling Of Asynchronous Event Sequence Data, Jin Shang

LSU Doctoral Dissertations

Large volumes of temporal event data, such as online check-ins and electronic records of hospital admissions, are becoming increasingly available in a wide variety of applications including healthcare analytics, smart cities, and social network analysis. Those temporal events are often asynchronous, interdependent, and exhibiting self-exciting properties. For example, in the patient's diagnosis events, the elevated risk exists for a patient that has been recently at risk. Machine learning that leverages event sequence data can improve the prediction accuracy of future events and provide valuable services. For example, in e-commerce and network traffic diagnosis, the analysis of user activities can be …

A Multi-Input Deep Learning Model For C/C++ Source Code Attribution, Richard J. Tindell Ii

Masters Theses, 2020-current

Code stylometry is applying analysis techniques to a collection of source code or binaries to determine variations in style. The variations extracted are often used to identify the author of the text or to differentiate one piece from another.

In this research, we were able to create a multi-input deep learning model that could accurately categorize and group code from multiple projects. The deep learning model took as input word-based tokenization for code comments, character-based tokenization for the source code text, and the metadata features described by A. Caliskan-Islam et al. Using these three inputs, we were able to achieve …

Detecting Credit Card Fraud: An Analysis Of Fraud Detection Techniques, William Lovo

Senior Honors Projects, 2020-current

Advancements in the modern age have brought many conveniences, one of those being credit cards. Providing an individual the ability to hold their entire purchasing power in the form of pocket-sized plastic cards have made credit cards the preferred method to complete financial transactions. However, these systems are not infallible and may provide criminals and other bad actors the opportunity to abuse them. Financial institutions and their customers lose billions of dollars every year to credit card fraud. To combat this issue, fraud detection systems are deployed to discover fraudulent activity after they have occurred. Such systems rely on advanced …

Towards Natural Language Understanding In Text-Based Games, Anthony Snarr

Senior Honors Projects, 2020-current

Text-based games are a very promising space for language-focused machine learning. Within them are huge hurdles in machine learning, like long-term planning and memory, interpretation and generation of natural language, unpredictability, and more. One problem to consider in the realm of natural language interpretation is how to train a machine learning model to understand a text-based game’s objective. This work considers treating this issue like a machine translation problem, where a detailed objective or list of instructions is given as input, and output is a predicted list of actions. This work also explores how a supervised learning system might learn …

Superb: Superior Behavior-Based Anomaly Detection Defining Authorized Users' Traffic Patterns, Daniel Karasek

Master of Science in Computer Science Theses

Network anomalies are correlated to activities that deviate from regular behavior patterns in a network, and they are undetectable until their actions are defined as malicious. Current work in network anomaly detection includes network-based and host-based intrusion detection systems. However, network anomaly detection schemes can suffer from high false detection rates due to the base rate fallacy. When the detection rate is less than the false positive rate, which is found in network anomaly detection schemes working with live data, a high false detection rate can occur. To overcome such a drawback, this paper proposes a superior behavior-based anomaly detection …

Machines And Human Language, Gabe Wilberscheid

Student Academic Conference

A look at the history of Natural Language Processing (NLP) and how machines learn to understand humans.

A Physics-Based Machine Learning Study Of The Behavior Of Interstitial Helium In Single Crystal W–Mo Binary Alloys, Adib J. Samin

Faculty Publications

In this work, the behavior of dilute interstitial helium in W–Mo binary alloys was explored through the application of a first principles-informed neural network (NN) in order to study the early stages of helium-induced damage and inform the design of next generation materials for fusion reactors. The neural network (NN) was trained using a database of 120 density functional theory (DFT) calculations on the alloy. The DFT database of computed solution energies showed a linear dependence on the composition of the first nearest neighbor metallic shell. This NN was then employed in a kinetic Monte Carlo simulation, which took into …

Using Taint Analysis And Reinforcement Learning (Tarl) To Repair Autonomous Robot Software, Damian Lyons, Saba Zahra

Faculty Publications

It is important to be able to establish formal performance bounds for autonomous systems. However, formal verification techniques require a model of the environment in which the system operates; a challenge for autonomous systems, especially those expected to operate over longer timescales. This paper describes work in progress to automate the monitor and repair of ROS-based autonomous robot software written for an a-priori partially known and possibly incorrect environment model. A taint analysis method is used to automatically extract the data-flow sequence from input topic to publish topic, and instrument that code. A unique reinforcement learning approximation of MDP utility …

Applying Imitation And Reinforcement Learning To Sparse Reward Environments, Haven Brown

Computer Science and Computer Engineering Undergraduate Honors Theses

The focus of this project was to shorten the time it takes to train reinforcement learning agents to perform better than humans in a sparse reward environment. Finding a general purpose solution to this problem is essential to creating agents in the future capable of managing large systems or performing a series of tasks before receiving feedback. The goal of this project was to create a transition function between an imitation learning algorithm (also referred to as a behavioral cloning algorithm) and a reinforcement learning algorithm. The goal of this approach was to allow an agent to first learn to …