Computer Sciences Commons^™

Research On Glide Width Simulation System Of Instrument Landing System, Chunying Jiang, Yuxiang Kang, Xiaofeng You, Xiaoxin Zhang, Changlong Ye

Journal of System Simulation

Abstract: Based on the principle of the formation of the instrumental landing system ILS(Instrument Landing System) gliding DDM(Different in the Depth of Modulation) index, and the factors that affect DDM are found as the amplitude of SBO(Sideband Only) signal. The relationmodel between the amplitude and the glide width, of the Half-width SBO signal in the linear variation range of DDM are obtained by the control variable method. And Based on the measured data, the correctness of the model is verified. Based on the mathematical model and combined with the NM7000 equipment, a simulation system is built to dynamically …

Monocular Depth Image Mark-Less Pose Estimation Based On Feature Regression, Chen Ying, Shen Li

Journal of System Simulation

Abstract: Monocular camera mark-less pose estimation system suffers low accuracy, robustness and efficiency due to variety of action, self-occlusion of human body. A method of feature exaction from point clouds was proposed, in which a single-to-multiple (S2M) feature regressor and a joint position regressor were designed to quickly and accurately predict the 3D positions of body joints from a single depth image without any temporal information. Experiment result shows that the estimation accuracy is superior to that of state-of-the-arts and multi-camera based methods.

Simulation And Optimization Of Aircraft Sliding Path, Zhiwei Xing, Mingyi Xu, Luo Xiao, Luo Qian

Journal of System Simulation

Abstract: Variable taxiing time is an important indicator to the characteristics of the airport traffic flow assessment, which affects the airport operating efficiency, the passenger satisfaction for the airline and the pollution emissions. For a large hub airport, according to the principle of cellular automata and the congestion of traffic flow, the airport taxiing area is regarded as the network topology of nodes and links, and the conflict between taxi rules and aircraft is taken as the constraint. The simulation analysis is carried out on the basis of constructing the model of airplane departure traffic flow, using Monte Carlo algorithm …

Modelling And Simulation For NoX Emission Concentration Of Scr Denitrification System, Dong Ze, Laiqing Yan

Journal of System Simulation

Abstract: The selective catalytic reduction (SCR) denitrification system has the features of non-linearity, large lag and strong disturbance, when the operating condition changes. Based on mutual information (MI) and Kernel-based Orthogonal Projections to Latent Structures (KOPLS), the model for NO_x emission concentration is proposed. The time-delay of each input variable is estimated by mutual information, and phase space construction is performed, KOPLS is utilized to modelling. KOPLS shows the merits of strong generalization, nonlinear fitting and anti-noise in the simulation of benchmark datasets. According to field data analysis, RMSE of MI-KOPLS in training and test are reduced by 17% …

Research On Approximate Reference Algorithm Of Svdbn Based On Sliding Window, Haiyang Chen, Chai Bing, Ruilan Wang, Cao Lu

Journal of System Simulation

Abstract: Structure-variable dynamic Bayesian networks (SVDBN) have the special advantage in dealing with the uncertainty of the unstable processes. In order to overcome the disadvantage that the inference algorithms of the SVDBN are unable to apply online, introducing the concepts of SVDBN sliding window and the window width, the online approximate inference mechanism of structure-variable dynamic Bayesian networks based on sliding window is explained, and two online algorithms are proposed, that is the recursive inference algorithm of structure-variable discrete dynamic Bayesian networks (SVDDBN) based on sliding window and the fast inference algorithm of SVDDBN based on sliding window. Experimental simulations …

Lambda Edge: A Lambda Computing Platform For Edge Computing, Dung Nguyen

Theses and Dissertations

Edge computing is a solution to the mobile computation offloading problem. Previous works show that virtual machines can be the computation units in edge computing. However, virtual machine-based methods are usually associated with large overheads and long latencies. In this thesis, we explore the possibility of using Docker containers instead of virtual machines in edge computing enabled by lambda architecture. We propose an edge computing platform, called Lambda Edge, which can be used to build edge computing applications and pave the way for further research on lambda-based edge computing. We also provide a sample application built upon the platform. We …

Situation Cognition And Decision Modeling Method For Submarine Operation Based On Discriminant Matrix, Dongjun Zhang, Weiping Wang, Li Xiao, Zhang Lei, Xiaobo Li, Guojie Liu

Journal of System Simulation

Abstract: Submarine operations have the characteristics of dynamic game confrontation in complex environments. Situation cognition and decision (SCD) behavior of combatants have an important impact on the effectiveness of submarine operations. Aiming at the SCD modeling in submarine engagement-level operational experiments, based on analyzing the SCD process, the representative variable set is refined, and a SCD modeling method for submarine operation based on the discrimination matrix is proposed. The submarine engagement-level confrontation is used as an example to study the SCD process in the given scenarios, and the feasibility and effectiveness of the method are verified. The established model …

Scraping Bepress: Downloading Dissertations For Preservation, Stephen Zweibel

Copyright, Fair Use, Scholarly Communication, etc.

This article will describe our process developing a script to automate downloading of documents and secondary materials from our library’s BePress repository. Our objective was to collect the full archive of dissertations and associated files from our repository into a local disk for potential future applications and to build out a preservation system.

Unlike at some institutions, our students submit directly into BePress, so we did not have a separate repository of the files; and the backup of BePress content that we had access to was not in an ideal format (for example, it included “withdrawn” items and did not …

Responsive Economic Model Predictive Control For Next-Generation Manufacturing, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

There is an increasing push to make automated systems capable of carrying out tasks which humans perform, such as driving, speech recognition, and anomaly detection. Automated systems, therefore, are increasingly required to respond to unexpected conditions. Two types of unexpected conditions of relevance in the chemical process industries are anomalous conditions and the responses of operators and engineers to controller behavior. Enhancing responsiveness of an advanced control design known as economic model predictive control (EMPC) (which uses predictions of future process behavior to determine an economically optimal manner in which to operate a process) to unexpected conditions of these types …

Taking The *Sigh* Out Of Science, Kathleen Devlin

Q2S Enhancing Pedagogy

This PowerPoint presentation describes a project where I will use social media in an attempt to improve the negative perception of science. Beginning Fall 2020, on the first day of class, I will have the students complete a pre-assessment on their perception of science. I will then ask the students to follow at least one pre-selected science person/group on either Instagram, Twitter, or Youtube. Each week I will have them do a quick think-pair-share on the topic they followed, and then do a short writing assignment. At the end of the semester I will have them complete a post-assessment and …

Efficient Forward-Secure And Compact Signatures For The Internet Of Things (Iot), Efe Ulas Akay Seyitoglu

USF Tampa Graduate Theses and Dissertations

In the modern Internet of Things (IoT) applications, the system entities collect security-sensitive information that must be cryptographically protected. In particular, authentication and integrity, as foundational security services, are essential for any IoT applications. Digital signatures provide both authentication and integrity to these applications. Nevertheless, once an IoT device is compromised, its signature private key is leaked to an adversary. Forward-secure digital signatures mitigate the impact of such key compromises by incorporating a key-evolving mechanism into the authentication process. However, existing forward-secure signatures suffer from large signature/key sizes, heavy computational overhead, and some prominent variants that can only sign a …

Novel View Synthesis In Time And Space, Simon Niklaus

Dissertations and Theses

Novel view synthesis is a classic problem in computer vision. It refers to the generation of previously unseen views of a scene from a set of sparse input images taken from different viewpoints. One example of novel view synthesis is the interpolation of views in between the two images of a stereo camera. Another classic problem in computer vision is video frame interpolation, which is important for video processing. It refers to the generation of video frames in between existing ones and is commonly used to increase the frame rate of a video or to match the frame rate to …

A Collaboration Between Neural Networks And Reinforcement Learning: Applying Concepts To A Brick Breaking Game, Bryce Kadrlik

Augsburg Honors Review

The intent of this work is to explore the interactions of artificial neural networks and digital games. It details the development of an artificial neural network trained upon a brick breaking game like the Atari game Breakout. This network was designed with the goals of not dropping the ball and maximizing the game score. Full game and network integration was not completed. However, two versions of the network were developed to move the paddle to the right or left based on the ball's point of impact on the paddle. In preliminary testing using manual inputs, these networks eventually learned to …

Combing Texts: A Quest To Increase The Timeliness And Accuracy Of Geotagging Multilingual Toponyms And Tagging Persons In Large Corpora Using Tensors For Disambiguation, Anthony D. Davis

Theses and Dissertations

This research demonstrates an effective algorithm and provides a tool for efficient and accurate disambiguation of domain specific texts. The goals outlined in the research are: 1) to demonstrate that a simple knowledge base can be used to tag texts, 2) to demonstrate that a tensor can be used to efficiently and accurately tag entities in raw text documents, and, 3) create and provide a machine learning digital humanities tool for scholars interested in early Christian documents in English and Greek from late-antiquity. The research shows that a simple knowledgebase using a comma delimited file along with a rank-3 tensor …

An Alternative To The One-Size-Fits-All Approach To Isa Training: A Design Science Approach To Isa Regarding The Adaption To Student Vulnerability Based On Knowledge And Behavior, Thomas Jernejcic

SDSU Data Science Symposium

Any connection to the university’s network is a conduit that has the potential of being exploited by an attacker, resulting in the possibility of substantial harm to the infrastructure, to the university, and to the student body of whom the university serves. While organizations rightfully “baton down the hatches” by building firewalls, creating proxies, and applying important updates, the most significant vulnerability, that of the student, continues to be an issue due to lack of knowledge, insufficient motivation, and inadequate or misguided training. Utilizing the Design Science Research (DSR) methodology, this research effort seeks to address the latter concern of …

Evaluation Of Text Mining Techniques Using Twitter Data For Hurricane Disaster Resilience, Joshua Eason, Sathish Kumar

SDSU Data Science Symposium

Data obtained from social media microblogging websites such as Twitter provide the unique ability to collect and analyze conversations of the public in order to gain perspective on the thoughts and feelings of the general public. Sentiment and volume analysis techniques were applied to the dataset in order to gain an understanding of the amount and level of sentiment associated with certain disaster-related tweets, including a topical analysis of specific terms. This study showed that disaster-type events such as a hurricane can cause some strong negative sentiment in the period of time directly preceding the event, but ultimately returns quickly …

Psidb: A Framework For Batched Query Processing And Optimization, Mehrad Eslami

USF Tampa Graduate Theses and Dissertations

Techniques based on sharing data and computation among queries have been an active research topic in database systems. While work in this area developed algorithms and systems that are shown to be effective, there is a lack of logical foundation for query processing and optimization. In this paper, we present PsiDB, a system model for processing a large number of database queries in a batch. The key idea is to generate a single query expression that returns a global relation containing all the data needed for individual queries. For that, we propose the use of a type of relational operators …

Wireless Underground Communications In Sewer And Stormwater Overflow Monitoring: Radio Waves Through Soil And Asphalt Medium, Usman Raza, Abdul Salam

Faculty Publications

Storm drains and sanitary sewers are prone to backups and overflows due to extra amount wastewater entering the pipes. To prevent that, it is imperative to efficiently monitor the urban underground infrastructure. The combination of sensors system and wireless underground communication system can be used to realize urban underground IoT applications, e.g., storm water and wastewater overflow monitoring systems. The aim of this article is to establish a feasibility of the use of wireless underground communications techniques, and wave propagation through the subsurface soil and asphalt layers, in an underground pavement system for storm water and sewer overflow monitoring application. …

Virtual Water Flows Embodied In International And Interprovincial Trade Of Yellow River Basin: A Multiregional Input-Output Analysis, Guilian Tian, Xiaosheng Han, Chen Zhang, Jiaojiao Li, Jinjing Liu

Information Systems and Analytics Department Faculty Journal Articles

With the imminent need of regional environmental protection and sustainable economic development, the concept of virtual water is widely used to solve the problem of regional water shortage. In this paper, nine provinces, namely Qinghai, Sichuan, Gansu, Ningxia, Inner Mongolia, Shaanxi, Shanxi, Henan, and Shandong in the Yellow River Basin (YRB), are taken as the research objects. Through the analysis of input-output tables of 30 provinces in China in 2012, the characteristics of virtual water trade in this region are estimated by using a multi-regional input-output (MRIO) model. The results show that: (1) The YRB had a net inflow of …

Critical Temperature Prediction Of Superconductors Based On Atomic Vectors And Deep Learning, Shaobo Li, Yabo Dan, Xiang Li, Tiantian Hu, Rongzhi Dong, Zhuo Cao, Jianjun Hu

Faculty Publications

In this paper, a hybrid neural network (HNN) that combines a convolutional neural network (CNN) and long short-term memory neural network (LSTM) is proposed to extract the high-level characteristics of materials for critical temperature (Tc) prediction of superconductors. Firstly, by obtaining 73,452 inorganic compounds from the Materials Project (MP) database and building an atomic environment matrix, we obtained a vector representation (atomic vector) of 87 atoms by singular value decomposition (SVD) of the atomic environment matrix. Then, the obtained atom vector was used to implement the coded representation of the superconductors in the order of the atoms in the chemical …

Who Owns Bitcoin? Private Law Facing The Blockchain, Matthias Lehmann

Minnesota Journal of Law, Science & Technology

No abstract provided.

Hierarchical Clustering Analyses Of Plasma Proteins In Subjects With Cardiovascular Risk Factors Identify Informative Subsets Based On Differential Levels Of Angiogenic And Inflammatory Biomarkers, Zachary Winder, Tiffany L. Sudduth, David W. Fardo, Qiang Cheng, Larry B. Goldstein, Peter T. Nelson, Frederick A. Schmitt, Gregory A. Jicha, Donna M. Wilcock

Sanders-Brown Center on Aging Faculty Publications

Agglomerative hierarchical clustering analysis (HCA) is a commonly used unsupervised machine learning approach for identifying informative natural clusters of observations. HCA is performed by calculating a pairwise dissimilarity matrix and then clustering similar observations until all observations are grouped within a cluster. Verifying the empirical clusters produced by HCA is complex and not well studied in biomedical applications. Here, we demonstrate the comparability of a novel HCA technique with one that was used in previous biomedical applications while applying both techniques to plasma angiogenic (FGF, FLT, PIGF, Tie-2, VEGF, VEGF-D) and inflammatory (MMP1, MMP3, MMP9, IL8, TNFα) protein data to …

Developing Big Data Projects In Open University Engineering Courses: Lessons Learned, Juan A. Lara, Aurea Anguera De Sojo, Shadi Aljawarneh, Robert P. Schumaker, Bassam Al-Shargabi

Computer Science Faculty Publications and Presentations

Big Data courses in which students are asked to carry out Big Data projects are becoming more frequent as a part of University Engineering curriculum. In these courses, instructors and students must face a series of special characteristics, difficulties and challenges that it is important to know about beforehand, so the lecturer can better plan the subject and manage the teaching methods in order to prevent students' academic dropout and low performance. The goal of this research is to approach this problem by sharing the lessons learned in the process of teaching e-learning courses where students are required to develop …

2020 February 04 - Computation And Research In Data Science (Cards) Minutes, Computation And Research In Data Science, East Tennessee State University

Computation and Research in Data Science (CaRDS) Board Meeting Minutes

No abstract provided.

Integrated Quantum Information Processing Controlled Phase Gate, Richard S. Kim, Attila A. Szep, Michael L. Fanto, Paul M. Alsing, Gordon E. Lott, Christopher C. Tison

AFIT Patents

An electro-optical directional coupler is provided having a substrate and a first and second optical waveguide formed on the substrate, where the second waveguide extends adjacent to and parallel with the first waveguide for at least one interaction length. The interaction length has a first end and a second end such that an optical signal applied only to one of the first and second waveguides couples to the other of the first and second waveguides between the ends. A first electrode is proximate the first and second waveguides and between the ends of the interaction length. A first voltage applied …

Classifying Emotions With Eeg And Peripheral Physiological Data Using 1d Convolutional Long Short-Term Memory Neural Network, Rupal Agarwal

USF Tampa Graduate Theses and Dissertations

Recognizing emotions is very important while building robust and interactive Affective Brain-Computer Interfaces as it allows the machines to have some degree of emotional intelligence with the help of which they can understand the changing emotional state of users. In the past, emotions have been recognized via unimodal data such as electroencephalography (EEG) signals, speech, facial expressions or peripheral physiological signals. However, emotions are complex as they are a combination of human behavior, thinking and feeling. Therefore, as compared to unimodal methods, multi-modal techniques, recognize emotions with more reliability. This thesis aims to recognize and classify human emotions into high/low …

A Cost Analysis Of Internet Of Things Sensor Data Storage On Blockchain Via Smart Contracts, Yesem Kurt Peker, Xavier Rodriguez, James Ericsson, Suk Jin Lee, Alfredo J. Perez

Computer Science Faculty Publications

Blockchain is a developing technology that can be utilized for secure data storage and sharing. In this work, we examine the cost of Blockchain-based data storage for constrained Internet of Things (IoT) devices. We had two phases in the study. In the first phase, we stored data retrieved from a temperature/humidity sensor connected to an Ethereum testnet blockchain using smart contracts in two different ways: first, appending the new data to the existing data, storing all sensor data; and second, overwriting the new data onto the existing data, storing only a recent portion of the data. In the second phase, …

A Monte Carlo Approach To Closing The Reality Gap, Damian Lyons, James Finocchiaro, Michael Novitzky, Christopher Korpela

Faculty Publications

We propose a novel approach to the ’reality gap’ problem, i.e., modifying a robot simulation so that its performance becomes more similar to observed real world phenomena. This problem arises whether the simulation is being used by human designers or in an automated policy development mechanism. We expect that the program/policy is developed using simulation, and subsequently deployed on a real system. We further assume that the program includes a monitor procedure with scalar output to determine when it is achieving its performance objectives. The proposed approach collects simulation and real world observations and builds conditional probability functions. These are …

A Cloud Based Approach For Secure Storage And Retrieval Of Standard Electronic Health Records, Raghavendra Ganiga

Manipal Institute of Technology, Manipal Theses and Dissertations

No abstract provided.

Singapore’S National Ai Strategy, Singapore Management University

Perspectives@SMU

The island state is banking on industry-wide projects and building an AI ecosystem to transform its economy