Sorting By Strip Moves And Strip Swaps, 2020 University of North Florida
Sorting By Strip Moves And Strip Swaps, Chandrika Pandurang Rao
UNF Graduate Theses and Dissertations
Genome rearrangement problems in computational biology [19, 29, 27] and zoning algorithms in optical character recognition [14, 4] have been modeled as combinatorial optimization problems related to the familiar problem of sorting, namely transforming arbitrary permutations to the identity permutation. The term permutation is used for an arbitrary arrangement of the integers 1, 2,···, n, and the term identity permutation for the arrangement of 1, 2,···, n in increasing order. When a permutation is viewed as the string of integers from 1 through n, any substring in it that is also a substring in the identity permutation will be called ...
A Direct Data-Cluster Analysis Method Based On Neutrosophic Set Implication, 2020 University of New Mexico
A Direct Data-Cluster Analysis Method Based On Neutrosophic Set Implication, Florentin Smarandache, Sudan Jha, Gyanendra Prasad Joshi, Lewis Nkenyereya, Dae Wan Kim
Mathematics and Statistics Faculty and Staff Publications
Raw data are classified using clustering techniques in a reasonable manner to create disjoint clusters. A lot of clustering algorithms based on specific parameters have been proposed to access a high volume of datasets. This paper focuses on cluster analysis based on neutrosophic set implication, i.e., a k-means algorithm with a threshold-based clustering technique. This algorithm addresses the shortcomings of the k-means clustering algorithm by overcoming the limitations of the threshold-based clustering algorithm. To evaluate the validity of the proposed method, several validity measures and validity indices are applied to the Iris dataset (from the University of California, Irvine ...
Predicting Imports In Java Code With Graph Neural Networks, 2020 Bard College
Predicting Imports In Java Code With Graph Neural Networks, Aleksandr Fedchin
Senior Projects Spring 2020
Programmers tend to split their code into multiple files or sub-modules. When a program is executed, these sub-modules interact to produce the desired effect. One can, therefore, represent programs with graphs, where each node corresponds to some file and each edge corresponds to some relationship between files, such as two files being located in the same package or one file importing the content of another. This project trains Graph Neural Networks on such graphs to learn to predict future imports in Java programs and shows that Graph Neural Networks outperform various baseline methods by a wide margin.
Deep Learning Based Face Detection And Recognition In Mwir And Visible Bands, 2020 West Virginia University
Deep Learning Based Face Detection And Recognition In Mwir And Visible Bands, Suha Reddy Mokalla
Graduate Theses, Dissertations, and Problem Reports
In non-favorable conditions for visible imaging like extreme illumination or nighttime, there is a need to collect images in other spectra, specifically infrared. Mid-Wave infrared (3-5 microm) images can be collected without giving away the location of the sensor in varying illumination conditions. There are many algorithms for face detection, face alignment, face recognition etc. proposed in visible band till date, while the research using MWIR images is highly limited. Face detection is an important pre-processing step for face recognition, which in turn is an important biometric modality. This thesis works towards bridging the gap between MWIR and visible spectrum ...
Smart Collar, 2020 The University of Akron
Smart Collar, Gretchen T. Woodling, Sean Moran, Justen Bischoff, Jacob Sindelar
Williams Honors College, Honors Research Projects
The Smart Collar is a universal pet tracker, designed to be small and exceedingly comfortable for any pet to wear. GPS technology is used to locate the device, allowing the user to track their pet, via a smart phone application. This application can be used to program the device, view maps of their pet’s location and history of travel. Operating primarily on Long Range Wide Area Network (LoRaWAN) for data transfer, the device consumes very little power, allowing for several days of run-time per charge of the battery. Boasting no monthly service fees, The Smart Collar provides pet owner ...
Piezoelectric Energy Harvester Improvement, 2020 The University of Akron
Piezoelectric Energy Harvester Improvement, Nathan Embaugh, Jason Mack, Jeremiah Fitzgerald, Zachary J. Lindsey
Williams Honors College, Honors Research Projects
The energy harvester is used to convert a portion of the tire deflection waste energy to power up tire embedded sensors. A piezoelectric energy harvester is designed and some preliminary tests are done on it. So far, it has been shown that this design is sufficient for tire application. The team will need to modify the design of the energy harvester, the measurement setup and add a temperature and a strain senor to the existing setup so that the tire deflection and temperature can be measured and at the same time the energy harvester should be tested to see how ...
Jc Drain And Sewer Website, 2020 Arcadia University
Jc Drain And Sewer Website, Jarod Pichler, Nathan Houman
A website for a small plumbing business in Scranton, Pennsylvania. The website includes a Home, About Us, Services, Contact Us, and Testimonials page. The home page introduces the company to the website viewer. The About Us page provides information about the company and owner, to the website viewer. The Services page provides the website viewer with all of the services that the company can provide. The Contact Us page allows the website viewer to send the company an email. Finally, the Testimonials page will allow the website viewer to leave a comment about the company’s services. The website also ...
Instructor Activity Recognition Using Smartwatch And Smartphone Sensors, 2020 Georgia Southern University
Instructor Activity Recognition Using Smartwatch And Smartphone Sensors, Zayed Uddin Chowdhury
Electronic Theses and Dissertations
During a classroom session, an instructor performs several activities, such as writing on the board, speaking to the students, gestures to explain a concept. A record of the time spent in each of these activities could be valuable information for the instructors to virtually observe their own style of instruction. It can help in identifying activities that engage the students more, thereby enhancing teaching effectiveness and efficiency. In this work, we present a preliminary study on profiling multiple activities of an instructor in the classroom using smartwatch and smartphone sensor data. We use 2 benchmark datasets to test out the ...
Automated Field Boundary Detection Using Modern Machine Learning Techniques, 2020 Iowa State University
Automated Field Boundary Detection Using Modern Machine Learning Techniques, Rishikumar Suresh Kumar
The Agricultural Conservation Planning Framework (ACPF) is a framework for watershed analysis that is supported by a unique land management database. Implementing the ACPF Framework comprises several steps. One of the most important steps in this framework is manually editing the United States Department of Agriculture (USDA) Farm Service Agency (FSA) Common Land Unit (CLU) boundaries to match cropping patterns per USDA National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) and National Agricultural Imagery Program (NAIP) aerial imagery. This step uses lot of man-hours and is highly susceptible to human errors. The use of latest deep-learning techniques will help ...
Analyzing Social Media Data And Performance Comparison With Traditional Database, Data Warehouse, And Mapreduce Approaches, Wei Xu
Data warehouse, OLAP technology and distributed analysis show great potential in improving business analysis, tendency prediction and decision making. With the assistance of data mining techniques, databases can also be a useful tool for analyzing societal trends by gathering data from social media networks. As these networks can contain huge amounts of text data, it can serve as a perfect platform for testing text mining technologies, and discovering what kind of trend or what kind of topic concern people the most during a certain time period. This project utilizes a data set of tweets generated from May to June 2019 ...
Splunk Software Platform Data Transformation, 2020 Iowa State University
Splunk Software Platform Data Transformation, Shanell Hurst
Machine data can be harvested from virtually any device in a structured or unstructured format. The amount of information collected can be massive, confusing and challenging to interpret. Data compilation has the ability to tell a story about events that have taken place. Splunk’s software platform can demystify obscurity by allowing users to view machine data in an understandable format, correlate information with log files, send alerts as well as pinpoint sources for troubleshooting and problem resolution. I implemented different forwarder instances on various servers located in both public facing and virtual environments. Indexers were created to store, process ...
High-Performance Spectral Methods For Computer-Aided Design Of Integrated Circuits, 2020 Michigan Technological University
High-Performance Spectral Methods For Computer-Aided Design Of Integrated Circuits, Zhiqiang Zhao
Dissertations, Master's Theses and Master's Reports
Recent research shows that by leveraging the key spectral properties of eigenvalues and eigenvectors of graph Laplacians, more efficient algorithms can be developed for tackling many graph-related computing tasks. In this dissertation, spectral methods are utilized for achieving faster algorithms in the applications of very-large-scale integration (VLSI) computer-aided design (CAD)
First, a scalable algorithmic framework is proposed for effective-resistance preserving spectral reduction of large undirected graphs. The proposed method allows computing much smaller graphs while preserving the key spectral (structural) properties of the original graph. Our framework is built upon the following three key components: a spectrum-preserving node aggregation and ...
Bibliometric Analysis Of Bearing Fault Detection Using Artificial Intelligence, 2020 Symbiosis Institute of Technology,Symbiosis International University, MITSOE, MIT-ADT University, Pune, India
Bibliometric Analysis Of Bearing Fault Detection Using Artificial Intelligence, Pooja Kamat, Rekha Sugandhi Dr.
Library Philosophy and Practice (e-journal)
The new industrial revolution called Industry 4.0 is proliferating at its peak. The time is no longer away when the human race is going to witness a huge paradigm shift. Intelligent machines empowered by Artificial Intelligence (AI)will take over the presence of human workers in the industrial manufacturing sector with the target of achieving 100% automation. With the emergence of cut-throat price competition in the product market, it has become equally important to manufacture goods at minimal costs and with the highest quality. Predicting the decrease in machinery efficiency at an earlier stage to accomplish this objective helps ...
Palmprint Gender Classification Using Deep Learning Methods, Minou Khayami
Graduate Theses, Dissertations, and Problem Reports
Gender identification is an important technique that can improve the performance of authentication systems by reducing searching space and speeding up the matching process. Several biometric traits have been used to ascertain human gender. Among them, the human palmprint possesses several discriminating features such as principal-lines, wrinkles, ridges, and minutiae features and that offer cues for gender identification. The goal of this work is to develop novel deep-learning techniques to determine gender from palmprint images. PolyU and CASIA palmprint databases with 90,000 and 5502 images respectively were used for training and testing purposes in this research. After ROI extraction ...
Modeling Electrochemical Systems With Weakly Imposed Dirichlet Boundary Conditions, 2020 Iowa State University
Modeling Electrochemical Systems With Weakly Imposed Dirichlet Boundary Conditions, Sungu Kim, Robbyn Anand, Baskar Ganapathysubramanian
Mechanical Engineering Publications
Finite element modeling of charged species transport has enabled analysis, design and optimization of a diverse array of electrochemical and electrokinetic devices. These systems are represented by the Poisson-Nernst-Plank equations coupled with the Navier-Stokes equation, with a key quantity of interest being the current at the system boundaries. Accurately computing the current flux is challenging due to the small critical dimension of the boundary layers (small Debye layer) that require fine mesh resolution at the boundaries. We resolve this challenge by using the Dirichlet-to-Neumann transformation to weakly impose the Dirichlet conditions for the Poisson-Nernst-Plank equations. The results obtained with weakly ...
Applying Artificial Intelligence To Medical Data, 2020 Shaikh Shiam Rahman
Applying Artificial Intelligence To Medical Data, Shaikh Shiam Rahman
Electronic Theses and Dissertations
Machine learning, data mining, and deep learning has become the methodology of choice for analyzing medical data and images. In this study, we implemented three different machine learning techniques to medical data and image analysis. Our first study was to implement different log base entropy for a decision tree algorithm. Our results suggested that using a higher log base for the dataset with mostly categorical attributes with three or more categories for each attribute can obtain a higher accuracy. For the second study, we analyzed mental health data tuning the parameters of the decision tree (splitting method, depth and entropy ...
Benchmarking Java And Kotlin In Android Runtime Environment, 2020 Iowa State University
Benchmarking Java And Kotlin In Android Runtime Environment, Arnoldo Montoya-Gamez
In 2017, Google announced that the Kotlin Programming Language would become an official Android Development language. In the meantime, it has become one of the fastest-growing programming languages. In this study, we studied the trade-offs between using Kotlin and what was officially the Android programming language, Java. This study focuses on seeing if there are differences between Java and Kotlin in execution speeds, Application size, and lines of code. To analyze the trade-offs, we wrote two Android Apps, one using only Java, and the other using only Kotlin. To measure runtime, we wrote 5 commonly used algorithms using the same ...
Identifying Customer Churn In After-Market Operations Using Machine Learning Algorithms, 2019 Southern Methodist University
Identifying Customer Churn In After-Market Operations Using Machine Learning Algorithms, Vitaly Briker, Richard Farrow, William Trevino, Brent Allen
SMU Data Science Review
This paper presents a comparative study on machine learning methods as they are applied to product associations, future purchase predictions, and predictions of customer churn in aftermarket operations. Association rules are used help to identify patterns across products and find correlations in customer purchase behaviour. Studying customer behaviour as it pertains to Recency, Frequency, and Monetary Value (RFM) helps inform customer segmentation and identifies customers with propensity to churn. Lastly, Flowserve’s customer purchase history enables the establishment of churn thresholds for each customer group and assists in constructing a model to predict future churners. The aim of this model ...
Cluster-Based Chained Transfer Learning For Energy Forecasting With Big Data, 2019 The University of Western Ontario
Cluster-Based Chained Transfer Learning For Energy Forecasting With Big Data, Yifang Tian
Electronic Thesis and Dissertation Repository
Smart meter popularity has resulted in the ability to collect big energy data and has created opportunities for large-scale energy forecasting. Machine Learning (ML) techniques commonly used for forecasting, such as neural networks, involve computationally intensive training typically with data from a single building/group to predict future consumption for that same building/group. With hundreds of thousands of smart meters, it becomes impractical or even infeasible to individually train a model for each meter. Consequently, this paper proposes Cluster-Based Chained Transfer Learning (CBCTL), an approach for building neural network-based models for many meters by taking advantage of already trained ...
Computer Science and Computer Engineering Undergraduate Honors Theses
Deep learning has advanced progressively in the last years and now demonstrates state-of-the-art performance in various fields. In the era of big data, transformation of data into valuable knowledge has become one of the most important challenges in computing. Therefore, we will review multiple algorithms for face recognition that have been researched for a long time and are maturely developed, and analyze deep learning, presenting examples of current research.
To provide a useful and comprehensive perspective, in this paper we categorize research by deep learning architecture, including neural networks, convolutional neural networks, depthwise Separable Convolutions, densely connected convolutional networks, and ...