Physical Sciences and Mathematics Commons^™

Pattern Discovery In Dna Using Stochastic Automata, Shweta Shweta

Master's Projects

We consider the problem of identifying similarities between different species of DNA. To do this we infer a stochastic finite automata from a given training data and compare it with a test data. The training and test data consist of DNA sequence of different species. Our method first identifies sentences in DNA. To identify sentences we read DNA sequence one character at a time, 3 characters form a codon and codons form proteins (also known as amino acid chains).Each amino acid in proteins belongs to a group. In total we have 5 groups’ polar, non-polar, acidic, basic and stop codons. …

Designing For Positive Health Affect: Decoupling Negative Emotion And Health Monitoring Technologies, Tammy R. Toscos, Kay Connelly, Yvonne Rogers

Tammy R Toscos

Through various health-focused technology projects, we discovered that the emotional response to technology was related to uptake and sustained use of health monitoring technologies. In this paper we present a case study of how we synthesized constructs of social cognitive theory, technology as experience, and diabetes management guidelines as a framework for making design recommendations for blood glucose monitoring technology that address the emotional response of users. We suggest applying this theoretical lens for design may help attend to emotional responses of users in an effort to decouple strong negative emotions that are paired to health monitoring technologies that provide …

Optical Flow At Occlusion Boundaries And In Occlusion Regions, Hua Meng

Electronic Thesis and Dissertation Repository

Optical flow is an important research area in the Computer Vision field, with the estimation of optical flow at occlusion still an open problem. Traditional approaches to this problem have either used additional terms in a regularization calculation (the flow still tends to “bleed” across occlusion boundaries) or a local least squares calculation that attempted to minimize the influence of two adjacent differently moving regions on the optical flow at points close to both regions (the flow still tends to be “corrupted” by the two regions). Ideally, optical flow for two adjacent differently moving regions should be distinct right up …

Surface Reconstruction From Noisy And Sparse Data, Mark A. Brophy

Electronic Thesis and Dissertation Repository

We introduce a set of algorithms for registering, filtering and measuring the similarity of unorganized 3d point clouds, usually obtained from multiple views.

We contribute a method for computing the similarity between point clouds that represent closed surfaces, specifically segmented tumors from CT scans. We obtain watertight surfaces and utilize volumetric overlap to determine similarity in a volumetric way. This similarity measure is used to quantify treatment variability based on target volume segmentation both prior to and following radiotherapy planning stages.

We also contribute an algorithm for the drift-free registration of thin, non- rigid scans, where drift is the build-up …

An Immersive Telepresence System Using Rgb-D Sensors And Head-Mounted Display, Xinzhong Lu, Ju Shen, Saverio Perugini, Jianjun Yang

Computer Science Faculty Publications

We present a tele-immersive system that enables people to interact with each other in a virtual world using body gestures in addition to verbal communication. Beyond the obvious applications, including general online conversations and gaming, we hypothesize that our proposed system would be particularly beneficial to education by offering rich visual contents and interactivity. One distinct feature is the integration of egocentric pose recognition that allows participants to use their gestures to demonstrate and manipulate virtual objects simultaneously. This functionality enables the instructor to effectively and efficiently explain and illustrate complex concepts or sophisticated problems in an intuitive manner. The …

Salad: A Multimodal Approach For Contextual Video Advertising, Chen Xiang, Tam Nguyen, Mohan Kankanhalli

Computer Science Faculty Publications

The explosive growth of multimedia data on Internet has created huge opportunities for online video advertising. In this paper, we propose a novel advertising technique called SalAd, which utilizes textual information, visual content and the webpage saliency, to automatically associate the most suitable companion ads with online videos. Unlike most existing approaches that only focus on selecting the most relevant ads, SalAd further considers the saliency of selected ads to reduce intentional ignorance. SalAd consists of three basic steps. Given an online video and a set of advertisements, we first roughly identify a set of relevant ads based on the …

Neural Decomposition Of Time-Series Data For Effective Generalization, Luke Godfrey

Graduate Theses and Dissertations

We present a neural network technique for the analysis and extrapolation of time-series data called Neural Decomposition (ND). Units with a sinusoidal activation function are used to perform a Fourier-like decomposition of training samples into a sum of sinusoids, augmented by units with nonperiodic activation functions to capture linear trends and other nonperiodic components. We show how careful weight initialization can be combined with regularization to form a simple model that generalizes well. Our method generalizes effectively on the Mackey-Glass series, a dataset of unemployment rates as reported by the U.S. Department of Labor Statistics, a time-series of monthly international …

Mlaas: Machine Learning As A Service, Mauro Ribeiro, Katarina Grolinger, Miriam Am Capretz

Electrical and Computer Engineering Publications

The demand for knowledge extraction has been increasing. With the growing amount of data being generated by global data sources (e.g., social media and mobile apps) and the popularization of context-specific data (e.g., the Internet of Things), companies and researchers need to connect all these data and extract valuable information. Machine learning has been gaining much attention in data mining, leveraging the birth of new solutions. This paper proposes an architecture to create a flexible and scalable machine learning as a service. An open source solution was implemented and presented. As a case study, a forecast of electricity demand was …

Qubit Measurement Error From Coupling With A Detuned Neighbor In Circuit Qed, Mostafa Khezri, Justin Dressel, Alexander N. Korotkov

Mathematics, Physics, and Computer Science Faculty Articles and Research

In modern circuit QED architectures, superconducting transmon qubits are measured via the state-dependent phase and amplitude shift of a microwave field leaking from a coupled resonator. Determining this shift requires integrating the field quadratures for a nonzero duration, which can permit unwanted concurrent evolution. Here we investigate such dynamical degradation of the measurement fidelity caused by a detuned neighboring qubit. We find that in realistic parameter regimes, where the qubit ensemble-dephasing rate is slower than the qubit-qubit detuning, the joint qubit-qubit eigenstates are better discriminated by measurement than the bare states. Furthermore, we show that when the resonator leaks much …

Why It Is Difficult To Apply Revenue Management Techniques To The Car Rental Business And What Can Be Done About It, Robert F. Gordon Ph.D.

Faculty Works: MCS (1984-2023)

Revenue management systems are used by airlines, hotels, and cruise lines to manipulate prices and availability of inventory in real-time, in order to increase profit. We discuss the reasons that the revenue management problem is more complex when applied to the car rental business. We then show how to simplify the model formulation and provide the human-computer interaction, organization, and procedures to make the problem tractable for the car rental business.

Study Solar Activity In The Backside Of The Sun, Catherine A. Gibbs

Von Braun Symposium Student Posters

No abstract provided.

The Digital Incunabula: Rock • Paper • Pixels, Patrick Aievoli

Zea E-Books Collection

“The Digital Incunabula is Patrick Aievoli’s personal sonnet through media, interaction and communication design. He carefully crafts each evolutionary step into ripples that are supported by his own storied professional and academic experiences. It’s full of facts, terms and historical information which makes it perfect for anyone looking to flat out learn!” ● James Pannafino, Professor, Millersville University & Interaction Design

“This is a serious work that will find a broad community of readers. The depth and breadth of Aievoli’s experience in the publication industry give his voice and ideas credibility in the extreme. This book will inspire deep reflection.” …

Analyzing And Organizing The Sonic Space Of Vocal Imitation, Davide Andrea Mauro Phd, D. Rocchesso

Computer Sciences and Electrical Engineering Faculty Research

The sonic space that can be spanned with the voice is vast and complex and, therefore, it is difficult to organize and explore. In order to devise tools that facilitate sound design by vocal sketching we attempt at organizing a database of short excerpts of vocal imitations. By clustering the sound samples on a space whose dimensionality has been reduced to the two principal components, it is experimentally checked how meaningful the resulting clusters are for humans. Eventually, a representative of each cluster, chosen to be close to its centroid, may serve as a landmark in the exploration of the …

Data Science In Statistics Curricula: Preparing Students To “Think With Data”, J. Hardin, R. Hoerl, Nicholas J. Horton, D. Nolan, B. Baumer, O. Hall-Holt, P. Murrell, R. Peng, P. Roback, D. Temple Lang, M. D. Ward

Statistical and Data Sciences: Faculty Publications

A growing number of students are completing undergraduate degrees in statistics and entering the workforce as data analysts. In these positions, they are expected to understand how to use databases and other data warehouses, scrape data from Internet sources, program solutions to complex problems in multiple languages, and think algorithmically as well as statistically. These data science topics have not traditionally been a major component of undergraduate programs in statistics. Consequently, a curricular shift is needed to address additional learning outcomes. The goal of this article is to motivate the importance of data science proficiency and to provide examples and …

Mutations Of Adjacent Amino Acid Pairs Are Not Always Independent, Jyotsna Ramanan, Peter Revesz

CSE Conference and Workshop Papers

Evolutionary studies usually assume that the genetic mutations are independent of each other. This paper tests the independence hypothesis for genetic mutations with regard to protein coding regions. According to the new experimental results the independence assumption generally holds, but there are certain exceptions. In particular, the coding regions that represent two adjacent amino acids seem to change in ways that sometimes deviate significantly from the expected theoretical probability under the independence assumption.

A Computational Translation Of The Phaistos Disk, Peter Revesz

CSE Conference and Workshop Papers

For over a century the text of the Phaistos Disk remained an enigma without a convincing translation. This paper presents a novel semi-automatic translation method that uses for the first time a recently discovered connection between the Phaistos Disk symbols and other ancient scripts, including the Old Hungarian alphabet. The connection between the Phaistos Disk script and the Old Hungarian alphabet suggested the possibility that the Phaistos Disk language may be related to Proto-Finno-Ugric, Proto-Ugric, or Proto-Hungarian. Using words and suffixes from those languages, it is possible to translate the Phaistos Disk text as an ancient sun hymn, possibly connected …

A Computational Model Of The Spread Of Ancient Human Populations Based On Mitochondrial Dna Samples, Peter Revesz

CSE Conference and Workshop Papers

The extraction of mitochondrial DNA (mtDNA) from ancient human population samples provides important data for the reconstruction of population influences, spread and evolution from the Neolithic to the present. This paper presents a mtDNA-based similarity measure between pairs of human populations and a computational model for the evolution of human populations. In a computational experiment, the paper studies the mtDNA information from five Neolithic and Bronze Age populations, namely the Andronovo, the Bell Beaker, the Minoan, the Rössen and the Únětice populations. In the past these populations were identified as separate cultural groups based on geographic location, age and the …

A-Maze-D: Advanced Maze Development Kit Using Constraint Databases, Shruti Daggumarti, Peter Revesz, Corey Svehla

CSE Conference and Workshop Papers

In this paper, we describe the A-Maze-D system which shows that constraint databases can be applied conveniently and efficiently to the design of maze games. A-Maze-D provides a versatile set of features by a combination of a MATLAB library and the MLPQ constraint database system. A-Maze-D is the first system that uses constraint databases to build maze games and opens new ideas in video game development.

A Computational Study Of The Evolution Of Cretan And Related Scripts, Peter Revesz

CSE Conference and Workshop Papers

Crete was the birthplace of several ancient writings, including the Cretan Hieroglyphs, the Linear A and the Linear B scripts. Out of these three only Linear B is deciphered. The sound values of the Cretan Hieroglyph and the Linear A symbols are unknown and attempts to reconstruct them based on Linear B have not been fruitful. In this paper, we compare the ancient Cretan scripts with four other Mediterranean and Black Sea scripts, namely Phoenician, South Arabic, Greek and Old Hungarian. We provide a computational study of the evolution of the three Cretan and four other scripts. This study encompasses …

Sense Beyond Expressions: Cuteness, Kang Wang, Tam Nguyen, Jiashi Feng, Jose Sepulveda

Computer Science Faculty Publications

With the development of Internet culture, cute has become a popular concept. Many people are curious about what factors making a person look cute. However, there is rare research to answer this interesting question. In this work, we construct a dataset of personal images with comprehensively annotated cuteness scores and facial attributes to investigate this high-level concept in depth. Based on this dataset, through an automatic attributes mining process, we find several critical attributes determining the cuteness of a person.

We also develop a novel Continuous Latent Support Vector Machine (C-LSVM) method to predict the cuteness score of one person …

Adaptive Nonparametric Image Parsing, Tam Nguyen, Canyi Lu, Jose Sepulveda, Shuicheng Yan

Computer Science Faculty Publications

In this paper, we present an adaptive nonparametric solution to the image parsing task, namely, annotating each image pixel with its corresponding category label. For a given test image, first, a locality-aware retrieval set is extracted from the training data based on superpixel matching similarities, which are augmented with feature extraction for better differentiation of local superpixels. Then, the category of each superpixel is initialized by the majority vote of the k -nearest-neighbor superpixels in the retrieval set. Instead of fixing k as in traditional nonparametric approaches, here, we propose a novel adaptive nonparametric approach that determines the sample-specific k …

Enhancing Manufacturing Planning And Control Systems Through Artificial Intelligence Techniques, Ronald S. Dattero, John J. Kanet, Edna M. White

John J. Kanet

Manufacturing planning and control systems are currently dominated by systems based upon Material Requirements Planning (MRP). MRP systems have a number of fundamental flaws. A potential alternative to MRP systems is suggested after research into the economic batch scheduling problem. Based on the ideas of economic batch scheduling, and enhanced through artificial intelligence techniques, an alternative approach to manufacturing planning and control is developed. A framework for future research on this alternative to MRP is presented.

Capacity Planning With Financial And Operational Hedging In Low‐Cost Countries, Lijian Chen, Shanling Li, Letian Wang

Lance (Lijian) Chen

The authors of this paper outline a capacity planning problem in which a risk-averse firm reserves capacities with potential suppliers that are located in multiple low-cost countries. While demand is uncertain, the firm also faces multi-country foreign currency exposures. This study develops a mean-variance model that maximizes the firm’s optimal utility and derives optimal utility and optimal decisions in capacity and financial hedging size. The authors show that when demand and exchange rate risks are perfectly correlated, a risk- averse firm, by using financial hedging, will achieve the same optimal utility as a risk-neutral firm. In this paper as well, …

A Simulation-Based Approach To Solve A Specific Type Of Chance Constrained Optimization, Lijian Chan

Lance (Lijian) Chen

We solve the chance constrained optimization with convex feasible set through approximating the chance constraint by another convex smooth function. The approximation is based on the numerical properties of the Bernstein polynomial that is capable of effectively controlling the approximation error for both function value and gradient. Thus, we adopt a first-order algorithm to reach a satisfactory solution which is expected to be optimal. When the explicit expression of joint distribution is not available, we then use Monte Carlo approach to numerically evaluate the chance constraint to obtain an optimal solution by probability. Numerical results for known problem instances are …

Re-Solving Stochastic Programming Models For Airline Revenue Management, Lijian Chen, Tito Homem-De-Mello

Lance (Lijian) Chen

We study some mathematical programming formulations for the origin-destination model in airline revenue management. In particular, we focus on the traditional probabilistic model proposed in the literature. The approach we study consists of solving a sequence of two-stage stochastic programs with simple recourse, which can be viewed as an approximation to a multi-stage stochastic programming formulation to the seat allocation problem. Our theoretical results show that the proposed approximation is robust, in the sense that solving more successive two-stage programs can never worsen the expected revenue obtained with the corresponding allocation policy. Although intuitive, such a property is known not …

Ancillary Service Capacity Optimization For Both Electric Power Suppliers And Independent System Operator, Lijian Chen, Dengfeng Sun, Guang Li

Lance (Lijian) Chen

Ancillary Services (AS) in electric power industry are critical to support the transmission of energy from generators to load demands while maintaining reliable operation of transmission systems in accordance with good utility practice. The ancillary services are procured by the independent system operator (ISO) through a process called the market clearing process which can be modeled by the partial equilibrium from the ends of ISO. There are two capacity optimization problems for both Market participants (MP) and Independent System Operator (ISO). For a market participant, the firm needs to determine the capacity allocation plan for various AS to pursue operating …

Capacity-Driven Pricing Mechanism In Special Service Industries, Lijian Chen, Suraj M. Alexander

Lance (Lijian) Chen

We propose a capacity driven pricing mechanism for several service industries in which the customer behavior, the price demand relationship, and the competition are significantly distinct from other industries. According our observation, we found that the price demand relationship in these industries cannot be modeled by fitted curves; the customers would neither plan in advance nor purchase the service strategically; and the competition would be largely local. We analyze both risk neutral and risk aversion pricing models and conclude the proposed capacity driven model would be the optimal solution under mild assumptions. The resulting pricing mechanism has been implemented at …

Information Diffusion, Facebook Clusters, And The Simplicial Model Of Social Aggregation: A Computational Simulation Of Simplicial Diffusers For Community Health Interventions, Kerk Kee, Lisa Sparks, Daniele C. Struppa, Mirco A. Manucci, Alberto Damiano

Communication Faculty Articles and Research

By integrating the simplicial model of social aggregation with existing research on opinion leadership and diffusion networks, this article introduces the constructs of simplicial diffusers (mathematically defined as nodes embedded in simplexes; a simplex is a socially bonded cluster) and simplicial diffusing sets (mathematically defined as minimal covers of a simplicial complex; a simplicial complex is a social aggregation in which socially bonded clusters are embedded) to propose a strategic approach for information diffusion of cancer screenings as a health intervention on Facebook for community cancer prevention and control. This approach is novel in its incorporation of interpersonally bonded clusters, …

Implementation Techniques For The Truncated Fourier Transform, Li Zhang

Electronic Thesis and Dissertation Repository

We study various algorithms for the Truncated Fourier Transform (TFT) which is a variation of the Discrete Fourier Transform (DFT) that allows one to work with an input vector of arbitrary size without zero padding. After a review of the original algorithms for the forward and inverse TFT introduced by J. van der Hoeven, we consider the variation of D. Harvey as well as that of J. Johnson and L.C. Meng. Both variations are based on Cooley-Tukey like formulas. The former is called strict general radix as it strictly follows the specifications proposed by J. van der Hoeven, while the …

Design And Implementation Of Satellite Software To Facilitate Future Cubesat Development, Timothy Whitney, Jeremy Straub, Ronald Marsh

Jeremy Straub

The OpenOrbiter project is a campus-wide effort at the University of North Dakota to design and build a low-cost CubeSat-class satellite. The intent is to create a publically- available framework that allows a spacecraft to be built with a parts cost of less than USD $5,000 (excluding mission payload-specific costs). This paper focuses on OpenOrbiter’s software system methodology and implementation.

Current work seeks to create a generalized framework that other CubeSat developers can use directly or alter to suit their mission needs. It discusses OpenOrbiter’s overall design goals with an emphasis on software design. The software architecture is divided into …