Computer Sciences Commons^™

On The Approximability Of The Exemplar Adjacency Number Problem For Genomes With Gene Repetitions, Zhinxiag Chen, Bin Fu, Randy Goebel, Guohui Lin, Weitian Tong, Jinhui Xu, Boting Yang, Zhiyu Zhao, Binhai Zhu

Computer Science Faculty Publications and Presentations

In this paper, we apply a measure, exemplar adjacency number, which complements and extends the well-studied breakpoint distance between two permutations, to measure the similarity between two genomes (or in general, between any two sequences drawn from the same alphabet). For two genomes and drawn from the same set of n gene families and containing gene repetitions, we consider the corresponding Exemplar Adjacency Number problem (EAN), in which we delete duplicated genes from and such that the resultant exemplar genomes (permutations) G and H have the maximum adjacency number. We obtain the following results. First, we prove that the one-sided …

Exponential Replication Of Patterns In The Signal Tile Assembly Model, Alexandra Keenan, Robert Schweller, Xingsi Zhong

Computer Science Faculty Publications and Presentations

Chemical self-replicators are of considerable interest in the field of nanomanufacturing and as a model for evolution. We introduce the problem of self-replication of rectangular two-dimensional patterns in the practically motivated Signal Tile Assembly Model (STAM) [9]. The STAM is based on the Tile Assembly Model (TAM) which is a mathematical model of self-assembly in which DNA tile monomers may attach to other DNA tile monomers in a programmable way. More abstractly, four-sided tiles are assigned glue types to each edge, and self-assembly occurs when singleton tiles bind to a growing assembly, if the glue types match and the glue …

Design Of A Flexible Component Gathering Algorithm For Converting Cell-Based Models To Graph Representations For Use In Evolutionary Search, Marianna Budnikova, Jeffrey W. Habig, Daniel Lobo, Nicolas Cornia, Michael Levin, Tim Andersen

Computer Science Faculty Publications and Presentations

Background

The ability of science to produce experimental data has outpaced the ability to effectively visualize and integrate the data into a conceptual framework that can further higher order understanding. Multidimensional and shape-based observational data of regenerative biology presents a particularly daunting challenge in this regard. Large amounts of data are available in regenerative biology, but little progress has been made in understanding how organisms such as planaria robustly achieve and maintain body form. An example of this kind of data can be found in a new repository (PlanformDB) that encodes descriptions of planaria experiments and morphological outcomes using a …

Inference Of Snp-Gene Regulatory Networks By Integrating Gene Expressions And Genetic Perturbations, Dongchul Kim, Jiao Wang, Chunyu Liu, Jean Gao

Computer Science Faculty Publications and Presentations

In order to elucidate the overall relationships between gene expressions and genetic perturbations, we propose a network inference method to infer gene regulatory network where single nucleotide polymorphism (SNP) is involved as a regulator of genes. In the most of the network inferences named as SNP-gene regulatory network (SGRN) inference, pairs of SNP-gene are given by separately performing expression quantitative trait loci (eQTL) mappings. In this paper, we propose a SGRN inference method without predefined eQTL information assuming a gene is regulated by a single SNP at most. To evaluate the performance, the proposed method was applied to random data …

What We Can And Cannot (Yet) Do With Functional Near Infrared Spectroscopy, Megan K. Strait, Matthias Scheutz

Computer Science Faculty Publications and Presentations

Functional near infrared spectroscopy (NIRS) is a relatively new technique complimentary to EEG for the development of brain-computer interfaces (BCIs). NIRS-based systems for detecting various cognitive and affective states such as mental and emotional stress have already been demonstrated in a range of adaptive human–computer interaction (HCI) applications. However, before NIRS-BCIs can be used reliably in realistic HCI settings, substantial challenges oncerning signal processing and modeling must be addressed. Although many of those challenges have been identified previously, the solutions to overcome them remain scant. In this paper, we first review what can be currently done with NIRS, specifically, NIRS-based …

Learning Two-Input Linear And Nonlinear Analog Functions With A Simple Chemical System, Peter Banda, Christof Teuscher

Computer Science Faculty Publications and Presentations

The current biochemical information processing systems behave in a predetermined manner because all features are defined during the design phase. To make such unconventional computing systems reusable and programmable for biomedical applications, adaptation, learning, and self-modification baaed on external stimuli would be highly desirable. However, so far, it haa been too challenging to implement these in real or simulated chemistries. In this paper we extend the chemical perceptron, a model previously proposed by the authors, to function as an analog instead of a binary system. The new analog asymmetric signal perceptron learns through feedback and supports MichaelisMenten kinetics. The results …

The Insecurity Of Two Proxy Signcryption Schemes: Proxy Credential Forgery Attack And How To Prevent It, Jyh-Haw Yeh

Computer Science Faculty Publications and Presentations

Securing different online e-business activities usually requires applying different cryptographic algorithms. The proxy signcryption algorithms are designed for applications such as online proxy auction or online proxy signatures on business contracts, which require a proxy agent to sign on confidential messages. This paper proposes a proxy credential forgery attack to two recent proxy signcryption schemes in the literature. Using the attack, a malicious proxy signer can create a fake proxy credential from his original credential to extend his signing power. Simple modifications to these two schemes are also provided in this paper to prevent the attack without adding too much …

Damage Spreading In Spatial And Small-World Random Boolean Networks, Qiming Lu, Christof Teuscher

Computer Science Faculty Publications and Presentations

The study of the response of complex dynamical social, biological, or technological networks to external perturbations has numerous applications. Random Boolean networks (RBNs) are commonly used as a simple generic model for certain dynamics of complex systems. Traditionally, RBNs are interconnected randomly and without considering any spatial extension and arrangement of the links and nodes. However, most real-world networks are spatially extended and arranged with regular, power-law, small-world, or other nonrandom connections. Here we explore the RBN network topology between extreme local connections, random small-world, and pure random networks, and study the damage spreading with small perturbations. We find that …

Visualization Of Off-Screen Data On Tablets Using Context-Providing Bar Graphs And Scatter Plots, Peter S. Games, Alark Joshi

Computer Science Faculty Publications and Presentations

Visualizing data on tablets is challenging due to the relatively small screen size and limited user interaction capabilities. Standard data visualization apps provide support for pinch-and-zoom and scrolling operations, but do not provide context for data that is off-screen. When exploring data on tablets, the user must be able to focus on a region of interest and quickly find interesting patterns in the data. We present visualization techniques that facilitate seamless interaction with the region of interest on a tablet using context-providing bar graphs and scatter plots. Through aggregation, fisheye-style, and overview+detail representations, we provide context to the users as …

Mqvc: Measuring Quranic Verses Similarity And Sura Classification Using N-Gram, Mohammed Akour, Izzat Alsmadi, Iyad Alazzam

Computer Science Faculty Publications and Presentations

Extensive research efforts in the area of Information Retrieval were concentrated on developing retrieval systems related to Arabic language for the different natural language and information retrieval methodologies. However, little effort was conducted in those areas for knowledge extraction from the Holly Muslim book, the Quran. In this paper, we present an approach (MQVC) for retrieving the most similar verses in comparison with a user input verse as a query. To demonstrate the accuracy of our approach, we performed a set of experiments and compared the results with an evaluation from a Quran Specialist who manually identified all relevant chapters …

Adapting In-Game Agent Behavior By Observation Of Players Using Learning Behavior Trees, Emmett Tomai, Roberto Flores

Computer Science Faculty Publications and Presentations

In this paper we describe Learning Behavior Trees, an extension of the popular game AI scripting technique. Behavior Trees provide an effective way for expert designers to describe complex, in-game agent behaviors. Scripted AI captures human intuition about the structure of behavioral decisions, but suffers from brittleness and lack of the natural variation seen in human players. Learning Behavior Trees are designed by a human designer, but then are trained by observation of players performing the same role, to introduce human-like variation to the decision structure. We show that, using this model, a single hand-designed Behavior Tree can cover a …

P2p Email Encryption By An Identity-Based One-Way Group Key Agreement Protocol, Jyh-Haw Yeh, Fiona Zeng, Thomas Long

Computer Science Faculty Publications and Presentations

As a result of high-tech companies such as Google, Yahoo, and Microsoft offering free email services, email has become a primary channel of communication. However, email service providers have traditionally offered little in the way of message privacy protection. This has made emails, of which billions are sent around the world on any day, an attractive data source for personal identity information thieves. Google was one of the first companies to provide substantial email privacy protection when they began using the HTTPS always-on option to encrypt messages sent through their email service, Gmail. Unfortunately, Gmail's encryption option does not offer …

A Comparative Study Of Reservoir Computing For Temporal Signal Processing, Alireza Goudarzi, Peter Banda, Matthew R. Lakin, Christof Teuscher, Darko Stefanovic

Computer Science Faculty Publications and Presentations

Reservoir computing (RC) is a novel approach to time series prediction using recurrent neural networks. In RC, an input signal perturbs the intrinsic dynamics of a medium called a reservoir. A readout layer is then trained to reconstruct a target output from the reservoir's state. The multitude of RC architectures and evaluation metrics poses a challenge to both practitioners and theorists who study the task-solving performance and computational power of RC. In addition, in contrast to traditional computation models, the reservoir is a dynamical system in which computation and memory are inseparable, and therefore hard to analyze. Here, we compare …

Guiding Data-Driven Transportation Decisions, Kristin A. Tufte, Basem Elazzabi, Nathan Hall, Morgan Harvey, Kath Knobe, David Maier, Veronika Margaret Megler

Computer Science Faculty Publications and Presentations

Urban transportation professionals are under increasing pressure to perform data-driven decision making and to provide data-driven performance metrics. This pressure comes from sources including the federal government and is driven, in part, by the increased volume and variety of transportation data available. This sudden increase of data is partially a result of improved technology for sensors and mobile devices as well as reduced device and storage costs. However, using this proliferation of data for decisions and performance metrics is proving to be difficult. In this paper, we describe a proposed structure for a system to support data-driven decision making. A …