Computer Sciences Commons^™

Mixed Logical And Probabilistic Reasoning In The Game Of Clue, Todd W. Neller, Ziqian Luo

Computer Science Faculty Publications

Neller and Ziqian Luo ’18 presented a means of mixed logical and probabilistic reasoning with knowledge in the popular deductive mystery game Clue. Using at-least constraints, we more efficiently represented and reasoned about cardinality constraints on Clue card deal knowledge, and then employed a WalkSAT-based solution sampling algorithm with a tabu search metaheuristic in order to estimate the probabilities of unknown card places.

A Survey Of Matrix Completion Methods For Recommendation Systems, Andy Ramlatchan, Mengyun Yang, Quan Liu, Min Li, Jianxin Wang, Yaohang Li

Computer Science Faculty Publications

In recent years, the recommendation systems have become increasingly popular and have been used in a broad variety of applications. Here, we investigate the matrix completion techniques for the recommendation systems that are based on collaborative filtering. The collaborative filtering problem can be viewed as predicting the favorability of a user with respect to new items of commodities. When a rating matrix is constructed with users as rows, items as columns, and entries as ratings, the collaborative filtering problem can then be modeled as a matrix completion problem by filling out the unknown elements in the rating matrix. This article …

Approximate Set Union Via Approximate Randomization, Bin Fu, Pengfei Gu, Yuming Zhao

Computer Science Faculty Publications

No abstract provided.

A Multiple Radar Approach For Automatic Target Recognition Of Aircraft Using Inverse Synthetic Aperture Radar, Carlos Pena-Caballero, Elifaleth Cantu, Jesus Rodriguez, Adolfo Gonzales, Osvaldo Castellanos, Angel Cantu, Megan K. Strait, Jae Son, Dong-Chul Kim

Computer Science Faculty Publications

Following the recent advancements in radar technologies, research on automatic target recognition using Inverse Synthetic Aperture Radar (ISAR) has correspondingly seen more attention and activity. ISAR automatic target recognition researchers aim to fully automate recognition and classification of military vehicles, but because radar images often do not present a clear image of what they detect, it is considered a challenging process to do this. Here we present a novel approach to fully automate a system with Convolutional Neural Networks (CNNs) that results in better target recognition and requires less training time. Specifically, we developed a simulator to generate images with …

Design And Evaluation Of A Privacy Architecture For Crowdsensing Applications, Alfredo J. Perez, Sherali Zeadally

Computer Science Faculty Publications

By using consumer devices such as cellphones, wearables and Internet of Things devices owned by citizens, crowdsensing systems are providing solutions to the community in areas such as transportation, security, entertainment and the environment through the collection of various types of sensor data. Privacy is a major issue in these systems because the data collected can potentially reveal aspects considered private by the contributors of data. We propose the Privacy-Enabled ARchitecture (PEAR), a layered architecture aimed at protecting privacy in privacy-aware crowdsensing systems. We identify and describe the layers of the architecture. We propose and evaluate the design of MetroTrack, …

Optimal Staged Self-Assembly Of General Shapes, Cameron Chalk, Eric M. Martinez, Robert Schweller, Luis Vega, Andrew Winslow, Tim Wylie

Computer Science Faculty Publications

We analyze the number of tile types t, bins b, and stages necessary to assemble n \times n squares and scaled shapes in the staged tile assembly model. For n \times n squares, we prove \mathcal{O}(\frac{\log{n} - tb - t\log t}{b^2} + \frac{\log \log b}{\log t}) stages suffice and \Omega(\frac{\log{n} - tb - t\log t}{b^2}) are necessary for almost all n. For shapes S with Kolmogorov complexity K(S), we prove \mathcal{O}(\frac{K(S) - tb - t\log t}{b^2} + \frac{\log \log b}{\log t}) stages suffice and \Omega(\frac{K(S) - tb - t\log t}{b^2}) are necessary to assemble a scaled version of S, for …

Security And Privacy In Ubiquitous Sensor Networks, Alfredo J. Perez, Sherali Zeadally, Nafaa Jabeur

Computer Science Faculty Publications

The availability of powerful and sensor-enabled mobile and Internet-connected devices have enabled the advent of the ubiquitous sensor network (USN) paradigm. USN provides various types of solutions to the general public in multiple sectors, including environmental monitoring, entertainment, transportation, security, and healthcare. Here, we explore and compare the features of wireless sensor networks and USN. Based on our extensive study, we classify the security- and privacy-related challenges of USNs. We identify and discuss solutions available to address these challenges. Finally, we briefly discuss open challenges for designing more secure and privacy-preserving approaches in next-generation USNs.

Tracing Actin Filament Bundles In Three-Dimensional Electron Tomography Density Maps Of Hair Cell Stereocilia, Salim Sazzed, Junha Song, Julio Kovacs, Willi Wriggers, Manfred Auer, Jing He

Computer Science Faculty Publications

Cryo-electron tomography (cryo-ET) is a powerful method of visualizing the three-dimensional organization of supramolecular complexes, such as the cytoskeleton, in their native cell and tissue contexts. Due to its minimal electron dose and reconstruction artifacts arising from the missing wedge during data collection, cryo-ET typically results in noisy density maps that display anisotropic XY versus Z resolution. Molecular crowding further exacerbates the challenge of automatically detecting supramolecular complexes, such as the actin bundle in hair cell stereocilia. Stereocilia are pivotal to the mechanoelectrical transduction process in inner ear sensory epithelial hair cells. Given the complexity and dense arrangement of actin …

Prediction Of Lncrna-Disease Associations Based On Inductive Matrix Completion, Chengqian Lu, Mengyun Yang, Feng Luo, Fang-Xiang Wu, Min Li, Yi Pan, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

Motivation: Accumulating evidences indicate that long non-coding RNAs (lncRNAs) play pivotal roles in various biological processes. Mutations and dysregulations of lncRNAs are implicated in miscellaneous human diseases. Predicting lncRNA–disease associations is beneficial to disease diagnosis as well as treatment. Although many computational methods have been developed, precisely identifying lncRNA–disease associations, especially for novel lncRNAs, remains challenging.

Results: In this study, we propose a method (named SIMCLDA) for predicting potential lncRNA– disease associations based on inductive matrix completion. We compute Gaussian interaction profile kernel of lncRNAs from known lncRNA–disease interactions and functional similarity of diseases based on disease–gene and gene–gene onotology …

A Model For Donation Verification, Bin Fu, Fengjuan Zhu, John P. Abraham

Computer Science Faculty Publications

In this paper, we introduce a model for donation verification. A randomized algorithm is developed to check if the money claimed being received by the collector is (1 - ϵ)-approximation to the total amount money contributed by the donors. We also derive some negative results that show it is impossible to verify the donations under some circumstances.

Dynamic Non-Rigid Objects Reconstruction With A Single Rgb-D Sensor, Sen Wang, Xinxin Zuo, Chao Du, Runxiao Wang, Jiangbin Zheng, Ruigang Yang

Computer Science Faculty Publications

This paper deals with the 3D reconstruction problem for dynamic non-rigid objects with a single RGB-D sensor. It is a challenging task as we consider the almost inevitable accumulation error issue in some previous sequential fusion methods and also the possible failure of surface tracking in a long sequence. Therefore, we propose a global non-rigid registration framework and tackle the drifting problem via an explicit loop closure. Our novel scheme starts with a fusion step to get multiple partial scans from the input sequence, followed by a pairwise non-rigid registration and loop detection step to obtain correspondences between neighboring partial …

Plentiful Possibilities For Pen, Pencil, And Paper Play, Todd W. Neller

Computer Science Faculty Publications

Neller presented games such as Dots and Boxes, Sprouts, Jotto, Chomp, and Pentominoes in order to illustrate the diversity of existing pencil and paper games. Additionally, he presented his own pencil and paper game design, Paper Penguins, and discussed the game design process.

Scheduling Based On Interruption Analysis And Pso For Strictly Periodic And Preemptive Partitions In Integrated Modular Avionics, Hui Lu, Qianlin Zhou, Zongming Fei, Rongrong Zhou

Computer Science Faculty Publications

Integrated modular avionics introduces the concept of partition and has been widely used in avionics industry. Partitions share the computing resources together. Partition scheduling plays a key role in guaranteeing correct execution of partitions. In this paper, a strictly periodic and preemptive partition scheduling strategy is investigated. First, we propose a partition scheduling model that allows a partition to be interrupted by other partitions, but minimizes the number of interruptions. The model not only retains the execution reliability of the simple partition sets that can be scheduled without interruptions, but also enhances the schedulability of the complex partition sets that …

Kratylos: A Tool For Sharing Interlinearized And Lexical Data In Diverse Formats, Daniel Kaufman, Raphael Finkel

Computer Science Faculty Publications

In this paper we present Kratylos, at www.kratylos.org/, a web application that creates searchable multimedia corpora from data collections in diverse formats, including collections of interlinearized glossed text (IGT) and dictionaries. There exists a crucial lacuna in the electronic ecology that supports language documentation and linguistic research. Vast amounts of IGT are produced in stand-alone programs without an easy way to share them publicly as dynamic databases. Solving this problem will not only unlock an enormous amount of linguistic information that can be shared easily across the web, it will also improve accountability by allowing us to verify analyses …

Https://Onlinelibrary.Wiley.Com/Doi/10.1002/Spy2.15#:~:Text=A%20review%20and%20an%20empirical%20analysis%20of%20privacy%20policy%20and%20notices%20for%20consumer%20internet%20of%20things, Alfredo J. Perez, Sherali Zeadally, Jonathan Cochran

Computer Science Faculty Publications

The privacy policies and practices of six consumer Internet of things (IoT) devices were reviewed and compared. In addition, an empirical verification of the compliance of privacy policies for data collection practices on two voice-activated intelligent assistant devices, namely the Amazon Echo Dot and Google Home devices was performed. The review shows that IoT privacy policies may not be usable from the human-computer interaction perspective because IoT policies are included as part of the manufacturers' general privacy policy (which may include policies unrelated to the device), or the IoT policy requires to read (in addition to the IoT policies) the …

Faith And Finance, Todd W. Neller

Computer Science Faculty Publications

The seminar covered scriptures concerning money, basic concepts of financial literacy, and a Christian perspective on investing. More information is available at http://cs.gettysburg.edu/~tneller/resources/investing/ .

Auditing Snomed Ct Hierarchical Relations Based On Lexical Features Of Concepts In Non-Lattice Subgraphs, Licong Cui, Olivier Bodenreider, Jay Shi, Guo-Qiang Zhang

Computer Science Faculty Publications

Objective—We introduce a structural-lexical approach for auditing SNOMED CT using a combination of non-lattice subgraphs of the underlying hierarchical relations and enriched lexical attributes of fully specified concept names. Our goal is to develop a scalable and effective approach that automatically identifies missing hierarchical IS-A relations.

Methods—Our approach involves 3 stages. In stage 1, all non-lattice subgraphs of SNOMED CT’s IS-A hierarchical relations are extracted. In stage 2, lexical attributes of fully-specified concept names in such non-lattice subgraphs are extracted. For each concept in a non-lattice subgraph, we enrich its set of attributes with attributes from its ancestor …

Edda: An Efficient Distributed Data Replication Algorithm In Vanets, Junyu Zhu, Chuanhe Huang, Xiying Fan, Sipei Guo, Bin Fu

Computer Science Faculty Publications

Efficient data dissemination in vehicular ad hoc networks (VANETs) is a challenging issue due to the dynamic nature of the network. To improve the performance of data dissemination, we study distributed data replication algorithms in VANETs for exchanging information and computing in an arbitrarily-connected network of vehicle nodes. To achieve low dissemination delay and improve the network performance, we control the number of message copies that can be disseminated in the network and then propose an efficient distributed data replication algorithm (EDDA). The key idea is to let the data carrier distribute the data dissemination tasks to multiple nodes to …

Natural Language, Mixed-Initiative Personal Assistant Agents, Joshua W. Buck, Saverio Perugini, Tam W. Nguyen

Computer Science Faculty Publications

The increasing popularity and use of personal voice assistant technologies, such as Siri and Google Now, is driving and expanding progress toward the long-term and lofty goal of using artificial intelligence to build human-computer dialog systems capable of understanding natural language. While dialog-based systems such as Siri support utterances communicated through natural language, they are limited in the flexibility they afford to the user in interacting with the system and, thus, support primarily action-requesting and information-seeking tasks. Mixed-initiative interaction, on the other hand, is a flexible interaction technique where the user and the system act as equal participants in an …

Web Development With Node.Js, Seikyung Jung

Computer Science Faculty Publications

This tutorial demonstrates how to teach a Web development course by building web applications with Node.js and Express then deploying to Heroku, a cloud hosting service. This tutorial assumes some familiarity with HTML and JavaScript, but no prior experience with Node.js is necessary. The tutorial covers all necessary setup and step-by-step instructions to build a sample web application with these technologies. The tutorial concludes by describing how to incorporate Node.js, PostgreSQL, Git and Heroku in a web development course, and my experiences with using it for the past two years.

Model Ai Assignments 2018, Todd W. Neller, Zack Butler, Nate Derbinsky, Heidi Furey, Fred Martin, Michael Guerzhoy, Ariel Anders, Joshua Eckroth

Computer Science Faculty Publications

The Model AI Assignments session seeks to gather and disseminate the best assignment designs of the Artificial Intelligence (AI) Education community. Recognizing that assignments form the core of student learning experience, we here present abstracts of seven AI assignments from the 2018 session that are easily adoptable, playfully engaging, and flexible for a variety of instructor needs. Assignment specifications and supporting resources may be found at http://modelai.gettysburg.edu.

Ai Education Matters: Teaching Hidden Markov Models, Todd W. Neller

Computer Science Faculty Publications

In this column, we share resources for learning about and teaching Hidden Markov Models (HMMs). HMMs find many important applications in temporal pattern recognition tasks such as speech/handwriting/gesture recognition and robot localization. In such domains, we may have a finite state machine model with known state transition probabilities, state output probabilities, and state outputs, but lack knowledge of the states generating such outputs. HMMs are useful in framing problems where external sequential evidence is used to derive underlying state information (e.g. intended words and gestures). [excerpt]

Ai Education Matters: Lessons From A Kaggle Click-Through Rate Prediction Competition, Todd W. Neller

Computer Science Faculty Publications

In this column, we will look at a particular Kaggle.com click-through rate (CTR) prediction competition, observe what the winning entries teach about this part of the machine learning landscape, and then discuss the valuable opportunities and resources this commends to AI educators and their students. [excerpt]

Random Models Of Very Hard 2qbf And Disjunctive Programs: An Overview, Giovanni Amendola, Francesco Ricca, Miroslaw Truszczynski

Computer Science Faculty Publications

We present an overview of models of random quantified boolean formulas and their natural random disjunctive ASP program counter-parts that we have recently proposed. The models have a simple structure but also theoretical and empirical properties that make them useful for further advancement of the SAT, QBF and ASP solvers.

Learning To Generate Natural Language Rationales For Game Playing Agents, Upol Ehsan, Pradyumna Tambwekar, Larry Chan, Brent Harrison, Mark O. Riedl

Computer Science Faculty Publications

Many computer games feature non-player charactert (NPC) teammates and companions; however, playing with or against NPCs can be frustrating when they perform unexpectedly. These frustrations can be avoided if the NPC has the ability to explain its actions and motivations. When NPC behavior is controlled by a black box AI system it can be hard to generate the necessary explanations. In this paper, we present a system that generates human-like, natural language explanations—called rationales—of an agent's actions in a game environment regardless of how the decisions are made by a black box AI. We outline a robust data collection …

Privacy In Iot Cloud, Aftab Ahmad, Ravi Mukkamala, Karthik Navuluri

Computer Science Faculty Publications

We present a framework for privacy preservation in an information cloud of IoT devices. We contend that privacy provisioning should be located in the user device and must protect the user, the information, and the device from breaches in privacy. We elaborate on how the layered privacy model can ensure such privacy provisioning, and justify the device being the provisioning point instead of the cloud alone. We present the point of view that, due to resource limitations of the IoT devices in general, the privacy preserving measures need to be hard-coded in the device technology. We fall short of suggesting …

Off Topic Memento Toolkit, Shawn M. Jones, Michele C. Weigle, Michael L. Nelson

Computer Science Faculty Publications

Web archive collections are created with a particular purpose in mind. A curator selects seeds, or original resources, which are then captured by an archiving system and stored as archived web pages, or mementos. The systems that build web archive collections are often configured to revisit the same original resource multiple times. This is incredibly useful for understanding an unfolding news story or the evolution of an organization. Unfortunately, over time, some of these original resources can go off-topic and no longer suit the purpose for which the collection was originally created. They can go off-topic due to web site …

Unobtrusive And Extensible Archival Replay Banners Using Custom Elements, Sawood Alam, Mat Kelly, Michele C. Weigle, Michael L. Nelson

Computer Science Faculty Publications

We compare and contrast three different ways to implement an archival replay banner. We propose an implementation that utilizes Custom Elements and adds some unique behaviors, not common in existing archival replay systems, to enhance the user experience. Our approach has a minimal user interface footprint and resource overhead while still providing rich interactivity and extended on-demand provenance information about the archived resources.

Quantification Of Twist From The Central Lines Of Β-Strands, Tunazzina Islam, Michael Poteat, Jing He

Computer Science Faculty Publications

Since the discovery of right-handed twist of a β-strand, many studies have been conducted to understand the twist. Given the atomic structure of a protein, twist angles have been defined using atomic positions of the backbone. However, limited study is available to characterize twist when the atomic positions are not available, but the central lines of β-strands are. Recent studies in cryoelectron microscopy show that it is possible to predict the central lines of β-strands from a medium-resolution density map. Accurate measurement of twist angles is important in identification of β-strands from such density maps. We propose an effective method …

Efficient Randomized Algorithms For The Fixed Precision Low Rank Matrix Approximation, Wenjian Yu, Yu Gu, Yaohang Li

Computer Science Faculty Publications

Randomized algorithms for low-rank matrix approximation are investigated, with the emphasis on the fixed-precision problem and computational efficiency for handling large matrices. The algorithms are based on the so-called QB factorization, where Q is an orthonormal matrix. First, a mechanism for calculating the approximation error in the Frobenius norm is proposed, which enables efficient adaptive rank determination for a large and/or sparse matrix. It can be combined with any QB-form factorization algorithm in which B's rows are incrementally generated. Based on the blocked randQB algorithm by Martinsson and Voronin, this results in an algorithm called randQB_EI. Then, we further revise …