Physical Sciences and Mathematics Commons^™

The Birds Of A Feather Research Challenge, Todd W. Neller

Computer Science Faculty Publications

Neller presented a set of research challenges for undergraduates that allow an excellent formative experience of research, writing, peer review, and potential presentation and publication through a top-tier conference. The focus problem is the analysis of a newly-designed solitaire card game, Birds of a Feather, so potentials for discovery abound. Open access talk slides, research code, solvability data sets, research tutorial videos, and more are also available at http://cs.gettysburg.edu/~tneller/puzzles/boaf .

Ordinal Convolutional Neural Networks For Predicting Rdoc Positive Valence Psychiatric Symptom Severity Scores, Anthony Rios, Ramakanth Kavuluru

Computer Science Faculty Publications

Background—The CEGS N-GRID 2016 Shared Task in Clinical Natural Language Processing (NLP) provided a set of 1000 neuropsychiatric notes to participants as part of a competition to predict psychiatric symptom severity scores. This paper summarizes our methods, results, and experiences based on our participation in the second track of the shared task.

Objective—Classical methods of text classification usually fall into one of three problem types: binary, multi-class, and multi-label classification. In this effort, we study ordinal regression problems with text data where misclassifications are penalized differently based on how far apart the ground truth and model predictions are …

Predicting Mental Conditions Based On "History Of Present Illness" In Psychiatric Notes With Deep Neural Networks, Tung Tran, Ramakanth Kavuluru

Computer Science Faculty Publications

Background—Applications of natural language processing to mental health notes are not common given the sensitive nature of the associated narratives. The CEGS N-GRID 2016 Shared Task in Clinical Natural Language Processing (NLP) changed this scenario by providing the first set of neuropsychiatric notes to participants. This study summarizes our efforts and results in proposing a novel data use case for this dataset as part of the third track in this shared task.

Objective—We explore the feasibility and effectiveness of predicting a set of common mental conditions a patient has based on the short textual description of patient’s history …

Amazons, Penguins, And Amazon Penguins, Todd W. Neller

Computer Science Faculty Publications

This talk discussed a family of games based on Amazons (1988), a distant relative of Go (area control) and Chess (queen-like movement), innovated with the introduction of move obstacles. Hey! That’s My Fish! (2003) restricted the addition of obstacles and added varying points for position visits. Introducing original related game designs (e.g. Amazon Penguins (2009) and Paper Pen-guins (2009)), we demonstrated how game mechanics are like genes that mutate, crossover, and invite evolution of new games.

Single Versus Concurrent Systems: Nominal Classification In Mian, Greville G. Corbett, Sebastian Fedden, Raphael Finkel

Computer Science Faculty Publications

The Papuan language Mian allows us to refine the typology of nominal classification. Mian has two candidate classification systems, differing completely in their formal realization but overlapping considerably in their semantics. To determine whether to analyse Mian as a single system or concurrent systems we adopt a canonical approach. Our criteria – orthogonality of the systems (we give a precise measure), semantic compositionality, morphosyntactic alignment, distribution across parts of speech, exponence, and interaction with other features – point mainly to an analysis as concurrent systems. We thus improve our analysis of Mian and make progress with the typology of nominal …

Systematic Adaptation Of Dynamically Generated Source Code Via Domain-Specific Examples, Myoungkyu Song, Eli Tilevich

Computer Science Faculty Publications

In modern web-based applications, an increasing amount of source code is generated dynamically at runtime. Web applications commonly execute dynamically generated code (DGC) emitted by third-party, black-box generators, run at remote sites. Web developers often need to adapt DGC before it can be executed: embedded HTML can be vulnerable to cross-site scripting attacks; an API may be incompatible with some browsers; and the program's state created by DGC may not be persisting. Lacking any systematic approaches for adapting DGC, web developers resort to ad-hoc techniques that are unsafe and error-prone. This study presents an approach for adapting DGC systematically that …

A Reliable And Efficient Wireless Sensor Network System For Water Quality Monitoring, Dung Nguyen, Phu Huu Phung

Computer Science Faculty Publications

Wireless sensor networks (WSNs) are strongly useful to monitor physical and environmental conditions to provide realtime information for improving environment quality. However, deploying a WSN in a physical environment faces several critical challenges such as high energy consumption, and data loss.In this work, we have proposed a reliable and efficient environmental monitoring system in ponds using wireless sensor network and cellular communication technologies. We have designed a hardware and software ecosystem that can limit the data loss yet save the energy consumption of nodes. A lightweight protocol acknowledges data transmission among the nodes. Data are transmitted to the cloud using …

Forest Understory Trees Can Be Segmented Accurately Within Sufficiently Dense Airborne Laser Scanning Point Clouds, Hamid Hamraz, Marco A. Contreras, Jun Zhang

Computer Science Faculty Publications

Airborne laser scanning (LiDAR) point clouds over large forested areas can be processed to segment individual trees and subsequently extract tree-level information. Existing segmentation procedures typically detect more than 90% of overstory trees, yet they barely detect 60% of understory trees because of the occlusion effect of higher canopy layers. Although understory trees provide limited financial value, they are an essential component of ecosystem functioning by offering habitat for numerous wildlife species and influencing stand development. Here we model the occlusion effect in terms of point density. We estimate the fractions of points representing different canopy layers (one overstory and …

Mining Non-Lattice Subgraphs For Detecting Missing Hierarchical Relations And Concepts In Snomed Ct, Licong Cui, Wei Zhu, Shiqiang Tao, James T. Case, Olivier Bodenreider, Guo-Qiang Zhang

Computer Science Faculty Publications

Objective: Quality assurance of large ontological systems such as SNOMED CT is an indispensable part of the terminology management lifecycle. We introduce a hybrid structural-lexical method for scalable and systematic discovery of missing hierarchical relations and concepts in SNOMED CT.

Material and Methods: All non-lattice subgraphs (the structural part) in SNOMED CT are exhaustively extracted using a scalable MapReduce algorithm. Four lexical patterns (the lexical part) are identified among the extracted non-lattice subgraphs. Non-lattice subgraphs exhibiting such lexical patterns are often indicative of missing hierarchical relations or concepts. Each lexical pattern is associated with a potential specific type of error. …

Privacy Issues And Solutions For Consumer Wearables, Alfredo J. Perez, Sherali Zeadally

Computer Science Faculty Publications

Consumer wearables have emerged as disrupting devices that benefit citizens in areas such as mobile health, fitness, security, and entertainment. The mass adoption of these devices not only generates high revenues but also exposes important privacy issues. The authors identify some of the major privacy issues associated with consumer wearables and explore possible solutions to address privacy concerns.

Bystanders' Privacy, Alfredo J. Perez, Sherali Zeadally, Scott Griffith

Computer Science Faculty Publications

The growing adoption of Internet-connected devices has given rise to significant privacy issues not only for users but also for bystanders. The authors explore privacy concerns related to bystanders' privacy and present a taxonomy of the solutions found in the literature to handle this issue. They also explore open issues that must be addressed in the future.

P4sinc – An Execution Policy Framework For Iot Services In The Edge, Phu Huu Phung, Hong-Linh Truong, Divya Teja Yasoju

Computer Science Faculty Publications

Internet of Things (IoT) services are increasingly deployed at the edge to access and control Things. The execution of such services needs to be monitored to provide information for security, service contract, and system operation management. Although different techniques have been proposed for deploying and executing IoT services in IoT gateways and edge servers, there is a lack of generic policy frameworks for instrumentation and assurance of various types of execution policies for IoT services. In this paper, we present P4SINC as an execution policy framework that covers various functionalities for IoT services deployed in software-defined machines in IoT infrastructures. …

Hybridguard: A Principal-Based Permission And Fine-Grained Policy Enforcement Framework For Web-Based Mobile Applications, Phu Huu Phung, Abhinav Mohanty, Rahul Rachapalli, Meera Sridhar

Computer Science Faculty Publications

Web-based or hybrid mobile applications (apps) are widely used and supported by various modern hybrid app development frameworks. In this architecture, any JavaScript code, local or remote, can access available APIs, including JavaScript bridges provided by the hybrid framework, to access device resources. This JavaScript inclusion capability is dangerous, since there is no mechanism to determine the origin of the code to control access, and any JavaScript code running in the mobile app can access the device resources through the exposed APIs. Previous solutions are either limited to a particular platform (e.g., Android) or a specific hybrid framework (e.g., Cordova) …

Toward An Iot-Based Expert System For Heart Disease Diagnosis, Do Thanh Thai, Quang Tran Minh, Phu Huu Phung

Computer Science Faculty Publications

IoT technology has been recently adopted in the healthcare system to collect Electrocardiogram (ECG) signals for heart disease diagnosis and prediction. However, noises in collected ECG signals make the diagnosis and prediction system unreliable and imprecise. In this work, we have proposed a new lightweight approach to removing noises in collected ECG signals to perform precise diagnosis and prediction. First, we have used a revised Sequential Recursive (SR) algorithm to transform the signals into digital format. Then, the digital data is proceeded using a revised Discrete Wavelet Transform (DWT) algorithm to detect peaks in the data to remove noises. Finally, …

Mixed-Initiative Personal Assistants, Joshua W. Buck, Saverio Perugini

Computer Science Faculty Publications

Specification and implementation of flexible human-computer dialogs is challenging because of the complexity involved in rendering the dialog responsive to a vast number of varied paths through which users might desire to complete the dialog. To address this problem, we developed a toolkit for modeling and implementing task-based, mixed-initiative dialogs based on metaphors from lambda calculus. Our toolkit can automatically operationalize a dialog that involves multiple prompts and/or sub-dialogs, given a high-level dialog specification of it. Our current research entails incorporating the use of natural language to make the flexibility in communicating user utterances commensurate with that in dialog completion …

Playful Ai Education, Todd W. Neller

Computer Science Faculty Publications

In this talk, Neller shared how games can serve as a fun means of teaching not only game-tree search in Artificial Intelligence (AI), but also such diverse topics as constraint satisfaction, logical reasoning, planning, uncertain reasoning, machine learning, and robotics. He observed that teachers teach best when they enjoy what they share and encouraged AI educators present to teach to their unique strengths and enthusiasms.

Static Human Detection And Scenario Recognition Via Wearable Thermal Sensing System, Qingquan Sun, Ju Shen, Haiyan Qiao, Xinlin Huang, Chen Chen, Fei Hu

Computer Science Faculty Publications

Conventional wearable sensors are mainly used to detect the physiological and activity information of individuals who wear them, but fail to perceive the information of the surrounding environment. This paper presents a wearable thermal sensing system to detect and perceive the information of surrounding human subjects. The proposed system is developed based on a pyroelectric infrared sensor. Such a sensor system aims to provide surrounding information to blind people and people with weak visual capability to help them adapt to the environment and avoid collision. In order to achieve this goal, a low-cost, low-data-throughput binary sampling and analyzing scheme is …

Mdp: Minimum Delay Hot-Spot Parking, Peng Liu, Biao Xu, Guojun Dai, Zhen Jiang, Jie Wu

Computer Science Faculty Publications

Hot-spot parking is becoming the Achilles' heel of the tourism industry. The more tourists that are attracted to the scenic site, the more often they will encounter a hassle of congestion to find a parking place; while those existing facilities for daily traffic are not supposed to support the excessive volume outburst. In this paper, we present a new parking guidance information system (PGI). By taking advantage of the technical advances of today in wireless communication of vehicular ad-hoc network, each vehicle will request and obtain a relatively fair opportunity to park. The competition and the corresponding allocation on the …

Ai Education: Open-Access Educational Resources On Ai, Todd W. Neller

Computer Science Faculty Publications

Open-access AI educational resources are vital to the quality of the AI education we offer. Avoiding the reinvention of wheels is especially important to us because of the special challenges of AI Education. AI could be said to be “the really interesting miscellaneous pile of Computer Science”. While “artificial” is well-understood to encompass engineered artifacts, “intelligence” could be said to encompass any sufficiently difficult problem as would require an intelligent approach and yet does not fall neatly into established Computer Science subdisciplines. Thus AI consists of so many diverse topics that we would be hard-pressed to individually create quality learning …

Ai Education: Deep Neural Network Learning Resources, Todd W. Neller

Computer Science Faculty Publications

In this column, we focus on resources for learning and teaching deep neural network learning. Many exciting advances have been made in this area of late, and so many resources have become available online that the flood of relevant concepts and techniques can be overwhelming. Here, we hope to provide a sampling of high-quality resources to guide the newcomer into this booming field. [excerpt]

Identifying Inexpensive Off-The-Shelf Laser Pointers For Multi-User Interaction On Large Scale Displays, Christopher S. Stuetzle, Barbara Cutler, Tyler Sammann

Computer Science Faculty Publications

We present a method for identifying inexpensive, off-the-shelf laser pointers in a multiuser interaction environment on large-scale displays. We identify a laser pointer's personality, a measure of its output in a particular context. Our method requires a set of inexpensive and unmodified green lasers, a large screen, a projector, and a camera with an infrared (IR) filter. The camera detects the IR spillover from the green laser beam, while ignoring color information projected onto the screen. During a calibration phase, a radial histogram of each laser's IR spillover are used to represent the laser's personality. Our system is able to …

Ai Education: Machine Learning Resources, Todd W. Neller

Computer Science Faculty Publications

In this column, we focus on resources for learning and teaching three broad categories of machine learning (ML): supervised, unsupervised, and reinforcement learning. In ournext column, we will focus specifically on deep neural network learning resources, so if you have any resource recommendations, please email them to the address above. [excerpt]

Evaluating Network Test Scenarios For Network Simulators Systems, A. Zarrad, Izzat M. Alsmadi

Computer Science Faculty Publications

Networks continue to grow as industries use both wired and wireless networks. Creating experiments to test those networks can be very expensive if conducted on production networks; therefore, the evaluation of networks and their performance is usually conducted using emulation. This growing reliance on simulation raises the risk of correctness and validation. Today, many network simulators have widely varying focuses and are employed in different fields of research. The trustworthiness of results produced from simulation models must be investigated. The goal of this work is first to compare and assess the performance of three prominent network simulators—NS-2, NS-3, and OMNet++—by …

Online Integrity And Authentication Checking For Quran Electronic Versions, Izzat M. Alsmadi, M. Zarour

Computer Science Faculty Publications

The ability to control data and information through the Internet can be challenging. Preliminary analysis showed that some tampering and forgery may occur to some words of the Quran in the electronic versions that span the Internet. Such small modifications may not be noticed by public audience. The holy book of Quran includes a unique feature in that its worldwide copies are all identical. The 114 chapters (Suras) and all their verses and words are preserved in the exact form. As such, we designed and evaluated a model and a tool to evaluate the integrity of the wording in the …

Comparing An Atomic Model Or Structure To A Corresponding Cryo-Electron Microscopy Image At The Central Axis Of A Helix, Stephanie Zeil, Julio Kovacs, Willy Wriggers, Jing He

Computer Science Faculty Publications

Three-dimensional density maps of biological specimens from cryo-electron microscopy (cryo-EM) can be interpreted in the form of atomic models that are modeled into the density, or they can be compared to known atomic structures. When the central axis of a helix is detectable in a cryo-EM density map, it is possible to quantify the agreement between this central axis and a central axis calculated from the atomic model or structure. We propose a novel arc-length association method to compare the two axes reliably. This method was applied to 79 helices in simulated density maps and six case studies using cryo-EM …

Efficient Core Utilization In A Hybrid Parallel Delaunay Meshing Algorithm On Distributed-Memory Cluster, Daming Feng, Andrey N. Chernikov, Nikos P. Chrisochoides

Computer Science Faculty Publications

Most of the current supercomputer architectures consist of clusters of nodes that are used by many clients (users). A user wants his/her job submitted in the job queue to be scheduled promptly. However, the resource sharing and job scheduling policies that are used in the scheduling system to manage the jobs are usually beyond the control of users. Therefore, in order to reduce the waiting time of their jobs, it is becoming more and more crucial for the users to consider how to implement the algorithms that are suitable to the system scheduling policies and are able to effectively and …

Homeomorphic Tetrahedral Tessellation For Biomedical Images, Jing Xu, Andrey N. Chernikov

Computer Science Faculty Publications

We present a novel algorithm for generating three-dimensional unstructured tetrahedral meshes for biomedical images. The method uses an octree as the background grid from which to build the final graded conforming meshes. The algorithm is fast and robust. It produces meshes with high quality since it provides dihedral angle lower bound for the output tetrahedra. Moreover, the mesh boundary is a geometrically and topologically accurate approximation of the object surface in the sense that it allows for guaranteed bounds on the two-sided Hausdorff distance and the homeomorphism between the boundaries of the mesh and the boundaries of the materials. The …

Ansi/Niso Z39.99-2017 Resourcesync Framework Specification, Kevin Ruthen, Jill Emery, Mark Doyle, Mark Needleman, Sue Baughman, Evan Owens, Oliver Pesch, Mike Dicus, Nassib Nassar, Tim Auger, Amy Kirchhoff, Sally Mccallum, Diana Magnoni, Paul Swanson, Gregory Grazevich, Nara Newcomer, Gregory Grazevich, Juha Hakala, Barbara Rapp, Beverly Geckle, Carol Brent, Gary Van Overborg, Rick Burke, Kristin Antelman, Scott Bernier, Pascal Calarco, John Dove, Lucy Harrison, Peter Murray, Christine Stohn, Julie Zhu, Todd Carpenter, Bernhard Haslhofer, Richard Jones, Martin Klein, Graham Klyne, Carl Lagoze, Stuart Lewis, Peter Murray, Michael Nelson, Shlomo Sanders, Robert Sanderson, Herbert Van De Sompel, Paul Walk, Simeon Warner, Zhiwu Xie, Jeff Young

Computer Science Faculty Publications

This ResourceSync specification describes a synchronization framework for the web consisting of various capabilities that allow third-party systems to remain synchronized with a server’s evolving resources. The capabilities may be combined in a modular manner to meet local or community requirements. This specification also describes how a server should advertise the synchronization capabilities it supports and how third-party systems may discover this information. The specification repurposes the document formats defined by the Sitemap protocol and introduces extensions for them.

Modeling Beta-Traces For Beta-Barrels From Cryo-Em Density Maps, Dong Si, Jing He

Computer Science Faculty Publications

Cryo-electron microscopy (cryo-EM) has produced density maps of various resolutions. Although ά-helices can be detected from density maps at 5-8 angstrom resolutions, β-strands are challenging to detect at such density maps due to close-spacing of β-strands. The variety of shapes of β-sheets adds the complexity of β-strands detection from density maps. We propose a new approach to model traces of β-strands for β-barrel density regions that are extracted from cryo-EM density maps. In the test containing eight β-barrels extracted from experimental cryo-EM density maps at 5.5 angstrom-8.25 angstrom resolution, StrandRoller detected about 74.26% of the amino acids in the β-strands …

Homeomorphic Tetrahedralization Of Multi-Material Images With Quality And Fidelity Guarantees, Jing Xu, Andrey N. Chernikov

Computer Science Faculty Publications

We present a novel algorithm for generating three-dimensional unstructured tetrahedral meshes of multi-material images. The algorithm produces meshes with high quality since it provides a guaranteed dihedral angle bound of up to 19.47° for the output tetrahedra. In addition, it allows for user-specified guaranteed bounds on the two-sided Hausdorff distance between the boundaries of the mesh and the boundaries of the materials. Moreover, the mesh boundary is proved to be homeomorphic to the object surface. The algorithm is fast and robust, it produces a sufficiently small number of mesh elements that comply with these guarantees, as compared to other software. …