Computer Sciences Commons^™

Noise Reduction Of Eeg Signals Using Autoencoders Built Upon Gru Based Rnn Layers, Esra Aynali

Dissertations

Understanding the cognitive and functional behaviour of the brain by its electrical activity is an important area of research. Electroencephalography (EEG) is a method that measures and record electrical activities of the brain from the scalp. It has been used for pathology analysis, emotion recognition, clinical and cognitive research, diagnosing various neurological and psychiatric disorders and for other applications. Since the EEG signals are sensitive to activities other than the brain ones, such as eye blinking, eye movement, head movement, etc., it is not possible to record EEG signals without any noise. Thus, it is very important to use an …

How Quantum Cryptography And Quantum Computing Can Make Cyber-Physical Systems More Secure, Deepak Tosh, Oscar Galindo, Vladik Kreinovich, Olga Kosheleva

Departmental Technical Reports (CS)

For cyber-physical systems, cyber-security is vitally important. There are many cyber-security tools that make communications secure -- e.g., communications between sensors and the computers processing the sensor's data. Most of these tools, however, are based on RSA encryption, and it is known that with quantum computing, this encryption can be broken. It is therefore desirable to use an unbreakable alternative -- quantum cryptography -- for such communications. In this paper, we discuss possible consequences of this option. We also explain how quantum computers can help even more: namely, they can be used to optimize the system's design -- in particular, …

Why Squashing Functions In Multi-Layer Neural Networks, Julio Urenda, Orsoly Csiszár, Gábor Csiszár, József Dombi, Olga Kosheleva, Vladik Kreinovich, György Eigner

Departmental Technical Reports (CS)

Most multi-layer neural networks used in deep learning utilize rectified linear neurons. In our previous papers, we showed that if we want to use the exact same activation function for all the neurons, then the rectified linear function is indeed a reasonable choice. However, preliminary analysis shows that for some applications, it is more advantageous to use different activation functions for different neurons -- i.e., select a family of activation functions instead, and select the parameters of activation functions of different neurons during training. Specifically, this was shown for a special family of squashing functions that contain rectified linear neurons …

A Mystery Of Human Biological Development -- Can It Be Used To Speed Up Computations?, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

For many practical problems, the only known algorithms for solving them require non-feasible exponential time. To make computations feasible, we need an exponential speedup. A reasonable way to look for such possible speedup is to search for real-life phenomena where such a speedup can be observed. A natural place to look for such a speedup is to analyze the biological activities of human beings -- since we, after all, solve many complex problems that even modern super-fast computers have trouble solving. Up to now, this search was not successful -- e.g., there are people who compute much faster than others, …

Automating Deep-Sea Video Annotation Using Machine Learning, Hanson Egbert, Lubomir Stanchev, Benjamin Ruttenberg

Computer Science and Software Engineering

As the world explores opportunities to develop offshore renewable energy capacity, there will be a growing need for pre-construction biological surveys and post-construction monitoring in the challenging marine environment. Underwater video is a powerful tool to facilitate such surveys, but the interpretation of the imagery is costly and time-consuming. Emerging technologies have improved automated analysis of underwater video, but these technologies are not yet accurate or accessible enough for widespread adoption in the scientific community or industries that might benefit from these tools. To address these challenges, we developed a website that allows us to: (1) Quickly play and annotate …

Color-Based Template Selection For Detection Of Gastric Abnormalities In Video Endoscopy, Hussam Ali, Muhammad Sharif, Mussarat Yasmin, Mubashir Husain Rehmani

Publications

Computer-aided diagnosis of gastric diseases from endoscopy frames is an important task. It facilitates both the patient and gastroenterologist in terms of time, money and most important health. Colors are the basic visual features of endoscopic images and also provide clues about abnormal regions in endoscopy frames. A variety of color spaces available for representation of color frames. However, we are not certain about which color space is more suitable for representing color features of gastric images. This paper presents a comparison of color features in different color spaces for detection of abnormal areas in chromoendoscopy (CH) frames. In addition, …

Establishing An Information System For Documenting Valuable Buildings By Using Gis In Egypt, Mona Mahrous Abdel Wahed

Emirates Journal for Engineering Research

Valuable heritage buildings are the history of nations, and history forms the identities of these nations. Many of these buildings are exposed to deterioration, destruction and distortion. Therefore, it is essential to protect and maintain these buildings to protect history. Effective documentation of valuable buildings is necessary to guide and assist stakeholders in making decisions regarding valuable buildings. Documentation requires robust and scientific methods. Therefore, it is important to utilize new technology in general and geographic information system GIS in particular in documenting valuable buildings. GIS has the potential to contribute and deal with valuable buildings at various stages and …

How To Gauge The Quality Of A Testing Method When Ground Truth Is Known With Uncertainty, Nicholas Gray, Scott Ferson, Vladik Kreinovich

Departmental Technical Reports (CS)

The quality of a testing method is usually measured by using sensitivity, specificity, and/or precision. To compute each of these three characteristics, we need to know the ground truth, i.e., we need to know which objects actually have the tested property. In many applications (e.g., in medical diagnostics), the information about the objects comes from experts, and this information comes with uncertainty. In this paper, we show how to take this uncertainty into account when gauging the quality of testing methods.

Experiential Learning Framework For Smaller Computer Science Programs, Zachary A. Kissel, Christopher S. Stuetzle

Computer and Data Science Faculty Publications

Experiential learning (EL) permeates the Computer Science discipline. This work seeks to codify EL practices for computer science pedagogy into ve key pillars. These pillars have been successfully applied at a small to mid-sized college within the heavily competitive Boston area. This paper further describes how a computer science department may eectively implement the pillars in their own curriculum.

Experiential Learning In The Technology Disciplines February 2020, Patricia Sendall, Christopher S. Stuetzle, Zachary A. Kissel, Tahir Hameed

Computer and Data Science Faculty Publications

Learning-by-doing has long been a tradition in the technology disciplines. It is the "hands-on" work, combined with student reflection, feedback and assessment, that reinforces theory into practice. Over the past 40 years, experiential learning (EL) in higher education has grown beyond in-class assignments to include internships, cooperative education, team-based learning, project-based learning, community engagement, service learning, international and study-away experiences, capstone projects and research opportunities. This paper provides an overview of experiential education theory and practice in the undergraduate technology disciplines, and presents examples of how experiential learning practices have evolved over time at a medium-sized institution in the Northeast …

Information Security Recommendation System, Vildan Bina

Theses and Dissertations

Konsiderimi gjithëpërfshirës i rreziqeve të TI-së rezulton nga një përdorim i shtuar i TI-së dhe ankesave dhe skandaleve që rezultojnë në fushën e teknologjisë së informacionit. Në veçanti, humbjet financiare që vijnë nga dëmtimi në reputacion dhe pretendimet për dëme kontribuojnë në një vetëdije të rritur për rreziqet themelore të TI.

Ky studim vë në pah disa prej shkaqeve të cilat bëjnë kanosjen e rrezikut ne sferen e sigurisë së informacionit,duke analizuar situatën nga ana e bizneseve në gjërat të cilat nuk u kushtojnë rëndësinë e merituar deri tek një zhvillues me qëllim të keq i cili tenton të bëj …

Are The Code Snippets What We Are Searching For? A Benchmark And An Empirical Study On Code Search With Natural-Language Queries, Shuhan Yan, Hang Yu, Yuting Chen, Beijun Shen

Research Collection School Of Computing and Information Systems

Code search methods, especially those that allow programmers to raise queries in a natural language, plays an important role in software development. It helps to improve programmers' productivity by returning sample code snippets from the Internet and/or source-code repositories for their natural-language queries. Meanwhile, there are many code search methods in the literature that support natural-language queries. Difficulties exist in recognizing the strengths and weaknesses of each method and choosing the right one for different usage scenarios, because (1) the implementations of those methods and the datasets for evaluating them are usually not publicly available, and (2) some methods leverage …

Cache-Enabled In Cooperative Cognitive Radio Networks For Transmission Performance, Jiachen Yang, Houbing Song, Chaofan Ma, Jiabao Man, Huifang Xu, Gan Zheng

Publications

The proliferation of mobile devices that support the acceleration of data services (especially smartphones) has resulted in a dramatic increase in mobile traffic. Mobile data also increased exponentially, already exceeding the throughput of the backhaul. To improve spectrum utilization and increase mobile network traffic, in combination with content caching, we study the cooperation between primary and secondary networks via content caching. We consider that the secondary base station assists the primary user by pre-caching some popular primary contents. Thus, the secondary base station can obtain more licensed bandwidth to serve its own user. We mainly focus on the time delay …

Crowdprivacy: Publish More Useful Data With Less Privacy Exposure In Crowdsourced Location-Based Services, Fang Jing Wu, Tie Luo

Computer Science Faculty Research & Creative Works

Location-based services (LBSs) typically crowdsource geo-tagged data from mobile users. Collecting more data will generally improve the utility for LBS providers; however, it also leads to more privacy exposure of users' mobility patterns. Although the tension between data utility and user privacy has been recognized, there lacks a solution that determines how much data to collect-in both spatial and temporal domains-is the "best" for both mobile users and the service provider. This article proposes a strategy toward making an optimal tradeoff such that a user submits data only if her mobility privacy will not be compromised and the data utility …

Workshop On The Development And Evaluation Of Digital Therapeutics For Health Behavior Change: Science, Methods, And Projects, Alan J. Budney, Lisa A. Marsch, Will M. Aklin, Jacob T. Borodovsky, Mary F. Brunette, Andrew T. Campbell, Jesse Dallery, David Kotz, Ashley A. Knapp, Sarah E. Lord, Edward V. Nunes, Emily A. Scherer, Catherine Stanger, William C. Torrey

Dartmouth Scholarship

The health care field has integrated advances into digital technology at an accelerating pace to improve health behavior, health care delivery, and cost-effectiveness of care. The realm of behavioral science has embraced this evolution of digital health, allowing for an exciting roadmap for advancing care by addressing the many challenges to the field via technological innovations. Digital therapeutics offer the potential to extend the reach of effective interventions at reduced cost and patient burden and to increase the potency of existing interventions. Intervention models have included the use of digital tools as supplements to standard care models, as tools that …

The Changing Profile Of Ecs Teachers, Steven Mcgee, Lucia Dettori, Ronald I. Greenberg, Andrew M. Rasmussen, Dale F. Reed, Don Yanek

Computer Science: Faculty Publications and Other Works

This study compares the characteristics and professional development (PD) experiences between teachers who began teaching Exploring Computer Science before and after the enactment of a CS graduation requirement in the Chicago Public Schools. The post-requirement teachers were less likely to have a CS background, but their experience in the ECS PD and their level of confidence at the end of the PD were equivalent to the early adopters.

Algorithms Of Oppression [Uno Pa Theory Proseminar Presentation], Sue Ann Gardner

University of Nebraska-Lincoln Libraries: Presentations

Slides of two classes taught in the Theory Proseminar in the School of Public Administration at the University of Nebraska at Omaha by Sue Ann Gardner on February 11 and 18, 2020.

Connects information theory to applicable knowledge frameworks in public administration. Includes an in-depth discussion of the concepts addressed in Samiya Umoja Noble's book Algorithms of Oppression (published by New York University Press, New York, New York, United States, 2018) in the context of public administration and public academic libraries.

Supporting Blockchain-Based Cryptocurrency Mobile Payment With Smart Devices, Lei Xu, Lin Chen, Zhimin Gao, Larry Carranco, Xinxin Fan, Nolah Shah

Computer Science Faculty Publications

The smart device owning rate such as smart phone and smart watch is higher than ever before and mobile payment has become one of the major payment methods in many different areas. At the same time, blockchain-based cryptocurrency is becoming a nonnegligible type of currency and the total value of all types of cryptocurrency has reached USD 200 billion. Therefore, it is a natural demand to support cryptocurrency payment on mobile devices. Considering the poor infrastructure and low penetration of financial service in developing countries, this combination is especially attractive. The high storage cost and payment processing latency are the …

Computer Science Through Concurrent Enrollment: A Strategy To Broaden Participation, Renee Fall, Seth Freeman, Ronald I. Greenberg, Dan Kaiser, Nigamanth Sridhar

Computer Science: Faculty Publications and Other Works

Most U.S. states support college-readiness and access through dual enrollment, in which high school students enroll in college courses. Concurrent enrollment (CE) allows students to take college courses in their own high school, taught by high school teachers approved by the partner college. CE has positive effects on students' education, but rarely is CS available through CE. Unlike AP, CE provides college credit to students who are assessed throughout the course rather than by a single high-stakes exam/project. This panel will showcase four different types of post-secondary institutions' experiences offering CS-through-CE and discuss its potential as an entry point into …

Defect-Free Plastic Deformation Through Dimensionality Reduction And Self-Annihilation Of Topological Defects In Crystalline Solids, Yipeng Gao, Yongfeng Zhang, Larry K. Aagesen, Jianguo Yu, Min Long, Yunzhi Wang

Computer Science Faculty Publications and Presentations

As a signature of symmetry-breaking processes, the generation and annihilation of topological defects (domain walls, strings, etc.) are of great interest in condensed matter physics and cosmology. Here we propose a distinctive self-organization process through phase transitions, in which all the generated topological defects are dimensionality reduced and self-annihilated. In crystalline solids, such a unique mechanism allows a perfect single crystal after plastic deformation, which originates from the coupling of different types of broken symmetries.

Spanning Properties Of Theta-Theta-6, Mirela Damian, John Iacono, Andrew Winslow

Computer Science Faculty Publications

We show that, unlike the Yao–Yao graph YY6, the Theta–Theta graph ΘΘ6 defined by six cones is a spanner for sets of points in convex position. We also show that, for sets of points in non-convex position, the spanning ratio of ΘΘ6 is unbounded.

Geographic Difference Shaped Human Ocular Surface Metagenome Of Young Han Chinese From Beijing, Wenzhou, And Guangzhou Cities, Paul W. Bible, Yuhua Deng, Xiaofeng Wen, Xiao Hu, Et Al.

Computer Science Faculty publications

Purpose: Microbial ecosystems interact with the human body and affect human health. The microbial community on the ocular surface remains an underexplored territory despite its importance as the first line of defense barrier that protects the eye and ultimately sight. We investigated how age and sex affected human ocular surface microbiome, and in the present study wanted to understand how geographic difference shaped the microbiome in the ocular surface.

Methods: We collected conjunctival specimens of 172 eyes from 86 healthy volunteers living in three Chinese cities, namely, Guangzhou, Wenzhou, and Beijing. Using the direct metagenomic shotgun sequencing approach, we characterized …

Deepmicrobes: Taxonomic Classification For Metagenomics With Deep Learning, Paul W. Bible, Qiaoxing Liang, Yu Liu, Bin Zou, Lai Wei

Computer Science Faculty publications

Large-scale metagenomic assemblies have uncovered thousands of new species greatly expanding the known diversity of microbiomes in specific habitats. To investigate the roles of these uncultured species in human health or the environment, researchers need to incorporate their genome assemblies into a reference database for taxonomic classification. However, this procedure is hindered by the lack of a well-curated taxonomic tree for newly discovered species, which is required by current metagenomics tools. Here we report DeepMicrobes, a deep learning-based computational framework for taxonomic classification that allows researchers to bypass this limitation. We show the advantage of DeepMicrobes over state-of-the-art tools in …

Robust Neural Machine Translation, Abdul Rafae Khan

Dissertations, Theses, and Capstone Projects

This thesis aims for general robust Neural Machine Translation (NMT) that is agnostic to the test domain. NMT has achieved high quality on benchmarks with closed datasets such as WMT and NIST but can fail when the translation input contains noise due to, for example, mismatched domains or spelling errors. The standard solution is to apply domain adaptation or data augmentation to build a domain-dependent system. However, in real life, the input noise varies in a wide range of domains and types, which is unknown in the training phase. This thesis introduces five general approaches to improve NMT accuracy and …

Multi-Level Fine-Scaled Sentiment Sensing With Ambivalence Handling, Zhaoxia Wang, Seng-Beng Ho, Erik Cambria

Research Collection School Of Computing and Information Systems

Social media represent a rich source of information, such as critiques, feedback, and other opinions posted online by Internet users. Such information is typically a good reflection of users’ sentiments and attitudes towards various services, topics, or products. Sentiment analysis has become an increasingly important natural language processing (NLP) task to help users make sense of what is happening in the Internet blogosphere and it can be useful for companies as well as public organizations. However, most existing sentiment analysis techniques are only able to analyze data at the aggregate level, merely providing a binary classification (positive vs. negative), and …

Saga: Efficient And Large-Scale Detection Of Near-Miss Clones With Gpu Acceleration, Guanhua Li, Yijian Wu, Chanchal K. Roy, Jun Sun, Xin Peng, Nanjie Zhan, Bin Hu, Jingyi Ma

Research Collection School Of Computing and Information Systems

Clone detection on large code repository is necessary for many big code analysis tasks. The goal is to provide rich information on identical and similar code across projects. Detecting near-miss code clones on big code is challenging since it requires intensive computing and memory resources as the scale of the source code increases. In this work, we propose SAGA, an efficient suffix-array based code clone detection tool designed with sophisticated GPU optimization. SAGA not only detects Type-l and Type-2 clones but also does so for cross-project large repositories and for the most computationally expensive Type-3 clones. Meanwhile, it also works …

Zero-Shot Ingredient Recognition By Multi-Relational Graph Convolutional Network, Jingjing Chen, Liangming Pan, Zhipeng Wei, Xiang Wang, Chong-Wah Ngo, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Recognizing ingredients for a given dish image is at the core of automatic dietary assessment, attracting increasing attention from both industry and academia. Nevertheless, the task is challenging due to the difficulty of collecting and labeling sufficient training data. On one hand, there are hundred thousands of food ingredients in the world, ranging from the common to rare. Collecting training samples for all of the ingredient categories is difficult. On the other hand, as the ingredient appearances exhibit huge visual variance during the food preparation, it requires to collect the training samples under different cooking and cutting methods for robust …

Giving Voice To Parents In The Development Of The Preemie Prep For Parents (P3) Mobile App, Kris Pizur-Barnekow, Una Olivia Kim, Sheikh Iqbal Ahamed, Md Kamrul Hasan, Shannon Dreier, Steven R. Leuthner, Nicole Rau, Mir A. Basir

Computer Science Faculty Research and Publications

Background:

Parents at risk for preterm birth frequently receive prematurity education when the mother is hospitalized for premature labor. Parental ability to learn and consider the information is limited because of the stress of the hospitalization. A promising approach is dissemination of information to at-risk parents before the birth hospitalization.

Purpose:

This article describes formative research used to develop smartphone-based prematurity education app for parents at-risk for preterm birth.

Methods:

Stakeholders were parents with a prior preterm birth. Using stakeholder meeting transcripts, constant comparative analysis was used to reflect upon the parental voice.

Results:

The parents named the app, Preemie …

Deepbindiff: Learning Program-Wide Code Representations For Binary Diffing, Yue Duan, Xuezixiang Li, Jinghan Wang, Wang, Heng Yin

Research Collection School Of Computing and Information Systems

Binary diffing analysis quantitatively measures the differences between two given binaries and produces fine-grained basic block matching. It has been widely used to enable different kinds of critical security analysis. However, all existing program analysis and machine learning based techniques suffer from low accuracy, poor scalability, coarse granularity, or require extensive labeled training data to function. In this paper, we propose an unsupervised program-wide code representation learning technique to solve the problem. We rely on both the code semantic information and the program-wide control flow information to generate block embeddings. Furthermore, we propose a k-hop greedy matching algorithm to find …

Five Challenges In Cloud-Enabled Intelligence And Control, Tarek Abdelzaher, Yifan Hao, Kasthuri Jayarajah, Archan Misra, Per Skarin, Shuochao Yao, Dulanga Kaveesha Weerakoon Weerakoon Mudiyanselage, Karl-Erik Arzen

Research Collection School Of Computing and Information Systems

The proliferation of connected embedded devices, or the Internet of Things (IoT), together with recent advances in machine intelligence, will change the profile of future cloud services and introduce a variety of new research problems, both in cloud applications and infrastructure layers. These problems are centered around empowering individually resource-limited devices to exhibit intelligent behavior, both in sensing and control, thanks to a judicious utilization of cloud resources. Cloud services will enable learning from data, performing inference, and executing control, all with assurances on outcomes. The paper discusses such emerging services and outlines five resulting new research directions towards enabling …