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2020

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Full-Text Articles in Computer Sciences

How To Describe Measurement Errors: A Natural Generalization Of The Central Limit Theorem Beyond Normal (And Other Infinitely Divisible) Distributions, Julio Urenda, Olga Kosheleva, Vladik Kreinovich Oct 2020

How To Describe Measurement Errors: A Natural Generalization Of The Central Limit Theorem Beyond Normal (And Other Infinitely Divisible) Distributions, Julio Urenda, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

When precise measurement instruments are designed, designers try their best to decrease the effect of the main factors leading to measurement errors. As a result of this decrease, the remaining measurement error is the joint result of a large number of relatively small independent error components. According to the Central Limit Theorem, under reasonable conditions, when the number of components increases, the resulting distribution tends to Gaussian (normal). Thus, in practice, when the number of components is large, the distribution is close to normal -- and normal distributions are indeed ubiquitous in measurements. However, in some practical situations, the distribution …

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A Survey On Securing Personally Identifiable Information On Smartphones, Dar’Rell Pope, Yen-Hung (Frank) Hu, Mary Ann Hoppa Oct 2020

A Survey On Securing Personally Identifiable Information On Smartphones, Dar’Rell Pope, Yen-Hung (Frank) Hu, Mary Ann Hoppa

Virginia Journal of Science

With an ever-increasing footprint, already topping 3 billion devices, smartphones have become a huge cybersecurity concern. The portability of smartphones makes them convenient for users to access and store personally identifiable information (PII); this also makes them a popular target for hackers. This survey shares practical insights derived from analyzing 16 real-life case studies that exemplify: the vulnerabilities that leave smartphones open to cybersecurity attacks; the mechanisms and attack vectors typically used to steal PII from smartphones; the potential impact of PII breaches upon all parties involved; and recommended defenses to help prevent future PII losses. The contribution of this …

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Some Generalizations Of Classical Integer Sequences Arising In Combinatorial Representation Theory, Sasha Verona Malone Oct 2020

Some Generalizations Of Classical Integer Sequences Arising In Combinatorial Representation Theory, Sasha Verona Malone

Masters Theses & Specialist Projects

There exists a natural correspondence between the bases for a given finite-dimensional representation of a complex semisimple Lie algebra and a certain collection of finite edge-colored ranked posets, laid out by Donnelly, et al. in, for instance, [Don03]. In this correspondence, the Serre relations on the Chevalley generators of the given Lie algebra are realized as conditions on coefficients assigned to poset edges. These conditions are the so-called diamond, crossing, and structure relations (hereinafter DCS relations.) New representation constructions of Lie algebras may thus be obtained by utilizing edge-colored ranked posets. Of particular combinatorial interest are those representations whose corresponding …

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Csci 49380/79526: Fundamentals Of Reactive Programming- Assignment 1, Raffi Khatchadourian Oct 2020

Csci 49380/79526: Fundamentals Of Reactive Programming- Assignment 1, Raffi Khatchadourian

Open Educational Resources

No abstract provided.

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Csci 49380/79526: Fundamentals Of Reactive Programming- Syllabus, Raffi Khatchadourian Oct 2020

Csci 49380/79526: Fundamentals Of Reactive Programming- Syllabus, Raffi Khatchadourian

Open Educational Resources

No abstract provided.

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Csci 49380/79526: Fundamentals Of Reactive Programming - Assignment 2, Raffi Khatchadourian Oct 2020

Csci 49380/79526: Fundamentals Of Reactive Programming - Assignment 2, Raffi Khatchadourian

Open Educational Resources

No abstract provided.

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Video Game Genre Classification Based On Deep Learning, Yuhang Jiang Oct 2020

Video Game Genre Classification Based On Deep Learning, Yuhang Jiang

Masters Theses & Specialist Projects

Video games have played a more and more important role in our life. While the genre classification is a deeply explored research subject by leveraging the strength of deep learning, the automatic video game genre classification has drawn little attention in academia. In this study, we compiled a large dataset of 50,000 video games, consisting of the video game covers, game descriptions and the genre information. We explored three approaches for genre classification using deep learning techniques. First, we developed five image-based models utilizing pre-trained computer vision models such as MobileNet, ResNet50 and Inception, based on the game covers. Second, …

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Lenskit For Python: Next-Generation Software For Recommender Systems Experiments, Michael D. Ekstrand Oct 2020

Lenskit For Python: Next-Generation Software For Recommender Systems Experiments, Michael D. Ekstrand

Computer Science Faculty Publications and Presentations

LensKit is an open-source toolkit for building, researching, and learning about recommender systems. First released in 2010 as a Java framework, it has supported diverse published research, small-scale production deployments, and education in both MOOC and traditional classroom settings. In this paper, I present the next generation of the LensKit project, re-envisioning the original tool's objectives as flexible Python package for supporting recommender systems research and development. LensKit for Python (LKPY) enables researchers and students to build robust, flexible, and reproducible experiments that make use of the large and growing PyData and Scientific Python ecosystem, including scikit-learn, and TensorFlow. To …

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An Evaluation Of The 6tisch Distributed Resource Management Mode, Francesca Righetti, Carlo Vallati, Sajal K. Das, Giuseppe Anastasi Oct 2020

An Evaluation Of The 6tisch Distributed Resource Management Mode, Francesca Righetti, Carlo Vallati, Sajal K. Das, Giuseppe Anastasi

Computer Science Faculty Research & Creative Works

The IETF is currently defining the 6TiSCH architecture for the Industrial Internet of Things to ensure reliable and timely communication. 6TiSCH relies on the IEEE TSCH MAC protocol and defines different scheduling approaches for managing TSCH cells, including a distributed (neighbor-to-neighbor) scheduling scheme, where cells are allocated by nodes in a cooperative way. Each node leverages a Scheduling Function (SF) to compute the required number of cells, and the 6top (6P) protocol to negotiate them with neighbors. Currently, the Minimal Scheduling Function (MSF) is under consideration for standardization. However, multiple SFs are expected to be used in real deployments, in …

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Efficient Column-Oriented Processing For Mutual Subspace Skyline Queries, Tao Jiang, Bin Zhang, Dan Lin, Yunjun Gao, Qing Li Oct 2020

Efficient Column-Oriented Processing For Mutual Subspace Skyline Queries, Tao Jiang, Bin Zhang, Dan Lin, Yunjun Gao, Qing Li

Computer Science Faculty Research & Creative Works

A mutual skyline query will enable some new applications, such as marketing analysis, task allocation, and personalized matching. Algorithms for efficient processing of this query have been recently proposed in the literature. Those approaches use the R-tree indexes and apply a series of pruning criteria toward efficient processing. However, they are characterized by several limitations: (1) they cannot process different interests on attributes for skyline and reverse skyline, (2) they require a multidimensional index, which suffers from performance degradation, especially in high-dimensional space, and (3) they do not support vertically decomposed data that is a natural and intuitive choice for …

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Coding Overhead Of Mobile Apps, Yoonsik Cheon Oct 2020

Coding Overhead Of Mobile Apps, Yoonsik Cheon

Departmental Technical Reports (CS)

A mobile app runs on small devices such as smartphones and tablets. Perhaps, because of this, there is a common misconception that writing a mobile app is simpler than a desktop application. In this paper, we show that this is indeed a misconception, and it's the other way around. We perform a small experiment to measure the source code sizes of a desktop application and an equivalent mobile app written in the same language. We found that the mobile version is 19% bigger than the desktop version in terms of the source lines of code, and the mobile code is …

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Data Analytics Beyond Traditional Probabilistic Approach To Uncertainty, Vladik Kreinovich Oct 2020

Data Analytics Beyond Traditional Probabilistic Approach To Uncertainty, Vladik Kreinovich

Departmental Technical Reports (CS)

Data for processing mostly comes from measurements, and measurements are never absolutely accurate: there is always the "measurement error" -- the difference between the measurement result and the actual (unknown) value of the measured quantity. In many applications, it is important to find out how these measurement errors affect the accuracy of the result of data processing. Traditional data processing techniques implicitly assume that we know the probability distributions. In many practical situations, however, we only have partial information about these distributions. In some cases, all we know is the upper bound on the absolute value of the measurement error. …

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White- And Black-Box Computing And Measurements Under Limited Resources: Cloud, High Performance, And Quantum Computing, And Two Case Studies -- Robotic Boat And Hierarchical Covid Testing, Vladik Kreinovich, Martine Ceberio, Olga Kosheleva Oct 2020

White- And Black-Box Computing And Measurements Under Limited Resources: Cloud, High Performance, And Quantum Computing, And Two Case Studies -- Robotic Boat And Hierarchical Covid Testing, Vladik Kreinovich, Martine Ceberio, Olga Kosheleva

Departmental Technical Reports (CS)

In many practical problems, it is important to take into account that our computational and measuring resources are limited. In this paper, we overview main resource limitations for different types of computers, and we provide two case studies explaining how to best take this resource limitation into account.

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How To Separate Absolute And Relative Error Components: Interval Case, Christian Servin, Olga Kosheleva, Vladik Kreinovich Oct 2020

How To Separate Absolute And Relative Error Components: Interval Case, Christian Servin, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Usually, measurement errors contain both absolute and relative components. To correctly gauge the amount of measurement error for all possible values of the measured quantity, it is important to separate these two error components. For probabilistic uncertainty, this separation can be obtained by using traditional probabilistic techniques. The problem is that in many practical situations, we do not know the probability distribution, we only know the upper bound on the measurement error. In such situations of interval uncertainty, separation of absolute and relative error components is not easy. In this paper, we propose a technique for such a separation based …

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What If We Use Almost-Linear Functions Instead Of Linear Ones As A First Approximation In Interval Computations, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich Oct 2020

What If We Use Almost-Linear Functions Instead Of Linear Ones As A First Approximation In Interval Computations, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, the only information that we have about measurement errors is the upper bound on their absolute values. In such situations, the only information that we have after the measurement about the actual (unknown) value of the corresponding quantity is that this value belongs to the corresponding interval: e.g., if the measurement result is 1.0, and the upper bound is 0.1, then this interval is [1.0−0.1,1.0+0.1] = [0.9,1.1]. An important practical question is what is the resulting interval uncertainty of indirect measurements, i.e., in other words, how interval uncertainty propagates through data processing. There exist feasible algorithms …

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Why Number Of Color Difference Works Better In Detecting Melanoma Than Number Of Colors: A Possible Fractal-Based Explanation, Julio Urenda, Olga Kosheleva, Vladik Kreinovich Oct 2020

Why Number Of Color Difference Works Better In Detecting Melanoma Than Number Of Colors: A Possible Fractal-Based Explanation, Julio Urenda, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

At present, the best way to detect melanoma based on an image of a skin spot is to count the number of different colors in this image. A recent paper has shown that the detection can improve if instead of the number of colors, we use the difference between numbers of colors computed by using different thresholds. In this paper, we provide a possible fractal-based explanation for this empirical fact.

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The Hidden Advantage Among Digital Natives Within Bug Bounty Programs, James (Jimmy) Allah-Mensah Oct 2020

The Hidden Advantage Among Digital Natives Within Bug Bounty Programs, James (Jimmy) Allah-Mensah

Cybersecurity Undergraduate Research Showcase

Bug bounty programs are a great way for companies and organizations to help keep their systems and information secure; however, there are only a limited number of white hat hacking participant spots. With only so many seats available at the table, being able to determine the most qualified group of individuals is critical to the efficiency of the program at large. Digital natives, people born into the digital age, provide an instinctive approach when dealing with technology. On the other hand, digital immigrants, people who grew up before the digital age and had to adapt to new technology, evidently utilize …

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Secure Authentication And Privacy-Preserving Techniques In Vehicular Ad-Hoc Networks (Vanets), Dakshnamoorthy Manivannan, Shafika Showkat Moni, Sherali Zeadally Oct 2020

Secure Authentication And Privacy-Preserving Techniques In Vehicular Ad-Hoc Networks (Vanets), Dakshnamoorthy Manivannan, Shafika Showkat Moni, Sherali Zeadally

Computer Science Faculty Publications

In the last decade, there has been growing interest in Vehicular Ad Hoc NETworks (VANETs). Today car manufacturers have already started to equip vehicles with sophisticated sensors that can provide many assistive features such as front collision avoidance, automatic lane tracking, partial autonomous driving, suggestive lane changing, and so on. Such technological advancements are enabling the adoption of VANETs not only to provide safer and more comfortable driving experience but also provide many other useful services to the driver as well as passengers of a vehicle. However, privacy, authentication and secure message dissemination are some of the main issues that …

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How Do Kosovo Firms Utilize Business Intelligence? An Exploratory Study, Ardian Hyseni Oct 2020

How Do Kosovo Firms Utilize Business Intelligence? An Exploratory Study, Ardian Hyseni

UBT International Conference

The purpose of this paper is to examine how Kosovo firms utilize business intelligence to analyze their data and better understand the past, present and the future of their firm. Business intelligence offers firms the ability to analyze large amount of data quicker and more effective. Decision making has become easier with the use of BI tools, but making the right decision at right time has become vital for the firms performance. This research will contribute on business industry by providing evidence how Kosovo firms utilize the BI system, what BI tools and what business values and processes BI offers …

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Visual Cryptography Scheme With Digital Watermarking In Sharing Secret Information From Car Number Plate Digital Images, Ana Savic, Goran Bjelobaba, Radosav Veselinovic, Hana Stefanovic Oct 2020

Visual Cryptography Scheme With Digital Watermarking In Sharing Secret Information From Car Number Plate Digital Images, Ana Savic, Goran Bjelobaba, Radosav Veselinovic, Hana Stefanovic

UBT International Conference

In this paper a visual cryptography scheme with a binary additive stream cipher is used to form the meaningless shares (share images or multiple layers) of original digital image, hiding some secret information. Each share image holds some information, but at the receiver side only when all of them are superimposed, the secret information is revealed by human vision without any complex computation. Proposed algorithm for generating shares is applied in MATLAB programming environment, using MATLAB built-in functions to create sequences of pseudorandom numbers or streams, which are used to make share images of original digital image. The input image …

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Analysis Of Cloud Bursting On Openstack Infrastructure To Aws, Bao Pham, Ronald C. Jones, Majid Shaalan Oct 2020

Analysis Of Cloud Bursting On Openstack Infrastructure To Aws, Bao Pham, Ronald C. Jones, Majid Shaalan

Other Student Works

Cloud computing is the development of distributed and parallel computing that seeks to provide a new model of business computing by automating services and efficiently storing proprietary data. Cloud bursting is one of the cloud computing techniques that adopts the hybrid cloud model which seeks to expand the resources of a private cloud through the integration with a public cloud infrastructure. In this paper, the viability of cloud bursting is experimented and an attempt to integrate AWS EC2 onto an Openstack cloud environment using the Openstack OMNI driver is conducted.

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The Internet Never Forgets: Image-Based Sexual Abuse And The Workplace, John Schriner, Melody Lee Rood Oct 2020

The Internet Never Forgets: Image-Based Sexual Abuse And The Workplace, John Schriner, Melody Lee Rood

Publications and Research

Image-based sexual abuse (IBSA), commonly known as revenge pornography, is a type of cyberharassment that often results in detrimental effects to an individual's career and livelihood. Although there exists valuable research concerning cyberharassment in the workplace generally, there is little written about specifically IBSA and the workplace. This chapter examines current academic research on IBSA, the issues with defining this type of abuse, victim blaming, workplace policy, and challenges to victim-survivors' redress. The authors explore monetary motivation for websites that host revenge pornography and unpack how the dark web presents new challenges to seeking justice. Additionally, this chapter presents recommendations …

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Chapter 7: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana Oct 2020

Chapter 7: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana

Open Educational Resources

No abstract provided.

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Compact Bilinear Augmented Query Structured Attention For Sport Highlights Classification, Yanbin Hao, Hao Zhang, Chong-Wah Ngo, Qing Liu, Xiaojun Hu Oct 2020

Compact Bilinear Augmented Query Structured Attention For Sport Highlights Classification, Yanbin Hao, Hao Zhang, Chong-Wah Ngo, Qing Liu, Xiaojun Hu

Research Collection School Of Computing and Information Systems

Understanding fine-grained activities, such as sport highlights, is a problem being overlooked and receives considerably less research attention. Potential reasons include absences of specific fine-grained action benchmark datasets, research preferences to general supercategorical activities classification, and challenges of large visual similarities between fine-grained actions. To tackle these, we collect and manually annotate two sport highlights datasets, i.e., Basketball8 & Soccer-10, for fine-grained action classification. Sample clips in the datasets are annotated with professional sub-categorical actions like “dunk”, “goalkeeping” and etc. We also propose a Compact Bilinear Augmented Query Structured Attention (CBA-QSA) module and stack it on top of general three-dimensional …

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Deepsonar: Towards Effective And Robust Detection Of Ai-Synthesized Fake Voices, Run Wang, Felix Juefei-Xu, Yihao Huang, Qing Guo, Xiaofei Xie, Lei Ma, Yang Liu Oct 2020

Deepsonar: Towards Effective And Robust Detection Of Ai-Synthesized Fake Voices, Run Wang, Felix Juefei-Xu, Yihao Huang, Qing Guo, Xiaofei Xie, Lei Ma, Yang Liu

Research Collection School Of Computing and Information Systems

With the recent advances in voice synthesis, AI-synthesized fake voices are indistinguishable to human ears and widely are applied to produce realistic and natural DeepFakes, exhibiting real threats to our society. However, effective and robust detectors for synthesized fake voices are still in their infancy and are not ready to fully tackle this emerging threat. In this paper, we devise a novel approach, named DeepSonar, based on monitoring neuron behaviors of speaker recognition (SR) system, i.e., a deep neural network (DNN), to discern AI-synthesized fake voices. Layer-wise neuron behaviors provide an important insight to meticulously catch the differences among inputs, …

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Livesnippets: Voice-Based Live Authoring Of Multimedia Articles About Experiences, Hyeongcheol Kim, Shengdong Zhao, Can Liu, Kotaro Hara Oct 2020

Livesnippets: Voice-Based Live Authoring Of Multimedia Articles About Experiences, Hyeongcheol Kim, Shengdong Zhao, Can Liu, Kotaro Hara

Research Collection School Of Computing and Information Systems

We transform traditional experience writing into in-situ voice-based multimedia authoring. Documenting experiences digitally in blogs and journals is a common activity that allows people to socially connect with others by sharing their experiences (e.g. travelogue). However, documenting such experiences can be time-consuming and cognitively demanding as it is typically done OUT-OF-CONTEXT (after the actual experience). We propose in-situ voice-based multimedia authoring (IVA), an alternative workflow to allow IN-CONTEXT experience documentation. Unlike the traditional approach, IVA encourages in-context content creations using voice-based multimedia input and stores them in multi-modal "snippets". The snippets can be rearranged to form multimedia articles and can …

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Hysia: Serving Dnn-Based Video-To-Retail Applications In Cloud, Huaizheng Zhang, Yuanming Li, Qiming Ai, Yong Luo, Yonggang Wen, Yichao Jin, Nguyen Binh Duong Ta Oct 2020

Hysia: Serving Dnn-Based Video-To-Retail Applications In Cloud, Huaizheng Zhang, Yuanming Li, Qiming Ai, Yong Luo, Yonggang Wen, Yichao Jin, Nguyen Binh Duong Ta

Research Collection School Of Computing and Information Systems

Combining video streaming and online retailing (V2R) has been a growing trend recently. In this paper, we provide practitioners and researchers in multimedia with a cloud-based platform named Hysia for easy development and deployment of V2R applications. The system consists of: 1) a back-end infrastructure providing optimized V2R related services including data engine, model repository, model serving and content matching; and 2) an application layer which enables rapid V2R application prototyping. Hysia addresses industry and academic needs in large-scale multimedia by: 1) seamlessly integrating state-of-the-art libraries including NVIDIA video SDK, Facebook faiss, and gRPC; 2) efficiently utilizing GPU computation; and …

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White-Box Fairness Testing Through Adversarial Sampling, Peixin Zhang, Jingyi Wang, Jun Sun, Guoliang Dong, Xinyu Wang, Xingen Wang, Jin Song Dong, Dai Ting Oct 2020

White-Box Fairness Testing Through Adversarial Sampling, Peixin Zhang, Jingyi Wang, Jun Sun, Guoliang Dong, Xinyu Wang, Xingen Wang, Jin Song Dong, Dai Ting

Research Collection School Of Computing and Information Systems

Although deep neural networks (DNNs) have demonstrated astonishing performance in many applications, there are still concerns on their dependability. One desirable property of DNN for applications with societal impact is fairness (i.e., non-discrimination). In this work, we propose a scalable approach for searching individual discriminatory instances of DNN. Compared with state-of-the-art methods, our approach only employs lightweight procedures like gradient computation and clustering, which makes it significantly more scalable than existing methods. Experimental results show that our approach explores the search space more effectively (9 times) and generates much more individual discriminatory instances (25 times) using much less time (half …

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A Human Error Based Approach To Understanding Programmer-Induced Software Vulnerabilities, Vaibhav Anu, Kazi Zakia Sultana, Bharath K. Samanthula Oct 2020

A Human Error Based Approach To Understanding Programmer-Induced Software Vulnerabilities, Vaibhav Anu, Kazi Zakia Sultana, Bharath K. Samanthula

Department of Computer Science Faculty Scholarship and Creative Works

Many security incidents can be traced back to software vulnerabilities, which can be described as security-related defects/bugs in the code that can potentially be exploited by the attackers to perform unauthorized actions. An analysis of vulnerability data disseminated by organizations such as NIST' s National Vulnerability (NVD) and SANS Institute shows that a majority of vulnerabilities can be traced back to a relatively small set of root causes mostly related to the repeated mistakes by the programmers. That is, programmers exhibit a pattern of erroneous coding practices or behavior which lead to vulnerable code. Cognitive Psychologists have long been studying …

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A Highly-Parameterized Ensemble To Play Gin Rummy, Masayuki Nagai, Kavya Shrivastava, Kien Ta, Chad Byers, Steven Bogaerts Oct 2020

A Highly-Parameterized Ensemble To Play Gin Rummy, Masayuki Nagai, Kavya Shrivastava, Kien Ta, Chad Byers, Steven Bogaerts

Annual Student Research Poster Session

In this work we describe the development and tuning of a computer Gin Rummy player. The system includes three main components to make decisions about drawing cards, discarding, and ending the game, with numerous hyperparameters controlling behavior. After the components are described, three sets of hyperparameter tuning and performance experiments are analyzed.

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