Computer Sciences Commons^™

A Digital Application For Assessment Of Neurocognitive Disabilities, Thomas H. Auriemma

Theses and Dissertations

Background: Neuropsychological assessment is designed to identify neurocognitive impairment and has traditionally relied on pen-and-paper tests. The behavior collected from these tests is usually expressed as a total summary score or a score that reflects a restricted number of features that assess errors. There is now interest in coupling traditional paper and pencil tests with digital assessment technology. In this context traditional metrics such as summary scores are still available. However, using digital technology, a host of time-based parameters can now be obtained. These time-based parameters include the total time to complete the task or total time to completion, as …

Using Graph Theoretical Methods And Traceroute To Visually Represent Hidden Networks, Jordan M. Sahs

UNO Student Research and Creative Activity Fair

Within the scope of a Wide Area Network (WAN), a large geographical communication network in which a collection of networking devices communicate data to each other, an example being the spanning communication network, known as the Internet, around continents. Within WANs exists a collection of Routers that transfer network packets to other devices. An issue pertinent to WANs is their immeasurable size and density, as we are not sure of the amount, or the scope, of all the devices that exists within the network. By tracing the routes and transits of data that traverses within the WAN, we can identify …

Analysis Of Federated Scheduling For Integer-Valued Workloads, Marion Sudvarg, Chris Gill

Computer Science Faculty Research & Creative Works

In federated scheduling of parallel real-time tasks on multiprocessor systems, high-utilization tasks are allocated dedicated processors on which they execute exclusively. Several methods exist for allocating a sufficient number of processors to guarantee that each task meets its deadline. In this paper, we propose two new strategies for allocating unit-speed cores to tasks with integer workload and deadline values. The first method can be performed in constant time for each high-utilization task, given the task's total workload, critical-path length, and deadline. The second method exploits the DAG structure of high-utilization tasks, providing a potentially better schedule in pseudo-polynomial time. We …

Learning To Control Under Time-Varying Environment, Yuzhen Han, Ruben Solozabal, Jing Dong, Xingyu Zhou, Martin Takac, Bin Gu

Machine Learning Faculty Publications

This paper investigates the problem of regret minimization in linear time-varying (LTV) dynamical systems. Due to the simultaneous presence of uncertainty and non-stationarity, designing online control algorithms for unknown LTV systems remains a challenging task. At a cost of NP-hard offline planning, prior works have introduced online convex optimization algorithms, although they suffer from nonparametric rate of regret. In this paper, we propose the first computationally tractable online algorithm with regret guarantees that avoids offline planning over the state linear feedback policies. Our algorithm is based on the optimism in the face of uncertainty (OFU) principle in which we optimistically …

Flecs: A Federated Learning Second-Order Framework Via Compression And Sketching, Artem Agafonov, Dmitry Kamzolov, Rachael Tappenden, Alexander Gasnikov, Martin Takac

Machine Learning Faculty Publications

Inspired by the recent work FedNL (Safaryan et al, FedNL: Making Newton-Type Methods Applicable to Federated Learning), we propose a new communication efficient second-order framework for Federated learning, namely FLECS. The proposed method reduces the high-memory requirements of FedNL by the usage of an L-SR1 type update for the Hessian approximation which is stored on the central server. A low dimensional 'sketch' of the Hessian is all that is needed by each device to generate an update, so that memory costs as well as number of Hessian-vector products for the agent are low. Biased and unbiased compressions are utilized to …

Offline Reinforcement Learning With Causal Structured World Models, Zheng-Mao Zhu, Xiong-Hui Chen, Hong-Long Tian, Kun Zhang, Yang Yu

Machine Learning Faculty Publications

Model-based methods have recently shown promising for offline reinforcement learning (RL), aiming to learn good policies from historical data without interacting with the environment. Previous model-based offline RL methods learn fully connected nets as world-models to map the states and actions to the next-step states. However, it is sensible that a world-model should adhere to the underlying causal effect such that it will support learning an effective policy generalizing well in unseen states. In this paper, We first provide theoretical results that causal world-models can outperform plain world-models for offline RL by incorporating the causal structure into the generalization error …

Spotlight Report #6: Proffering Machine-Readable Personal Privacy Research Agreements: Pilot Project Findings For Ieee P7012 Wg, Noreen Y. Whysel, Lisa Levasseur

Publications and Research

What if people had the ability to assert their own legally binding permissions for data collection, use, sharing, and retention by the technologies they use? The IEEE P7012 has been working on an interoperability specification for machine-readable personal privacy terms to support this ability since 2018. The premise behind the work of IEEE P7012 is that people need technology that works on their behalf—i.e. software agents that assert the individual’s permissions and preferences in a machine-readable format.

Thanks to a grant from the IEEE Technical Activities Board Committee on Standards (TAB CoS), we were able to explore the attitudes of …

(R1881) Impatient Customers In Queueing System With Optional Vacation Policies And Power Saving Mode, Poonam Gupta, Rajni Gupta, Sangeeta Malik

Applications and Applied Mathematics: An International Journal (AAM)

In this manuscript, a queueing system with two optional vacation policies, power-saving mode under reneging and retention of reneged customers in both vacations is analyzed. If the server is free, it chooses either of the vacations, classical vacation or working vacation. During vacations, the customers may get impatient due to delays and may leave the system, but they are retained in the system with some convincing mechanisms. On vacation completion, if the system is empty, the server is turned off to facilitate better utilization of the resources. Some of the operating system characteristics are derived using the probability generating functions …

Analysis Of A Quantum Attack On The Blum-Micali Pseudorandom Number Generator, Tingfei Feng

Mathematical Sciences Technical Reports (MSTR)

In 2012, Guedes, Assis, and Lula proposed a quantum attack on a pseudorandom number generator named the Blum-Micali Pseudorandom number generator. They claimed that the quantum attack can outperform classical attacks super-polynomially. However, this paper shows that the quantum attack cannot get the correct seed and provides another corrected algorithm that is in exponential time but still faster than the classical attack. Since the original classical attacks are in exponential time, the Blum-Micali pseudorandom number generator would be still quantum resistant.

Why Flash Radiotherapy Is Efficient: A Possible Explanation, Julio Urenda, Olga Kosheleva, Vladik Kreinovich, Nguyen Hoang Phuong

Departmental Technical Reports (CS)

Usually, a cancer radiotherapy session lasts between 10 to 20 minutes. Technically, it is possible to transmit the dose faster, but traditionally, medical doctors were reluctant to do it, since they were afraid of negative effects of such a speedy treatment. Recent experiments show, however, that these fears are unfounded; moreover, transmitting the whole radiation dose in a shorter time turns out to be more beneficial for the patients. In this paper, we provide a possible geometric explanation for this empirical phenomenon.

Why Rejuvenation Attempts Often Lead To Cancer And Why Cyclic Rejuvenation Is Better: A Simple Qualitative Explanation, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Since the 1960s, biologists have shown that, contrary to the previous belief that ageing is irreversible, many undesirable biological effects of ageing can be reversed. First attempts to perform this reversal on living creatures were not fully successful: while mice achieved some rejuvenation, many of these rejuvenated mice developed cancer. Later experiments showed that these cancers can be avoided if we apply cyclic rejuvenation: a short period of rejuvenation followed by a longer pause. This modified strategy led to recent successes of mice that recovered their age-deteriorated vision and mice that recovered their heart tissue after a heart attack. However, …

What’S So Artificial And Intelligent About Artificial Intelligence? A Conceptual Framework For Ai, Rebekah L. H. Rice

SPU Works

There is currently a good deal of attention being focused on artificial intelligence, broadly speaking, and deep learning, specifically. The attention is warranted, as these technologies are predicted to affect our collective lives in innumerable ways even beyond their already expansive social reach. There is much to consider regarding the benefits and potential harms of AI. And of course there are the apocalyptic musings about super-intelligent machines running amok, bringing science fiction scenarios uncomfortably close to anticipated reality. But productively engaging in discussions about the ethical and social implications of AI, and about which sorts of futures it is reasonable …

A Theological Framework For Reflection On Artificial Intelligence, Michael D. Langford

SPU Works

The theological questions before us in a digital age are pressing. What does God think of AI? Is AI good or evil? Will AI save us? What sort of future will AI give us? In what follows, I want to briefly introduce a few theological concepts that will hopefully help equip us for theological reflection on AI. We will begin with the question of epistemology, or how it is that we come by knowledge; in the realm of theology, this centers on revelation. We will then touch on the doctrine of creation, including the understanding of what it means to …

Artificial Intelligence And Theological Personhood, Michael D. Langford

SPU Works

Can AI be a person? What does God tell us about humanity and personhood? These are questions of theological anthropology and involve inquiring after the nature of humanity as God’s creation and what God wills for human personhood.

To address these inquiries, we will look at three biblical texts that bear on issues of theological anthropology, hopefully garnering some theological resources to consider the anthropological status of AI. Specifically, we will look at three “creation” texts that necessarily deal with the nature of human personhood within the divine economy of salvation history. The first is Genesis 1 and 2, which …

Reinforcement In The Information Revolution, Phillip M. Baker

SPU Works

This chapter will outline what it means to be a behaving human and how AI makes sense of these concepts. It will then explore possible near-future implications of our remarkable progress in understanding how human behavior works with the assistance of AI from a neurobiological basis. A focus on understanding the reinforcement mechanisms of the brain will reveal the consequences of ceding control of so much of our brain-environment interactions to AI. It will conclude by offering a potential Christian response to this digital reality from a uniquely Anabaptist perspective.

An Introduction To Artificial Intelligence, Carlos R. Arias

SPU Works

This chapter explores the evolution of artificial intelligence, starting with the first ideas of Alan Turing, going through the promises of its inception, and landing in our current state, when AI invokes a sense of power and awe. Next, the chapter will provide a summary of different technologies related to AI and machine learning, such as deep neural networks, to help the reader distinguish different terminologies. The chapter will end with a discussion of some potential tendencies concerning how AI may be used or evolve in the near future, and some questions about the technology in the long term.

Sin And Grace, Bruce D. Baker

SPU Works

The theological lens of sin and grace gives a broader and deeper viewpoint than mere ethics. Ethical analysis is of course useful and necessary, but ethics alone is not enough. Ethics apart from a robust, holistic understanding of humans as persons-in-communion will remain mired in reductionist thinking about human dignity and morality. Therefore, this final chapter addresses the ethical issues of AI through the lens of sin and grace.

Epilogue: A Litany For Faithful Engagement With Artificial Intelligence, Bruce D. Baker

SPU Works

A litany is a thoughtfully organized prayer for use in public worship by the church, or as a personal devotional practice by individuals. This seems a fitting way to close our reflection on AI, faith, and the future. Prayer will be essential to our faithful response to the new opportunities and challenges AI brings. Our hope is that this litany will serve as a practical guide to thoughtful invocation of the Holy Spirit in prayers for wisdom and discernment, and in the daily disciplines of spiritual growth.

Computational Paradox Of Deep Learning: A Qualitative Explanation, Jonatan Contreras, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich, Nguyen Hoang Phuong

Departmental Technical Reports (CS)

In general, the more unknowns in a problem, the more computational efforts is necessary to find all these unknowns. Interestingly, in state-of-the-art machine learning methods like deep learning, computations become easier when we increase the number of unknown parameters way beyond the number of equations. In this paper, we provide a qualitative explanation for this computational paradox.

Efficient Algorithms For Data Processing Under Type-3 (And Higher) Fuzzy Uncertainty, Vladik Kreinovich, Olga Kosheleva, Patricia Melin, Oscar Castillo

Departmental Technical Reports (CS)

It is known that to more adequately describe expert knowledge, it is necessary to go from the traditional (type-1) fuzzy techniques to higher order ones: type-2, probably type-3 and even higher. Until recently, only type-1 and type-2 fuzzy sets were used in practical applications. However, lately, it turned out that type-3 fuzzy sets are also useful in some applications. Because of this practical importance, it is necessary to design efficient algorithms for data processing under such type-3 (and higher order) fuzzy uncertainty. In this paper, we show how we can combine known efficient algorithms for processing type-1 and type-2 uncertainty …

Why Quantiles Are A Good Description Of Volatility In Economics: An Alternative Explanation, Laxman Bokati, Olga Kosheleva, Vladik Kreinovich, Kittawit Autchariyapanitkul

Departmental Technical Reports (CS)

In econometrics, volatility of an investment is usually described by its Value-at-Risk (VaR), i.e., by an appropriate quantile of the corresponding probability distribution. The motivations for selecting VaR are largely empirical: VaR provides a more adequate description of what people intuitively perceive as risk. In this paper, we analyze this situation from the viewpoint of decision theory, and we show that this analysis naturally leads to the Value-at-Risk, i.e., to a quantile.

Interestingly, this analysis also naturally leads to an optimization problem related to quantile regression.

Why Decreased Gaps Between Brain Cells Cause Severe Headaches: A Symmetry-Based Geometric Explanation, Laxman Bokati, Olga Kosheleva, Vladik Kreinovich, Nguyen Hoang Phuong

Departmental Technical Reports (CS)

When we analyze biological tissue under the microscope, cells are directly neighboring each other, with no gaps between them. However, a more detailed analysis shows that in vivo, there are small liquid-filled gaps between the cells, and these gaps are important: e.g., in abnormal situations, when the size of the gaps between brain cells decreases, this leads to severe headaches and other undesired effects. At present, there is no universally accepted explanation for this phenomenon. In this case, we show that the analysis of correpsonding geometric symmetries empirical phenomenon leads to a natural explanation for this effect.

How To Represent Uncertainty Via Qudits: Probability Distributions, Regular, Intuitionistic, And Picture Fuzzy Sets, F-Transforms, Etc., Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

While modern computers are fast, there are still many important practical situations in which we need even faster computations. It turns out that, due to the fact that the speed of all communications is limited by the speed of light, the only way to make computers drastically faster is to drastically decrease the size of computer's components. When we decrease their size to sizes comparable with micro-sizes of individual molecules, it becomes necessary to take into account specific physics of the micro-world -- known as quantum physics. Traditional approach to designing quantum computers -- i.e., computers that take effect of …

Why Rarity Score Is A Good Evaluation Of A Non-Fungible Token, Laxman Bokati, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

One of the new forms of investment is investing in so-called non-fungible tokens -- unique software objects associated with different real-life objects like songs, painting, photos, videos, characters in computer games, etc. Since these tokens are a form of financial investment, investors would like to estimate the fair price of such tokens. For tokens corresponding to objects that have their own price -- such as a song or a painting -- a reasonable estimate is proportional to the price of the corresponding object. However, for tokens corresponding to computer game characters, we cannot estimate their price this way. Based on …

Towards Better Ways To Compute The Overall Grade For A Class, Christian Servin, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Traditional way to compute the overall grade for the class is to use the weighted sum of the grades for all the assignments and exams, including the final exam. In terms of encouraging students to study hard throughout the semester, this grading scheme is better than an alternative scheme, in which all that matters is the grade on the final exam: in contrast to this alternative scheme, in the weighted-sum approach, students are penalized if they did not do well in the beginning of the semester. In practice, however, instructors sometimes deviate from the weighted-sum scheme: indeed, if the weighted …

How To Combine Expert Estimates? How To Estimate Probability In The Intersection Of Two Populations?, Miroslav Svitek, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In this paper, we consider two different practical problems that turned to be mathematically similar: (1) how to combine two expert-provided probabilities of some event and (2) how to estimate the frequency of a certain phenomenon (e.g., illness) in an intersection of two populations if we know the frequencies in each of these populations. In both cases, we use the maximum entropy approach to come up with a solution.

Why Quantile Regression Works Well In Economics: A Partial Explanation, Olga Kosheleva, Vassilis G. Kaburlasos, Vladik Kreinovich, Roengchai Tansuchat

Departmental Technical Reports (CS)

To get a better picture of the future behavior of different economics-related quantities, we need to be able to predict not only their mean values, but also their distribution. For example, it is desirable not only to predict future average income, but also to predict the future distribution of income. One of the convenient ways to describe a probability distribution is by using alpha-quantiles such as medians (corresponding to alpha = 0.5), quartiles (corresponding to alpha = 0.25 and alpha = 0.75), etc. In principle, an alpha-quantile of the desired future quantity can depend on beta-quantiles of current distributions corresponding …

Invariance-Based Approach Explains Empirical Formulas From Pavement Engineering To Deep Learning, Edgar Daniel Rodriguez Velasquez, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In many application areas, there are effective empirical formulas that need explanation. In this paper, we focus on two such challenges: neural networks, where a so-called softplus activation function is known to be very efficient, and pavement engineering, where there are empirical formulas describing the dependence of the pavement strength on the properties of the underlying soil. We show that similar scale-invariance ideas can explain both types of formulas -- and, in the case of pavement engineering, invariance ideas can lead to a new formula that combines the advantages of several known ones.

Towards A Computational Model Of Narrative On Social Media, Anne Bailey

Dartmouth College Undergraduate Theses

This thesis describes a variety of approaches to developing a computational model of narrative on social media. Our goal is to use such a narrative model to identify efforts to manipulate public opinion on social media platforms like Twitter. We present a model in which narratives in a collection of tweets are represented as a graph. Elements from each tweet that are relevant to potential narratives are made into nodes in the graph; for this thesis, we populate graph nodes with tweets’ authors, hashtags, named entities (people, locations, organizations, etc.,), and moral foundations (central moral values framing the discussion). Two …

Torsh: Obfuscating Consumer Internet-Of-Things Traffic With A Collaborative Smart-Home Router Network, Adam Vandenbussche

Dartmouth College Undergraduate Theses

When consumers install Internet-connected "smart devices" in their homes, metadata arising from the communications between these devices and their cloud-based service providers enables adversaries privy to this traffic to profile users, even when adequate encryption is used. Internet service providers (ISPs) are one potential adversary privy to users’ incom- ing and outgoing Internet traffic and either currently use this insight to assemble and sell consumer advertising profiles or may in the future do so. With existing defenses against such profiling falling short of meeting user preferences and abilities, there is a need for a novel solution that empowers consumers to …