Theory and Algorithms Commons^™

Artificial Intelligence And The Situational Rationality Of Diagnosis: Human Problem-Solving And The Artifacts Of Health And Medicine, Michael W. Raphael

Publications and Research

What is the problem-solving capacity of artificial intelligence (AI) for health and medicine? This paper draws out the cognitive sociological context of diagnostic problem-solving for medical sociology regarding the limits of automation for decision-based medical tasks. Specifically, it presents a practical way of evaluating the artificiality of symptoms and signs in medical encounters, with an emphasis on the visualization of the problem-solving process in doctor-patient relationships. In doing so, the paper details the logical differences underlying diagnostic task performance between man and machine problem-solving: its principle of rationality, the priorities of its means of adaptation to abstraction, and the effects …

Teaching Machine Learning For The Physical Sciences: A Summary Of Lessons Learned And Challenges, Viviana Acquaviva

Publications and Research

This paper summarizes some challenges encountered and best practices established in several years of teaching Machine Learning for the Physical Sciences at the undergraduate and graduate level. I discuss motivations for teaching ML to physicists, desirable properties of pedagogical materials, such as accessibility, relevance, and likeness to real-world research problems, and give examples of components of teaching units.

An Adaptive Cryptosystem On A Finite Field, Awnon Bhowmik, Unnikrishnan Menon

Publications and Research

Owing to mathematical theory and computational power evolution, modern cryptosystems demand ingenious trapdoor functions as their foundation to extend the gap between an enthusiastic interceptor and sensitive information. This paper introduces an adaptive block encryption scheme. This system is based on product, exponent, and modulo operation on a finite field. At the heart of this algorithm lies an innovative and robust trapdoor function that operates in the Galois Field and is responsible for the superior speed and security offered by it. Prime number theorem plays a fundamental role in this system, to keep unwelcome adversaries at bay. This is a …

On Communication For Distributed Babai Point Computation, Maiara F. Bollauf, Vinay A. Vaishampayan, Sueli I.R. Costa

Publications and Research

We present a communication-efficient distributed protocol for computing the Babai point, an approximate nearest point for a random vector X∈Rn in a given lattice. We show that the protocol is optimal in the sense that it minimizes the sum rate when the components of X are mutually independent. We then investigate the error probability, i.e. the probability that the Babai point does not coincide with the nearest lattice point, motivated by the fact that for some cases, a distributed algorithm for finding the Babai point is sufficient for finding the nearest lattice point itself. Two different probability models for X …

Decoding Clinical Biomarker Space Of Covid-19: Exploring Matrix Factorization-Based Feature Selection Methods, Farshad Saberi-Movahed, Mahyar Mohammadifard, Adel Mehrpooya, Mohammad Rezaei-Ravari, Kamal Berahmand, Mehrdad Rostami, Saeed Karami, Mohammad Najafzadeh, Davood Hajinezhad, Mina Jamshidi, Farshid Abedi, Mahtab Mohammadifard, Elnaz Farbod, Farinaz Safavi, Mohammadreza Dorvash, Shahrzad Vahedi, Mahdi Eftekhari, Farid Saberi-Movahed, Iman Tavassoly

Publications and Research

One of the most critical challenges in managing complex diseases like COVID-19 is to establish an intelligent triage system that can optimize the clinical decision-making at the time of a global pandemic. The clinical presentation and patients’ characteristics are usually utilized to identify those patients who need more critical care. However, the clinical evidence shows an unmet need to determine more accurate and optimal clinical biomarkers to triage patients under a condition like the COVID-19 crisis. Here we have presented a machine learning approach to find a group of clinical indicators from the blood tests of a set of COVID-19 …

Extending Import Detection Algorithms For Concept Import From Two To Three Biomedical Terminologies, Vipina K. Keloth, James Geller, Yan Chen, Julia Xu

Publications and Research

Background: While enrichment of terminologies can be achieved in different ways, filling gaps in the IS-A hierarchy backbone of a terminology appears especially promising. To avoid difficult manual inspection, we started a research program in 2014, investigating terminology densities, where the comparison of terminologies leads to the algorithmic discovery of potentially missing concepts in a target terminology. While candidate concepts have to be approved for import by an expert, the human effort is greatly reduced by algorithmic generation of candidates. In previous studies, a single source terminology was used with one target terminology.

Methods: In this paper, we are extending …

Philosophical Perspectives, Jochen Albrecht

Publications and Research

This entry follows in the footsteps of Anselin’s famous 1989 NCGIA working paper entitled “What is special about spatial?” (a report that is very timely again in an age when non-spatial data scientists are ignorant of the special characteristics of spatial data), where he outlines three unrelated but fundamental characteristics of spatial data. In a similar vein, I am going to discuss some philosophical perspectives that are internally unrelated to each other and could warrant individual entries in this Body of Knowledge. The first one is the notions of space and time and how they have evolved in …

An Optimized Encoding Algorithm For Systematic Polar Codes, Xiumin Wang, Zhihong Zhang, Jun Li, Yu Wang, Haiyan Cao, Zhengquan Li, Liang Shan

Publications and Research

Many different encoding algorithms for systematic polar codes (SPC) have been introduced since SPC was proposed in 2011. However, the number of the computing units of exclusive OR (XOR) has not been optimized yet. According to an iterative property of the generator matrix and particular lower triangular structure of the matrix, we propose an optimized encoding algorithm (OEA) of SPC that can reduce the number of XOR computing units compared with existing non-recursive algorithms. We also prove that this property of the generator matrix could extend to different code lengths and rates of the polar codes. Through the matrix segmentation …

Multiple Sclerosis Identification Based On Fractional Fourier Entropy And A Modified Jaya Algorithm, Shui-Hua Wang, Hong Cheng, Preetha Phillips, Yu-Dong Zhang

Publications and Research

Aim: Currently, identifying multiple sclerosis (MS) by human experts may come across the problem of “normal-appearing white matter”, which causes a low sensitivity. Methods: In this study, we presented a computer vision based approached to identify MS in an automatic way. This proposed method first extracted the fractional Fourier entropy map from a specified brain image. Afterwards, it sent the features to a multilayer perceptron trained by a proposed improved parameter-free Jaya algorithm. We used cost-sensitivity learning to handle the imbalanced data problem. Results: The 10 × 10-fold cross validation showed our method yielded a sensitivity of 97.40 ± 0.60%, …

Cryptosystems Using Subgroup Distortion, Indira Chatterji, Delaram Kahrobaei, Ni Yen Lu

Publications and Research

In this paper we propose cryptosystems based on subgroup distortion in hyperbolic groups. We also include concrete examples of hyperbolic groups as possible platforms.

The History Of Algorithmic Complexity, Audrey A. Nasar

Publications and Research

This paper provides a historical account of the development of algorithmic complexity in a form that is suitable to instructors of mathematics at the high school or undergraduate level. The study of algorithmic complexity, despite being deeply rooted in mathematics, is usually restricted to the computer science curriculum. By providing a historical account of algorithmic complexity through a mathematical lens, this paper aims to equip mathematics educators with the necessary background and framework for incorporating the analysis of algorithmic complexity into mathematics courses as early on as algebra or pre-calculus.

Nearest Neighbor Search With Strong Location Privacy, Stavros Papadopoulos, Spiridon Bakiras, Dimitris Papadias

Publications and Research

The tremendous growth of the Internet has significantly reduced the cost of obtaining and sharing information about individuals, raising many concerns about user privacy. Spatial queries pose an additional threat to privacy because the location of a query may be sufficient to reveal sensitive information about the querier. In this paper we focus on k nearest neighbor (kNN) queries and define the notion of strong location privacy, which renders a query indistinguishable from any location in the data space. We argue that previous work fails to support this property for arbitrary kNN search. Towards this end, we introduce methods that …

Flocking In The Time-Dissonance Plane, Adam James Wilson

Publications and Research

This paper describes a technique for the sonification of an idealized model of the flocking behavior of birds, fish, and insects. Flocking agents are represented by pitches that move through time to produce chords of variable dissonance. The objective of each agent is to move toward more consonant chord formations with other agents. The output of the sonification is intended to provide material for use in musical composition.

A Symbolic Sonification Of L-Systems, Adam James Wilson

Publications and Research

This paper describes a simple technique for the sonification of branching structures in plants. The example is intended to illustrate a qualitative definition of best practices for sonification aimed at the production of musical material. Visually manifest results of tree growth are modelled and subsequently mapped to pitch, time, and amplitude. Sample results are provided in symbolic music notation.

Classical And Quantum Algorithms For Finding Cycles, Jill Cirasella

Publications and Research

Quantum computing—so weird, so wonderful—inspires much speculation about the line between the possible and the impossible. (Of course, there is still unclarity about how “impossible” intractable problems are and about how “possible” quantum computers are.) This thesis takes a slightly different tack: instead of focusing on how to make the impossible possible, it focuses on how to make the possible easier.

More specifically, this paper discusses quantum algorithms for finding cycles in graphs, a problem for which polynomial-time classical algorithms already exist. It explains and compares the classical and quantum algorithms, and it introduces a few new algorithms and observations. …