Computer Sciences Commons^™

Fractals As Basis For Design And Critique, John Charles Driscoll

Dissertations and Theses

The design profession is responding to the complex systems represented by architecture and planning by increasingly incorporating the power of computer technology into the design process. This represents a paradigm shift, and requires that designers rise to the challenge of both embracing modern technologies to perform increasingly sophisticated tasks without compromising their objective to create meaningful and environmentally sensitive architecture. This dissertation investigated computer-based fractal tools applied within a traditional architectural charette towards a design process with the potential to address the complex issues architects and planners face today. We developed and presented an algorithm that draws heavily from fractal …

Identifying Relationships Of Interest In Complex Environments By Using Channel Theory, Andreas Bildstein, Junkang Feng

Communications of the IIMA

Complex environments show a high degree of dynamics caused by vital interactions between objects within those environments and alterations through which the set of objects and their characteristics within those environments go over time. Within this work, we show that we can tame the level of complexity in dynamic environments by identifying ‘relationships of interest’ between objects in such environments. To this end, we apply the theory of Information Flow, also known as Channel Theory, to the application area of smart manufacturing. We enhance the way how the Channel Theory has been applied so far by using an …

Efficient Distributed Reachability Querying Of Massive Temporal Graphs, Tianming Zhang, Yunjun Gao, Chen Lu, Wei Guo, Shiliang Pu, Baihua Zheng, Christian S. Jensen

Research Collection School Of Computing and Information Systems

Reachability computation is a fundamental graph functionality with a wide range of applications. In spite of this, little work has as yet been done on efficient reachability queries over temporal graphs, which are used extensively to model time-varying networks, such as communication networks, social networks, and transportation schedule networks. Moreover, we are faced with increasingly large real-world temporal networks that may be distributed across multiple data centers. This state of affairs motivates the paper's study of efficient reachability queries on distributed temporal graphs. We propose an efficient index, called Temporal Vertex Labeling (TVL), which is a labeling scheme for distributed …

Detecting Toxicity Triggers In Online Discussions, Hamad Bin Khalifa University, Haewoon Kwak

Research Collection School Of Computing and Information Systems

Despite the considerable interest in the detection of toxic comments, there has been little research investigating the causes -- i.e., triggers -- of toxicity. In this work, we first propose a formal definition of triggers of toxicity in online communities. We proceed to build an LSTM neural network model using textual features of comments, and then, based on a comprehensive review of previous literature, we incorporate topical and sentiment shift in interactions as features. Our model achieves an average accuracy of 82.5% of detecting toxicity triggers from diverse Reddit communities.

A Common Approach For Consumer And Provider Fairness In Recommendations, Dimitris Sacharidis, Kyriakos Mouratidis, Dimitrios Kleftogiannis

Research Collection School Of Computing and Information Systems

We present a common approach for handling consumer and provider fairness in recommendations. Our solution requires defining two key components, a classification of items and a target distribution, which together define the case of perfect fairness. This formulation allows distinct fairness concepts to be specified in a common framework. We further propose a novel reranking algorithm that optimizes for a desired trade-off between utility and fairness of a recommendation list.

A Machine Learning Model For Clustering Securities, Vanessa Torres, Travis Deason, Michael Landrum, Nibhrat Lohria

SMU Data Science Review

In this paper, we evaluate the self-declared industry classifications and industry relationships between companies listed on either the Nasdaq or the New York Stock Exchange (NYSE) markets. Large corporations typically operate in multiple industries simultaneously; however, for investment purposes they are classified as belonging to a single industry. This simple classification obscures the actual industries within which a company operates, and, therefore, the investment risks of that company.
By using Natural Language Processing (NLP) techniques on Security and Exchange Commission (SEC) filings, we obtained self-defined industry classifications per company. Using clustering techniques such as Hierarchical Agglomerative and k-means clustering we …

Machine Learning In Support Of Electric Distribution Asset Failure Prediction, Robert D. Flamenbaum, Thomas Pompo, Christopher Havenstein, Jade Thiemsuwan

SMU Data Science Review

In this paper, we present novel approaches to predicting as- set failure in the electric distribution system. Failures in overhead power lines and their associated equipment in particular, pose significant finan- cial and environmental threats to electric utilities. Electric device failure furthermore poses a burden on customers and can pose serious risk to life and livelihood. Working with asset data acquired from an electric utility in Southern California, and incorporating environmental and geospatial data from around the region, we applied a Random Forest methodology to predict which overhead distribution lines are most vulnerable to fail- ure. Our results provide evidence …

Machine Learning Predicts Aperiodic Laboratory Earthquakes, Olha Tanyuk, Daniel Davieau, Charles South, Daniel W. Engels

SMU Data Science Review

In this paper we find a pattern of aperiodic seismic signals that precede earthquakes at any time in a laboratory earthquake’s cycle using a small window of time. We use a data set that comes from a classic laboratory experiment having several stick-slip displacements (earthquakes), a type of experiment which has been studied as a simulation of seismologic faults for decades. This data exhibits similar behavior to natural earthquakes, so the same approach may work in predicting the timing of them. Here we show that by applying random forest machine learning technique to the acoustic signal emitted by a laboratory …

Texture-Based Deep Neural Network For Histopathology Cancer Whole Slide Image (Wsi) Classification, Nelson Zange Tsaku

Master of Science in Computer Science Theses

Automatic histopathological Whole Slide Image (WSI) analysis for cancer classification has been highlighted along with the advancements in microscopic imaging techniques. However, manual examination and diagnosis with WSIs is time-consuming and tiresome. Recently, deep convolutional neural networks have succeeded in histopathological image analysis. In this paper, we propose a novel cancer texture-based deep neural network (CAT-Net) that learns scalable texture features from histopathological WSIs. The innovation of CAT-Net is twofold: (1) capturing invariant spatial patterns by dilated convolutional layers and (2) Reducing model complexity while improving performance. Moreover, CAT-Net can provide discriminative texture patterns formed on cancerous regions of histopathological …

Inspect: Iterated Local Search For Solving Path Conditions, Fuxiang Chen, Aldy Gunawan, David Lo, Sunghun Kim

Research Collection School Of Computing and Information Systems

Automated test case generation is attractive as it can reduce developer workload. To generate test cases, many Symbolic Execution approaches first produce Path Conditions (PCs), a set of constraints, and pass them to a Satisfiability Modulo Theories (SMT) solver. Despite numerous prior studies, automated test case generation by Symbolic Execution is still slow, partly due to SMT solvers’ high computationally complexity. We introduce InSPeCT, a Path Condition solver, that leverages elements of ILS (Iterated Local Search) and Tabu List. ILS is not computational intensive and focuses on generating solutions in search spaces while Tabu List prevents the use of previously …

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 …

Formally Designing And Implementing Cyber Security Mechanisms In Industrial Control Networks., Mehdi Sabraoui

Electronic Theses and Dissertations

This dissertation describes progress in the state-of-the-art for developing and deploying formally verified cyber security devices in industrial control networks. It begins by detailing the unique struggles that are faced in industrial control networks and why concepts and technologies developed for securing traditional networks might not be appropriate. It uses these unique struggles and examples of contemporary cyber-attacks targeting control systems to argue that progress in securing control systems is best met with formal verification of systems, their specifications, and their security properties. This dissertation then presents a development process and identifies two technologies, TLA+ and seL4, that can be …

State-Of-The-Art Solution Techniques For Op And Top, Pieter Vansteenwegen, Aldy Gunawan

Research Collection School Of Computing and Information Systems

Definitions and mathematical models of the OP and the TOP were introduced in Chaps. 2 and 3. In this chapter, we will discuss the benchmark instances and state-of-the-art solution techniques for both OP and TOP. Some illustrations of benchmark instances and solutions are included in order to increase the understanding in the difficulty of solving this problem and to provide additional insights. The solution techniques are classified into two different categories: exact approaches and (meta)heuristic techniques.

State-Of-The-Art Solution Techniques For Optw And Toptw, Pieter Vansteenwegen, Aldy Gunawan

Research Collection School Of Computing and Information Systems

In Chaps. 2 and 3, different orienteering problems (or routing problems with profits) were introduced. The single vehicle problems were discussed in Chap. 2: the profitable tour problem (PTP), the prize-collecting traveling salesperson problem (PCTSP), and the orienteering problem (OP). The multi vehicle problems were discussed in Chap. 3: the team orienteering problem (TOP) and the team orienteering problem with time windows (TOPTW). For discussing the state-of-the-art solution techniques for these different orienteering problems in Chaps. 4, 5, and 6, the problems will be classified differently, based on the similarities between the solution techniques. Therefore, the PTP and PCTSP are …

Faster First-Order Methods For Stochastic Non-Convex Optimization On Riemannian Manifolds, Pan Zhou, Xiao-Tong Yuan, Shuicheng Yan, Jiashi Feng

Research Collection School Of Computing and Information Systems

First-order non-convex Riemannian optimization algorithms have gained recent popularity in structured machine learning problems including principal component analysis and low-rank matrix completion. The current paper presents an efficient Riemannian Stochastic Path Integrated Differential EstimatoR (R-SPIDER) algorithm to solve the finite-sum and online Riemannian non-convex minimization problems. At the core of R-SPIDER is a recursive semi-stochastic gradient estimator that can accurately estimate Riemannian gradient under not only exponential mapping and parallel transport, but also general retraction and vector transport operations. Compared with prior Riemannian algorithms, such a recursive gradient estimation mechanism endows R-SPIDER with higher computational efficiency in first-order oracle complexity. …

Simulated Annealing For The Multi-Vehicle Cyclic Inventory Routing Problem, Aldy Gunawan, Vincent F. Yu, Audrey Tedja Widjaja, Pieter Vansteenwegen

Research Collection School Of Computing and Information Systems

This paper studies the Multi-Vehicle Cyclic Inventory Routing Problem (MV-CIRP) as the extension of the Single-Vehicle CIRP (SV-CIRP). The objective is to minimize both distribution and inventory costs at the customers and to maximize the collected rewards simultaneously. The problem is treated as a single objective optimization problem. A subset of customers is selected for each vehicle including the quantity to be delivered to each customer. For each vehicle, a cyclic distribution plan is developed. We construct a mathematical programming model and propose a simulated annealing (SA) metaheuristic for solving both SV-CIRP and MV-CIRP. For SV-CIRP, experimental results on benchmark …

Definitions And Mathematical Models Of Single Vehicle Routing Problems With Profits, Pieter Vansteenwegen, Aldy Gunawan

Research Collection School Of Computing and Information Systems

In this chapter, single vehicle routing problems with profits are introduced anddefined. Three variants are considered: the profitable tour problem, the prizecollecting traveling salesperson problem, and the orienteering problem. The difference between these variants is the way in which the profit and the travel cost, mostlydistance or time, are modeled. Profit and travel cost can be modeled as (part of) theobjective or as a constraint. All three problems differ from the well-known travelingsalesperson problem, for which the only objective is to find the shortest route to visitall customers in a given set. In vehicle routing problems with profits, some customerswill …

Applications Of The Op, Pieter Vansteenwegen, Aldy Gunawan

Research Collection School Of Computing and Information Systems

In recent years, we observe from literature that the VRP and OP, including their variants, have been used to model many different planning and scheduling problems from practice, such as the routing of technicians, athlete recruitment, or military applications. Recently, other practical applications, such as the tourist trip design problem, the mobile crowdsourcing problem, the smuggler search problem, the wildfire routing problem, and the integration of vehicle routing, inventory management, and customer selection problems, have been studied and use the OP as a basic model. In this chapter, various practical applications will be discussed in more detail. We will describe …

Bidding Mechanisms In Graph Games, Guy Avni, Thomas A. Henzinger, Dorde Zikelic

Research Collection School Of Computing and Information Systems

In two-player games on graphs, the players move a token through a graph to produce a finite or infinite path, which determines the qualitative winner or quantitative payoff of the game. We study bidding games in which the players bid for the right to move the token. Several bidding rules were studied previously. In Richman bidding, in each round, the players simultaneously submit bids, and the higher bidder moves the token and pays the other player. Poorman bidding is similar except that the winner of the bidding pays the “bank” rather than the other player. Taxman bidding spans the spectrum …

Who Should Pay The Cost: A Game-Theoretic Model For Government Subsidized Investments To Improve National Cybersecurity, Xinrun Wang, Bo An, Hau Chan

Research Collection School Of Computing and Information Systems

Due to the recent cyber attacks, cybersecurity is becoming more critical in modern society. A single attack (e.g., WannaCry ransomware attack) can cause as much as $4 billion in damage. However, the cybersecurity investment by companies is far from satisfactory. Therefore, governments (e.g., in the UK) launch grants and subsidies to help companies to boost their cybersecurity to create a safer national cyber environment. The allocation problem is hard due to limited subsidies and the interdependence between self-interested companies and the presence of a strategic cyber attacker. To tackle the government's allocation problem, we introduce a Stackelberg game-theoretic model where …

Suitability Of Finite State Automata To Model String Constraints In Probablistic Symbolic Execution, Andrew Harris

Boise State University Theses and Dissertations

Probabilistic Symbolic Execution (PSE) extends Symbolic Execution (SE), a path-sensitive static program analysis technique, by calculating the probabilities with which program paths are executed. PSE relies on the ability of the underlying symbolic models to accurately represent the execution paths of the program as the collection of input values following these paths. While researchers established PSE for numerical data types, PSE for complex data types such as strings is a novel area of research.

For string data types SE tools commonly utilize finite state automata to represent a symbolic string model. Thus, PSE inherits from SE automata-based symbolic string models …

Quantum Algorithms With Applications To Simulating Physical Systems, Anirban Ch Narayan Chowdhury

Physics & Astronomy ETDs

The simulation of quantum physical systems is expected to be an important application for quantum computers. The work presented in this dissertation aims to improve the resource requirements of quantum computers for solving simulation problems, by providing both novel quantum algorithms and improved implementations of existing ones. I present three main results that cover diverse aspects of simulation including equilibrium physics, the preparation of useful quantum states, and simulations based on classical stochastic processes. The results rely on established quantum algorithms and other recent techniques which I review. My first original contribution is a new quantum algorithm to sample from …

Mathematical And Computer Simulation Of The Processes Of Two-Phase Joint Gas Filtration And Water In A Porous Environment, Elmira Nazirova

Bulletin of TUIT: Management and Communication Technologies

A mathematical model, methods and algorithms for the numerical solution of problems of joint gas-water filtration in porous media are considered. The mathematical model of the process of non-stationary joint gas-water filtration in a porous medium is described by a system of nonlinear differential equations of parabolic type. In the numerical solution of the boundary value problem of gas displacement by water in a porous medium, the differential sweeping method is used for systems of differential-difference equations. The system of differential-difference equations with respect to the gas pressure function is nonlinear, therefore, an iterative method is used for it, based …

Adaboost‑Based Security Level Classifcation Of Mobile Intelligent Terminals, Feng Wang, Houbing Song, Dingde Jiang, Hong Wen

Publications

With the rapid development of Internet of Things, massive mobile intelligent terminals are ready to access edge servers for real-time data calculation and interaction. However, the risk of private data leakage follows simultaneously. As the administrator of all intelligent terminals in a region, the edge server needs to clarify the ability of the managed intelligent terminals to defend against malicious attacks. Therefore, the security level classification for mobile intelligent terminals before accessing the network is indispensable. In this paper, we firstly propose a safety assessment method to detect the weakness of mobile intelligent terminals. Secondly, we match the evaluation results …

Some Theoretical Links Between Shortest Path Filters And Minimum Spanning Tree Filters, Sravan Danda, Aditya Challa, B. S.Daya Sagar, Laurent Najman

Journal Articles

Edge-aware filtering is an important pre-processing step in many computer vision applications. In the literature, there exist several versions of collaborative edge-aware filters based on spanning trees and shortest path heuristics which work well in practice. For instance, tree filter (TF) which is recently proposed based on a minimum spanning tree (MST) heuristic yields promising results in many filtering applications. However, links between the tree-based filters and shortest path-based filters are faintly explored. In this article, we introduce an edge-aware generalization of the TF termed as UMST filter based on a subgraph generated by edges of all MSTs. The major …

Identifying Depression In The National Health And Nutrition Examination Survey Data Using A Deep Learning Algorithm, Jihoon Oh, Kyongsik Yun, Uri Maoz, Tae-Suk Kim, Jeong-Ho Chae

Psychology Faculty Articles and Research

Background

As depression is the leading cause of disability worldwide, large-scale surveys have been conducted to establish the occurrence and risk factors of depression. However, accurately estimating epidemiological factors leading up to depression has remained challenging. Deep-learning algorithms can be applied to assess the factors leading up to prevalence and clinical manifestations of depression.

Methods

Customized deep-neural-network and machine-learning classifiers were assessed using survey data from 19,725 participants from the NHANES database (from 1999 through 2014) and 4949 from the South Korea NHANES (K-NHANES) database in 2014.

Results

A deep-learning algorithm showed area under the receiver operating characteristic curve (AUCs) …

Wing Design Using Sail, Leonid Scott

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

In engineering spaces where modeling is difficult, engineers seek a variety of well performing solutions in order to concentrate resources on promising areas of the problem space. We call this process illumination. Gaire et al have designed an algorithm specifically for illumination of problem spaces where the underlying model is computationally expensive. This algorithm, Surrogate Assisted Illumination (SAIL) uses an evolutionary algorithm called MAP-Elites to do illumination. However, SAIL introduces a Gaussian process to simulate the computationally expensive model, and Bayesian optimization for quality control of the Gaussian process. SAIL has demonstrated potential for finding a variety of well performing …

Tools To Improve Interruption Management, Matthew R. Munns

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

Interruptions carry a high cost, especially to software developers. To prevent unnecessary interruptions, several technologies are being explored that can help manage the timing of interruptions, such as displaying the interruptibility of a worker to their peers. Relatively simple algorithms utilizing computer interaction data have been created and used successfully in the workplace, while technology using bio-metric emotion recognition to detect the interruptibility of a user is also being developed.

Using Forensics To Introduce Ir Spectroscopy & Molecular Modeling, Joseph T. Golab

Faculty Publications & Research

A student activity is reported that analyzes “medical evidence” with experimental and computational methods. The lesson demonstrates benefits of solving practical problems with integrated tools.

Early Information Access To Alleviate Emergency Department Congestion, Anjee Gorkhali

Theses and Dissertations in Business Administration

Alleviating Emergency Department (ED) congestion results in shorter hospital stay which not only reduces the cost of medical procedure but also increase the hospital performance. Length of patient stay is used to determine the hospital performance. Organization Information Processing (OIPT) Theory is used to explain the impact of information access and availability on the information processing need and ability of a hospital. Technical devices such as RFID that works as “Auto Identification tags” is suggested to increase the information availability as well as the information processing capability of the hospitals. This study suggests that the OIPT needs to be further …