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Exposing And Fixing Causes Of Inconsistency And Nondeterminism In Clustering Implementations, Xin Yin 2021 New Jersey Institute of Technology

Exposing And Fixing Causes Of Inconsistency And Nondeterminism In Clustering Implementations, Xin Yin

Dissertations

Cluster analysis aka Clustering is used in myriad applications, including high-stakes domains, by millions of users. Clustering users should be able to assume that clustering implementations are correct, reliable, and for a given algorithm, interchangeable. Based on observations in a wide-range of real-world clustering implementations, this dissertation challenges the aforementioned assumptions.This dissertation introduces an approach named SmokeOut that uses differential clustering to show that clustering implementations suffer from nondeterminism and inconsistency: on a given input dataset and using a given clustering algorithm, clustering outcomes and accuracy vary widely between (1) successive runs of the same toolkit, i.e., nondeterminism ...


Taxthemis: Interactive Mining And Exploration Of Suspicious Tax Evasion Group, Yating LIN, Kamkwai WONG, Yong WANG, Rong ZHANG, Bo DONG, Huamin QU, Qinghua ZHENG 2021 Singapore Management University

Taxthemis: Interactive Mining And Exploration Of Suspicious Tax Evasion Group, Yating Lin, Kamkwai Wong, Yong Wang, Rong Zhang, Bo Dong, Huamin Qu, Qinghua Zheng

Research Collection School Of Computing and Information Systems

Tax evasion is a serious economic problem for many countries, as it can undermine the government’s tax system and lead to an unfair business competition environment. Recent research has applied data analytics techniques to analyze and detect tax evasion behaviors of individual taxpayers. However, they have failed to support the analysis and exploration of the related party transaction tax evasion (RPTTE) behaviors (e.g., transfer pricing), where a group of taxpayers is involved. In this paper, we present TaxThemis, an interactive visual analytics system to help tax officers mine and explore suspicious tax evasion groups through analyzing heterogeneous tax-related ...


Qlens: Visual Analytics Of Multi-Step Problem-Solving Behaviors For Improving Question Design, Meng XIA, Reshika P. VELUMANI, Yong WANG, Huamin QU, Xiaojuan MA 2021 Singapore Management University

Qlens: Visual Analytics Of Multi-Step Problem-Solving Behaviors For Improving Question Design, Meng Xia, Reshika P. Velumani, Yong Wang, Huamin Qu, Xiaojuan Ma

Research Collection School Of Computing and Information Systems

With the rapid development of online education in recent years, there has been an increasing number of learning platforms that provide students with multi-step questions to cultivate their problem-solving skills. To guarantee the high quality of such learning materials, question designers need to inspect how students’ problem-solving processes unfold step by step to infer whether students’ problem-solving logic matches their design intent. They also need to compare the behaviors of different groups (e.g., students from different grades) to distribute questions to students with the right level of knowledge. The availability of fine-grained interaction data, such as mouse movement trajectories ...


Visual Analysis Of Discrimination In Machine Learning, Qianwen WANG, Zhenghua XU, Zhutian CHEN, Yong WANG, Yong WANG, Huamin Qu 2021 Singapore Management University

Visual Analysis Of Discrimination In Machine Learning, Qianwen Wang, Zhenghua Xu, Zhutian Chen, Yong Wang, Yong Wang, Huamin Qu

Research Collection School Of Computing and Information Systems

The growing use of automated decision-making in critical applications, such as crime prediction and college admission, has raised questions about fairness in machine learning. How can we decide whether different treatments are reasonable or discriminatory? In this paper, we investigate discrimination in machine learning from a visual analytics perspective and propose an interactive visualization tool, DiscriLens, to support a more comprehensive analysis. To reveal detailed information on algorithmic discrimination, DiscriLens identifies a collection of potentially discriminatory itemsets based on causal modeling and classification rules mining. By combining an extended Euler diagram with a matrix-based visualization, we develop a novel set ...


Tradao: A Visual Analytics System For Trading Algorithm Optimization, Ka Wing TSANG, Haotian LI, Fuk Ming LAM, Yifan MU, Yong WANG, Huamin QU 2021 Singapore Management University

Tradao: A Visual Analytics System For Trading Algorithm Optimization, Ka Wing Tsang, Haotian Li, Fuk Ming Lam, Yifan Mu, Yong Wang, Huamin Qu

Research Collection School Of Computing and Information Systems

With the wide applications of algorithmic trading, it has become critical for traders to build a winning trading algorithm to beat the market. However, due to the lack of efficient tools, traders mainly rely on their memory to manually compare the algorithm instances of a trading algorithm and further select the best trading algorithm instance for the real trading deployment. We work closely with industry practitioners to discover and consolidate user requirements and develop an interactive visual analytics system for trading algorithm optimization. Structured expert interviews are conducted to evaluateTradAOand a representative case study is documented for illustrating the system ...


Splash: Learnable Activation Functions For Improving Accuracy And Adversarial Robustness, Mohammadamin Tavakoli, Forest Agostinelli, Pierre Baldi 2021 University of California, Irvine

Splash: Learnable Activation Functions For Improving Accuracy And Adversarial Robustness, Mohammadamin Tavakoli, Forest Agostinelli, Pierre Baldi

Publications

We introduce SPLASH units, a class of learnable activation functions shown to simultaneously improve the accuracy of deep neural networks while also improving their robustness to adversarial attacks. SPLASH units have both a simple parameterization and maintain the ability to approximate a wide range of non-linear functions. SPLASH units are: (1) continuous; (2) grounded (f(0)=0"); (3) use symmetric hinges; and (4) their hinges are placed at fixed locations which are derived from the data (i.e. no learning required). Compared to nine other learned and fixed activation functions, including ReLU and its variants, SPLASH units show superior performance ...


Hierarchical Mapping For Crosslingual Word Embedding Alignment, Ion Madrazo Azpiazu, Maria Soledad Pera 2021 Boise State University

Hierarchical Mapping For Crosslingual Word Embedding Alignment, Ion Madrazo Azpiazu, Maria Soledad Pera

Computer Science Faculty Publications and Presentations

The alignment of word embedding spaces in different languages into a common crosslingual space has recently been in vogue. Strategies that do so compute pairwise alignments and then map multiple languages to a single pivot language (most often English). These strategies, however, are biased towards the choice of the pivot language, given that language proximity and the linguistic characteristics of the target language can strongly impact the resultant crosslingual space in detriment of topologically distant languages. We present a strategy that eliminates the need for a pivot language by learning the mappings across languages in a hierarchicalway. Experiments demonstrate that ...


Blockchain For Automotive: An Insight Towards The Ipfs Blockchain-Based Auto Insurance Sector, Nishara Nizamuddin, Ahed Abugabah 2021 Zayed University

Blockchain For Automotive: An Insight Towards The Ipfs Blockchain-Based Auto Insurance Sector, Nishara Nizamuddin, Ahed Abugabah

All Works

The advancing technology and industrial revolution have taken the automotive industry by storm in recent times. The auto sector’s constantly growing demand has paved the way for the automobile sector to embrace new technologies and disruptive innovations. The multi-trillion dollar, complex auto insurance sector is still stuck in the regulations of the past. Most of the customers still contact the insurance company by phone to buy new policies and process existing insurance claims. The customers still face the risk of fraudulent online brokers, as policies are mostly signed and processed on papers which often require human supervision, with a ...


An Empirical Study Of Refactorings And Technical Debt In Machine Learning Systems, Yiming Tang, Raffi T. Khatchadourian, Mehdi Bagherzadeh, Rhia Singh, Ajani Stewart, Anita Raja 2021 CUNY Graduate Center

An Empirical Study Of Refactorings And Technical Debt In Machine Learning Systems, Yiming Tang, Raffi T. Khatchadourian, Mehdi Bagherzadeh, Rhia Singh, Ajani Stewart, Anita Raja

Publications and Research

Machine Learning (ML), including Deep Learning (DL), systems, i.e., those with ML capabilities, are pervasive in today’s data-driven society. Such systems are complex; they are comprised of ML models and many subsystems that support learning processes. As with other complex systems, ML systems are prone to classic technical debt issues, especially when such systems are long-lived, but they also exhibit debt specific to these systems. Unfortunately, there is a gap of knowledge in how ML systems actually evolve and are maintained. In this paper, we fill this gap by studying refactorings, i.e., source-to-source semantics-preserving program transformations, performed ...


2vt: Visions, Technologies, And Visions Of Technologies For Understanding Human Scale Spaces, Ville Paanen, Piia Markkanen, Jonas Oppenlaender, Haider Akmal, Lik Hang Lee, Ava Fatah Gen Schieck, John Dunham, Konstantinos Papangelis, Nicolas Lalone, Niels Van Berkel, Jorge Goncalves, Simo Hosio 2021 University of Oulu

2vt: Visions, Technologies, And Visions Of Technologies For Understanding Human Scale Spaces, Ville Paanen, Piia Markkanen, Jonas Oppenlaender, Haider Akmal, Lik Hang Lee, Ava Fatah Gen Schieck, John Dunham, Konstantinos Papangelis, Nicolas Lalone, Niels Van Berkel, Jorge Goncalves, Simo Hosio

Presentations and other scholarship

Spatial experience is an important subject in various fields, and in HCI it has been mostly investigated in the urban scale. Research on human scale spaces has focused mostly on the personal meaning or aesthetic and embodied experiences in the space. Further, spatial experience is increasingly topical in envisioning how to build and interact with technologies in our everyday lived environments, particularly in so-called smart cities. This workshop brings researchers and practitioners from diverse fields to collaboratively discover new ways to understand and capture human scale spatial experience and envision its implications to future technological and creative developments in our ...


A Game Theoretical Analysis Of Non-Linear Blockchain System, Lin Chen, Lei Xu, Zhimin Gao, Ahmed Sunny, Keshav Kasichainula, Weidong Shi 2021 The University of Texas Rio Grande Valley

A Game Theoretical Analysis Of Non-Linear Blockchain System, Lin Chen, Lei Xu, Zhimin Gao, Ahmed Sunny, Keshav Kasichainula, Weidong Shi

Computer Science Faculty Publications and Presentations

Recent advances in the blockchain research have been made in two important directions. One is refined resilience analysis utilizing game theory to study the consequences of selfish behavior of users (miners), and the other is the extension from a linear (chain) structure to a non-linear (graphical) structure for performance improvements, such as IOTA and Graphcoin. The first question that comes to mind is what improvements that a blockchain system would see by leveraging these new advances. In this paper, we consider three major properties for a blockchain system: 𝛼-partial verification, scalability, and finality-duration. We establish a formal framework and prove ...


A Comparison Of Word Embedding Techniques For Similarity Analysis, Tyler Gerth 2021 University of Arkansas, Fayetteville

A Comparison Of Word Embedding Techniques For Similarity Analysis, Tyler Gerth

Computer Science and Computer Engineering Undergraduate Honors Theses

There have been a multitude of word embedding techniques developed that allow a computer to process natural language and compare the relationships between different words programmatically. In this paper, similarity analysis, or the testing of words for synonymic relations, is used to compare several of these techniques to see which performs the best. The techniques being compared all utilize the method of creating word vectors, reducing words down into a single vector of numerical values that denote how the word relates to other words that appear around it. In order to get a holistic comparison, multiple analyses were made, with ...


Analysis Of Theoretical And Applied Machine Learning Models For Network Intrusion Detection, Jonah Baron 2021 Dakota State University

Analysis Of Theoretical And Applied Machine Learning Models For Network Intrusion Detection, Jonah Baron

Masters Theses & Doctoral Dissertations

Network Intrusion Detection System (IDS) devices play a crucial role in the realm of network security. These systems generate alerts for security analysts by performing signature-based and anomaly-based detection on malicious network traffic. However, there are several challenges when configuring and fine-tuning these IDS devices for high accuracy and precision. Machine learning utilizes a variety of algorithms and unique dataset input to generate models for effective classification. These machine learning techniques can be applied to IDS devices to classify and filter anomalous network traffic. This combination of machine learning and network security provides improved automated network defense by developing highly-optimized ...


A Novel Dynamic Analysis Infrastructure To Instrument Untrusted Execution Flow Across User-Kernel Spaces, Jiaqi HONG, Xuhua DING 2021 Singapore Management University

A Novel Dynamic Analysis Infrastructure To Instrument Untrusted Execution Flow Across User-Kernel Spaces, Jiaqi Hong, Xuhua Ding

Research Collection School Of Computing and Information Systems

Code instrumentation and hardware based event trapping are two primary approaches used in dynamic malware analysis systems. In this paper, we propose a new approach called Execution Flow Instrumentation (EFI) where the analyzer execution flow is interleaved with the target flow in user- and kernel-mode, at junctures flexibly chosen by the analyzer at runtime. We also propose OASIS as the system infrastructure to realize EFI with virtues of the current two approaches, however without their drawbacks. Despite being securely and transparently isolated from the target, the analyzer introspects and controls it in the same native way as instrumentation code. We ...


Deep Learning And Optimization In Visual Target Tracking, Mohammadreza Javanmardi 2021 Utah State University

Deep Learning And Optimization In Visual Target Tracking, Mohammadreza Javanmardi

All Graduate Theses and Dissertations

Visual tracking is the process of estimating states of a moving object in a dynamic frame sequence. It has been considered as one of the most paramount and challenging topics in computer vision. Although numerous tracking methods have been introduced, developing a robust algorithm that can handle different challenges still remains unsolved. In this dissertation, we introduce four different trackers and evaluate their performance in terms of tracking accuracy on challenging frame sequences. Each of these trackers aims to address the drawbacks of their peers. The first developed method is called a structured multi-task multi-view tracking (SMTMVT) method, which exploits ...


Security Fatigue And Its Effects On Perceived Password Strength Among University Students, Chase Carroll 2021 University of Tennessee at Chattanooga

Security Fatigue And Its Effects On Perceived Password Strength Among University Students, Chase Carroll

Honors Theses

This study was performed with the goal of observing the effect, if any, that security fatigue has on students’ perceived strength of passwords. In doing so, it was hoped to find some correlation between the two that would help in establishing a measurable effect of the phenomenon in students. This could potentially aid organizational decision-makers, such as security policy writers and system admins, to make more informed decisions about implementing security measures. To achieve the goal of observing this fatigue and attempting to measure it, a survey was distributed to numerous students on the University of Tennessee at Chattanooga campus ...


An In-Depth Look At Learning Computer Language Syntax In A High-Repetition Practice Environment, Stephanie Gonzales 2021 Utah State University

An In-Depth Look At Learning Computer Language Syntax In A High-Repetition Practice Environment, Stephanie Gonzales

All Graduate Theses and Dissertations

Students in an introductory computer science course generally have difficulty producing code that follows the arrangement rules known as syntax. Phanon was created to help students practice writing correct code that follows the rules of syntax. Previous research suggests this tool has helped students improve their exam scores and strengthen effectiveness in the course. A study was conducted to observe students while they complete the syntax exercises to find meaningful patterns in the steps the students take to complete an exercise.

Evidence to support high intrinsic load was found throughout the study, which is a measure of difficulty learning a ...


Power Of Near-Peers: Conceptualizing And Testing A Near-Peer Mentoring Model In Raising Youths' Self-Efficacy In Computer Programming, Chongning Sun 2021 Utah State University

Power Of Near-Peers: Conceptualizing And Testing A Near-Peer Mentoring Model In Raising Youths' Self-Efficacy In Computer Programming, Chongning Sun

All Graduate Theses and Dissertations

Self-efficacy is seen as a barrier for youth, females in particular, to enter computer science (CS). In this study, I presented a near-peer mentoring model that focused on changing the mentee’s self-efficacy in CS. The present study had three objectives: (a) to design a near-peer mentoring model (i.e., a conceptual model) around the sources of information that influence self-efficacy, (b) to develop a mentor training model based on the conceptual model, and (c) to test the effectiveness of the training model in increasing mentees’ self-efficacy in the context of a summer App programming camp. The present study adopted ...


Data-Driven Recommendation Of Academic Options Based On Personality Traits, Aashish Ghimire 2021 Utah State University

Data-Driven Recommendation Of Academic Options Based On Personality Traits, Aashish Ghimire

All Graduate Theses and Dissertations

The choice of academic major and, subsequently, an academic institution has a massive effect on a person’s career. It not only determines their career path but their earning potential, professional happiness, etc. [1] About 40% of people who are admitted to a college do not graduate within six years. Yet, very limited resources are available for students to help make those decisions, and each guidance counselor is responsible for roughly 400 to 900 students across the United States. A tool to help these decisions would benefit students, parents, and guidance counselors.

Various research studies have shown that personality traits ...


Trust Models And Risk In The Internet Of Things, Jeffrey Hemmes 2021 Regis University

Trust Models And Risk In The Internet Of Things, Jeffrey Hemmes

Regis University Faculty Publications

The Internet of Things (IoT) is envisaged to be a large-scale, massively heterogeneous ecosystem of devices with varying purposes and capabilities. While architectures and frameworks have focused on functionality and performance, security is a critical aspect that must be integrated into system design. This work proposes a method of risk assessment of devices using both trust models and static capability profiles to determine the level of risk each device poses. By combining the concepts of trust and secure device fingerprinting, security mechanisms can be more efficiently allocated across networked IoT devices. Simultaneously, devices can be allowed a greater degree of ...


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