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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 ...


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 ...


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 ...


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 ...


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 ...


Analysis Of Students’ Multi-Representation Ability In Augmented Reality-Assisted Learning, Sri Jumini, Edy Cahyono, Muhamad Miftakhul Falah 2021 Universitas Sains Al-Qur'an of Central Java in Wonosobo

Analysis Of Students’ Multi-Representation Ability In Augmented Reality-Assisted Learning, Sri Jumini, Edy Cahyono, Muhamad Miftakhul Falah

Library Philosophy and Practice (e-journal)

Not all learning sources can directly and cheaply be presented, so augmented reality media is needed to be applied to students with various talents and intelligence. This study aims to analyze students’ multi-representation ability through the use of augmented reality media. The research method was carried out through pre-experiment with one group posttest only design. Test question items were given to see the students’ multi-representation ability. Data analysis was carried out through the percentage of the number of students achieving test scores of more than or equal to 80 on a scale of 100. The results showed that 88% (28 ...


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 ...


Applying Emotional Analysis For Automated Content Moderation, John Shelnutt 2021 University of Arkansas, Fayetteville

Applying Emotional Analysis For Automated Content Moderation, John Shelnutt

Computer Science and Computer Engineering Undergraduate Honors Theses

The purpose of this project is to explore the effectiveness of emotional analysis as a means to automatically moderate content or flag content for manual moderation in order to reduce the workload of human moderators in moderating toxic content online. In this context, toxic content is defined as content that features excessive negativity, rudeness, or malice. This often features offensive language or slurs. The work involved in this project included creating a simple website that imitates a social media or forum with a feed of user submitted text posts, implementing an emotional analysis algorithm from a word emotions dataset, designing ...


City Goers: An Exploration Into Creating Seemingly Intelligent A.I. Systems, Matthew Brooke 2021 University of Arkansas, Fayetteville

City Goers: An Exploration Into Creating Seemingly Intelligent A.I. Systems, Matthew Brooke

Computer Science and Computer Engineering Undergraduate Honors Theses

Artificial Intelligence systems have come a long way over the years. One particular application of A.I. is its incorporation in video games. A key goal of creating an A.I. system in a video game is to convey a level of intellect to the player. During playtests for Halo: Combat Evolved, the developers at Bungie noticed that players deemed tougher enemies as more intelligent than weaker ones, despite the fact that there were no differences in behavior in the enemies. The tougher enemies provided a greater illusion of intelligence to the players. Inspired by this, I set out to ...


Simplifying The Creation Of Virtual Topologies Using Mpi Sessions, Tom Herschberg 2021 University of Tennessee at Chattanooga

Simplifying The Creation Of Virtual Topologies Using Mpi Sessions, Tom Herschberg

Honors Theses

As supercomputers have approached exascale performance, several scalability issues have emerged within MPI. These issues arise because MPI includes all processes in the World model, which consumes unacceptable amounts of time and resources at large scale. The Sessions model was developed to combat these issues by removing the requirement of MPI_COMM_WORLD, which provides a more scalable method of creating communication groups in large jobs. Additionally, the Sessions model enables the creation of virtual topologies directly from sets of processes allocated to the execution of a parallel application rather than building virtual topologies from an existing communication group such as MPI_COMM_WORLD ...


Attendio: Attendance Tracking Made Simple, Benjamin L. Greenberg, Spencer L. Howell, Tucker R. Miles, Vicki Tang, Daniel N. Troutman 2021 University of Tennessee, Knoxville

Attendio: Attendance Tracking Made Simple, Benjamin L. Greenberg, Spencer L. Howell, Tucker R. Miles, Vicki Tang, Daniel N. Troutman

Chancellor’s Honors Program Projects

No abstract provided.


App Development For Wearable Sensors, Connor Pittman, Christopher Chappie, Patrick A. Tetreault 2021 University of Southern Maine

App Development For Wearable Sensors, Connor Pittman, Christopher Chappie, Patrick A. Tetreault

Thinking Matters Symposium

The objective of this research project was to create a wearable device that monitors bodily functions for the user to view on their smartphone. Sensor data is processed using the Arduino Nano 33 BLE microcontroller. The sensors used in this project include: proximity, temperature, humidity, heart rate, pressure, and skin impedance. This project takes advantage of the Arduino's Bluetooth low energy (BLE) capabilities so that all the data can be transmitted to a smartphone. This presentation shows the challenges faced during the project and how they were overcome. Some of these challenges include: programming, how heart rate sensors work ...


Student Academic Conference, Caitlin Brooks 2021 Minnesota State University Moorhead

Student Academic Conference, Caitlin Brooks

Student Academic Conference

No abstract provided.


Exploring Ai And Multiplayer In Java, Ronni Kurtzhals 2021 Minnesota State University Moorhead

Exploring Ai And Multiplayer In Java, Ronni Kurtzhals

Student Academic Conference

I conducted research into three topics: artificial intelligence, package deployment, and multiplayer servers in Java. This research came together to form my project presentation on the implementation of these topics, which I felt accurately demonstrated the various things I have learned from my courses at Moorhead State University. Several resources were consulted throughout the project, including the work of W3Schools and StackOverflow as well as relevant assignments and textbooks from previous classes. I found this project relevant to computer science and information systems for several reasons, such as the AI component and use of SQL data tables; but it was ...


Poker Chip Calculator Application, Ryan Illies 2021 Minnesota State University Moorhead

Poker Chip Calculator Application, Ryan Illies

Student Academic Conference

Application to help start up in person poker games with friends.


Automated Evolution Of Feature Logging Statement Levels Using Git Histories And Degree Of Interest, Yiming Tang, Allan Spektor, Raffi Khatchadourian, Mehdi Bagherzadeh 2021 CUNY Graduate Center

Automated Evolution Of Feature Logging Statement Levels Using Git Histories And Degree Of Interest, Yiming Tang, Allan Spektor, Raffi Khatchadourian, Mehdi Bagherzadeh

Publications and Research

Logging—used for system events and security breaches to more informational yet essential aspects of software features—is pervasive. Given the high transactionality of today’s software, logging effectiveness can be reduced by information overload. Log levels help alleviate this problem by correlating a priority to logs that can be later filtered. As software evolves, however, levels of logs documenting surrounding feature implementations may also require modification as features once deemed important may have decreased in urgency and vice-versa. We present an automated approach that assists developers in evolving levels of such (feature) logs. The approach, based on mining Git ...


Best Practices In Industry And Cse Senior Design, Conner Hallett 2021 University of Nebraska - Lincoln

Best Practices In Industry And Cse Senior Design, Conner Hallett

Honors Theses, University of Nebraska-Lincoln

The widespread use of Agile practices in the software development industry creates the need for new college graduates to be adept in Agile processes and teams. The University of Nebraska-Lincoln’s Computer Science and Engineering (CSE) Senior Design courses gives students an introduction to such processes, but is met with many challenges in doing so, such as time constraints and student inexperience. Following a detailed look at the Scrum Agile framework and its expanded practices in industry, potential improvements for CSE Senior Design’s practice of Agile are suggested. These include the creation of resource forums for students to accelerate ...


Proximity-Based Video Communication With Cocktailparty, Addison Fabry, William Heffernan, Andrew Shroyer 2021 University of South Carolina - Columbia

Proximity-Based Video Communication With Cocktailparty, Addison Fabry, William Heffernan, Andrew Shroyer

Senior Theses

CocktailParty is a video communication application designed to uniquely and efficiently solve the problems faced by traditional online video communication. The proposal for this start-up project was accepted in August 2020. CocktailParty enables users to join a video chat room overlayed on top of a virtual house, in which each user can move their own video feed around the house. Each room in each house layout hosts a different video call, allowing users to easily host large virtual gatherings that facilitate multiple conversations taking place simultaneously. This functionality makes important steps towards effective simulation of the real-life gathering experience.


Practical Server-Side Wifi-Based Indoor Localization: Addressing Cardinality & Outlier Challenges For Improved Occupancy Estimation, Anuradha RAVI, Archan MISRA 2021 Singapore Management University

Practical Server-Side Wifi-Based Indoor Localization: Addressing Cardinality & Outlier Challenges For Improved Occupancy Estimation, Anuradha Ravi, Archan Misra

Research Collection School Of Computing and Information Systems

Server-side WiFi-based indoor localization offers a compelling approach for passive occupancy estimation (i.e., without requiring active participation by client devices, such as smartphones carried by visitors), but is known to suffer from median error of 6–8 meters. By analyzing the characteristics of an operationally-deployed, WiFi-based passive indoor location system, based on the classical RADAR algorithm, we identify and tackle 2 practical challenges for accurate individual device localization. The first challenge is the low-cardinality issue, whereby only the associated AP generates sufficiently frequent RSSI reports, causing a client to experience large localization error due to the absence of sufficient ...


On-Device Deep Learning Inference For System-On-Chip (Soc) Architectures, Tom Springer, Elia Eiroa-Lledo, Elizabeth Stevens, Erik Linstead 2021 Chapman University

On-Device Deep Learning Inference For System-On-Chip (Soc) Architectures, Tom Springer, Elia Eiroa-Lledo, Elizabeth Stevens, Erik Linstead

Engineering Faculty Articles and Research

As machine learning becomes ubiquitous, the need to deploy models on real-time, embedded systems will become increasingly critical. This is especially true for deep learning solutions, whose large models pose interesting challenges for target architectures at the “edge” that are resource-constrained. The realization of machine learning, and deep learning, is being driven by the availability of specialized hardware, such as system-on-chip solutions, which provide some alleviation of constraints. Equally important, however, are the operating systems that run on this hardware, and specifically the ability to leverage commercial real-time operating systems which, unlike general purpose operating systems such as Linux, can ...


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