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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 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 ...


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 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 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 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 ...


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 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 ...


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 ...


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 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 ...


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 ...


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 ...


Towards A Framework For Certification Of Reliable Autonomous Systems, Michael Fisher, Viviana Mascardi, Kristin Yvonne Rozier, Bernd-Holger Schlingloff, Michael Winikoff, Neil Yorke-Smith 2021 University of Manchester

Towards A Framework For Certification Of Reliable Autonomous Systems, Michael Fisher, Viviana Mascardi, Kristin Yvonne Rozier, Bernd-Holger Schlingloff, Michael Winikoff, Neil Yorke-Smith

Aerospace Engineering Publications

A computational system is called autonomous if it is able to make its own decisions, or take its own actions, without human supervision or control. The capability and spread of such systems have reached the point where they are beginning to touch much of everyday life. However, regulators grapple with how to deal with autonomous systems, for example how could we certify an Unmanned Aerial System for autonomous use in civilian airspace? We here analyse what is needed in order to provide verified reliable behaviour of an autonomous system, analyse what can be done as the state-of-the-art in automated verification ...


Kennesaw State University Hpc Facilities And Resources, Tom Boyle, Ramazan Aygun 2021 Kennesaw State University

Kennesaw State University Hpc Facilities And Resources, Tom Boyle, Ramazan Aygun

Digital Commons Training Materials

The Kennesaw State University High Performance Computing (HPC) resources represent the University’s commitment to research computing. This resource contains verbiage for users of Kennesaw State University's HPC resources to include in their grants and publications.


Investigating The Adoption Of Hybrid Encrypted Cloud Data Deduplication With Game Theory, Xueqin LIANG, Zheng YAN, Robert H. DENG, Qinghu ZHENG 2021 Xidian University

Investigating The Adoption Of Hybrid Encrypted Cloud Data Deduplication With Game Theory, Xueqin Liang, Zheng Yan, Robert H. Deng, Qinghu Zheng

Research Collection School Of Information Systems

Encrypted data deduplication, along with different preferences in data access control, brings the birth of hybrid encrypted cloud data deduplication (H-DEDU for short). However, whether H-DEDU can be successfully deployed in practice has not been seriously investigated. Obviously, the adoption of H-DEDU depends on whether it can bring economic benefits to all stakeholders. But existing economic models of cloud storage fail to support H-DEDU due to complicated interactions among stakeholders. In this article, we establish a formal economic model of H-DEDU by formulating the utilities of all involved stakeholders, i.e., data holders, data owners, and Cloud Storage Providers (CSPs ...


3d Object Detection, Instance Segmentation And Classification From 3d Range And 2d Color Images, Xiaoke Shen 2021 The Graduate Center, City University of New York

3d Object Detection, Instance Segmentation And Classification From 3d Range And 2d Color Images, Xiaoke Shen

Dissertations, Theses, and Capstone Projects

We address the problem of 3D object detection and instance segmentation by proposing a novel object segmentation and detection system. First, we detect 2D objects based on RGB, Depth only, or RGB-D images. A 3D convolutional-based system, named Frustum VoxNet, is proposed. This system 1) generates frustums from 2D detection results, 2) proposes 3D candidate voxelized images for each frustum, and uses a 3D convolutional neural network (CNN) based on these candidates voxelized images to perform the 3D instance segmentation and object detection. Although the volumetric data representation is widely used for 3D object classification, there are fewer works on ...


Clinical Term Normalization Using Learned Edit Patterns And Subconcept Matching: System Development And Evaluation, Rohit J. Kate 2021 University of Wisconsin Milwaukee

Clinical Term Normalization Using Learned Edit Patterns And Subconcept Matching: System Development And Evaluation, Rohit J. Kate

Computer Science Faculty Articles

Background: Clinical terms mentioned in clinical text are often not in their standardized forms as listed in clinical terminologies because of linguistic and stylistic variations. However, many automated downstream applications require clinical terms mapped to their corresponding concepts in clinical terminologies, thus necessitating the task of clinical term normalization.

Objective: In this paper, a system for clinical term normalization is presented that utilizes edit patterns to convert clinical terms into their normalized forms.

Methods: The edit patterns are automatically learned from the Unified Medical Language System (UMLS) Metathesaurus as well as from the given training data. The edit patterns are ...


Implementation Of Smartphone Navigation Features By Combined Forces In Determining The Hazards Of Terrorism In Poso, Mahturai Rian Fitra Mrf, Arthur Josias Simon Runturambi Ajsr 2021 SKSG Universitas Indonesia

Implementation Of Smartphone Navigation Features By Combined Forces In Determining The Hazards Of Terrorism In Poso, Mahturai Rian Fitra Mrf, Arthur Josias Simon Runturambi Ajsr

Journal of Terrorism Studies

The presence of armed terrorist groups in Poso can threaten security conditions in the country because their activities are considered quite dangerous for the surrounding community. This terrorist group did not hesitate to kill civilians who tried to deny its existence. Therefore, various joint military operations have been launched to crush this armed terrorist group, such as Camar Maleo and Tinombala. However, until now this terrorist group is difficult to destroy, due to the condition of the operating area in the form of dense tropical rainforest and steep slopes. This makes it difficult for troops to carry out chases and ...


Multi-Modal Classification Using Images And Text, Stuart J. Miller, Justin Howard, Paul Adams, Mel Schwan, Robert Slater 2021 Southern Methodist University

Multi-Modal Classification Using Images And Text, Stuart J. Miller, Justin Howard, Paul Adams, Mel Schwan, Robert Slater

SMU Data Science Review

This paper proposes a method for the integration of natural language understanding in image classification to improve classification accuracy by making use of associated metadata. Traditionally, only image features have been used in the classification process; however, metadata accompanies images from many sources. This study implemented a multi-modal image classification model that combines convolutional methods with natural language understanding of descriptions, titles, and tags to improve image classification. The novelty of this approach was to learn from additional external features associated with the images using natural language understanding with transfer learning. It was found that the combination of ResNet-50 image ...


Sars-Cov-2 Pandemic Analytical Overview With Machine Learning Predictability, Anthony Tanaydin, Jingchen Liang, Daniel W. Engels 2021 Southern Methodist University

Sars-Cov-2 Pandemic Analytical Overview With Machine Learning Predictability, Anthony Tanaydin, Jingchen Liang, Daniel W. Engels

SMU Data Science Review

Understanding diagnostic tests and examining important features of novel coronavirus (COVID-19) infection are essential steps for controlling the current pandemic of 2020. In this paper, we study the relationship between clinical diagnosis and analytical features of patient blood panels from the US, Mexico, and Brazil. Our analysis confirms that among adults, the risk of severe illness from COVID-19 increases with pre-existing conditions such as diabetes and immunosuppression. Although more than eight months into pandemic, more data have become available to indicate that more young adults were getting infected. In addition, we expand on the definition of COVID-19 test and discuss ...


Gophish: Implementing A Real-World Phishing Exercise To Teach Social Engineering, Andy Luse, Jim Burkman 2021 Oklahoma State University

Gophish: Implementing A Real-World Phishing Exercise To Teach Social Engineering, Andy Luse, Jim Burkman

Journal of Cybersecurity Education, Research and Practice

Social engineering is a large problem in our modern technological world, but while conceptually understood, it is harder to teach compared to traditional pen testing techniques. This research details a class project where students implemented a phishing exercise against real-world targets. Through cooperation with an external corporate partner, students learned the legal, technical, behavioral, analysis, and reporting aspects of social engineering. The outcome provided both usable data for a real-world corporation as well as valuable educational experience for the students.


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