Computer Sciences Commons^™

Graph Neural Network With Self-Attention And Multi-Task Learning For Credit Default Risk Prediction, Zihao Li, Xianzhi Wang, Lina Yao, Yakun Chen, Guandong Xu, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

We propose a graph neural network with self-attention and multi-task learning (SaM-GNN) to leverage the advantages of deep learning for credit default risk prediction. Our approach incorporates two parallel tasks based on shared intermediate vectors for input vector reconstruction and credit default risk prediction, respectively. To better leverage supervised data, we use self-attention layers for feature representation of categorical and numeric data; we further link raw data into a graph and use a graph convolution module to aggregate similar information and cope with missing values during constructing intermediate vectors. Our method does not heavily rely on feature engineering work and …

Itiger: An Automatic Issue Title Generation Tool, Ting Zhang, Ivana Clairine Irsan, Thung Ferdian, Donggyun Han, David Lo, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

In both commercial and open-source software, bug reports or issues are used to track bugs or feature requests. However, the quality of issues can differ a lot. Prior research has found that bug reports with good quality tend to gain more attention than the ones with poor quality. As an essential component of an issue, title quality is an important aspect of issue quality. Moreover, issues are usually presented in a list view, where only the issue title and some metadata are present. In this case, a concise and accurate title is crucial for readers to grasp the general concept …

Recipegen++: An Automated Trigger Action Programs Generator, Imam Nur Bani Yusuf, Diyanah Abdul Jamal, Lingxiao Jiang, David Lo

Research Collection School Of Computing and Information Systems

Trigger Action Programs (TAPs) are event-driven rules that allow users to automate smart-devices and internet services. Users can write TAPs by specifying triggers and actions from a set of predefined channels and functions. Despite its simplicity, composing TAPs can still be challenging for users due to the enormous search space of available triggers and actions. The growing popularity of TAPs is followed by the increasing number of supported devices and services, resulting in a huge number of possible combinations between triggers and actions. Motivated by such a fact, we improve our prior work and propose RecipeGen++, a deep-learning-based approach that …

Api-Related Developer Information Needs In Stack Overflow, Mingwei Liu, Xin Peng, Andrian Marcus, Shuangshuang Xing, Christoph Treude, Chengyuan Zhao

Research Collection School Of Computing and Information Systems

Stack Overflow (SO) provides informal documentation for APIs in response to questions that express API related developer needs. Navigating the information available on SO and getting information related to a particular API and need is challenging due to the vast amount of questions and answers and the tag-driven structure of SO. In this paper we focus on identifying and classifying fine-grained developer needs expressed in sentences of API-related SO questions, as well as the specific information types used to express such needs, and the different roles APIs play in these questions and their answers. We derive a taxonomy, complementing existing …

Generating Realistic Cyber Data For Training And Evaluating Machine Learning Classifiers For Network Intrusion Detection Systems, Marc W. Chalé, Nathaniel D. Bastian

Faculty Publications

No abstract provided.

Mechatronics Bachelor Curriculum Development In Light Of Industry 4.0 Technology Needs: Contrasting Us And German University Curricula, Paniz Hazaveh, Aleksandr Sergeyev, Nathir Rawashdeh

Michigan Tech Publications, Part 1

This study compares Mechatronics bachelor curricula at universities in the United States of America and German universities. Mechatronics education is relatively new in the United States, but has been common in Germany for over a decade. With the multidisciplinary nature of technologies required by the 4’th industrial revolution, a.k.a. Industry 4.0, composing an appropriate Mechatronics curriculum becomes a challenge and an opportunity. This paper studies how Mechatronics education can address the future needs of industry, while building on a specific university’s strengths and industry links. We have also analyzed the new undergraduate Mechatronics program at Michigan Technological University (MTU) and …

A Smart Parallel Gripper Industrial Automation System For Measurement Of Gripped Work Piece Thickness, Erik Kocher, Chukwuemeka George Ochieze, Ahmat Oumar, Travis Winter, Aleksandr Sergeyev, Mark Gauthier, Nathir Rawashdeh

Michigan Tech Publications, Part 1

As part of the advanced programmable logic controllers (PLC) course at Michigan Tech, this class project is performed on a mechatronics system gifted by Donald Engineering, a Michigan-based supplier of industrial automation systems and components. This paper explores the functionality and ladder programming of the smart parallel gripper system to measure the width of components grasped with the gripper. In addition, details of the system’s components, operation, more advanced uses are discussed. On the automation line, this smart gripper can be used to measure the thickness of work pieces while handling them and classifying these as either acceptable, too large …

Gesture Controlled Collaborative Robot Arm And Lab Kit, Abel A. Reyes, Skylar Reinhardt, Tony Wise, Nathir Rawashdeh, Sidike Paheding

Michigan Tech Publications, Part 1

In this paper, a mechatronics system was designed and implemented to include the subjects of artificial intelligence, control algorithms, robot servo motor control, and human-machine interface (HMI). The goal was to create an inexpensive, multi-functional robotics lab kit to promote students’ interest in STEM fields including computing and mechtronics. Industrial robotic systems have become vastly popular in manufacturing and other industries, and the demand for individuals with related skills is rapidly increasing. Robots can complete jobs that are dangerous, dull, or dirty for humans to perform. Recently, more and more collaborative robotic systems have been developed and implemented in the …

Operation Of A Controllable Force-Sensing Industrial Pneumatic Parallel Gripper System, Brian Piechocki, Chelsey Spitzner, Namratha Karanam, Travis Winter, Aleksandr Sergeyev, Mark Gauthier, Nathir Rawashdeh

Michigan Tech Publications, Part 1

As part of the advanced programmable logic controllers (PLC) course at Michigan Tech, this class project was performed on a mechatronics system gifted by Donald Engineering, a Michigan-based supplier of industrial automation systems and components. This paper explores the functionality and application of a force-programmable and sensing pneumatic parallel gripper system. Force sensing is a critical part of many systems in modern automation systems. Applications such as prosthetics, robotic surgery, or basic manufacturing systems may rely on the ability to properly read and control forces applied to an object. This work evaluates the basic operation of the pneumatic force-sensing gripper …

An Industrial Pneumatic And Servo Four-Axis Robotic Gripper System: Description And Unitronics Ladder Logic Programming, Zongguang Liu, Chrispin Johnston, Aleksi Leino, Travis Winter, Aleksandr Sergeyev, Mark Gauthier, Nathir Rawashdeh

Michigan Tech Publications, Part 1

As part of the advanced programmable logic controllers (PLC) course at Michigan Tech, this class project is performed on a mechatronics system gifted by Donald Engineering, a Michigan-based supplier of industrial automation systems and components. This paper explores the functionality and ladder programming of a four-axis robot enclosed in a cage with one side guarded by an optical fence. The robot has pneumatically actuated X-Y linear motion and a pneumatic gripper. Furthermore, the Z-axis motion and gripper wrist rotation are controlled by servo motors. A human machine interface (HMI) is also present, and it allows for easy manipulation and programming …

The Eu's Capacity To Lead The Transatlantic Alliance In Ai Regulation, Varun Roy, Vignesh Sreedhar

Claremont-UC Undergraduate Research Conference on the European Union

In the face of Chinese advances in AI in terms of technological prowess and influence, there has been a call for collaboration between the EU and the US to create a foundation for AI governance based on shared democratic beliefs. This paper maps out the EU, US, and Chinese approaches to AI development and regulation as we analyze the capacity of the US and EU to establish international standards for AI regulation through channels such as the TTC. As the EU rolled out a proportionate and risk-based approach to ensure stricter regulation for high-risk AI technologies, it laid the foundation …

Marginal Proportional Hazards Models For Clustered Interval-Censored Data With Time-Dependent Covariates, Kaitlyn Cook, Wenbin Lu, Rui Wang

Statistical and Data Sciences: Faculty Publications

The Botswana Combination Prevention Project was a cluster-randomized HIV prevention trial whose follow-up period coincided with Botswana’s national adoption of a universal test-and-treat strategy for HIV management. Of interest is whether, and to what extent, this change in policy (i) modified the observed preventative effects of the study intervention and (ii) was associated with a reduction in the population-level incidence of HIV in Botswana. To address these questions, we propose a stratified proportional hazards model for clustered intervalcensored data with time-dependent covariates and develop a composite expectation maximization algorithm that facilitates estimation of model parameters without placing parametric assumptions on …

Preventing Variadic Function Attacks Through Argument Width Counting, Brennan Ward

USF Tampa Graduate Theses and Dissertations

Format String attacks, first noted in June 2000 [1], are a type of attack in which anadversary has control of the string argument (the format string) passed to a string format function (such as printf). Such control allows the attacker to read and write arbitrary program memory. To prevent these attacks, various methodologies have been proposed, each with their own costs and benefits. I present a novel solution to this problem through argument width counting, ensuring that such format functions cannot access stack memory beyond the space where arguments were placed. Additionally, I show how this approach can be expanded …

Sila: A System For Scientific Image Analysis, Daniel Moreira, João Phillipe Cardenuto, Ruiting Shao, Sriram Baireddy, Davide Cozzolino, Diego Gragnaniello, Wael Abd-Almageed, Paolo Bestagini, Stefano Tubaro, Anderson Rocha, Walter Scheirer, Luisa Verdoliva, Edward Delp

Computer Science: Faculty Publications and Other Works

A great deal of the images found in scientific publications are retouched, reused, or composed to enhance the quality of the presentation. In most instances, these edits are benign and help the reader better understand the material in a paper. However, some edits are instances of scientific misconduct and undermine the integrity of the presented research. Determining the legitimacy of edits made to scientific images is an open problem that no current technology can perform satisfactorily in a fully automated fashion. It thus remains up to human experts to inspect images as part of the peer-review process. Nonetheless, image analysis …

Development Of A Smartphone Application As An Asset To Pavement Management Engineers, Smartp3m, Damien Stephens

Electrical Engineering Theses

An application specific multi-platform smartphone application can utilize on-board accelerometer, gyroscope, and GPS sensors, along with software derived signals from the same sensors, to sample vibrational and geolocation datasets to capture pavement distresses such as potholes when mounted in a standardized configuration in a vehicle. Several observations were made with regard to the signals obtained from the accelerometer, gyroscope, and GPS sensors, and it was determined that the raw sensor outputs are capable of sampling statistically significant datasets which can be used to distinguish pavement distress from normal driving conditions. Furthermore, an approximate sensor noise margin is established, and a …

Policy-Based Redactable Signatures, Zachary Kissel

Computer and Data Science Faculty Publications

In this work we make progress towards solving an open problem posed by Bilzhause et. al, to give constructions of redactable signature schemes that allow the signer to limit the possible redactions performed by a third party. A separate, but related notion, called controlled disclosure allows a redactor to limit future redactions. We look at two types of data, sets and linear data (data organized as a sequence). In the case of sets, we limit redactions using a policy modeled by a monotone circuit or any circuit depending on the size of the universe the set is drawn from. In …

The Human Element In The Era Of Digitalization And Automation Of Ports : A Case Study Of South Africa, Lucky Njabulo Sithole

World Maritime University Dissertations

No abstract provided.

The Necessity Of Cloud-Based Simulator For Indonesia's Maritime Education And Training Institutions, Stevian Geerbel Adrianes Rakka

World Maritime University Dissertations

No abstract provided.

Text Mining Policy Documents To Support Transboundary Integrated Ecosystem Assessment : The Case Of The South Mid-Atlantic Ridge, Debora Cristina Ferrari Ramalho

World Maritime University Dissertations

No abstract provided.

Streaming Algorithms For Multitasking Scheduling With Shared Processing, Bin Fu, Yumei Huo, Hairong Zhao

Computer Science Faculty Publications

In this paper, we design the first streaming algorithms for the problem of multitasking scheduling on parallel machines with shared processing. In one pass, our streaming approximation schemes can provide an approximate value of the optimal makespan. If the jobs can be read in two passes, the algorithm can find the schedule with the approximate value. This work not only provides an algorithmic big data solution for the studied problem, but also gives an insight into the design of streaming algorithms for other problems in the area of scheduling.

Monitoring Activities Of Daily Living For Maintaining Independent Living In Dementia, Jonathan Turner, Ciaran Nugent, Damon Berry, Dympna O'Sullivan, Michael Wilson, Julie Doyle

Articles

Our ability to live independent meaningful lives depends on our ability to perform various activities and to maintain our cognitive functions. Maintaining independent living is important for persons with dementia, it increases selfworth and allows to remain independent and in their own homes for longer. We describe the activities established as being important for the maintenance of independent living, and methods for monitoring these activities using technology.

Incoherent And Online Dictionary Learning Algorithm For Motion Prediction, Farrukh Hafeez, Usman Ullah Sheikh, Asif Iqbal, Muhammad Naveed Aman

School of Computing: Faculty Publications

Accurate model development and efficient representations of multivariate trajectories are crucial to understanding the behavioral patterns of pedestrian motion. Most of the existing algorithms use offline learning approaches to learn such motion behaviors. However, these approaches cannot take advantage of the streams of data that are available after training has concluded, and typically are not generalizable to data that they have not seen before. To solve this problem, this paper proposes two algorithms for learning incoherent dictionaries in an offline and online manner by extending the offline augmented semi-non-negative sparse coding (ASNSC) algorithm. We do this by adding a penalty …

Machine Learning For Aiding Blood Flow Velocity Estimation Based On Angiography, Swati Padhee, Mark Johnson, Hang Yi, Tanvi Banerjee, Zifeng Yang

Computer Science and Engineering Faculty Publications

Computational fluid dynamics (CFD) is widely employed to predict hemodynamic characteristics in arterial models, while not friendly to clinical applications due to the complexity of numerical simulations. Alternatively, this work proposed a framework to estimate hemodynamics in vessels based on angiography images using machine learning (ML) algorithms. First, the iodine contrast perfusion in blood was mimicked by a flow of dye diffusing into water in the experimentally validated CFD modeling. The generated projective images from simulations imitated the counterpart of light passing through the flow field as an analogy of X-ray imaging. Thus, the CFD simulation provides both the ground …

Mobility-Aware Hierarchical Fog Computing Framework For Industrial Internet Of Things (Iiot), Tariq Qayyum, Zouheir Trabelsi, Asad Waqar Malik, Kadhim Hayawi

All Works

The Industrial Internet of Things (IIoTs) is an emerging area that forms the collaborative environment for devices to share resources. In IIoT, many sensors, actuators, and other devices are used to improve industrial efficiency. As most of the devices are mobile; therefore, the impact of mobility can be seen in terms of low-device utilization. Thus, most of the time, the available resources are underutilized. Therefore, the inception of the fog computing model in IIoT has reduced the communication delay in executing complex tasks. However, it is not feasible to cover the entire region through fog nodes; therefore, fog node selection …

An Evaluation Framework For Digital Image Forensics Tools, Zainab Khalid, Sana Qadir

Journal of Digital Forensics, Security and Law

The boom of digital cameras, photography, and social media has drastically changed how humans live their day-to-day, but this normalization is accompanied by malicious agents finding new ways to forge and tamper with images for unlawful monetary (or other) gains. Disinformation in the photographic media realm is an urgent threat. The availability of a myriad of image editing tools renders it almost impossible to differentiate between photo-realistic and original images. The tools available for image forensics require a standard framework against which they can be evaluated. Such a standard framework can aid in evaluating the suitability of an image forensics …

A Study Of The Data Remaining On Second-Hand Mobile Devices In The Uk, Olga Angelopoulou, Andy Jones, Graeme Horsman, Seyedali Pourmoafi

Journal of Digital Forensics, Security and Law

This study was carried out intending to identify the level and type of information that remained on portable devices that were purchased from the second-hand market in the UK over the last few years. The sample for this study consisted of 100 second hand mobile phones and tablets. The aim of the study was to determine the proportion of devices that still contained data and the type of data that they contained. Where data was identified, the study attempted to determine the level of personal identifiable information that is associated with the previous owner. The research showed that when sensitive …

Data Sharing Through Open Access Data Repositories, Karin Bennedsen

All Things Open

The National Institutes of Health has expanded their data sharing requirements for obtaining funding to now include all awards for research producing scientific data to accelerate “biomedical research discovery, in part, by enabling validation of research results, providing accessibility to high-value datasets, and promoting data reuse for future research studies.” The new policy requiring a Data Management & Sharing Plan (DMSP) for all applications goes into effect January 25th, 2023. A DMSP includes where the data will be stored. This lightning talk will review Open Access Data Repositories. Don’t let the task of trying to find data storage hold you …

The Impact Of Ethical Hacking Within Small Businesses, Nygia Tribbey

Cybersecurity Undergraduate Research Showcase

The Internet has brought about a new way for businesses to reach their customers. With the help of social media, websites, and email marketing, small businesses have gained a lot of new customers. However, these new online customers have also opened up their businesses to a whole new world of cyber crime. Cyber crime is the illegal use of computers and networks to cause damage or steal information. This type of crime affects small businesses as well as large corporations. Small businesses often find themselves at a disadvantage because they don't have the resources to hire an ethical hacker or …

Utilizing Federated Learning And Meta Learning For Few-Shot Learning On Edge Devices, Kousalya Soumya Lahari Voleti

Theses and Dissertations

The efficient and effective handling of few-shot learning tasks on mobile devices is challenging due to the small training set issue and the physical limitations in power and computational resources on these devices. In this thesis, we propose a solution that combines federated learning and meta-learning to handle independent few-shot learning tasks on multiple devices (or clients) and the server. In particular, we utilize the Prototypical Networks to perform meta-learning on all devices to learn multiple independent few-shot learning models and to combine the models in a centralized data distributed architecture using federated learning which can be reused by the …

Social Media Time Series Forecasting And User-Level Activity Prediction With Gradient Boosting, Deep Learning, And Data Augmentation, Fred Mubang

USF Tampa Graduate Theses and Dissertations

In the overall history of technological innovations, social media has only existed for a brief time, however its influence is undeniable. Researchers have found that it can be used to influence elections, spread health misinformation, and aid with financial pump-and-dump schemes. Keeping all this in mind, it is clear that more research is needed to predict the spread of information on social media in order to combat its malicious use.

To that end, in this dissertation, we explore the use of Machine Learning algorithms to perform time series forecasting and user-level activity prediction in social media. We address the different …