Computer Engineering Commons^™

How The Power Of Machine – Machine Learning, Data Science And Nlp Can Be Used To Prevent Spoofing And Reduce Financial Risks, Sasibhushan Rao Chanthati

Harrisburg University Other Works

This paper discusses the potential of machine learning, data science, and natural language processing (NLP) in mitigating the incidence of spoofing and financial risks hinged on cyber threats. Another one is spoofing; it is the act of impersonating legitimate entities to gain unauthorized information and it is indeed a threat to the public and companies to some extent. The research introduces two primary methodologies to combat spoofing: an email filtering system using a machine learning algorithm and an encryption and decryption system using a Caesar Cipher and Python programming language. It distinguishes between approved domains and unapproved domains by using …

Heterogeneous Resources Cost-Aware Geo-Distributed Data Analytics, Minmin Zhang

UNO Student Research and Creative Activity Fair

Many popular cloud service providers deploy tens of data centers (DCs) around the world to reduce user-perceived latency for better user experiences, in which a large amount of data is generated and stored in a geo-distributed manner. Geo-distributed Data Analytics (GDA) has gained great popularity in meeting the growing demand to mine meaningful and timely knowledge from such highly dispersed data. Since GDA systems require a large data migration between DCs via a wide area network (WAN), many existing works invested significant effort to optimize data transfer strategies to efficiently use limited WAN by considering the network pricing policies on …

Bibliometric Survey For Stock Market Prediction Using Sentimental Analysis And Lstm, Pooja Bagane, Nimit Mehta Mr, Parth Kakde Mr, Nisarg Bramhbhatt Mr, Ishansh Sahni Mr, Sirbi Kotrappa Dr

Library Philosophy and Practice (e-journal)

Creating an overview of the flow fundamentals of the global market trading and sublimation of equities into a superimposed system of economic agendas. Furthermore this leads to dynamic overlapping with the current technological advancements to create a platform for information exchange and inculcations. This created a new field of access points where we could enhance and analyse the data available and create an interface to predict the rise and fall trends involved with the stock market. These help create a sense of control and format over the public personification over the economic impacts and use social media and involve discrete …

Welcome To The Journal Of Electronic Theses And Dissertations (J-Etd), Edward A. Fox

The Journal of Electronic Theses and Dissertations

On behalf of the Networked Digital Library of Theses and Dissertations (NDLTD; see our website with multiple aliases: ndltd.org, theses.org, dissertations.org), I welcome you to the first volume of J-ETD. Now is the time to broadly share through an archival journal some of the most interesting discussions related to the global movement around ETDs. We hope you will find this journal to be of interest, and will spread the word that it is globally accessible as an open access archival forum empowering graduate student researchers and universities to broadly contribute to scholarship, knowledge, education, and understanding. We hope you and …

Review And Analysis Of Failure Detection And Prevention Techniques In It Infrastructure Monitoring, Deepali Arun Bhanage, Ambika Vishal Pawar, K Kotecha

Library Philosophy and Practice (e-journal)

Maintaining the health of IT infrastructure components for improved reliability and availability is a research and innovation topic for many years. Identification and handling of failures are crucial and challenging due to the complexity of IT infrastructure. System logs are the primary source of information to diagnose and fix failures.

In this work, we address three essential research dimensions about failures, such as the need for failure handling in IT infrastructure, understanding the contribution of system-generated log in failure detection and reactive & proactive approaches used to deal with failure situations.

This study performs a comprehensive analysis of existing literature …

Enterprise Architecture Transformation Process From A Federal Government Perspective, Tonia Canada, Leila Halawi

Publications

The need for information technology organizations to transform enterprise architecture is driven by federal government mandates and information technology budget constraints. This qualitative case study aimed to identify factors that hinder federal government agencies from driving enterprise architecture transformation processes from a compliancy to a flexible process. Common themes in interviewee responses were identified, coded, and summarized. Critical recommendations for future best practices, including further research, were also presented.

Infiniband Network Monitoring: Challenges And Possibilities, Kyle D. Hintze

Theses and Dissertations

Within the realm of High Performance Computing, the InfiniBand Architecture is among the leading interconnects used today. Capable of providing high bandwidth and low latency, InfiniBand is finding applications outside the High Performance Computing domain. One of these is critical infrastructure, encompassing almost all essential sectors as the work force becomes more connected. InfiniBand is not immune to security risks, as prior research has shown that common traffic analyzing tools cannot effectively monitor InfiniBand traffic transmitted between hosts, due to the kernel bypass nature of the IBA in conjunction with Remote Direct Memory Access operations. If Remote Direct Memory Access …

Spatio-Temporal Data Mining For Aviation Delay Prediction, Kai Zhang, Houbing Song, Yushan Jiang, Dahai Liu

Publications

To accommodate the unprecedented increase of commercial airlines over the next ten years, the Next Generation Air Transportation System (NextGen) has been implemented in the USA that records large-scale Air Traffic Management (ATM) data to make air travel safer, more efficient, and more economical. A key role of collaborative decision making for air traffic scheduling and airspace resource management is the accurate prediction of flight delay. There has been a lot of attempts to apply data-driven methods such as machine learning to forecast flight delay situation using air traffic data of departures and arrivals. However, most of them omit en-route …

Fault Analysis And Debugging Of Microservice Systems: Industrial Survey, Benchmark System, And Empirical Study, Xiang Zhou, Xin Peng, Tao Xie, Jun Sun, Chao Ji, Wenhai Li, Dan Ding

Research Collection School Of Computing and Information Systems

The complexity and dynamism of microservice systems pose unique challenges to a variety of software engineering tasks such as fault analysis and debugging. In spite of the prevalence and importance of microservices in industry, there is limited research on the fault analysis and debugging of microservice systems. To fill this gap, we conduct an industrial survey to learn typical faults of microservice systems, current practice of debugging, and the challenges faced by developers in practice. We then develop a medium-size benchmark microservice system (being the largest and most complex open source microservice system within our knowledge) and replicate 22 industrial …

Estimating Remaining Useful Life In Machines Using Artificial Intelligence: A Scoping Review, Sameer Sayyad, Satish Kumar, Arunkumar Bongale, Anupkumar Bongale, Shruti Patil

Library Philosophy and Practice (e-journal)

The remaining useful life (RUL) estimations become one of the most essential aspects of predictive maintenance (PdM) in the era of industry 4.0. Predictive maintenance aims to minimize the downtime of machines or process, decreases maintenance costs, and increases the productivity of industries. The primary objective of this bibliometric paper is to understand the scope of literature available related to RUL prediction. Scopus database is used to perform the analysis of 1673 extracted scientific literature from the year 1985 to 2020. Based on available published documents, analysis is done on the year-wise publication data, document types, language-wise distribution of documents, …

Bert For Question Answering On Bioasq, Eric R. Fu, Rikel Djoko, Maysam Mansor, Robert Slater

SMU Data Science Review

Machine reading comprehension and question answering are topics of considerable focus in the field of Natural Language Processing (NLP). In recent years, language models like Bidirectional Encoder Representations from Transformers (BERT) [3] have been very successful in language related tasks like question answering. The difficulty of the question answering task lies in developing accurate representations of language and being able to produce answers for questions. In this study, the focus is to investigate how to train and fine tune a BERT model to improve its performance on BioASQ, a challenge on large scale biomedical question answering. Our most accurate BERT …

Examining The Modelling Capabilities Of Defeasible Argumentation And Non-Monotonic Fuzzy Reasoning, Luca Longo, Lucas Rizzo, Pierpaolo Dondio

Articles

Knowledge-representation and reasoning methods have been extensively researched within Artificial Intelligence. Among these, argumentation has emerged as an ideal paradigm for inference under uncertainty with conflicting knowledge. Its value has been predominantly demonstrated via analyses of the topological structure of graphs of arguments and its formal properties. However, limited research exists on the examination and comparison of its inferential capacity in real-world modelling tasks and against other knowledge-representation and non-monotonic reasoning methods. This study is focused on a novel comparison between defeasible argumentation and non-monotonic fuzzy reasoning when applied to the representation of the ill-defined construct of human mental workload …

Annual Report 2020-2021, Depaul University College Of Computing And Digital Media

CDM Annual Reports

LETTER FROM THE DEAN

As I write this letter during the beginning of the 2021–22 academic year, we have started to welcome the majority of our students to campus— many for the very first time, and some for the first time in a year and a half. It has been wonderful to be together, in-person, again. Four quarters of learning and working remotely was challenging, to be sure, but I have been consistently amazed by the resilience, innovation, and hard work of our students, faculty, and staff, even in the most difficult of circumstances. This annual report, covering the 2020–21 …

A 3d Point Cloud Deep Learning Approach Using Lidar To Identify Ancient Maya Archaeological Sites, Heather Richards-Rissetto, David Newton, Aziza Al Zadjali

Department of Anthropology: Faculty Publications

Airborne light detection and ranging (LIDAR) systems allow archaeologists to capture 3D data of anthropogenic landscapes with a level of precision that permits the identification of archaeological sites in difficult to reach and inaccessible regions. These benefits have come with a deluge of LIDAR data that requires significant and costly manual labor to interpret and analyze. In order to address this challenge, researchers have explored the use of state-of-the-art automated object recognition algorithms from the field of deep learning with success. This previous research, however, has been limited to the exploration of deep learning processes that work with only 2D …

On The (Im)Practicality Of Adversarial Perturbation For Image Privacy, Arezoo Rajabi, Rakesh B. Bobba, Mike Rosulek, Charles Wright, Wu-Chi Feng

Computer Science Faculty Publications and Presentations

Image hosting platforms are a popular way to store and share images with family members and friends. However, such platforms typically have full access to images raising privacy concerns. These concerns are further exacerbated with the advent of Convolutional Neural Networks (CNNs) that can be trained on available images to automatically detect and recognize faces with high accuracy.

Recently, adversarial perturbations have been proposed as a potential defense against automated recognition and classification of images by CNNs. In this paper, we explore the practicality of adversarial perturbation based approaches as a privacy defense against automated face recognition. Specifically, we first …

Appointment Scheduling System, Guzaloi Noori

Undergraduate Honors Theses

Appointment Scheduling System designed for universities so that students can schedule appointments with their university’s faculty and staff regarding academic, employment, immigration, or personal issues. The scheduling system has the ability of being embedded to the Computer Science Capstone project iAcademic, which I took part in as a front-end developer.

A Comparison Of Artificial Neural Networks And The Statistical Methods In Predicting Mba Student’S Academic Performance, Ojoung Kwon, Harry Hui Xia, Serin Zhang

Journal of International Technology and Information Management

MBA has become one of the most popular and vital professional degrees internationally. The MBA program admission process’s essential task is to choose the best analysis tools to accurately predict applicants’ academic performance potential based on the evaluation criteria in making admission decisions. Prior research finds that the Graduate Management Admission Test (GMAT) and undergraduate grade point average (UGPA) are common predictors of MBA academic performance indicated by graduate grade point average (GGPA). Using a sample of 250 MBA students enrolled in a state university with AACSB accreditation from Fall 2010 to Fall 2017, we test and compare the effectiveness …

An Integrated View Of Knowledge Management Enablers, Components, And Benefits: Comprehensive Literature Review, Shuaibu Hassan Usman, Jigish Zaveri, Aminu Hamza

Journal of International Technology and Information Management

The key to success in the 21^st century, knowledge-based economy, will be the effective and efficient management of knowledge. Knowledge Management (KM) has a direct impact on organizational success. KM in a knowledge-based economy entails growth, value, and improving living standards through knowledge creation, storage, and dissemination. This study aims to integrate KM enablers, components, and benefits into a single view through a comprehensive literature search. The integrative view of these three factors would facilitate the understanding of KM initiatives within organizations. This paper performs a comprehensive literature review to explain the KM enablers, components, and benefits. From the …

Parallel Computation, Mahesh Wosti

Student Academic Conference

Parallel computing has always fascinated me since I became aware of it. I think it is the only path forward if we are to build and make a super-fast computer in days to come. For my senior seminar, I want to build a simple framework of the parallel system and dig deeper into potential benefits and drawbacks of using a parallel system compared to the serial computing that is still pervasive in today’s modern technology.

Energy-Efficient In-Memory Architectures Leveraging Intrinsic Behaviors Of Embedded Mram Devices, Shadi Sheikhfaal

Electronic Theses and Dissertations, 2020-2023

For decades, innovations to surmount the processor versus memory gap and move beyond conventional von Neumann architectures continue to be sought and explored. Recent machine learning models still expend orders of magnitude more time and energy to access data in memory in addition to merely performing the computation itself. This phenomenon referred to as a memory-wall bottleneck, is addressed herein via a completely fresh perspective on logic and memory technology design. The specific solutions developed in this dissertation focus on utilizing intrinsic switching behaviors of embedded MRAM devices to design cross-layer and energy-efficient Compute-in-Memory (CiM) architectures, accelerate the computationally-intensive operations …

Enabling Machine Learning On The Edge Using Sram Conserving Efficient Neural Networks Execution Approach, Bharath Sudharsan, Pankesh Patel, John G. Breslin, Muhammad Intizar Ali

Publications

Edge analytics refers to the application of data analytics and Machine Learning (ML) algorithms on IoT devices. The concept of edge analytics is gaining popularity due to its ability to perform AI-based analytics at the device level, enabling autonomous decision-making, without depending on the cloud. However, the majority of Internet of Things (IoT) devices are embedded systems with a low-cost microcontroller unit (MCU) or a small CPU as its brain, which often are incapable of handling complex ML algorithms.

In this paper, we propose an approach for the ecient execution of already deeply compressed, large neural networks (NNs) on tiny …

Simulation For Cybersecurity: State Of The Art And Future Directions, Hamdi Kavak, Jose J. Padilla, Daniele Vernon-Bido, Saikou Y. Diallo, Ross Gore, Sachin Shetty

VMASC Publications

In this article, we provide an introduction to simulation for cybersecurity and focus on three themes: (1) an overview of the cybersecurity domain; (2) a summary of notable simulation research efforts for cybersecurity; and (3) a proposed way forward on how simulations could broaden cybersecurity efforts. The overview of cybersecurity provides readers with a foundational perspective of cybersecurity in the light of targets, threats, and preventive measures. The simulation research section details the current role that simulation plays in cybersecurity, which mainly falls on representative environment building; test, evaluate, and explore; training and exercises; risk analysis and assessment; and humans …

Hidden Markov Model And Cyber Deception For The Prevention Of Adversarial Lateral Movement, Md Ali Reza Al Amin, Sachin Shetty, Laurent Njilla, Deepak K. Tosh, Charles Kamhoua

Computational Modeling & Simulation Engineering Faculty Publications

Advanced persistent threats (APTs) have emerged as multi-stage attacks that have targeted nation-states and their associated entities, including private and corporate sectors. Cyber deception has emerged as a defense approach to secure our cyber infrastructure from APTs. Practical deployment of cyber deception relies on defenders' ability to place decoy nodes along the APT path optimally. This paper presents a cyber deception approach focused on predicting the most likely sequence of attack paths and deploying decoy nodes along the predicted path. Our proposed approach combines reactive (graph analysis) and proactive (cyber deception technology) defense to thwart the adversaries' lateral movement. The …

Modeling And Simulation Of Cascading Failures In Transportation Systems During Hurricane Evacuations, Yuan Zhu, Kaan Ozbay, Hong Yang, Fan Zuo, Di Sha

Computational Modeling & Simulation Engineering Faculty Publications

Effective and timely evacuation is critical in alleviating the impact of hurricanes. As such, evacuation models are often sought to support the preparedness of evacuations. One important task in the modeling process is to evaluate exogenous factors that cause transportation system capacity loss during evacuation. Typical factors include direct damage to the roadway network due to storm surge and cascading impacts because of other facilities failures. For example, power outage can lead to signal failure and subway suspension. This paper aims to develop a macroscopic simulation-based approach to study the capacity loss of the roadway network in evacuation due to …

Analyzing And Improving Calculation And Tuning Process For A Uav, Laurel Wardell

Williams Honors College, Honors Research Projects

The nature of this project is confidential and cannot be disclosed in detail. Generally, this project deals with the analysis of a control system of a UAV with several electric motors and gimbals. The goal of this analysis is to improve control calculations for increased stability. In addition, development has been started on an application to streamline the tuning of gains for this particular controller, allowing for more efficient use of precious flight time.

Light Loaded Automated Guided Vehicle, Marcus Radtka, Nazar Paramashchuk, Lawrence Shevock

Williams Honors College, Honors Research Projects

The objective of the locomotion system was to design and implement the mechanical, electrical, and software related functions to ensure the LLAGV had the capability of maneuvering its surroundings. The LLAGV’s motors were represented in an open loop transfer function to utilize RPM feedback and a compensator when needed. The modeled compensator helped control the LLAGV’s speed and acceleration, enabling further control of the LLAGV. The internal circuitry has the means to properly distributed power to all components and allowed the user to control the LLAGV to their desire. The application software within the LLAGV locomotion system (LLAGV-LS) had consideration …

The Youplanner, Taylor Burgess

Williams Honors College, Honors Research Projects

Staying organized can be difficult. A four tier web application was created to help in the endeavor. Utilizing software engineering practices, an online notepad was created where users can add, update, and delete notes. The application was a full stack application. For the backend, MySQL was the language and phpMyAdmin was the server. For the front end, PHP and Bootstrap 5.1 was used.

Energy Harvesting And Sensor Based Hardware Security Primitives For Cyber-Physical Systems, Carson Labrado

Theses and Dissertations--Electrical and Computer Engineering

The last few decades have seen a large proliferation in the prevalence of cyber-physical systems. Although cyber-physical systems can offer numerous advantages to society, their large scale adoption does not come without risks. Internet of Things (IoT) devices can be considered a significant component within cyber-physical systems. They can provide network communication in addition to controlling the various sensors and actuators that exist within the larger cyber-physical system. The adoption of IoT features can also provide attackers with new potential avenues to access and exploit a system's vulnerabilities. Previously, existing systems could more or less be considered a closed system …

The Design, Development And Validation Of A Persuasive Content Generator, Sam Khataei, Michael J. Hine, Ali Arya

Journal of International Technology and Information Management

This paper addresses the automatic generation of persuasive content to influence users’ attitude and behaviour. Our research extends current approaches by leveraging individuals’ social media profiles and activity to personalize the persuasive content. Unlike most other implemented persuasive technology, our system is generic and can be adapted to any domain where collections of electronic text are available. Using the Yale Attitude Change approach, we describe: the multi-layered Pyramid of Individualization model; the design, development, and validation of integrated software that can generate individualized persuasive content based on a user’s social media profile and activity. Results indicate the proposed system can …

Wireless Mobile Phone Technology, Deregulation Policy, Competition And Economic Welfare In Nigeria’S Telecom Industry: An Analytic Model, Onochie J. Dieli Phd

Journal of International Technology and Information Management

This analytic model is about the Nigerian telecom industry’s structural change caused by the arrival of a new wireless mobile phone technology. Nigeria’s telecom industry transformed from natural monopoly to competitive market as a result of deregulation that occurred in 1999. Under the price regulation using underground or above the ground cable telephone lines, it could run only with the help of government subsidies. This study argues that the arrival of a new telecomm technology was the key to success of Nigeria’s deregulation of its telecom industry. An analysis of a simple microeconomic model shows that with the new wireless …