Computer Engineering Commons^™

Youtube’S Terms Of Service: Posthumanism, Algorithms, And Professional Writing, Sarah Bresnahan

Graduate Research Theses & Dissertations

This thesis aims to examine YouTube’s Terms of Service as it applies to content creators (known as YouTubers) who use the platform as a means of financial gain and how YouTube’s demonetization policy via an algorithm is negatively affecting them. I conducted a case study featuring one creator, Michelle Guido, and attempted to determine why some of her content is demonetized when it fulfills YouTube’s content standards for monetization. This study is meant as an examination through the lens of Dr. N. Katherine Hayles’s theory of posthumanism as stated in her book, How We Became Posthuman, and will offer insight …

Exploring Cyber-Physical Systems, Misbah Uddin Mohammed

Graduate Research Theses & Dissertations

The advances in IOT, Computer Vision, AI and Machine Learning have made these technologies ubiquitous to our daily lives. From Smart Phones to Connected Vehicles, Cyber Physical systems have been interspersed into everything we interact in today’s world. The aim or this thesis was to explore these advances in Cyber Physical Systems and analyze the different sectors they were affecting. We then hand-picked certain domains and explored further by carrying out practical projects using some of the latest software and hardware resources available. Technologies like Amazon Alexa services, NVIDIA Jetson boards, TensorFlow, OpenCV, NodeJS were heavily employed in our various …

Small Non-Profit Website And Social Media Efficacy, Juliana Maria Leprich

Graduate Research Theses & Dissertations

This thesis examines the website design and social media platform usage of small non-profit organizations (defined as less than $1M operating budget and less than ten staff). This research will be completed by first reviewing other studies that have been done on marketing in the non-profit sector, then by exploring marketing challenges firsthand through a mini-ethnographic case study as described in the mini-ethnographic case study approach, and finally through the examination of tax and financial data provided by Guidestar. The researcher was involved in website collaboration with The Gracie Center in a volunteer capacity and was employed with the two …

Annual Report 2018-2019, Depaul University College Of Computing And Digital Media

CDM Annual Reports

LETTER FROM THE DEAN

I am pleased to share with you the 2018-19 College of Computing and Digital Media (CDM) annual report, highlighting the important work done by our faculty, students, and staff. We’ve said this before, and we’ll say it again: it was a big year. In 2018-19, programs across all three of our schools (Computing, Cinematic Arts, and Design) were ranked nationally. Our faculty were published in dozens of scholarly journals, screened their films over 100 times, and had their work exhibited globally. Student and alumni accomplishments included an Emmy nomination, a first place win in a Department …

Distance,Time And Terms In First Story Detection, Fei Wang

Doctoral

First Story Detection (FSD) is an important application of online novelty detection within Natural Language Processing (NLP). Given a stream of documents, or stories, about news events in a chronological order, the goal of FSD is to identify the very first story for each event. While a variety of NLP techniques have been applied to the task, FSD remains challenging because it is still not clear what is the most crucial factor in defining the “story novelty”. Giventhesechallenges,thethesisaddressedinthisdissertationisthat the notion of novelty in FSD is multi-dimensional. To address this, the work presented has adopted a three dimensional analysis of the …

Music Information Retrieval For Irish Traditional Music Automatic Analysis Of Harmonic, Rhythmic, And Melodic Features For Efficient Key-Invariant Tune Recognition, Pierre Beauguitte

Doctoral

Music making and listening practices increasingly rely on techno logy,and,asaconsequence,techniquesdevelopedinmusicinformation retrieval (MIR) research are more readily available to end users, in par ticular via online tools and smartphone apps. However, the majority of MIRresearchfocusesonWesternpopandclassicalmusic,andthusdoes not address specificities of other musical idioms. Irishtraditionalmusic(ITM)ispopularacrosstheglobe,withregular sessionsorganisedonallcontinents. ITMisadistinctivemusicalidiom, particularly in terms of heterophony and modality, and these character istics can constitute challenges for existing MIR algorithms. The bene fitsofdevelopingMIRmethodsspecificallytailoredtoITMisevidenced by Tunepal, a query-by-playing tool that has become popular among ITM practitioners since its release in 2009. As of today, Tunepal is the state of the art for tune recognition in ITM. The research in …

Smart Control Of Automatic Voltage Regulators Using K-Means Clustering, Brook Abegaz, J. Kueber

Engineering Science Faculty Publications

The future cyber physical systems consist of voltage regulators distributed across wide geographical areas. In this paper, a smart control approach of voltage regulators is presented for cyber physical system applications. The approach is implemented using K-means clustering algorithms that use data from voltage and current sensors, compute the correlation of changes across the regulators and generate a proportional feedback. Advanced estimation methods are used in cases where the data from the sensors was not available. The results show that the approach could be used to improve the performance of networked, power dependent systems by 94.5% in terms of overshoot …

Big Five Technologies In Aeronautical Engineering Education: Scoping Review, Ruth Martinez-Lopez

International Journal of Aviation, Aeronautics, and Aerospace

The constant demands that technology creates in aerospace engineering also influence education. The identification of the technologies with practical application in aerospace engineering is of current interest to decision makers in both universities and industry. A social network approach enhances this scoping review of the research literature to identify the main topics using the Big Five technologies in aerospace engineering education. The conceptual structure of the dataset (n=447) was analyzed from different approaches: at macro-level, a comparative of the digital technology identified by cluster analysis with the number of co-words established in 3 and 8 and, a keyword central structure …

Inception: Virtual Space In Memory Space In Real Space, Peter Casey, Rebecca Lindsay-Decusati, Ibrahim Baggili, Frank Breitinger

Electrical & Computer Engineering and Computer Science Faculty Publications

Virtual Reality (VR) has become a reality. With the technology's increased use cases, comes its misuse. Malware affecting the Virtual Environment (VE) may prevent an investigator from ascertaining virtual information from a physical scene, or from traditional “dead” analysis. Following the trend of antiforensics, evidence of an attack may only be found in memory, along with many other volatile data points. Our work provides the primary account for the memory forensics of Immersive VR systems, and in specific the HTC Vive. Our approach is capable of reconstituting artifacts from memory that are relevant to the VE, and is also capable …

Safe Pass, Alycia Riese, Julia Hariharan, Greg Synek, Jonathan Hall

Williams Honors College, Honors Research Projects

The purpose of this project is to design a sensor to be mounted on Class IV and higher vehicles to detect on-coming traffic. If traffic has been detected, the system is to warn drivers behind the stopped vehicle that passing is unsafe. The vehicle detection is to be implemented using a LiDAR detection method along with signal processing. A wireless transceiver is to transmit from the front radar module to the rear warning indicator module when the conditions are unsafe for passing. The project goals are to increase road safety and maintain traffic flow. The report details the challenges due …

Smart Parking Deck, Ryne Turner, Matthew Mcdade, Julie Aichinger, Laveréna Wienclaw

Williams Honors College, Honors Research Projects

The Smart Parking Deck employs elementary circuit design elements and mobile application development. Each device module uses laser proximity sensors to check the availability of an individual parking space and a Zigbee unit to communicate with the adjacent device module. The modules are connected to a network hub that manages all of the incoming and outgoing parking data. This data is displayed on the mobile application. The system is easily manageable and energy efficient, significantly decreasing the costs associated with other smart parking systems on the market. This system is aimed at decreasing commute time for students by allowing them …

Energy Efficient Spintronic Device For Neuromorphic Computation, Md Ali Azam

Theses and Dissertations

Future computing will require significant development in new computing device paradigms. This is motivated by CMOS devices reaching their technological limits, the need for non-Von Neumann architectures as well as the energy constraints of wearable technologies and embedded processors. The first device proposal, an energy-efficient voltage-controlled domain wall device for implementing an artificial neuron and synapse is analyzed using micromagnetic modeling. By controlling the domain wall motion utilizing spin transfer or spin orbit torques in association with voltage generated strain control of perpendicular magnetic anisotropy in the presence of Dzyaloshinskii-Moriya interaction (DMI), different positions of the domain wall are realized …

Determination Of Personalized Asthma Triggers From Multimodal Sensing And A Mobile App: Observational Study, Revathy Venkataramanan, Krishnaprasad Thirunarayan, Utkarshani Jaimini, Dipesh Kadariya, Hong Yung Yip, Maninder Kalra, Amit Sheth

Publications

Background: Asthma is a chronic pulmonary disease with multiple triggers. It can be managed by strict adherence to an asthma care plan and by avoiding these triggers. Clinicians cannot continuously monitor their patients’ environment and their adherence to an asthma care plan, which poses a significant challenge for asthma management.

Objective: In this study, pediatric patients were continuously monitored using low-cost sensors to collect asthma-relevant information. The objective of this study was to assess whether kHealth kit, which contains low-cost sensors, can identify personalized triggers and provide actionable insights to clinicians for the development of a tailored asthma care plan. …

Identifying Key Topics Bearing Negative Sentiment On Twitter: Insights Concerning The 2015-2016 Zika Epidemic, Ravali Mamidi, Michele Miller, Tanvi Banerjee, William Romine, Amit Sheth

Publications

Background To understand the public sentiment regarding the Zika virus, social media can be leveraged to understand how positive, negative, and neutral sentiments are expressed in society. Specifically, understanding the characteristics of negative sentiment could help inform federal disease control agencies’ efforts to disseminate relevant information to the public about Zika-related issues.

Objective The purpose of this study was to analyze the public sentiment concerning Zika using posts on Twitter and determine the qualitative characteristics of positive, negative, and neutral sentiments expressed.

Methods Machine learning techniques and algorithms were used to analyze the sentiment of tweets concerning Zika. A supervised …

Secure Networked Control Via Software Rejuvenation, Paul Griffioen, Raffaele Romagnoli, Bruce H. Krogh, Bruno Sinopoli

Faculty Work Comprehensive List

Software rejuvenation has been proposed as a prevention mechanism against unanticipated and undetectable attacks on cyber-physical systems. Without needing to implement any detection algorithm, the system is periodically refreshed with a secure and trusted copy of the control software to eliminate any malicious modifications to the run-time code and data that may have corrupted the controller. Previous work has considered using software rejuvenation while being able to disconnect from the network when recovering from dangerous situations. In contrast, we consider using software rejuvenation in cases where a network connection is needed in order for proper recovery to occur. We present …

Solid Spherical Energy (Sse) Cnns For Efficient 3d Medical Image Analysis, Vincent Andrearczyk, Valentin Oreiller, Julien Fageot, Xavier Montet, Adrien Depeursinge

Session 2: Deep Learning for Computer Vision

Invariance to local rotation, to differentiate from the global rotation of images and objects, is required in various texture analysis problems. It has led to several breakthrough methods such as local binary patterns, maximum response and steerable filterbanks. In particular, textures in medical images often exhibit local structures at arbitrary orientations. Locally Rotation Invariant (LRI) Convolutional Neural Networks (CNN) were recently proposed using 3D steerable filters to combine LRI with Directional Sensitivity (DS). The steerability avoids the expensive cost of convolutions with rotated kernels and comes with a parametric representation that results in a drastic reduction of the number of …

Expressing Trust With Temporal Frequency Of User Interaction In Online Communities, Ekaterina Yashkina, Arseny Pinigin, Jooyoung Lee, Manuel Mazzara, Akinlolu Solomon Adekotujo, Adam Zubair, Luca Longo

Conference papers

Reputation systems concern soft security dynamics in diverse areas. Trust dynamics in a reputation system should be stable and adaptable at the same time to serve the purpose. Many reputation mechanisms have been proposed and tested over time. However, the main drawback of reputation management is that users need to share private information to gain trust in a system such as phone numbers, reviews, and ratings. Recently, a novel model that tries to overcome this issue was presented: the Dynamic Interaction-based Reputation Model (DIBRM). This approach to trust considers only implicit information automatically deduced from the interactions of users within …

Mediaeval2019: Flood Detection In Time Sequence Satellite Images, Palavi Jain, Bianca Schoen-Phelan, Robert J. Ross

Conference papers

In this work, we present a flood detection technique from time series satellite images for the City-centered satellite sequences (CCSS) task in the MediaEval 2019 competition [1]. This work utilises a three channel feature indexing technique [13] along with a VGG16 pretrained model for automatic detection of floods. We also compared our result with RGB images and a modified NDWI technique by Mishra et al, 2015 [15]. The result shows that the three channel feature indexing technique performed the best with VGG16 and is a promising approach to detect floods from time series satellite images.

Analyzing Twitter Feeds To Facilitate Crises Informatics And Disaster Response During Mass Emergencies, Arshdeep Kaur

Dissertations

It is a common practice these days for general public to use various micro-blogging platforms, predominantly Twitter, to share ideas, opinions and information about things and life. Twitter is also being increasingly used as a popular source of information sharing during natural disasters and mass emergencies to update and communicate the extent of the geographic phenomena, report the affected population and casualties, request or provide volunteering services and to share the status of disaster recovery process initiated by humanitarian-aid and disaster-management organizations. Recent research in this area has affirmed the potential use of such social media data for various disaster …

Augmenting American Fuzzy Lop To Increase The Speed Of Bug Detection, Raviraj Mahajan

Dissertations

Whitebox fuzz testing is a vital part of the software testing process in the software development life cycle (SDLC). It is used for bug detection and security vulnerability checking as well. But current tools lack the ability to detect all the bugs and cover the entire code under test in a reasonable time. This study will explore some of the various whitebox fuzzing techniques and tools (AFL, SAGE, Driller, etc.) currently in use followed by a discussion of their strategies and the challenges facing them. One of the most popular state-of-the-art fuzzers, American Fuzzy Lop (AFL) will be discussed in …