Completeness Of Nominal Props,
2023
Runtime Verication Inc.
Completeness Of Nominal Props, Samuel Balco, Alexander Kurz
Engineering Faculty Articles and Research
We introduce nominal string diagrams as string diagrams internal in the category of nominal sets. This leads us to define nominal PROPs and nominal monoidal theories. We show that the categories of ordinary PROPs and nominal PROPs are equivalent. This equivalence is then extended to symmetric monoidal theories and nominal monoidal theories, which allows us to transfer completeness results between ordinary and nominal calculi for string diagrams.
Famaid: A Tool For Aiding People With Disability,
2022
Department of Mathematics and Computer Science, Beirut Arab University
Famaid: A Tool For Aiding People With Disability, Mohamad Maad, Ahmad Owaydate, Mohammad Kojok, Firas Aboudaher, Layal Abu Daher, May Itani
BAU Journal - Science and Technology
People with disabilities suffer from discrimination and obstacles that restrict them from participating in society on an equal basis with others every day. They are deprived of their rights to be included in ordinary school systems and even in the work market. In the process of raising awareness, facilitating dailyroutines, and developing guidance, the idea of assisting such people with handy tools/software arose and was implemented in the FamAid tool. FamAid offers people with hearing disability the opportunity to be engaged in the society through many facilities. In this work, we implemented a web application that serves as a community …
Explainable Ai Helps Bridge The Ai Skills Gap: Evidence From A Large Bank,
2022
Carnegie Mellon University
Explainable Ai Helps Bridge The Ai Skills Gap: Evidence From A Large Bank, Selina Carter, Jonathan Hersh
Economics Faculty Articles and Research
Advances in machine learning have created an “AI skills gap” both across and within firms. As AI becomes embedded in firm processes, it is unknown how this will impact the digital divide between workers with and without AI skills. In this paper we ask whether managers trust AI to predict consequential events, what manager characteristics are associated with increasing trust in AI predictions, and whether explainable AI (XAI) affects users’ trust in AI predictions. Partnering with a large bank, we generated AI predictions for whether a loan will be late in its final disbursement. We embedded these predictions into a …
Analyzing Business-Focused Social Networks In Hiring: The Influence Of A Job Candidate's Network On A Recruiter's Hiring Recommendation,
2022
University of South Alabama
Analyzing Business-Focused Social Networks In Hiring: The Influence Of A Job Candidate's Network On A Recruiter's Hiring Recommendation, Hannah V. Kibby
Theses and Dissertations
Social media has altered the ways in which people interact. Business-focused social media profiles, such as those on LinkedIn, can act as a proxy for a traditional resume. However, these websites differ from a traditional resume in that information presented is sometimes informal, personal, and irrelevant to the member’s career. Furthermore, HR employees are able to view a job candidate’s social network. This research investigates the influence of a recruiter’s knowledge of an applicant’s professional network on the recruiter’s perception of the applicant’s trustworthiness and hence their willingness to take risk in the hiring relationship. A review of the literature …
Detecting Selfish Mining Attacks Against A Blockchain Using Machine Learing,
2022
University of South Alabama
Detecting Selfish Mining Attacks Against A Blockchain Using Machine Learing, Matthew A. Peterson
Theses and Dissertations
Selfish mining is an attack against a blockchain where miners hide newly discovered blocks instead of publishing them to the rest of the network. Selfish mining has been a potential issue for blockchains since it was first discovered by Eyal and Sirer. It can be used by malicious miners to earn a disproportionate share of the mining rewards or in conjunction with other attacks to steal money from network users. Several of these attacks were launched in 2018, 2019, and 2020 with the attackers stealing as much as $18 Million. Developers made several different attempts to fix this issue, but …
Computer Engineering Education,
2022
University of Nebraska-Lincoln
Computer Engineering Education, Marilyn Wolf
CSE Conference and Workshop Papers
Computer engineering is a rapidly evolving discipline. How should we teach it to our students?
This virtual roundtable on computer engineering education was conducted in summer 2022 over a combination of email and virtual meetings. The panel considered what topics are of importance to the computer engineering curriculum, what distinguishes computer engineering from related disciplines, and how computer engineering concepts should be taught.
Communicative Information Visualizations: How To Make Data More Understandable By The General Public,
2022
University of Massachusetts Amherst
Communicative Information Visualizations: How To Make Data More Understandable By The General Public, Alyxander Burns
Doctoral Dissertations
Although data visualizations have been around for centuries and are encountered frequently by the general public, existing evidence suggests that a significant portion of people have difficulty understanding and interpreting them. It might not seem like a big problem when a reader misreads a weather map and finds themselves without an umbrella in a rainstorm, but for those who lack the means, experience, or ability to make sense of data, misreading a data visualization concerning public health and safety could be a matter of life and death. However, figuring out how to make visualizations truly usable for a diverse audience …
Computing Concept: Genealogy Potential, Power, Arithmetic, Algorithm And Ritual Of Computation,
2022
Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
Computing Concept: Genealogy Potential, Power, Arithmetic, Algorithm And Ritual Of Computation, Yuhang Liu, Fei Zhang
Bulletin of Chinese Academy of Sciences (Chinese Version)
In the new era, China needs more rational, firm, dialectical, and practical cultural confidence in the field of computational technology. The study conducted rigorous literature research, and established the correspondence between the ancient Chinese ideologies and different focuses of computation. The study proposes the computation concept genealogy (i.e., potential, power, arithmetic, algorithm, and ritual of computation) to deepen the multi-dimensional understanding of the concept of computation, and gives some suggestions for cultivating the computational culture that is facing the world and is of Chinese characteristics.
An Investigation Into Time Gazed At Traffic Objects By Drivers,
2022
The University of Western Ontario
An Investigation Into Time Gazed At Traffic Objects By Drivers, Kolby R. Sarson
Electronic Thesis and Dissertation Repository
Several studies have considered driver’s attention for a multitude of distinct purposes, ranging from the analysis of a driver’s gaze and perception, to possible use in Advanced Driving Assistance Systems (ADAS). These works typically rely on simple definitions of what it means to “see,” considering a driver gazing upon an object for a single frame as being seen. In this work, we bolster this definition by introducing the concept of time. We consider a definition of ”seen” which requires an object to be gazed upon for a set length of time, or frames, before it can be considered as seen …
Agglomerative Hierarchical Clustering With Dynamic Time Warping For Household Load Curve Clustering,
2022
Western University
Agglomerative Hierarchical Clustering With Dynamic Time Warping For Household Load Curve Clustering, Fadi Almahamid, Katarina Grolinger
Electrical and Computer Engineering Publications
Energy companies often implement various demand response (DR) programs to better match electricity demand and supply by offering the consumers incentives to reduce their demand during critical periods. Classifying clients according to their consumption patterns enables targeting specific groups of consumers for DR. Traditional clustering algorithms use standard distance measurement to find the distance between two points. The results produced by clustering algorithms such as K-means, K-medoids, and Gaussian Mixture Models depend on the clustering parameters or initial clusters. In contrast, our methodology uses a shape-based approach that combines Agglomerative Hierarchical Clustering (AHC) with Dynamic Time Warping (DTW) to classify …
Virtual Sensor Middleware: Managing Iot Data For The Fog-Cloud Platform,
2022
Western University
Virtual Sensor Middleware: Managing Iot Data For The Fog-Cloud Platform, Fadi Almahamid, Hanan Lutfiyya, Katarina Grolinger
Electrical and Computer Engineering Publications
This paper introduces the Virtual Sensor Middleware (VSM), which facilitates distributed sensor data processing on multiple fog nodes. VSM uses a Virtual Sensor as the core component of the middleware. The virtual sensor concept is redesigned to support functionality beyond sensor/device virtualization, such as deploying a set of virtual sensors to represent an IoT application and distributed sensor data processing across multiple fog nodes. Furthermore, the virtual sensor deals with the heterogeneous nature of IoT devices and the various communication protocols using different adapters to communicate with the IoT devices and the underlying protocol. VSM uses the publish-subscribe design pattern …
Towards Qos-Based Embedded Machine Learning,
2022
Chapman University
Towards Qos-Based Embedded Machine Learning, Tom Springer, Erik Linstead, Peiyi Zhao, Chelsea Parlett-Pelleriti
Engineering Faculty Articles and Research
Due to various breakthroughs and advancements in machine learning and computer architectures, machine learning models are beginning to proliferate through embedded platforms. Some of these machine learning models cover a range of applications including computer vision, speech recognition, healthcare efficiency, industrial IoT, robotics and many more. However, there is a critical limitation in implementing ML algorithms efficiently on embedded platforms: the computational and memory expense of many machine learning models can make them unsuitable in resource-constrained environments. Therefore, to efficiently implement these memory-intensive and computationally expensive algorithms in an embedded computing environment, innovative resource management techniques are required at the …
(Si10-124) Inverse Reconstruction Methodologies: A Review,
2022
Graphic Era Deemed to be University
(Si10-124) Inverse Reconstruction Methodologies: A Review, Deepika Saini
Applications and Applied Mathematics: An International Journal (AAM)
The three-dimensional reconstruction problem is a longstanding ill-posed problem, which has made enormous progress in the field of computer vision. This field has attracted increasing interest and demonstrated an impressive performance. Due to a long era of increasing evolution, this paper presents an extensive review of the developments made in this field. For the three dimensional visualization, researchers have focused on the developments of three dimensional information and acquisition methodologies from two dimensional scenes or objects. These acquisition methodologies require a complex calibration procedure which is not practical in general. Hence, the requirement of flexibility was much needed in all …
Cov-Inception: Covid-19 Detection Tool Using Chest X-Ray,
2022
Southern Methodist University
Cov-Inception: Covid-19 Detection Tool Using Chest X-Ray, Aswini Thota, Ololade Awodipe, Rashmi Patel
SMU Data Science Review
Since the pandemic started, researchers have been trying to find a way to detect COVID-19 which is a cost-effective, fast, and reliable way to keep the economy viable and running. This research details how chest X-ray radiography can be utilized to detect the infection. This can be for implementation in Airports, Schools, and places of business. Currently, Chest imaging is not a first-line test for COVID-19 due to low diagnostic accuracy and confounding with other viral pneumonia. Different pre-trained algorithms were fine-tuned and applied to the images to train the model and the best model obtained was fine-tuned InceptionV3 model …
A Roller Coaster For The Mind: Virtual Reality Sickness Modes, Metrics, And Mitigation,
2022
University of Louisville
A Roller Coaster For The Mind: Virtual Reality Sickness Modes, Metrics, And Mitigation, Dalton C. Sparks
The Cardinal Edge
Understanding and preventing virtual reality sickness(VRS), or cybersickness, is vital in removing barriers for the technology's adoption. Thus, this article aims to synthesize a variety of academic sources to demonstrate the modes by which VRS occurs, the metrics by which it is judged, and the methods to mitigate it. The predominant theories on the biological origins of VRS are discussed, as well as the individual factors which increase the likelihood of a user developing VRS. Moreover, subjective and physiological measurements of VRS are discussed in addition to the development of a predictive model and conceptual framework. Finally, several methodologies of …
Parasol: Efficient Parallel Synthesis Of Large Model Spaces,
2022
University of Nebraska - Lincoln
Parasol: Efficient Parallel Synthesis Of Large Model Spaces, Clay Stevens, Hamid Bagheri
CSE Conference and Workshop Papers
Formal analysis is an invaluable tool for software engineers, yet state-of-the-art formal analysis techniques suffer from well-known limitations in terms of scalability. In particular, some software design domains—such as tradeoff analysis and security analysis—require systematic exploration of potentially huge model spaces, which further exacerbates the problem. Despite this present and urgent challenge, few techniques exist to support the systematic exploration of large model spaces. This paper introduces Parasol, an approach and accompanying tool suite, to improve the scalability of large-scale formal model space exploration. Parasol presents a novel parallel model space synthesis approach, backed with unsupervised learning to automatically derive …
Algorithm-Based Fault Tolerance At Scale,
2022
University of Alabama in Huntsville
Algorithm-Based Fault Tolerance At Scale, Hayden Estes
Summer Community of Scholars Posters (RCEU and HCR Combined Programs)
No abstract provided.
Towards Explaining Variation In Entrainment,
2022
The Graduate Center, City University of New York
Towards Explaining Variation In Entrainment, Andreas Weise
Dissertations, Theses, and Capstone Projects
Entrainment refers to the tendency of human speakers to adapt to their interlocutors to become more similar to them. This affects various dimensions and occurs in many contexts, allowing for rich applications in human-computer interaction. However, it is not exhibited by every speaker in every conversation but varies widely across features, speakers, and contexts, hindering broad application. This variation, whose guiding principles are poorly understood even after decades of entrainment research, is the subject of this thesis. We begin with a comprehensive literature review that serves as the foundation of our own work and provides a reference to guide future …
Finite Gaussian Neurons: Defending Against Adversarial Attacks By Making Neural Networks Say "I Don’T Know",
2022
The Graduate Center, City University of New York
Finite Gaussian Neurons: Defending Against Adversarial Attacks By Making Neural Networks Say "I Don’T Know", Felix Grezes
Dissertations, Theses, and Capstone Projects
In this work, I introduce the Finite Gaussian Neuron (FGN), a novel neuron architecture for artificial neural networks aimed at protecting against adversarial attacks.
Since 2014, artificial neural networks have been known to be vulnerable to adversarial attacks, which can fool the network into producing wrong or nonsensical outputs by making humanly imperceptible alterations to inputs. While defenses against adversarial attacks have been proposed, they usually involve retraining a new neural network from scratch, a costly task.
My works aims to:
- easily convert existing models to Finite Gaussian Neuron architecture,
- while preserving the existing model's behavior on real …
Influence Level Prediction On Social Media Through Multi-Task And Sociolinguistic User Characteristics Modeling,
2022
The Graduate Center, City University of New York
Influence Level Prediction On Social Media Through Multi-Task And Sociolinguistic User Characteristics Modeling, Denys Katerenchuk
Dissertations, Theses, and Capstone Projects
Prediction of a user’s influence level on social networks has attracted a lot of attention as human interactions move online. Influential users have the ability to influence others’ behavior to achieve their own agenda. As a result, predicting users’ level of influence online can help to understand social networks, forecast trends, prevent misinformation, etc. The research on user influence in social networks has attracted much attention across multiple disciplines, from social sciences to mathematics, yet it is still not well understood. One of the difficulties is that the definition of influence is specific to a particular problem or a domain, …