Calibrated Prediction With Covariate Shift Via Unsupervised Domain Adaptation, 2020 University of Pennsylvania
Calibrated Prediction With Covariate Shift Via Unsupervised Domain Adaptation, Sangdon Park, Osbert Bastani, James Weimer, Insup Lee
Departmental Papers (CIS)
Reliable uncertainty estimates are an important tool for helping autonomous agents or human decision makers understand and leverage predictive models. However, existing approaches to estimating uncertainty largely ignore the possibility of covariate shift—i.e., where the real-world data distribution may differ from the training distribution. As a consequence, existing algorithms can overestimate certainty, possibly yielding a false sense of confidence in the predictive model. We propose an algorithm for calibrating predictions that accounts for the possibility of covariate shift, given labeled examples from the training distribution and unlabeled examples from the real-world distribution. Our algorithm uses importance weighting to ...
Web Application For Movie Performance Prediction, 2020 California State University, San Bernardino
Web Application For Movie Performance Prediction, Devalkumar Patel
Electronic Theses, Projects, and Dissertations
This is an amazing and unique idea for the web application. The purpose of this application is to address those movie lover people who is always in a hurry to visit the theatre to watch upcoming movies irrespective of which star cast is in it. This system is a mixture of desktop applications, python libraries, and simple math arithmetic. The application can be used by anyone which is ultimately helping them to decide, either they should watch the movie or not. The user just submits the name of the movie. This application is developed in Visual Studio 2019 for functioning ...
Feature Agglomeration Networks For Single Stage Face Detection, 2020 Singapore Management University
Feature Agglomeration Networks For Single Stage Face Detection, Jialiang Zhang, Xiongwei Wu, Steven C. H. Hoi, Jianke Zhu
Research Collection School Of Information Systems
Recent years have witnessed promising results of exploring deep convolutional neural network for face detection. Despite making remarkable progress, face detection in the wild remains challenging especially when detecting faces at vastly different scales and characteristics. In this paper, we propose a novel simple yet effective framework of “Feature Agglomeration Networks” (FANet) to build a new single-stage face detector, which not only achieves state-of-the-art performance but also runs efficiently. As inspired by Feature Pyramid Networks (FPN) (Lin et al., 2017), the key idea of our framework is to exploit inherent multi-scale features of a single convolutional neural network by aggregating ...
Interoperable Ads-B Confidentiality, 2020 Air Force Institute of Technology
Interoperable Ads-B Confidentiality, Brandon C. Burfeind
Theses and Dissertations
The worldwide air traffic infrastructure is in the late stages of transition from legacy transponder systems to Automatic Dependent Surveillance - Broadcast (ADS-B) based systems. ADS-B relies on position information from GNSS and requires aircraft to transmit their identification, state, and position. ADS-B promises the availability of high-fidelity air traffic information; however, position and identification data are not secured via authentication or encryption. This lack of security for ADS-B allows non-participants to observe and collect data on both government and private flight activity. This is a proposal for a lightweight, interoperable ADS-B confidentiality protocol which uses existing format preserving encryption and ...
Techniques To Solve Decision-Making Problems, 2020 Scientific and Innovation Center of Information and Communication Technologies at Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, Address: Amir Temurstreet, 108, 100200, Tashkent city, Republic of Uzbekistan, Phone:+998-95-195-47-52
Techniques To Solve Decision-Making Problems, Dilnoz Tulkunovna Muhamediyeva, Bekmuratov Fayzievich Tulkun
Chemical Technology, Control and Management
Solving decision-making problems in poorly formalized systems only with the help of deterministic and probabilistic methods is insufficient. To do this, it is necessary to widely apply the methods of hybrid intelligent systems and, especially, the methods of “soft” calculations (SoftCalculation, SoftComputing) and the directions of ComputationalIntelligence — intelligent computing technologies that are emerging on this theoretical and methodological base. An immune - fuzzy algorithm for the synthesis of fuzzy inference systems (FIS) is proposed. A two-stage adaptive FIS synthesis algorithm is described. At the first stage, the initial fuzzy parameters are clustered in order to reduce the number of input parameters ...
A Mock Software Company: For Teaching Software Engineering (Cse 455) Course, 2020 California State University, San Bernardino
A Mock Software Company: For Teaching Software Engineering (Cse 455) Course, Arturo Concepcion
Q2S Enhancing Pedagogy
This is a novel way of teaching software engineering as an upper-division course for senior computer science students. Teach the class as a mock software company where students play a role in the “software company” such as project managers, assistant project managers, team leads, software engineers, software designers, UI designers, QA engineers, etc. Then to make a realistic work environment, solicit software projects from real clients, not toy software projects that the instructors think of. It has been proven, pedagogically, that project-based learning is one of the most effective way of teaching. There are no quizzes, no mid-terms, and no ...
Analysis Of Cloud Bursting On Openstack Infrastructure To Aws, 2020 Harrisburg University of Science and Technology
Analysis Of Cloud Bursting On Openstack Infrastructure To Aws, Bao Pham, Ronald C. Jones, Majid Shaalan
Other Student Works
Cloud computing is the development of distributed and parallel computing that seeks to provide a new model of business computing by automating services and efficiently storing proprietary data. Cloud bursting is one of the cloud computing techniques that adopts the hybrid cloud model which seeks to expand the resources of a private cloud through the integration with a public cloud infrastructure. In this paper, the viability of cloud bursting is experimented and an attempt to integrate AWS EC2 onto an Openstack cloud environment using the Openstack OMNI driver is conducted.
Sensitivity Calculations Of High-Speed Optical Receivers Based On Electron-Apds, 2020 University of Sheffield
Sensitivity Calculations Of High-Speed Optical Receivers Based On Electron-Apds, Vladimir Shulyak, Majeed M. Hayat, Jo Shien Ng
Electrical and Computer Engineering Faculty Research and Publications
Sensitivity of high-speed optical receivers is heavily influenced by the performance of the optical detectors used in the receivers, the data rate, and the target bit-error-rate (BER). A simulation model for sensitivity of optical receivers based on electron-avalanche photodiodes (e-APDs) is presented. It allows for the optimization of avalanche width and operating voltage to achieve the optimum receiver sensitivity for given bit rate and target BER. The effects modelled include inter-symbol interference (ISI), various dark current components (tunnelling, diffusion, and generation), current impulse duration, avalanche gain, and amplifier's noise. The model was demonstrated through simulations of Indium Arsenide (InAs ...
Apps For Actionable Workflows: Tools To Stay In The Loop And On Top Of Tasks, 2020 University of Georgia School of Law
Apps For Actionable Workflows: Tools To Stay In The Loop And On Top Of Tasks, Rachel S. Evans
No matter what member of the team you are or what type of library you are in - be it electronic resources manager, cataloger, head of acquisitions, ILS or systems administrator, or even repository coordinator - getting things done and meeting goals depends largely on how you communicate with one another and how you handle your time. Meeting goals and deadlines on both big and small projects in addition to your personal tasks can be achieved less painfully by making effective use of a few on point tools. This session will use the presenter's preferred platforms to show specific examples of ...
Wireless Underground Communications In Sewer And Stormwater Overflow Monitoring: Radio Waves Through Soil And Asphalt Medium, Usman Raza, Abdul Salam
Storm drains and sanitary sewers are prone to backups and overflows due to extra amount wastewater entering the pipes. To prevent that, it is imperative to efficiently monitor the urban underground infrastructure. The combination of sensors system and wireless underground communication system can be used to realize urban underground IoT applications, e.g., storm water and wastewater overflow monitoring systems. The aim of this article is to establish a feasibility of the use of wireless underground communications techniques, and wave propagation through the subsurface soil and asphalt layers, in an underground pavement system for storm water and sewer overflow monitoring ...
Piecing Together Summon Over Alma Documentation, 2020 Embry-Riddle Aeronautical University
Piecing Together Summon Over Alma Documentation, James M. Day
Ex Libris provides some useful documentation for “Alma-Summon Integration” but it is not complete. Most Alma documentation and online help pages assume you are using Primo. Sometimes the Alma configurations for Primo apply to Summon, but mostly they do not. The ELUNA Summon Product Working Group members using Summon over Alma started a project to identify existing documentation, consolidate it, and create supplemental documentation where necessary. We hope this will help Ex Libris provide better support for Summon over Alma.
Human-Machine Communication: Complete Volume. Volume 1, 2020 University of Central Florida
Human-Machine Communication: Complete Volume. Volume 1
This is the complete volume of HMC Volume 1.
Sharing Stress With A Robot: What Would A Robot Say?, 2020 University of Washington
Sharing Stress With A Robot: What Would A Robot Say?, Honson Y. Ling, Elin A. Björling
With the prevalence of mental health problems today, designing human-robot interaction for mental health intervention is not only possible, but critical. The current experiment examined how three types of robot disclosure (emotional, technical, and by-proxy) affect robot perception and human disclosure behavior during a stress-sharing activity. Emotional robot disclosure resulted in the lowest robot perceived safety. Post-hoc analysis revealed that increased perceived stress predicted reduced human disclosure, user satisfaction, robot likability, and future robot use. Negative attitudes toward robots also predicted reduced intention for future robot use. This work informs on the possible design of robot disclosure, as well as ...
The Robot Privacy Paradox: Understanding How Privacy Concerns Shape Intentions To Use Social Robots, 2020 BI Norwegian Business School
The Robot Privacy Paradox: Understanding How Privacy Concerns Shape Intentions To Use Social Robots, Christoph Lutz, Aurelia Tamò-Larrieux
Conceptual research on robots and privacy has increased but we lack empirical evidence about the prevalence, antecedents, and outcomes of different privacy concerns about social robots. To fill this gap, we present a survey, testing a variety of antecedents from trust, technology adoption, and robotics scholarship. Respondents are most concerned about data protection on the manufacturer side, followed by social privacy concerns and physical concerns. Using structural equation modeling, we find a privacy paradox, where the perceived benefits of social robots override privacy concerns.
Building A Stronger Casa: Extending The Computers Are Social Actors Paradigm, 2020 Penn State University
Building A Stronger Casa: Extending The Computers Are Social Actors Paradigm, Andrew Gambino, Jesse Fox, Rabindra A. Ratan
The computers are social actors framework (CASA), derived from the media equation, explains how people communicate with media and machines demonstrating social potential. Many studies have challenged CASA, yet it has not been revised. We argue that CASA needs to be expanded because people have changed, technologies have changed, and the way people interact with technologies has changed. We discuss the implications of these changes and propose an extension of CASA. Whereas CASA suggests humans mindlessly apply human-human social scripts to interactions with media agents, we argue that humans may develop and apply human-media social scripts to these interactions. Our ...
Me And My Robot Smiled At One Another: The Process Of Socially Enacted Communicative Affordance In Human-Machine Communication, 2020 Universidad Adolfo Ibáñez
Me And My Robot Smiled At One Another: The Process Of Socially Enacted Communicative Affordance In Human-Machine Communication, Carmina Rodríguez-Hidalgo
The term affordance has been inconsistently applied both in robotics and communication. While the robotics perspective is mostly object-based, the communication science view is commonly user-based. In an attempt to bring the two perspectives together, this theoretical paper argues that social robots present new social communicative affordances emerging from a two-way relational process. I first explicate conceptual approaches of affordance in robotics and communication. Second, a model of enacted communicative affordance in the context of Human-Machine Communication (HMC) is presented. Third and last, I explain how a pivotal social robot characteristic—embodiment—plays a key role in the process of ...
Ontological Boundaries Between Humans And Computers And The Implications For Human-Machine Communication, 2020 Northern Illinois University
Ontological Boundaries Between Humans And Computers And The Implications For Human-Machine Communication, Andrea L. Guzman
In human-machine communication, people interact with a communication partner that is of a different ontological nature from themselves. This study examines how people conceptualize ontological differences between humans and computers and the implications of these differences for human-machine communication. Findings based on data from qualitative interviews with 73 U.S. adults regarding disembodied artificial intelligence (AI) technologies (voice-based AI assistants, automated-writing software) show that people differentiate between humans and computers based on origin of being, degree of autonomy, status as tool/tool-user, level of intelligence, emotional capabilities, and inherent flaws. In addition, these ontological boundaries are becoming increasingly blurred as ...
Toward An Agent-Agnostic Transmission Model: Synthesizing Anthropocentric And Technocentric Paradigms In Communication, Jaime Banks, Maartje M. A. De Graaf
Technological and social evolutions have prompted operational, phenomenological, and ontological shifts in communication processes. These shifts, we argue, trigger the need to regard human and machine roles in communication processes in a more egalitarian fashion. Integrating anthropocentric and technocentric perspectives on communication, we propose an agent-agnostic framework for human-machine communication. This framework rejects exclusive assignment of communicative roles (sender, message, channel, receiver) to traditionally held agents and instead focuses on evaluating agents according to their functions as a means for considering what roles are held in communication processes. As a first step in advancing this agent-agnostic perspective, this theoretical paper ...
Pac Confidence Sets For Deep Neural Networks Via Calibrated Prediction, 2020 University of Pennsylvania
Pac Confidence Sets For Deep Neural Networks Via Calibrated Prediction, Sangdon Park, Osbert Bastani, Nikolai Matni, Insup Lee
Departmental Papers (CIS)
We propose an algorithm combining calibrated prediction and generalization bounds from learning theory to construct confidence sets for deep neural networks with PAC guarantees---i.e., the confidence set for a given input contains the true label with high probability. We demonstrate how our approach can be used to construct PAC confidence sets on ResNet for ImageNet, a visual object tracking model, and a dynamics model for the half-cheetah reinforcement learning problem.
Tiny Disco: A Cost-Effective, High-Fidelity Wireless Audio System, 2020 California Polytechnic State University, San Luis Obispo
Tiny Disco: A Cost-Effective, High-Fidelity Wireless Audio System, Luke Martin Liberatore
The Tiny Disco is a WiFi based concert system, featuring improvements on popular “Silent Disco” concerts. Rather than being tied to compression and bandwidth restrictions present in traditional silent disco systems, the Tiny Disco system can deliver 320kbps+ audio quality, and allows listeners to bring their own headphones, further lending to the high quality audio experience.
Tiny Disco uses a Raspberry Pi as the audio server, and Espressif ESP32 microcontrollers as audio receivers/clients. The Tiny Disco is primarily geared toward smaller concerts and niche events where audio quality is valued, though due to its WiFi-based architecture, it can be ...