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The Law Of Black Mirror - Syllabus, Yafit Lev-Aretz, Nizan Packin 2020 CUNY Bernard M Baruch College

The Law Of Black Mirror - Syllabus, Yafit Lev-Aretz, Nizan Packin

Open Educational Resources

Using episodes from the show Black Mirror as a study tool - a show that features tales that explore techno-paranoia - the course analyzes legal and policy considerations of futuristic or hypothetical case studies. The case studies tap into the collective unease about the modern world and bring up a variety of fascinating key philosophical, legal, and economic-based questions.


A Review Paper: Analysis Of Weka Data Mining Techniques For Heart Disease Prediction System, Basma Jumaa Saleh, Ahmed Yousif Falih Saedi, Ali Talib Qasim al-Aqbi, Lamees abdalhasan Salman 2020 Al-Mustansiriyah University

A Review Paper: Analysis Of Weka Data Mining Techniques For Heart Disease Prediction System, Basma Jumaa Saleh, Ahmed Yousif Falih Saedi, Ali Talib Qasim Al-Aqbi, Lamees Abdalhasan Salman

Library Philosophy and Practice (e-journal)

Data mining is characterized as searching for useful information through very large data sets. Some of the key and most common techniques for data mining are association rules, classification, clustering, prediction, and sequential models. For a wide range of applications, data mining techniques are used. Data mining plays a significant role in disease detection in the health care industry. The patient should be needed to detect a number of tests for the disease. However, the number of tests should be reduced by using data mining techniques. In time and performance, this reduced test plays an important role. Heart disease is ...


Wait, I'M Tagged?! Toward Ar In Project Aquaticus, Nicholas H. Franck CDT'20, Christa Chewar, Michael Novitzky, Christopher Korpela 2020 United States Military Academy

Wait, I'M Tagged?! Toward Ar In Project Aquaticus, Nicholas H. Franck Cdt'20, Christa Chewar, Michael Novitzky, Christopher Korpela

West Point Research Papers

Human-robot teaming to perform complex tasks in a large environment is limited by the human’s ability to make informed decisions. We aim to use augmented reality to convey critical information to the human to reduce cognitive workload and increase situational awareness. By bridging previous Project Aquaticus work to virtual reality in Unity 3D, we are creating a testbed to easily and repeatedly measure the effectiveness of augmented reality information display solutions to support competitive gameplay. We expect the human-robot teaming performance to be improved due to the increased situational awareness and reduced stress that the augmented reality data display ...


Synthesizing Expressive Behaviors For Humanoid Robots, Mathias Irwan Sunardi 2020 Portland State University

Synthesizing Expressive Behaviors For Humanoid Robots, Mathias Irwan Sunardi

Dissertations and Theses

Humanoid robots are expected to be able to communicate with expressive gestures at the same level of proficiency as humans. However, creating expressive gestures for humanoid robots is difficult and time consuming due to the high number of degrees of freedom (DOF) and the iterations needed to get the desired expressiveness.

Current robot motion editing software has varying levels of sophistication of motion editing tools ranging from basic ones that are text-only, to ones that provide graphical user interfaces (GUIs) which incorporate advanced features, such as curve editors and inverse kinematics. These tools enable users to create simple motions; but ...


Artificial Intelligence And Game Theory Controlled Autonomous Uav Swarms, Janusz Kusyk, M. Umit Uyar, Kelvin Ma, Eltan Samoylov, Ricardo Valdez, Joseph Plishka, Sagor E. Hoque, Giorgio Bertoli, Jefrey Boksiner 2020 CUNY New York City College of Technology

Artificial Intelligence And Game Theory Controlled Autonomous Uav Swarms, Janusz Kusyk, M. Umit Uyar, Kelvin Ma, Eltan Samoylov, Ricardo Valdez, Joseph Plishka, Sagor E. Hoque, Giorgio Bertoli, Jefrey Boksiner

Publications and Research

Autonomous unmanned aerial vehicles (UAVs) operating as a swarm can be deployed in austere environments, where cyber electromagnetic activities often require speedy and dynamic adjustments to swarm operations. Use of central controllers, UAV synchronization mechanisms or pre-planned set of actions to control a swarm in such deployments would hinder its ability to deliver expected services. We introduce artificial intelligence and game theory based flight control algorithms to be run by each autonomous UAV to determine its actions in near real-time, while relying only on local spatial, temporal and electromagnetic (EM) information. Each UAV using our flight control algorithms positions itself ...


Human Supremacy As Posthuman Risk, Daniel Estrada 2020 New Jersey Institute of Technology

Human Supremacy As Posthuman Risk, Daniel Estrada

The Journal of Sociotechnical Critique

Human supremacy is the widely held view that human interests ought to be privileged over other interests as a matter of ethics and public policy. Posthumanism is the historical situation characterized by a critical reevaluation of anthropocentrist theory and practice. This paper draws on animal studies, critical posthumanism, and the critique of ideal theory in Charles Mills and Serene Khader to address the appeal to human supremacist rhetoric in AI ethics and policy discussions, particularly in the work of Joanna Bryson. This analysis identifies a specific risk posed by human supremacist policy in a posthuman context, namely the classification of ...


Artificial Intelligence Towards Future Industrial Opportunities And Challenges, Gizealew Dagnaw 2020 Kennesaw State University

Artificial Intelligence Towards Future Industrial Opportunities And Challenges, Gizealew Dagnaw

African Conference on Information Systems and Technology

The industry 4.0 will bring reflective changes to our society, including an important digital shift in the manufacturing sector. At present, several manufacturing firms are trying to adopt the practices of industry 4.0 throughout their supply chain. The Fourth Industrial Revolution and the artificial intelligence at its core are fundamentally changing the way we live, work and interact as citizens. The complexity of this transformation may look overwhelming and to many threatening. Recently, the dramatic growth of new generation information technologies has prompted several countries to seek new strategies for industrial revolution. The globalization and the competitiveness are ...


Efficient Data Mining Algorithm Network Intrusion Detection System For Masked Feature Intrusions, Kassahun Admkie, Kassahun Admkie Tekle 2020 Kennesaw State University

Efficient Data Mining Algorithm Network Intrusion Detection System For Masked Feature Intrusions, Kassahun Admkie, Kassahun Admkie Tekle

African Conference on Information Systems and Technology

Most researches have been conducted to develop models, algorithms and systems to detect intrusions. However, they are not plausible as intruders began to attack systems by masking their features. While researches continued to various techniques to overcome these challenges, little attention was given to use data mining techniques, for development of intrusion detection. Recently there has been much interest in applying data mining to computer network intrusion detection, specifically as intruders began to cheat by masking some detection features to attack systems. This work is an attempt to propose a model that works based on semi-supervised collective classification algorithm. For ...


Moving Targets: Addressing Concept Drift In Supervised Models For Hacker Communication Detection, Susan McKeever, Brian Keegan, andrei quieroz 2020 Technological University Dublin

Moving Targets: Addressing Concept Drift In Supervised Models For Hacker Communication Detection, Susan Mckeever, Brian Keegan, Andrei Quieroz

Conference papers

Abstract—In this paper, we are investigating the presence of concept drift in machine learning models for detection of hacker communications posted in social media and hacker forums. The supervised models in this experiment are analysed in terms of performance over time by different sources of data (Surface web and Deep web). Additionally, to simulate real-world situations, these models are evaluated using time-stamped messages from our datasets, posted over time on social media platforms. We have found that models applied to hacker forums (deep web) presents an accuracy deterioration in less than a 1-year period, whereas models applied to Twitter ...


Design Of A Robotic Inspection Platform For Structural Health Monitoring, Jason R. Soto 2020 Florida International University

Design Of A Robotic Inspection Platform For Structural Health Monitoring, Jason R. Soto

FIU Electronic Theses and Dissertations

Actively monitoring infrastructure is key to detecting and correcting problems before they become costly. The vast scale of modern infrastructure poses a challenge to monitoring due to insufficient personnel. Certain structures, such as refineries, pose additional challenges and can be expensive, time-consuming, and hazardous to inspect.

This thesis outlines the development of an autonomous robot for structural-health-monitoring. The robot is capable of operating autonomously in level indoor environments and can be controlled manually to traverse difficult terrain. Both visual and lidar SLAM, along with a procedural-mapping technique, allow the robot to capture colored-point-clouds.

The robot is successfully able to automate ...


Short Run Box Maker, Jesus Valdez-Ruelas 2020 California Polytechnic State University, San Luis Obispo

Short Run Box Maker, Jesus Valdez-Ruelas

General Engineering

Small businesses with short run product catalogs have trouble finding the right size box that will work for multiple products. In turn, this leads most businesses to use oversized boxes resulting in unnecessary shipping fees. The objective of this project was to develop and test a cost-effective prototype of a box making machine that could create a short run of custom sized boxes. A Co2 laser was found to be the best option for cutting cardboard and a vertically standing machine was designed to feed the cardboard via rollers. To control cardboard movement stepper motors were used and controlled using ...


Rchex: A Radio-Controlled Hexapod, Dominique Sayo 2020 California Polytechnic State University, San Luis Obispo

Rchex: A Radio-Controlled Hexapod, Dominique Sayo

Computer Engineering

rcHex is a radio-controlled hexapod with 18 degrees of freedom, capable of positional and rotational body adjustment as well as omnidirectional travel at variable speeds using three common gaits. Its general-purpose design accessible to hobbyists makes rcHex an platform for further development, whether it be experimentation in advanced robotic movement or retrofitting sensors to utilize technologies such as computer vision and artificial intelligence. This report explores some of the design intricacies of hexapod movement, including gait sequencing and the application of inverse kinematics to multi-jointed limbs.


Flexible Fault Tolerance For The Robot Operating System, Sukhman S. Marok 2020 California Polytechnic State University, San Luis Obispo

Flexible Fault Tolerance For The Robot Operating System, Sukhman S. Marok

Master's Theses

The introduction of autonomous vehicles has the potential to reduce the number of accidents and save countless lives. These benefits can only be realized if autonomous vehicles can prove to be safer than human drivers. There is a large amount of active research around developing robust algorithms for all parts of the autonomous vehicle stack including sensing, localization, mapping, perception, prediction, planning, and control. Additionally, some of these research projects have involved the use of the Robot Operating System (ROS). However, another key aspect of realizing an autonomous vehicle is a fault-tolerant design that can ensure the safe operation of ...


Surface Autonomous Vehicle For Emergency Rescue, Max Emerick, Ryan Shields, Christopher Feickert, Raymond Impara 2020 California Polytechnic State University, San Luis Obispo

Surface Autonomous Vehicle For Emergency Rescue, Max Emerick, Ryan Shields, Christopher Feickert, Raymond Impara

Mechanical Engineering

The goal of this document is to clearly define the problem parameters and project objectives and to clearly describe the design process, planned final design, and manufacturing and testing procedures for the senior design project of Team 26: SAVER -- the Surface Autonomous Vehicle for Emergency Rescue. This is both for the purpose of project planning and for clear communication between all parties involved in the project.

The objective of the SAVER project is to develop a proof of concept for an autonomous maritime search and rescue vehicle for aiding in man-overboard missions. To accomplish this goal, a list of specifications ...


Lawn Buddy, Jayson Johnston, Andrew Brown, Jacob Maljian 2020 California Polytechnic State University, San Luis Obispo

Lawn Buddy, Jayson Johnston, Andrew Brown, Jacob Maljian

Electrical Engineering

Grass lawns are a common hallmark of the American home. In 2019, a survey from the National Association of Landscape Professionals found that 81% of all Americans owned a lawn [1]. Mowing is a time consuming and costly chore that is part of maintaining a grass lawn. The manual labor in mowing a lawn can exceed 40 hours per year [2]. People commonly incur weekly costs on mowing services to save time. Traditional gas powered mowers are physically demanding and use engines that need routine maintenance. They operate loudly enough that users should be wearing hearing protection and the noise ...


Non-Obstetrical Robotic-Assisted Laparoscopic Surgery In Pregnancy: A Systematic Literature Review., Courtney Capella, Joseph Godovchik, Thenappan Chandrasekar, Huda B. Al-Kouatly 2020 Thomas Jefferson University

Non-Obstetrical Robotic-Assisted Laparoscopic Surgery In Pregnancy: A Systematic Literature Review., Courtney Capella, Joseph Godovchik, Thenappan Chandrasekar, Huda B. Al-Kouatly

Department of Urology Faculty Papers

Urologic and gynecologic surgeons are the top utilizers of robotic surgery; however, non-obstetrical robotic-assisted laparoscopic surgery (RALS) in pregnant patients is infrequent. A systematic literature review was performed to ascertain the frequency, indication and complications of RALS in pregnancy. Results showed thirty-eight pregnancies from eleven publications between 2008-2020. Five cases were for urologic indication and thirty-three for gynecologic indication. Minimal surgical alterations were required. Although no adverse maternal-fetal outcomes were reported, there are not enough cases published to determine safety. This review demonstrates the feasibility of RALS for the pregnant population in the hands of competent robotic surgeons.


Using Taint Analysis And Reinforcement Learning (Tarl) To Repair Autonomous Robot Software, Damian Lyons, Saba Zahra 2020 Fordham University

Using Taint Analysis And Reinforcement Learning (Tarl) To Repair Autonomous Robot Software, Damian Lyons, Saba Zahra

Faculty Publications

It is important to be able to establish formal performance bounds for autonomous systems. However, formal verification techniques require a model of the environment in which the system operates; a challenge for autonomous systems, especially those expected to operate over longer timescales. This paper describes work in progress to automate the monitor and repair of ROS-based autonomous robot software written for an a-priori partially known and possibly incorrect environment model. A taint analysis method is used to automatically extract the data-flow sequence from input topic to publish topic, and instrument that code. A unique reinforcement learning approximation of MDP utility ...


Coordinated Autonomy Of Unmanned Aerial Vehicles (Uavs), Paribartan Dhakal 2020 The University of Southern Mississippi

Coordinated Autonomy Of Unmanned Aerial Vehicles (Uavs), Paribartan Dhakal

Honors Theses

Unmanned Aerial Vehicles (UAVs) are being extensively used in diverse sectors of the society for various tasks ranging from videography to an extremely sensitive situation such as first responders helping during a disaster. It has been seen that if a fleet of UAVs is deployed, they can perform a task quicker and more efficiently than a single UAV. With an increase in the number of UAVs, a problem arises of handling them with proper control structures. It has been studied that the Behavior Trees (BT) can be a better control architecture to handle the autonomous vehicles, as BTs are more ...


Using Robotics And Engineering Design Inquiries To Optimize Learning For Middle Level Teachers: A Case Study, Iman Chafik Chahine, Norman Robinson III, Kimbeni Mansion 2020 North-West University

Using Robotics And Engineering Design Inquiries To Optimize Learning For Middle Level Teachers: A Case Study, Iman Chafik Chahine, Norman Robinson Iii, Kimbeni Mansion

Publications & Research

This exploratory case study reports findings on 20 middle-level science and mathematics teachers’ perceptions of the effectiveness of a one-year project in which teachers engaged in using robotics and engineering design inquiries in their classrooms. Principled by Bandura’s Social Learning Theory (SLT) and using mixed methods approaches, the study measured teachers' efficacy through the Mathematics Teaching Efficacy Belief Instrument (MTEBI) and observation logs before and after the program. The results of this study showed statistically significant differences between PRE MTEBI and POST MTEBI scores. Furthermore, five themes emerged that illuminated potential affordances and constraints that teachers perceive as opportunities ...


Qlime-A Quadratic Local Interpretable Model-Agnostic Explanation Approach, Steven Bramhall, Hayley Horn, Michael Tieu, Nibhrat Lohia 2020 Southern Methodist University

Qlime-A Quadratic Local Interpretable Model-Agnostic Explanation Approach, Steven Bramhall, Hayley Horn, Michael Tieu, Nibhrat Lohia

SMU Data Science Review

In this paper, we introduce a proof of concept that addresses the assumption and limitation of linear local boundaries by Local Interpretable Model-Agnostic Explanations (LIME), a popular technique used to add interpretability and explainability to black box models. LIME is a versatile explainer capable of handling different types of data and models. At the local level, LIME creates a linear relationship for a given prediction through generated sample points to present feature importance. We redefine the linear relationships presented by LIME as quadratic relationships and expand its flexibility in non-linear cases and improve the accuracy of feature interpretations. We coin ...


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