วงจรควอนตัมสำหรับขั้นตอนวิธีการของชอร์,
2020
คณะวิศวกรรมศาสตร์
วงจรควอนตัมสำหรับขั้นตอนวิธีการของชอร์, วิภู เมธาชวลิต
Chulalongkorn University Theses and Dissertations (Chula ETD)
วิธีขั้นตอนการหาตัวประกอบจำนวนเฉพาะของชอร์เป็นหนึ่งในปัญหาที่น่าสนใจสำหรับคอมพิวเตอร์ควอนตัม โดยงานวิจัยนี้ต้องศึกษาถึงพฤติกรรมของวงจรขั้นตอนวิธีการของชอร์เมื่อนำมาใช้กับคอมพิวเตอร์ควอนตัมในปัจจุบัน โดยเลือกนำการออกแบบวงจรที่นำเสนอไว้โดย สตีเฟ่น เบอรีการ์ด มาทำการทดลองบนคอมพิวเตอร์ควอนตัมของทางบริษัทไอบีเอ็มขนาด 15 คิวบิต
Multi-Evidence Learning For Medical Diagnosis,
2020
Faculty of Engineering
Multi-Evidence Learning For Medical Diagnosis, Tongjai Yampaka
Chulalongkorn University Theses and Dissertations (Chula ETD)
In recent years, a great many approaches for learning from multiple sources by considering the diversity of different views have been proposed. The most interesting field is medical diagnosis. For example, breast cancer screening normally employs two views of mammography (Cranio-Caudal and Medio-Lateral-Oblique) or two modes of ultrasound (B-mode and Doppler mode) breast images. This study proposes a multi-evidence learning model that combines the multiple evidences of breast images to improve diagnosis. Two views mammography and two modes of ultrasound were used. Our proposed model consists of four stages. First, feature extraction using Convolutional Neuron Networks was operated to extract …
Adaptive Object Detection For Autonomous Vehicles,
2020
Northern Illinois University
Adaptive Object Detection For Autonomous Vehicles, Christopher Wolfe
Graduate Research Theses & Dissertations
Autonomous vehicles are gradually entering our daily lives. The goal of fully autonomous commercially available vehicles is becoming closer to reality each day as the contributions from researchers and various institutions are being added to the overall body of knowledge. Object detection is a critical component of an autonomous or semi-autonomous vehicle and draws extensively on results from many fields such as image processing and statistics. In this thesis, we consider ideas from the study of real-time computing and control systems to present a novel method of real-time adaptive object detection. We present a conceptual framework of the method as …
A Multi-Constraint Predictive Control System With Auxiliary Emergency Controllerfor Autonomous Vehicles,
2020
Northern Illinois University
A Multi-Constraint Predictive Control System With Auxiliary Emergency Controllerfor Autonomous Vehicles, Farhad Partovi Ebrahimpour
Graduate Research Theses & Dissertations
In the last few years, several research groups and companies have worked on developing autonomous vehicles. Among the first automation layers, the safety layer plays a significant role in this field. However, considering safety should not diminish the importance of the efficiency of the vehicle in terms of path tracking with the desired speed. This thesis introduces a multi-constraint predictive control algorithm along with a safety layer to guarantee object avoidance in emergency situations. First, there is a quick review of autonomous cars and their functionalities. In the following, a controller switching mechanism is proposed and designed. It switches the …
Table Of Contents Jitim Vol 29 Issue 2, 2020,
2020
California State University, San Bernardino
Table Of Contents Jitim Vol 29 Issue 2, 2020
Journal of International Technology and Information Management
Table of contents
Instructor Activity Recognition Using Smartwatch And Smartphone Sensors,
2020
Georgia Southern University
Instructor Activity Recognition Using Smartwatch And Smartphone Sensors, Zayed Uddin Chowdhury
College of Graduate Studies: Theses & Dissertations
During a classroom session, an instructor performs several activities, such as writing on the board, speaking to the students, gestures to explain a concept. A record of the time spent in each of these activities could be valuable information for the instructors to virtually observe their own style of instruction. It can help in identifying activities that engage the students more, thereby enhancing teaching effectiveness and efficiency. In this work, we present a preliminary study on profiling multiple activities of an instructor in the classroom using smartwatch and smartphone sensor data. We use 2 benchmark datasets to test out the …
Quantitative Performance Assessment Of Lidar-Based Vehicle Contour Estimation Algorithms For Integrated Vehicle Safety Applications,
2020
Georgia Southern University
Quantitative Performance Assessment Of Lidar-Based Vehicle Contour Estimation Algorithms For Integrated Vehicle Safety Applications, David M. Mothershed
College of Graduate Studies: Theses & Dissertations
Many nations and organizations are committing to achieving the goal of `Vision Zero' and eliminate road traffic related deaths around the world. Industry continues to develop integrated safety systems to make vehicles safer, smarter and more capable in safety critical scenarios. Passive safety systems are now focusing on pre-crash deployment of restraint systems to better protect vehicle passengers. Current commonly used bounding box methods for shape estimation of crash partners lack the fidelity required for edge case collision detection and advanced crash modeling. This research presents a novel algorithm for robust and accurate contour estimation of opposing vehicles. The presented …
Compound Vision Approach For Autonomous Vehicles Navigation,
2020
University of Texas at El Paso
Compound Vision Approach For Autonomous Vehicles Navigation, Michael Mikhael
Open Access Theses & Dissertations
An analogy can be made between the sensing that occurs in simple robots and drones and that in insects and crustaceans, especially in basic navigation requirements. Thus, an approach in robots/drones based on compound eye vision could be useful. In this research, several image processing algorithms were used to detect and track moving objects starting with images upon which a grid (compound eye image) was superimposed, including contours detection, the second moments of those contours along with the grid applied to the original image, and Fourier Transforms and inverse Fourier Transforms. The latter also provide information about scene or camera …
Evaluating Flow Features For Network Application Classification,
2020
University of Texas at El Paso
Evaluating Flow Features For Network Application Classification, Carlos Alcantara
Open Access Theses & Dissertations
Communication networks provide the foundational services on which our modern economy depends. These services include data storage and transfer, video and voice telephony, gaming, multimedia streaming, remote invocation, and the world wide web. Communication networks are large-scale distributed systems composed of heterogeneous equipment. As a result of scale and heterogeneity, communication networks are cumbersome to manage (e.g., configure, assess performance, detect faults) by human operators. With the emergence of easily accessible network data and machine learning algorithms, there is a great opportunity to move network management towards increasing automation. Network management automation will allow for a reduced likelihood of human …
Real-Time Urban Weather Observations For Urban Air Mobility,
2020
Embry-Riddle Aeronautical University
Real-Time Urban Weather Observations For Urban Air Mobility, Kevin A. Adkins, Mustafa Akbas, Marc Compere
International Journal of Aviation, Aeronautics, and Aerospace
Cities of the future will have to overcome congestion, air pollution and increasing infrastructure cost while moving more people and goods smoothly, efficiently and in an eco-friendly manner. Urban air mobility (UAM) is expected to be an integral component of achieving this new type of city. This is a new environment for sustained aviation operations. The heterogeneity of the urban fabric and the roughness elements within it create a unique environment where flight conditions can change frequently across very short distances. UAM vehicles with their lower mass, more limited thrust and slower speeds are especially sensitive to these conditions. Since …
Zips Racing Electric Can Communications,
2020
The University of Akron
Zips Racing Electric Can Communications, Andrew Jordan, Adam Long, Susanah Kowalewski, Rami Nehme
Williams Honors College, Honors Research Projects
The CAN protocol has been a standard of electronic communication networks of automotive vehicles since the early 2000s due to its robust reliability in harsh environments. For the 2020 competition year, the Zips Racing Electric design team will be building an entirely new, fully-electric vehicle with CAN communication implemented rather than communicating via pure analog signals. Hardware and software can be utilized to read analog electrical signals from a source, such as accelerator and brake sensors, and encode them into a digital message that meets the CAN 2.0B communication protocol standard. Likewise, software can be used to extract data from …
Smart Collar,
2020
The University of Akron
Smart Collar, Gretchen T. Woodling, Sean Moran, Justen Bischoff, Jacob Sindelar
Williams Honors College, Honors Research Projects
The Smart Collar is a universal pet tracker, designed to be small and exceedingly comfortable for any pet to wear. GPS technology is used to locate the device, allowing the user to track their pet, via a smart phone application. This application can be used to program the device, view maps of their pet’s location and history of travel. Operating primarily on Long Range Wide Area Network (LoRaWAN) for data transfer, the device consumes very little power, allowing for several days of run-time per charge of the battery. Boasting no monthly service fees, The Smart Collar provides pet owner’s an …
Piezoelectric Energy Harvester Improvement,
2020
The University of Akron
Piezoelectric Energy Harvester Improvement, Nathan Embaugh, Jason Mack, Jeremiah Fitzgerald, Zachary J. Lindsey
Williams Honors College, Honors Research Projects
The energy harvester is used to convert a portion of the tire deflection waste energy to power up tire embedded sensors. A piezoelectric energy harvester is designed and some preliminary tests are done on it. So far, it has been shown that this design is sufficient for tire application. The team will need to modify the design of the energy harvester, the measurement setup and add a temperature and a strain senor to the existing setup so that the tire deflection and temperature can be measured and at the same time the energy harvester should be tested to see how …
Data Science Methods For Standardization, Safety, And Quality Assurance In Radiation Oncology,
2020
Virginia Commonwealth University
Data Science Methods For Standardization, Safety, And Quality Assurance In Radiation Oncology, Khajamoinuddin Syed
Theses and Dissertations
Radiation oncology is the field of medicine that deals with treating cancer patients through ionizing radiation. The clinical modality or technique used to treat the cancer patients in the radiation oncology domain is referred to as radiation therapy. Radiation therapy aims to deliver precisely measured dose irradiation to a defined tumor volume (target) with as minimal damage as possible to surrounding healthy tissue (organs-at-risk), resulting in eradication of the tumor, high quality of life, and prolongation of survival. A typical radiotherapy process requires the use of different clinical systems at various stages of the workflow. The data generated in these …
Explainable Ai Using Knowledge Graphs,
2020
University of South Carolina - Columbia
Explainable Ai Using Knowledge Graphs, Manas Gaur, Ankit Desai, Keyur Faldu, Amit Sheth
Publications
During the last decade, traditional data-driven deep learning (DL) has shown remarkable success in essential natural language processing tasks, such as relation extraction. Yet, challenges remain in developing artificial intelligence (AI) methods in real-world cases that require explainability through human interpretable and traceable outcomes. The scarcity of labeled data for downstream supervised tasks and entangled embeddings produced as an outcome of self-supervised pre-training objectives also hinders interpretability and explainability. Additionally, data labeling in multiple unstructured domains, particularly healthcare and education, is computationally expensive as it requires a pool of human expertise. Consider Education Technology, where AI systems fall along a …
Relational Sequential Decision Making,
2020
University of South Carolina Columbia
Relational Sequential Decision Making, Kaushik Roy
Publications
Markov Decision Processes(MDPs) are the standard for sequential decision making. Comprehensive theory and methods have been developed to deal with solving MDPs in the propositional setting. Real world domains however are naturally represented using objects and relationships. To this effect, relational adaptations of algorithms to solve MDPs have been proposed in recent years. This paper presents a study of these techniques both in the model based and model free setting.
Knowledge-Infused Statistical Learning For Social Good,
2020
University of South Carolina - Columbia
Knowledge-Infused Statistical Learning For Social Good, Kaushik Roy, Manas Gaur
Publications
Humans are able to provide symbolic knowledge in structured form for potential use by an AI system in learning human-desirable concepts. In clinical settings, for instance, prediction of patient outcomes by an AI can be guided by knowledge from patient history. This history contains concepts such as treatment information, observational and drug-related information, mental health conditions, and severity of disease/disorder. Additionally, there is also often a certain graphical structure to the knowledge among the concepts, for example, ”patient symptoms cause certain tests to be taken”, which in turn affects the prescription of medication. This type of structure between human interpretable …
Exploring The Relationship Between Teamwork Skills And Team Members' Centrality,
2020
Old Dominion University
Exploring The Relationship Between Teamwork Skills And Team Members' Centrality, Francisco Cima, Pilar Pazos, Ana Maria Canto
Engineering Management & Systems Engineering Faculty Publications
The present paper describes an exploratory study of small teams working on a four-month project as part of a graduate engineering program. The research had two primary goals. The first was to utilize the log files from shared repositories used for team collaboration to describe the network structure of the teams. The second was to determine whether the network centrality of any individual team member is associated with their teamwork skills and attitudes towards the collaboration platform. The relationship between teamwork skills, attitudes towards the collaboration technology, and the centrality index was explored using Pearson correlations. A total of 35 …
Applications Of Artificial Intelligence To Cryptography,
2020
Technological University Dublin
Applications Of Artificial Intelligence To Cryptography, Jonathan Blackledge, Napo Mosola
Articles
This paper considers some recent advances in the field of Cryptography using Artificial Intelligence (AI). It specifically considers the applications of Machine Learning (ML) and Evolutionary Computing (EC) to analyze and encrypt data. A short overview is given on Artificial Neural Networks (ANNs) and the principles of Deep Learning using Deep ANNs. In this context, the paper considers: (i) the implementation of EC and ANNs for generating unique and unclonable ciphers; (ii) ML strategies for detecting the genuine randomness (or otherwise) of finite binary strings for applications in Cryptanalysis. The aim of the paper is to provide an overview on …
Novel Approaches For Reliable And Efficient Circuit Design,
2020
Missouri University of Science and Technology
Novel Approaches For Reliable And Efficient Circuit Design, Prashanthi Metku
Doctoral Dissertations
"In this research work, a suite of approaches are presented to improve reliability of 3D heterogeneous processors (3DHP) and to reduce the area overhead of asynchronous designs. This work is primarily divided into two parts. In the first part, we present an approach for improving reliability in 3DHP. Typically, in 3DHP, thermal hotspots introduce spatial and temporal variability that results in wide bit error variation in DRAM dies. To address this issue multi- path BCH decoder is introduced. Based on the thermal gradient data generated by on-chip temperature sensors, the proposed methodology specializes in adaptively estimating the number of errors …
