A computer aided teleoperator system Final report

Computer aided teleoperator system for remote handling task

Developing a Modeling Framework for Nonstationary Urban Hydraulic Analyses

Multiple recent national and international climate assessment reports suggest that the frequency, duration and intensity of future extreme precipitation in the North East US will increase. Urban cities in this region like Philadelphia are extremely vulnerable to these impacts due to their combined sewer overflows (CSO). These are mainly due to the fact that the sewer systems receive higher than normal flows during heavy precipitation. Hence, they seek to incorporate the best available information about current and future climate and understand the extent of their impacts on their stormwater network. This project intends to develop a general modeling framework for integrating multiple sources of information such as rain gauge data and climate scenarios for extreme rainfall events with prescribed duration using a Hierarchical Bayesian modeling technique. It aims to develop a stochastic temporal rainfall field simulator for the analysis of the extreme rainfall precipitation events. The approach here is to minimize uncertainties in stationary hydraulic assessment models with non-stationary ones. Five extreme rainfall models were developed for improvements with both stationary and non-stationary modeling frameworks. Recommendations and evaluations of these model outcomes are evaluated and discussed to provide a critical path towards informing climate adaptation decision on the ground.M.S., Environmental Engineering -- Drexel University, 201

An analysis of noise reduction in variable reluctance motors using pulse position randomization

Thesis (Nav. E.)--Massachusetts Institute of Technology, Dept. of Ocean Engineering, 1994, and Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering, 1994.Includes bibliographical references (leaves 80-82).by Melissa C. Smoot.M.S.Nav.E

Algorithms and programming tools for image processing on the MPP, part 2

A number of algorithms were developed for image warping and pyramid image filtering. Techniques were investigated for the parallel processing of a large number of independent irregular shaped regions on the MPP. In addition some utilities for dealing with very long vectors and for sorting were developed. Documentation pages for the algorithms which are available for distribution are given. The performance of the MPP for a number of basic data manipulations was determined. From these results it is possible to predict the efficiency of the MPP for a number of algorithms and applications. The Parallel Pascal development system, which is a portable programming environment for the MPP, was improved and better documentation including a tutorial was written. This environment allows programs for the MPP to be developed on any conventional computer system; it consists of a set of system programs and a library of general purpose Parallel Pascal functions. The algorithms were tested on the MPP and a presentation on the development system was made to the MPP users group. The UNIX version of the Parallel Pascal System was distributed to a number of new sites

Mini-Robot Group User's Guide Part 1: The 11/45 System

A.I. Laboratory Working Papers are produced for internal circulation, and may contain information that is, for example, too preliminary or too detailed for formal publication. Although some will be given a limited external distribution, it is not intended that they should be considered papers to which reference can be made in the literature. This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory's artificial intelligence research is provided in part by the Advanced Research Projects Agency of the Department of Defense under Office of Naval Research contract N00014-75-C-0643.This USER'S GUIDE is in two parts. Part 1 describes the facilities of the mini-robot group 11/45 and the software available to persons using those facilities. It is intended for those writing their own programs to be run on the 11/45 system.MIT Artificial Intelligence Laboratory Department of Defense Advanced Research Projects Agenc

Predicting the Future

Due to the increased capabilities of microprocessors and the advent of graphics processing units (GPUs) in recent decades, the use of machine learning methodologies has become popular in many fields of science and technology. This fact, together with the availability of large amounts of information, has meant that machine learning and Big Data have an important presence in the field of Energy. This Special Issue entitled “Predicting the Future—Big Data and Machine Learning” is focused on applications of machine learning methodologies in the field of energy. Topics include but are not limited to the following: big data architectures of power supply systems, energy-saving and efficiency models, environmental effects of energy consumption, prediction of occupational health and safety outcomes in the energy industry, price forecast prediction of raw materials, and energy management of smart buildings

New Research and Trends in Higher Education

This book aims to discuss new research and trends on all dimensions of Higher Education, as there is a growing interest in the field of Higher Education, regarding new methodologies, contexts, and technologies. It includes investigations of diverse issues that affect the learning processes in Higher Education: innovations in learning, new pedagogical methods, and new learning contexts.In this sense, original research contributions of research papers, case studies and demonstrations that present original scientific results, methodological aspects, concepts and educational technologies, on the following topics:a) Technological Developments in Higher Education: mobile technology, virtual environments, augmented reality, automation and robotics, and other tools for universal learning, focusing on issues that are not addressed by existing research;b) Digital Higher Education: mobile learning, eLearning, Game-based Learning, social media in education, new learning models and technologies and wearable technologies for education;c) Case Studies in Higher Education: empirical studies in higher education regarding digital technologies, new methodologies, new evaluation techniques and tools, perceptions of learning processes efficiency and digital learning best practice

Fuzzy Sets, Fuzzy Logic and Their Applications 2020

The present book contains the 24 total articles accepted and published in the Special Issue “Fuzzy Sets, Fuzzy Logic and Their Applications, 2020” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of fuzzy sets and systems of fuzzy logic and their extensions/generalizations. These topics include, among others, elements from fuzzy graphs; fuzzy numbers; fuzzy equations; fuzzy linear spaces; intuitionistic fuzzy sets; soft sets; type-2 fuzzy sets, bipolar fuzzy sets, plithogenic sets, fuzzy decision making, fuzzy governance, fuzzy models in mathematics of finance, a philosophical treatise on the connection of the scientific reasoning with fuzzy logic, etc. It is hoped that the book will be interesting and useful for those working in the area of fuzzy sets, fuzzy systems and fuzzy logic, as well as for those with the proper mathematical background and willing to become familiar with recent advances in fuzzy mathematics, which has become prevalent in almost all sectors of the human life and activity

Quantitative Methods for Economics and Finance

This book is a collection of papers for the Special Issue “Quantitative Methods for Economics and Finance” of the journal Mathematics. This Special Issue reflects on the latest developments in different fields of economics and finance where mathematics plays a significant role. The book gathers 19 papers on topics such as volatility clusters and volatility dynamic, forecasting, stocks, indexes, cryptocurrencies and commodities, trade agreements, the relationship between volume and price, trading strategies, efficiency, regression, utility models, fraud prediction, or intertemporal choice

Sustainability, Digital Transformation and Fintech: The New Challenges of the Banking Industry

In the current competitive scenario, the banking industry must contend with multiple challenges tied to regulations, legacy systems, disruptive models/technologies, new competitors, and a restive customer base, while simultaneously pursuing new strategies for sustainable growth. Banking institutions that can address these emerging challenges and opportunities to effectively balance long-term goals with short-term performance pressures could be aptly rewarded. This book comprises a selection of papers addressing some of these relevant issues concerning the current challenges and opportunities for international banking institutions. Papers in this collection focus on the digital transformation of the banking industry and its effect on sustainability, the emergence of new competitors such as FinTech companies, the role of mobile banking in the industry, the connections between sustainability and financial performance, and other general sustainability and corporate social responsibility (CSR) topics related to the banking industry. The book is a Special Issue of the MDPI journal Sustainability, which has been sponsored by the Santander Financial Institute (SANFI), a Spanish research and training institution created as a collaboration between Santander Bank and the University of Cantabria. SANFI works to identify, develop, support, and promote knowledge, study, talent, and innovation in the financial sector