Research and applications: Artificial intelligence

The program is reported for developing techniques in artificial intelligence and their application to the control of mobile automatons for carrying out tasks autonomously. Visual scene analysis, short-term problem solving, and long-term problem solving are discussed along with the PDP-15 simulator, LISP-FORTRAN-MACRO interface, resolution strategies, and cost effectiveness

Demonstrating Advantages of Neuromorphic Computation: A Pilot Study

Neuromorphic devices represent an attempt to mimic aspects of the brain's architecture and dynamics with the aim of replicating its hallmark functional capabilities in terms of computational power, robust learning and energy efficiency. We employ a single-chip prototype of the BrainScaleS 2 neuromorphic system to implement a proof-of-concept demonstration of reward-modulated spike-timing-dependent plasticity in a spiking network that learns to play the Pong video game by smooth pursuit. This system combines an electronic mixed-signal substrate for emulating neuron and synapse dynamics with an embedded digital processor for on-chip learning, which in this work also serves to simulate the virtual environment and learning agent. The analog emulation of neuronal membrane dynamics enables a 1000-fold acceleration with respect to biological real-time, with the entire chip operating on a power budget of 57mW. Compared to an equivalent simulation using state-of-the-art software, the on-chip emulation is at least one order of magnitude faster and three orders of magnitude more energy-efficient. We demonstrate how on-chip learning can mitigate the effects of fixed-pattern noise, which is unavoidable in analog substrates, while making use of temporal variability for action exploration. Learning compensates imperfections of the physical substrate, as manifested in neuronal parameter variability, by adapting synaptic weights to match respective excitability of individual neurons.Comment: Added measurements with noise in NEST simulation, add notice about journal publication. Frontiers in Neuromorphic Engineering (2019

Alternative sweetener from curculigo fruits

This study gives an overview on the advantages of Curculigo Latifolia as an alternative sweetener and a health product. The purpose of this research is to provide another option to the people who suffer from diabetes. In this research, Curculigo Latifolia was chosen, due to its unique properties and widely known species in Malaysia. In order to obtain the sweet protein from the fruit, it must go through a couple of procedures. First we harvested the fruits from the Curculigo trees that grow wildly in the garden. Next, the Curculigo fruits were dried in the oven at 50 0C for 3 days. Finally, the dried fruits were blended in order to get a fine powder. Curculin is a sweet protein with a taste-modifying activity of converting sourness to sweetness. The curculin content from the sample shown are directly proportional to the mass of the Curculigo fine powder. While the FTIR result shows that the sample spectrum at peak 1634 cm–1 contains secondary amines. At peak 3307 cm–1 contains alkynes

Advances in quantum machine learning

Here we discuss advances in the field of quantum machine learning. The following document offers a hybrid discussion; both reviewing the field as it is currently, and suggesting directions for further research. We include both algorithms and experimental implementations in the discussion. The field's outlook is generally positive, showing significant promise. However, we believe there are appreciable hurdles to overcome before one can claim that it is a primary application of quantum computation.Comment: 38 pages, 17 Figure

Space Station Freedom automation and robotics: An assessment of the potential for increased productivity

This report presents the results of a study performed in support of the Space Station Freedom Advanced Development Program, under the sponsorship of the Space Station Engineering (Code MT), Office of Space Flight. The study consisted of the collection, compilation, and analysis of lessons learned, crew time requirements, and other factors influencing the application of advanced automation and robotics, with emphasis on potential improvements in productivity. The lessons learned data collected were based primarily on Skylab, Spacelab, and other Space Shuttle experiences, consisting principally of interviews with current and former crew members and other NASA personnel with relevant experience. The objectives of this report are to present a summary of this data and its analysis, and to present conclusions regarding promising areas for the application of advanced automation and robotics technology to the Space Station Freedom and the potential benefits in terms of increased productivity. In this study, primary emphasis was placed on advanced automation technology because of its fairly extensive utilization within private industry including the aerospace sector. In contrast, other than the Remote Manipulator System (RMS), there has been relatively limited experience with advanced robotics technology applicable to the Space Station. This report should be used as a guide and is not intended to be used as a substitute for official Astronaut Office crew positions on specific issues

A framework for smart traffic management using heterogeneous data sources

A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy.Traffic congestion constitutes a social, economic and environmental issue to modern cities as it can negatively impact travel times, fuel consumption and carbon emissions. Traffic forecasting and incident detection systems are fundamental areas of Intelligent Transportation Systems (ITS) that have been widely researched in the last decade. These systems provide real time information about traffic congestion and other unexpected incidents that can support traffic management agencies to activate strategies and notify users accordingly. However, existing techniques suffer from high false alarm rate and incorrect traffic measurements. In recent years, there has been an increasing interest in integrating different types of data sources to achieve higher precision in traffic forecasting and incident detection techniques. In fact, a considerable amount of literature has grown around the influence of integrating data from heterogeneous data sources into existing traffic management systems. This thesis presents a Smart Traffic Management framework for future cities. The proposed framework fusions different data sources and technologies to improve traffic prediction and incident detection systems. It is composed of two components: social media and simulator component. The social media component consists of a text classification algorithm to identify traffic related tweets. These traffic messages are then geolocated using Natural Language Processing (NLP) techniques. Finally, with the purpose of further analysing user emotions within the tweet, stress and relaxation strength detection is performed. The proposed text classification algorithm outperformed similar studies in the literature and demonstrated to be more accurate than other machine learning algorithms in the same dataset. Results from the stress and relaxation analysis detected a significant amount of stress in 40% of the tweets, while the other portion did not show any emotions associated with them. This information can potentially be used for policy making in transportation, to understand the users��� perception of the transportation network. The simulator component proposes an optimisation procedure for determining missing roundabouts and urban roads flow distribution using constrained optimisation. Existing imputation methodologies have been developed on straight section of highways and their applicability for more complex networks have not been validated. This task presented a solution for the unavailability of roadway sensors in specific parts of the network and was able to successfully predict the missing values with very low percentage error. The proposed imputation methodology can serve as an aid for existing traffic forecasting and incident detection methodologies, as well as for the development of more realistic simulation networks

Functional requirements for the man-vehicle systems research facility

The NASA Ames Research Center proposed a man-vehicle systems research facility to support flight simulation studies which are needed for identifying and correcting the sources of human error associated with current and future air carrier operations. The organization of research facility is reviewed and functional requirements and related priorities for the facility are recommended based on a review of potentially critical operational scenarios. Requirements are included for the experimenter's simulation control and data acquisition functions, as well as for the visual field, motion, sound, computation, crew station, and intercommunications subsystems. The related issues of functional fidelity and level of simulation are addressed, and specific criteria for quantitative assessment of various aspects of fidelity are offered. Recommendations for facility integration, checkout, and staffing are included

Space life sciences strategic plan

Over the last three decades the Life Sciences Program has significantly contributed to NASA's manned and unmanned exploration of space, while acquiring new knowledge in the fields of space biology and medicine. The national and international events which have led to the development and revision of NASA strategy will significantly affect the future of life sciences programs both in scope and pace. This document serves as the basis for synthesizing the options to be pursued during the next decade, based on the decisions, evolution, and guiding principles of the National Space Policy. The strategies detailed in this document are fully supportive of the Life Sciences Advisory Subcommittee's 'A Rationale for the Life Sciences,' and the recent Aerospace Medicine Advisory Committee report entitled 'Strategic Considerations for Support of Humans in Space and Moon/Mars Exploration Missions.' Information contained within this document is intended for internal NASA planning and is subject to policy decisions and direction, and to budgets allocated to NASA's Life Sciences Program

Neural Networks for Modeling and Control of Particle Accelerators

We describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.Comment: 21 p

The use of a shiphandling simulator to complement practical training at the Saudi Border Guard Naval Institute [SBGNI]

The dissertation introduces the use of a shiphandling simulator to complement the theoretical training of students at the Saudi Border Guard Naval Institute. A review of the requirements of the 1995 STCW Convention in regard to the use of simulators for training and assessment and the implementation of a quality standard system is undertaken. The training of students and also of experienced mariners is a task for which simulators have become an increasingly valuable tool. The use of simulators for training purposes is especially important for MET institutions in which the practical training of students on board training ships is decreasing and in those areas in which the use of real vessels for training shows a risk to the mariner, to the vessel, to property and to the environment. The background to the development and use of simulators is considered at length and the possibility of having simulators for both training and assessment of performance at the Institute is discussed. One of the conclusions is that trainees at the Institute can be trained in manoeuvring conditions that would take many years to encounter in real life, and that due to the modernisation of the fleet, the experienced mariner can benefit from this type of training when required to transfer to ships of different size, type, propulsion, manoeuvring systems and modem navigational equipment The dissertation concludes that a change is appropriate, if the SBGNI wants to modernise the programs and curriculum and that the actual theoretical training does not guarantee the ability to perform. This would be the role of simulation, to produce practical situations so that trainees could gain experience under controlled and repeatable conditions