GLOBAL REFERENCE ATMOSPHERIC MODELS FOR AEROASSIST APPLICATIONS

Aeroassist is a broad category of advanced transportation technology encompassing aerocapture, aerobraking, aeroentry, precision landing, hazard detection and avoidance, and aerogravity assist. The eight destinations in the Solar System with sufficient atmosphere to enable aeroassist technology are Venus, Earth, Mars, Jupiter, Saturn, Uranus, Neptune, and Saturn's moon Titan. Engineering-level atmospheric models for five of these targets - Earth, Mars, Titan, Neptune, and Venus - have been developed at NASA's Marshall Space Flight Center. These models are useful as tools in mission planning and systems analysis studies associated with aeroassist applications. The series of models is collectively named the Global Reference Atmospheric Model or GRAM series. An important capability of all the models in the GRAM series is their ability to simulate quasi-random perturbations for Monte Carlo analysis in developing guidance, navigation and control algorithms, for aerothermal design, and for other applications sensitive to atmospheric variability. Recent example applications are discussed

Learning a Planning Domain Model from Natural Language Process Manuals

Artificial intelligence planning techniques have been widely used in many applications. A big challenge is to automate a planning model, especially for planning applications based on natural language (NL) input. This requires the analysis and understanding of NL text and a general learning technique does not exist in real-world applications. In this article, we investigate an intelligent planning technique for natural disaster management, e.g. typhoon contingency plan generation, through natural language process manuals. A planning model is to optimise management operations when a disaster occurs in a short time. Instead of manually building the planning model, we aim to automate the planning model generation by extracting disaster management-related content through NL processing (NLP) techniques. The learning input comes from the published documents that describe the operational process of preventing potential loss in the typhoon management. We adopt a classical planning model, namely planning domain definition language (PDDL), in the typhoon contingency plan generation. We propose a novel framework of FPTCP, which stands for a Framework of Planning Typhoon Contingency Plan , for learning a domain model of PDDL from NL text. We adapt NLP techniques to construct a ternary template of sentences of NL inputs from which actions and their objects are extracted to build a domain model. We also develop a comprehensive suite of user interaction components and facilitate the involvement of users in order to improve the learned domain models. The user interaction is to remove semantic duplicates of NL objects such that the users can select model-generated actions and predicates to better fit the PDDL domain model. We detail the implementation steps of the proposed FPTCP and evaluate its performance on real-world typhoon datasets. In addition, we compare FPTCP with two state-of-the-art approaches in applications of narrative generation, and discuss its capability and limitations

Comparison of models and standards for implementing IT service capacity management

Due to the recent and significant growth of the information technology (IT) services, industries need some sort of framework and / or standards for the management of their services, especially IT services. So, it becomes necessary and essential to define and adopt a set of best practices for providing and effectively managing the technology and services offered throughout its life cycle. Currently, the management of IT applications and services becomes more complex. Predicting and controlling the problems associated with system performance and capacity planning has become a difficult task. For large IT projects, the costs related to performance tuning, performance management and capacity planning, generally turn out to be the biggest and the most uncontrollable costs. In recent years, a number of frameworks aimed at covering certain issues of IT service management have been developed. One of these issues is the IT service capability management. In this paper, a comparison between the models and standards used today regarding capacity management are presented. A comparison of the strengths and weaknesses of each of the models/standards on the capacity management is presented, so that it can guide organizations to select the model/standard that best suits their needs

Large Language Models for Robotics: A Survey

The human ability to learn, generalize, and control complex manipulation tasks through multi-modality feedback suggests a unique capability, which we refer to as dexterity intelligence. Understanding and assessing this intelligence is a complex task. Amidst the swift progress and extensive proliferation of large language models (LLMs), their applications in the field of robotics have garnered increasing attention. LLMs possess the ability to process and generate natural language, facilitating efficient interaction and collaboration with robots. Researchers and engineers in the field of robotics have recognized the immense potential of LLMs in enhancing robot intelligence, human-robot interaction, and autonomy. Therefore, this comprehensive review aims to summarize the applications of LLMs in robotics, delving into their impact and contributions to key areas such as robot control, perception, decision-making, and path planning. We first provide an overview of the background and development of LLMs for robotics, followed by a description of the benefits of LLMs for robotics and recent advancements in robotics models based on LLMs. We then delve into the various techniques used in the model, including those employed in perception, decision-making, control, and interaction. Finally, we explore the applications of LLMs in robotics and some potential challenges they may face in the near future. Embodied intelligence is the future of intelligent science, and LLMs-based robotics is one of the promising but challenging paths to achieve this.Comment: Preprint. 4 figures, 3 table

An Assessment of PIER Electric Grid Research 2003-2014 White Paper

This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014

Correlating Architecture Maturity and Enterprise Systems Usage Maturity to Improve Business/IT Alignment

This paper compares concepts of maturity models in the areas of Enterprise Architecture and Enterprise Systems Usage. We investigate whether these concepts correlate, overlap and explain each other. The two maturity models are applied in a case study. We conclude that although it is possible to fully relate constructs from both kinds of models, having a mature architecture function in a company does not imply a high Enterprise Systems Usage maturity

An extensible manufacturing resource model for process integration

Driven by industrial needs and enabled by process technology and information technology, enterprise integration is rapidly shifting from information integration to process integration to improve overall performance of enterprises. Traditional resource models are established based on the needs of individual applications. They cannot effectively serve process integration which needs resources to be represented in a unified, comprehensive and flexible way to meet the needs of various applications for different business processes. This paper looks into this issue and presents a configurable and extensible resource model which can be rapidly reconfigured and extended to serve for different applications. To achieve generality, the presented resource model is established from macro level and micro level. A semantic representation method is developed to improve the flexibility and extensibility of the model

Specification of vertical semantic consistency rules of UML class diagram refinement using logical approach

Unified Modelling Language (UML) is the most popular modelling language use for software design in software development industries with a class diagram being the most frequently use diagram. Despite the popularity of UML, it is being affected by inconsistency problems of its diagrams at the same or different abstraction levels. Inconsistency in UML is mostly caused by existence of various views on the same system and sometimes leads to potentially conflicting system specifications. In general, syntactic consistency can be automatically checked and therefore is supported by current UML Computer-aided Software Engineering (CASE) tools. Semantic consistency problems, unlike syntactic consistency problems, there exists no specific method for specifying semantic consistency rules and constraints. Therefore, this research has specified twenty-four abstraction rules of class‟s relation semantic among any three related classes of a refined class diagram to semantically equivalent relations of two of the classes using a logical approach. This research has also formalized three vertical semantic consistency rules of a class diagram refinement identified by previous researchers using a logical approach and a set of formalized abstraction rules. The results were successfully evaluated using hotel management system and passenger list system case studies and were found to be reliable and efficient

Efficiency of Selected Risk Management Instruments - An Empirical Analysis of Risk Reduction in Kazakhstani Crop Production

Recent academic discussion regarding crop insurance in developing and transition countries has focused on weather index insurance. But empirical analyses of such schemes based on farm level data cannot be found in the literature, though this insurance type shows clear advantages compared to multiple-peril crop insurance and revenue insurance. Recent empirical applications of risk and stochastic programming models focus on the optimisation of production planning, while literature on the effects of crop insurance on the farm level mainly focuses on the empirical investigation of reductions in farm income variance. The novelty of this paper is that it integrates regionally-adapted insurance products and expert-evaluated technology choices into a programming model that analyses activities with regard to their utility-efficiency. Thus, the objective of this paper is to analyse the effects of different risk management instruments on the certainty equivalent of case study farms in three different regions. Specifically, the applied Expected Utility Model analyses on-farm risk management instruments and crop insurance products with regard to their capability of stabilising farm income. Results indicate that only a combination of on-farm and financial risk management measures increases income and efficiently reduces risk. Weather-based insurance, in combination with intensive technology, stabilises income most efficiently in a specialised grain region in Northern Kazakhstan whereas farm-yield insurance combined with an extensive technology is the preferred risk management option in East Kazakhstan, where diversification with oilproducing crops is possible.Risk, risk management, insurance, agriculture, Kazakhstan, Crop Production/Industries, Risk and Uncertainty, Q12, Q14, G22, D82,