Towards the ensemble: IPCBR model in investigating financial bubbles

Asset value predictability remains a major research concern in financial market especially when considering the effect of unprecedented market fluctuations on the behaviour of market participants. This paper presents preliminary results toward the building a reliable forward problem on ensemble approach IPCBR model, that leverages the capabilities of Case based Reasoning(CBR) and Inverse Problem Techniques (IPTs) to describe and model abnormal stock market fluctuations (often associated with asset bubbles) using datasets from historical stock market prices. The framework uses a rich set of past observations and geometric pattern description and then applies a CBR to formulate the forward problem, Inverse Problem formulation is then applied to identify a set of parameters that can statistically be associated with the occurrence of the observed patterns. This research work presents a formative strategy aimed to determine the causes of behaviour, rather than predict future time series points which brings a novel perspective to the problem of asset bubbles predictability, and a deviation from the existing research trend. The results depict the stock dynamics and statistical fluctuating evidence associated with the envisaged bubble problem

Internal Combustion Engines

This book on internal combustion engines brings out few chapters on the research activities through the wide range of current engine issues. The first section groups combustion-related papers including all research areas from fuel delivery to exhaust emission phenomena. The second one deals with various problems on engine design, modeling, manufacturing, control and testing. Such structure should improve legibility of the book and helps to integrate all singular chapters as a logical whole

Text Similarity Between Concepts Extracted from Source Code and Documentation

Context: Constant evolution in software systems often results in its documentation losing sync with the content of the source code. The traceability research field has often helped in the past with the aim to recover links between code and documentation, when the two fell out of sync. Objective: The aim of this paper is to compare the concepts contained within the source code of a system with those extracted from its documentation, in order to detect how similar these two sets are. If vastly different, the difference between the two sets might indicate a considerable ageing of the documentation, and a need to update it. Methods: In this paper we reduce the source code of 50 software systems to a set of key terms, each containing the concepts of one of the systems sampled. At the same time, we reduce the documentation of each system to another set of key terms. We then use four different approaches for set comparison to detect how the sets are similar. Results: Using the well known Jaccard index as the benchmark for the comparisons, we have discovered that the cosine distance has excellent comparative powers, and depending on the pre-training of the machine learning model. In particular, the SpaCy and the FastText embeddings offer up to 80% and 90% similarity scores. Conclusion: For most of the sampled systems, the source code and the documentation tend to contain very similar concepts. Given the accuracy for one pre-trained model (e.g., FastText), it becomes also evident that a few systems show a measurable drift between the concepts contained in the documentation and in the source code.</p

NASA SBIR abstracts of 1991 phase 1 projects

The objectives of 301 projects placed under contract by the Small Business Innovation Research (SBIR) program of the National Aeronautics and Space Administration (NASA) are described. These projects were selected competitively from among proposals submitted to NASA in response to the 1991 SBIR Program Solicitation. The basic document consists of edited, non-proprietary abstracts of the winning proposals submitted by small businesses. The abstracts are presented under the 15 technical topics within which Phase 1 proposals were solicited. Each project was assigned a sequential identifying number from 001 to 301, in order of its appearance in the body of the report. Appendixes to provide additional information about the SBIR program and permit cross-reference of the 1991 Phase 1 projects by company name, location by state, principal investigator, NASA Field Center responsible for management of each project, and NASA contract number are included

Contributions from computational intelligence to healthcare data processing

80 p.The increasing ability to gather, store and process health care information, through the electronic health records and improved communication methods opens the door for new applications intended to improve health care in many different ways. Crucial to this evolution is the development of new computational intelligence tools, related to machine learning and statistics. In this thesis we have dealt with two case studies involving health data. The first is the monitoring of children with respiratory diseases in the pediatric intensive care unit of a hospital. The alarm detection is stated as a classification problem predicting the triage selected by the nurse or medical doctor. The second is the prediction of readmissions leading to hospitalization in an emergency department of a hospital. Both problems have great impact in economic and personal well being. We have tackled them with a rigorous methodological approach, obtaining results that may lead to a real life implementation. We have taken special care in the treatment of the data imbalance. Finally we make propositions to bring these techniques to the clinical environment

Aeronautical engineering: A cumulative index to a continuing bibliography (supplement 274)

This publication is a cumulative index to the abstracts contained in supplements 262 through 273 of Aeronautical Engineering: A Continuing Bibliography. The bibliographic series is compiled through the cooperative efforts of the American Institute of Aeronautics and Astronautics (AIAA) and the National Aeronautics and Space Administration (NASA). Seven indexes are included: subject, personal author, corporate source, foreign technology, contract number, report number, and accession number

Situational awareness-based energy management for unmanned electric surveillance platforms

In the present day fossil fuel availability, cost, security and the pollutant emissions resulting from its use have driven industry into looking for alternative ways of powering vehicles. The aim of this research is to synthesize/design and develop a framework of novel control architectures which can result in complex powered vehicle subsystems to perform better with reduced exogeneuous information. This research looks into the area of energy management by proposing an intelligent based system which not only looks at the beaten path of where energy comes from and how much of it to use, but it goes further by taking into consideration the world around it. By operating without GPS, it realies on data such as usage, average consumption, system loads and even other surrounding vehicles are considered when making the difficult decisions of where to direct the energy into, how much of it, and even when to cut systems off in benefit of others. All this is achieved in an integrated way by working within the limitations of non-fossil fuelled energy sources like fuel cells, ultracapacitors and battery banks using driver-provided information or by crafting an artificial usage profile from historicaly learnt data. By using an organic computing philosophy based on artificial intelligence this alternative approach to energy supply systems presents a different perspective beginning by accepting the fact that when hardware is set energy can be optimized only so much and takes a step further by answering the question of how to best manage it when refuelling might not be an option. The result is a situationally aware system concept that is portable to any type of electrically powered platform be it ground, aerial or marine since it operates on the fact that all operate within three dimensional space. The system´s capabilities are then verified in a virtual reality environment which can be tailored to the meet reseach needs including allowing for different altitudes, environmental temperature and humidity profiles. This VR system is coupled with a chassis dynamometer to allow for testing of real physical prototype unmanned ground vehicles where the intelligent system will benefit by learning from real platform data. The Thesis contributions and objectives are summarised next: The control system proposed includes an awareness of the surroundings within which the vehicle is operating without relying on GPS position information. The system proposed is portable and could be used to control other systems. The test platform developed within the Thesis is flexible and could be used for other systems. The control system for the fuel cell system described within the work has included an allowance for altitude and humidity. These factors would appear to be significant for such systems. The structure of the control system and its hierarchy is novel. The ability of the system to be applied to a UAV and as such control a ‘vehicle’ in 3 dimensions, and yet be also applied to a ground vehicle, where roll and pitch are largely a function of the ground over which it travels (so the UGV only uses a subset of the control functionality). The mission awareness of the control structure appears to be the heart of the potential contribution to knowledge, and that this also includes the ability to create an estimated, artificial mission profile should one not be input by the operators. This learnt / adaptive input could be expanded on to highlight this aspect

Aeronautical engineering: A continuing bibliography with indexes (supplement 223)

This bibliography lists 423 reports, articles, and other documents introduced into the NASA scientific and technical information system in January, 1988