scholarly journals Applying Knowledge Discovery Process in General Aviation Flight Performance Analysis

2020 ◽  
Vol 04 (2) ◽  
Author(s):  
Chenyu Huang
Keyword(s):  
Performance Analysis ◽  
Knowledge Discovery ◽  
General Aviation ◽  
Flight Performance ◽  
Discovery Process

Biojet fuel production from oleaginous crop residues: thermoeconomic, life cycle and flight performance analysis

2021 ◽  
Vol 244 ◽  
pp. 114534
Author(s):  
Nicolas Vela-García ◽  
David Bolonio ◽  
María-Jesús García-Martínez ◽  
Marcelo F. Ortega ◽  
Daniela Almeida Streitwieser ◽  
...  
Keyword(s):  
Life Cycle ◽  
Performance Analysis ◽  
Crop Residues ◽  
Flight Performance ◽  
Fuel Production

INS reset removal for enhanced post-flight performance analysis

2002 ◽  
Author(s):  
J.S.A. Hepburn ◽  
J.Z. Zywiel ◽  
D.B. Reid
Keyword(s):  
Performance Analysis ◽  
Flight Performance

Modeling and Analysis of a Digital Hydraulic Actuator for Flight Control Surfaces

2021 ◽  
Author(s):  
R. S. Lopes ◽  
M. P. Nostrani ◽  
L. A. Carvalho ◽  
A. Dell’Amico ◽  
P. Krus ◽  
...  
Keyword(s):  
Performance Analysis ◽  
Flight Control ◽  
Data Model ◽  
Flight Performance ◽  
Hydraulic Actuator ◽  
Hydraulic Power ◽  
Fighter Aircraft ◽  
Modeling And Analysis ◽  
Modeling Process ◽  
Control Surfaces

Abstract This paper presents the design and modeling process of a flight control actuator using digital hydraulics and a performance analysis that compares the proposed solution and the Servo Hydraulic Actuator (SHA) on a fighter aircraft model. The proposed solution is named Digital Hydraulic Actuator (DHA) and comprises the use of a multi-chamber cylinder controlled by on/off valves and different pressures sources provided by a centralized hydraulic power unit, as proposed in the Fly-by-Wire (FbW) concept. The analyses were carried out using the Aero-Data Model in a Research Environment (ADMIRE), which was developed for flight performance analysis. The actuators were modeled using the software Matlab/Simulink® and Hopsan. They were applied to control the aircraft elevons in a flight mission close to the aircraft limits, to evaluate the actuator’s behavior and energy efficiency. The results show a reduction in energy dissipation up to 22.3 times when comparing the DHA with the SHA, and despite the overshooting and oscillations presented, the aircraft flight stability was not affected.

Knowledge Discovery Process Models

2012 ◽  
pp. 72-100 ◽  
Author(s):  
Mouhib Alnoukari ◽  
Asim El Sheikh
Keyword(s):  
Life Cycle ◽  
Knowledge Discovery ◽  
Process Model ◽  
Common Factor ◽  
Final Outcome ◽  
Process Models ◽  
Data Driven ◽  
Discovery Process ◽  
The Common ◽  
Discovery Process Models

Knowledge Discovery (KD) process model was first discussed in 1989. Different models were suggested starting with Fayyad’s et al (1996) process model. The common factor of all data-driven discovery process is that knowledge is the final outcome of this process. In this chapter, the authors will analyze most of the KD process models suggested in the literature. The chapter will have a detailed discussion on the KD process models that have innovative life cycle steps. It will propose a categorization of the existing KD models. The chapter deeply analyzes the strengths and weaknesses of the leading KD process models, with the supported commercial systems and reported applications, and their matrix characteristics.

Privacy Preserving Data Mining, Concepts, Techniques, and Evaluation Methodologies

2008 ◽  
pp. 2379-2401 ◽  
Author(s):  
Igor Nai Fovino
Keyword(s):  
Data Mining ◽  
Knowledge Discovery ◽  
Privacy Preserving ◽  
Research Field ◽  
Sensitive Information ◽  
Discovery Process ◽  
Privacy Preserving Data Mining ◽  
Mining Technology ◽  
Evaluation Methodologies ◽  
New Research

Intense work in the area of data mining technology and in its applications to several domains has resulted in the development of a large variety of techniques and tools able to automatically and intelligently transform large amounts of data in knowledge relevant to users. However, as with other kinds of useful technologies, the knowledge discovery process can be misused. It can be used, for example, by malicious subjects in order to reconstruct sensitive information for which they do not have an explicit access authorization. This type of “attack” cannot easily be detected, because, usually, the data used to guess the protected information, is freely accessible. For this reason, many research efforts have been recently devoted to addressing the problem of privacy preserving in data mining. The mission of this chapter is therefore to introduce the reader in this new research field and to provide the proper instruments (in term of concepts, techniques and example) in order to allow a critical comprehension of the advantages, the limitations and the open issues of the Privacy Preserving Data Mining Techniques.

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