We discuss basic structural properties of finite black box groups. A special emphasis is made on the use of centralisers of involutions in probabilistic recognition of black box groups. In particular, we suggest an algorithm for finding the p-core of a black box group of odd characteristic. This special role of involutions suggest that the theory of black box groups reproduces, at a non-determi...

Typically, these kinds of questions are answered with reference to the inherent properties of the assessment mechanism. For example, Lowry et.al. [7] and Menzies & Cukic [8] contrast the costs and defect detection decay rates of formal methods, white box testing, and black box testing. That analysis made assumptions about the completeness of the search and the cost of setting up each run. A dra...

Early prediction systems of student performance can be very useful to guide student learning. For a prediction model to be really useful as an effective aid for learning, it must provide tools to adequately interpret progress, to detect trends and behaviour patterns and to identify the causes of learning problems. White-box and black-box techniques have been described in literature to implement...

Continuum robotic arms that are inspired from nature, have many advantages compared to traditional robots, which motivate researchers in this field. Dynamic modeling and controlling these robots are challenging subjects due to complicated nonlinearities and considerable uncertainties existing in these structures. In this paper, first a dynamic three-dimensional model of the continuum robotic ar...

Usually grey-box modeling has better accuracy than black-box identification. The grey-box can be regarded as combination of mechanistic modelling and intelligent identification. But in many cases, mechanistic models are not available, for example the production quality of the shaft furnace which will be discussed in this paper, we can use fuzzy technique to obtain the mechanistic models that ca...

A statistically based modeling technique is developed for characterizing in-band and out-of-band intermodulation and cross-modulation distortions in multichannel amplifier environments. The model is based on a new multiple envelope memoryless behavioral model that captures the black-box characteristics of multichannel amplifiers. A power amplifier with a two code-division multiple-access channe...

Robots belong to a class of Cyber-Physical Systems where complex software as a mobile device has to fulfill tasks in a complex environment. Modeling robotics applications for analysis and code generation requires modeling languages for the logical software architecture and the system behavior. The MontiArcAutomaton modeling framework integrates six independently developed modeling languages to ...

This work compares a few attempts based on Wavelet and Neural networks, for extracting the Jominy hardness pro les of steels directly from the chemical composition. That is essentially a black-box modeling problem: Wavelet and Neural networks seem powerful, especially when compared with classical methods commonly found in literature. In particular, the paper proposes a multi-network architectur...

nonlinear, black box model, behavioral model, input-output model, time-series, embedology This technical report describes the groundwork for our nonlinear modeling technologies. Future technical reports will go into detail about the specific solutions we are developing to build accurate models for nonlinear electronic devices from input-output measurements for possible use in CAD simulators suc...

System identification is an important way of investigating and understanding the world around. Identification is a process of deriving a mathematical model of a predefined part of the world, using observations. There are several different approaches of system identification, and these approaches utilize different forms of knowledge about the system. When only input-output observations are used ...