Aimed at the demand of positioning in complicated environments such as indoor and built-up areas, the method of autonomous navigation positioning and orientation based on an adaptive step length model was proposed in this paper. Using an accelerometer placed on the human waist, stride was recognized and the relationship between the step length, stride factor, and walking speed was established. ...

Step length adaptation is central to evolutionary algorithms in real-valued search spaces. This paper contrasts several step length adaptation algorithms for evolution strategies on a family of ridge functions. The algorithms considered are cumulative step length adaptation, a variant of mutative self-adaptation, two-point adaptation, and hierarchically organized strategies. In all cases, analy...

The ridge function class is a parameterised family of test functions that is often used to evaluate the capabilities and limitations of optimisation strategies. Past research with the goal of analytically determining the performance of evolution strategies on the ridge has focused either on the parabolic case or on simple one-parent strategies without step length adaptation. This paper extends ...

In this paper a novel step length model using a handheld Micro Electrical Mechanical System (MEMS) is presented. It combines the user's step frequency and height with a set of three parameters for estimating step length. The model has been developed and trained using 12 different subjects: six men and six women. For reliable estimation of the step frequency with a handheld device, the frequency...

We construct a new harmonic family: dielectric flow solutions with maximal supersymmetry in eleven-dimensional supergravity. These solutions are asymptotically AdS4 ×S7, while in the infra-red the M2 branes are dielectrically polarized into M5 branes. These solutions are holographically dual to vacua of the mass deformed theory on M2 branes. They also provide an interesting insight on the super...

As mentioned before, the success of CASE relies on two noteworthy properties: the Sure Screening (SS) property and the Separable After Screening (SAS) property. In this section, we discuss the two properties in detail, and illustrate how these properties enable us to decompose the original regression problem to many small-size regression problems which can be fit separately. We then use these p...

I describe a modification to Shanks’ baby-step giant-step algorithm for computing the order n of an element g of a group G, assuming n is finite. My method has the advantage of being able to compute n quickly, which Shanks’ method fails to do when the order of G is infinite, unknown, or much larger than n. I describe the algorithm in detail. I also present the results of implementations of my a...