The MinMax k-means algorithm is widely used to tackle the effect of bad initialization by minimizing the maximum intraclustering errors. Two parameters, including the exponent parameter and memory parameter, are involved in the executive process. Since different parameters have different clustering errors, it is crucial to choose appropriate parameters. In the original algorithm, a practical fr...

Detection of sedimentary cycles is difficult in fine-grained or homogenous sediments but is a prerequisite for the interpretation of depositional environments. Here we use a new autocorrelation analysis to detect cycles in a homogenous sediment core, E602, from the northern shelf of the South China Sea. Autocorrelation coefficients were calculated for different mean grain sizes at various depth...

Content-based medical image retrieval can support diagnostic decisions by clinical experts. Examining similar images may provide clues to the expert to remove uncertainties in his/her final diagnosis. Beyond conventional feature descriptors, binary features in different ways have been recently proposed to encode the image content. A recent proposal is “Radon barcodes” that employ binarized Rado...

We consider the problem of approximating the minmax value of a multiplayer game in strategic form. We argue that in 3-player games with 0-1 payoffs, approximating the minmax value within an additive constant smaller than ξ/2, where ξ = 3− √ 5 2 ≈ 0.382, is not possible by a polynomial time algorithm. This is based on assuming hardness of a version of the socalled planted clique problem in Erdős...