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Humans are highly intelligent, and their brains are associated with rich states of consciousness. We typically assume that animals have different levels of consciousness, and this might be correlated with their intelligence. Very little is known about the relationships between intelligence and consciousness in artificial systems.

Most of our current definitions of intelligence describe human intelligence. They have severe limitations when they are applied to non-human animals and artificial systems. To address this issue, this chapter sets out a new interpretation of intelligence that is based on a system’s ability to make accurate predictions. Human intelligence is measured using tests whose results are converted into values of IQ and g-score. This approach does not work well with non-human animals and AIs, so people have been developing universal algorithms that can measure intelligence in any type of system. In this chapter a new universal algorithm for measuring intelligence is described, which is based on a system’s ability to make accurate predictions.

Many people agree that consciousness is the stream of colorful moving noisy sensations that starts when we wake up and ceases when we fall into deep sleep. Several mathematical algorithms have been developed to describe the relationship between consciousness and the physical world. If these algorithms can be shown to work on human subjects, then they could be used to measure consciousness in non-human animals and artificial systems.

At present we can use our own imagination, intelligence and consciousness to picture possible relationships between intelligence and consciousness in non-human systems. In the future, we could use mathematical algorithms to measure intelligence, measure consciousness and identify correlations between intelligence and consciousness. This would lead to a more rigorous scientific understanding of the relationships between intelligence and consciousness in natural and artificial systems.

We describe a procedure for identifying major minima and maxima of a time series, and present two applications of this procedure. The first application is fast compression of a series, by selecting major extrema and discarding the other points. The compression algorithm runs in linear time and takes constant memory. The second application is indexing of compressed series by their major extrema, and retrieval of series similar to a given pattern. The retrieval procedure searches for the series whose compressed representation is similar to the compressed pattern. It allows the user to control the trade-off between the speed and accuracy of retrieval. We show the effectiveness of the compression and retrieval for stock charts, meteorological data, and electroencephalograms.

Sorting is a classic problem and one to which many others reduce easily. In the streaming model, however, we are allowed only one pass over the input and sublinear memory, so in general we cannot sort. In this paper we show that, to determine the sorted order of a multiset s of size n containing σ distinct elements using one pass and o(n log σ) bits of memory, it is generally necessary and sufficient that its entropy H = o(log σ). Specifically, if s = {s₁, …, s_n} and S_i1,…, S_in is the stable sort of s, then we can compute i₁,…,i_n in one pass using O((H + 1)n) time, O(σ) words plus O((H + 1)n) bits of memory, and a simple combination of classic techniques. On the other hand, in the worst case it takes Ω(Hn) bits of memory to compute any sorted ordering of s in one pass.

This document describes a simple procedure for evaluating the capacity of single angle compression struts that are supported at each end by one leg to a gusset plate or directly to a leg or stem of the chord of a truss. This procedure allows the single angle to be treated for analysis and design as a pinned-end axially loaded compression member by use of an effective slenderness ratio. The procedure considers two levels of end restraint and addresses both equal and unequal-leg angles. This procedure is being proposed for use in the next version of the American Institute of Steel Construction specification.

We present a new high speed parallel architecture and its VLSI implementation to design a special purpose hardware for real-time lossless image compression/decompression using a decorrelation scheme. The proposed architecture can easily be implemented using state-of-the-art VLSI technology. The hardware yields a high compression rate. A prototype 1-micron VLSI chip based on this architectural idea has been designed. The scheme is favourably comparable to the lossless JPEG standard image compression schemes. We also discuss the parallelization issues of the lossless JPEG standard still compression schemes and their difficulties.

This paper presents a family of coset based constructed(CBC) two-dimensional biorthogonal inseparable wavelet, and we analyze the characters of two dimensional signals transformed though our wavelet. Combined with SPIHT coding scheme, a scheme of image compression is given out. Experimental result shows that our scheme performances nearly the same with that of CDF97 wavelet. The advantage of our scheme is that the filter coefficients we construct are all binary rational numbers, thus, the complexity of computation can be reduced notably, and the realization on hardware will be much easier.

For the characteristics of many monitory points, high cost of data transmission and sending scene pictures periodically in the Coal Bed Methane mining site, fractal theory is used in the compression of images. The compression rate of fractal is high, but it takes too much time to encode, so an improved compact genetic algorithm is used in this paper to improve the efficiency of encode. Experimental result shows that, the size of compressed image is smaller than before, so that it can be transmitted more quickly. And the image has minimum distortion after uncompressing, does not affect the correct judgment of site conditions.

This study was attempted to develop a new cell finite element model to present the cell mechanical response underlying the compression. The geometry and material properties of cytomembrane, cytoplasm, cytoskeleton, and the nucleus were obtained according the previous experimental data. 5Mpa compression loading was simulated in LS-DYNA solvers, the displacement, strain, stress contour of the cytomembrane, cytoplasm, cytoskeleton, and the nucleus were calculated in this study. According the prediction of this FE modeling, the mechanotransduction sequence of each part in cell was observed from cytomembrane to cytoskeleton and then the cytoplasm, finally to the nucleus. This phenomenon might indicate that the remodeling behavior of the cell cytoskeleton was influenced by the nucleus mechanical response.

Compression tests of 7050 aluminum alloy have been conducted at different temperatures (340, 380 and 420°C) and different strain rates of 0.1, 1 and 10s^-1. The microstructure characteristics of the alloy after deformation are investigated using EBSD technique. The results show that the stress level of the alloy can be presented by a Zener-Holloman parameter in a hyperbolic sine-type equation with the hot activation energy of 137.9 kJ/mol. The dynamic restoration mechanism of the 7050 aluminum alloy is dynamic recovery mechanism, and the main dislocation movement mechanism is cross-slipping of crew dislocation.

Rubber materials are widely used in aviation, aerospace, shipbuilding, automobile and other military field. However, rubber materials are easy to aging, which largely restricts its using life. In working environment, due to the combined effect of heat and oxygen, vulcanized rubber will undergo degradation and crosslinking reaction which will cause elasticity decease and permanent deformation, so mostly rubber products are used under stress state. Due to the asymmetric structure and asymmetric stress distribution, mechanical stress may cause serious damage to molecular structure; therefore, this paper is aimed to analyze the aging behavior of rubber materials under tensile and compressive loadings, through analyzing experiment data, and adopting Gauss function to describe stress relaxation coefficient, to build an aging equation containing compression ratio parameter and aging time.