Strength correlations of cement-mixed soils using data mapping

Development of comparisons and correlations between the unconfined compressive strength (UCS) and the undrained triaxial compressive strength, qu, is essential for generalising performance and optimising the design of cement-stabilised soils. This paper introduces current work in collecting and collating data from a number of research projects involving both laboratory strength tests performed on identical cement-stabilised soil samples. The research project on cement-stabilised Singapore marine clays at the National University of Singapore has been used as an example to explain the work on comparing and correlating results from both tests by normalising data and constructing contour plots. The effect of variables on strength comparison and correlations was evaluated. The variation in strength correlations was found to be dependent on a number of factors including: soil properties, cement content, curing time and stress, total water/cement ratio, confining stress and strain rate. The results showed that at ~ 100 kPa confining stress, UCS and qu, had similar magnitudes. Correlations between strengths and other design variables are discussed and presented.

Genome mapping in aquatic animals: Progress and future perspectives

The genome of aquatic animals is poorly understood and information from different taxonomic groups is sketchy. While there have been intensive genomic studies on some fish models, investigations on other fishes and invertebrates have been scarce. Yet there are recently some coordinated studies on genome mapping in a number of aquaculture animals of economic importance. This review summarizes information available on genome mapping of the important fish models and aquaculture animals. The future perspectives of this field of studies are discussed.

Iris recognition algorithm based on point covering of high-dimensional space and neural network

In this paper, we constructed a Iris recognition algorithm based on point covering of high-dimensional space and Multi-weighted neuron of point covering of high-dimensional space, and proposed a new method for iris recognition based on point covering theory of high-dimensional space. In this method, irises are trained as "cognition" one class by one class, and it doesn't influence the original recognition knowledge for samples of the new added class. The results of experiments show the rejection rate is 98.9%, the correct cognition rate and the error rate are 95.71% and 3.5% respectively. The experimental results demonstrate that the rejection rate of test samples excluded in the training samples class is very high. It proves the proposed method for iris recognition is effective.

Manifold covering theory in biomimetic pattern recognition

We describe a new model which is based on the concept of cognizing theory. The method identifies subsets of the data which are embedded in arbitrary oriented lower dimensional space. We definite manifold covering in biomimetic pattern recognition, and study its property. Furthermore, we propose this manifold covering algorithm based on Biomimetic Pattern Recognition. At last, the experimental results for face recognition demonstrates that the correct rejection rate of the test samples excluded in the classes of training samples is very high and effective.

Information geometry theory of high-dimension space and application for speaker independent continuous digit speech recognition

In the light of descriptive geometry and notions in set theory, this paper re-defines the basic elements in space such as curve and surface and so on, presents some fundamental notions with respect to the point cover based on the High-dimension space (HDS) point covering theory, finally takes points from mapping part of speech signals to HDS, so as to analyze distribution information of these speech points in HDS, and various geometric covering objects for speech points and their relationship. Besides, this paper also proposes a new algorithm for speaker independent continuous digit speech recognition based on the HDS point dynamic searching theory without end-points detection and segmentation. First from the different digit syllables in real continuous digit speech, we establish the covering area in feature space for continuous speech. During recognition, we make use of the point covering dynamic searching theory in HDS to do recognition, and then get the satisfying recognized results. At last, compared to HMM (Hidden Markov models)-based method, from the development trend of the comparing results, as sample amount increasing, the difference of recognition rate between two methods will decrease slowly, while sample amount approaching to be very large, two recognition rates all close to 100% little by little. As seen from the results, the recognition rate of HDS point covering method is higher than that of in HMM (Hidden Markov models) based method, because, the point covering describes the morphological distribution for speech in HDS, whereas HMM-based method is only a probability distribution, whose accuracy is certainly inferior to point covering.

coconceptmap: a system for collaborative concept mapping

Concept mapping is a technique for visualizing the relationships between different concepts, and collaborative concept mapping is used to model knowledge and transfer expert knowledge. Because of lacking some features,existing systems can’t support collaborative concept mapping effectively. In this paper, we analysis the collaborative concept mapping process according to the theory of distributed cognition, and argue the functions effective systems ought to include. A collaborative concept mapping system should have the following features: visualization of concept map, flexible collaboration style,supporting natural interaction, knowledge management and history management. Furthermore, we describe every feature in details. Finally,a prototype system has been built to fully explore the above technologies.

Block and parallel modelling of broad domain nonlinear continuous mapping based on NN

The necessity of the use of the block and parallel modeling of the nonlinear continuous mappings with NN is firstly expounded quantitatively. Then, a practical approach for the block and parallel modeling of the nonlinear continuous mappings with NN is proposed. Finally, an example indicating that the method raised in this paper can be realized by suitable existed software is given. The results of the experiment of the model discussed on the 3-D Mexican straw hat indicate that the block and parallel modeling based on NN is more precise and faster in computation than the direct ones and it is obviously a concrete example and the development of the large-scale general model established by Tu Xuyan.

Immobilized metal-ion chelating capillary microreactor for peptide mapping analysis of proteins by matrix assisted laser desorption/ionization-time of flight-mass spectrometry

Peptide mass mapping analysis, utilizing a regenerable enzyme microreactor with metal-ion chelated adsorption of enzyme, combined with matrix assisted laser desorption/ionization-time of flight-mass spectrometry (MALDI-TOF-MS) was developed. Different procedures from the conventional approaches were adopted to immobilize the chelator onto the silica supports, that is, the metal chelating agent of iminodiacetic acid (IDA) was reacted with glycidoxypropyltrimethoxysilane (GLYMO) before its immobilization onto the inner wall of the fused-silica capillary pretreated with NH4HF2. The metal ion of copper and subsequently enzyme was specifically adsorbed onto the surface to form the immobilized enzyme capillary microreactor, which was combined with MALDI-TOF-MS to apply for the mass mapping analysis of nL amounts of protein samples. The results revealed that the peptide mapping could routinely be generated from 0.5 pmol protein sample in 15 min at 50degreesC, even 20 fmol cytochrome c could be well digested and detected.

Alteration mineral mapping using masking and Crosta technique for mineral exploration in mid-vegetated areas: a case study in Areletuobie, Xinjiang (China)

Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM)+ data have been successfully employed in the field of mineral exploration to identify key minerals over arid and semi-arid terrains. However, redundant vegetation and cloud may seriously interfere with the discrimination of the minerals with diagnostic features. Therefore, in this study, we use masking technique to eliminate the negative influence of vegetation and cloud and Crosta technique to identify the diagnostic features of hydroxyl-minerals, carbonate-minerals and iron oxides. Then the anomalies were endowed with special colours and overlapped with the remote-sensing and geochemical data, overlaying images as remote-sensing anomalies. The mineral exploration work was carried through by synthetic analysis of the remote-sensing images, geochemical data and structures. Finally, areas with high correlation between the occurrence of hydrothermal alteration and presence of main faults and geochemical anomalies were considered as mineral exploration targets worthy of further detailed exploration programmes.