Distributed Sampling Measurement Model in a Large-Scale High-Speed IP Networks

The distributed passive measurement is an important technology for networkbehavior research. To achieve a consistent measurement, the same packets should be sampled atdistributed measurement points. And in order to estimate the character of traffic statistics, thetraffic sample should be random in statistics. A distributed samplingmask measurement model isintroduced to tackle the difficulty of measuring the full trace of high-speed networks. The keypoint of the model is to choose some bits that are suitable to be sampling mask. In the paper, thebit entropy and bit flow entropy of IP packet headers in CERNET backbone are analyzed, and we findthat the 16 bits of identification field in IP packet header are fit to the matching field ofsampling mask. Measurement traffic also can be used to analyze the statistical character ofmeasurement sample and the randomicity of the model. At the same time the experiment resultsindicate that the model has a good sampling performance.

The comparison between traditional Chinese literacy strategies and English vocabulary strategies

There is a positive transfer from native language vocabulary learning strategy to that of the second language. The comparison between them shows that the traditional Chinese character learning strategies have profound effect on English vocabulary learning on the basis of morphology, lexicon as well as discourse categories. If the mutual effect can be applied in English vocabulary learning effectively, positive transfer emerges.

Comparative Study on VQ-Based Efficient Mandarin Speech Recognition Method

A VQ based efficient speech recognition method is introduced, and the key parameters of this method are comparatively studied. This method is especially designed for mandarin speaker dependent small size word set recognition. It has less complexity, less resource consumption but higher ARR (accurate recognition rate) compared with traditional HMM or NN approach. A large scale test on the task of 11 mandarin digits recognition shows that the WER(word error rate) can reach 3 86%. This method is suitable for being embedded in PDA (personal digital assistant), mobile phone and so on to perform voice controlling like digits dialing, name dialing, calculating, voice commanding, etc.

《识字捷径字典》音系与新昌方音

文章对《识字捷径字典》的音系作了比较详细的介绍,并对音系特点和性质作了重点的分析,在此基础上进一步探讨了书中音系到今音的发展演变情况。

RECOGNITION OF SPOKEN CHINESE DIGIT BASED ON INTEGRATION OF VQ AND HMM

A new speech recognition method is proposed, that integrates a VQ distortion measure and a discrete HMM. This VQ distortion based HMM uses a VQ distortion measure at each state instead of a discrete probability output used by a discrete HMM. Although this method is regarded as a refined version of the VQ distortion based recognition method proposed by Burton et al, it is also considered as a special case of a mixed distribution density HMM. In this paper, the VQ distortion based HMM is described, and it is compared with the conventional HMMs and their speech recognition performance through the experiments on speaker independent spoken digit recognition. From these comparisons, we confirm that the new method is better than the traditional HMMs.

Traffic light detection and recognition in intersections based on intelligent vehicle

To ensure revulsive driving of intelligent vehicles at intersections, a method is presented to detect and recognize the traffic lights. First, the stabling siding at intersections is detected by applying Hough transformation. Then, the colors of traffic lights are detected with color space transformation. Finally, self-associative memory is used to recognize the countdown characters of the traffic lights. Test results at 20 real intersections show that the ratio of correct stabling siding recognition reaches up to 90%;and the ratios of recognition of traffic lights and divided characters are 85% and 97%, respectively. The research proves that the method is efficient for the detection of stabling siding and is robust enough to recognize the characters from images with noise and broken edges.

Kernel principal component analysis network for image classification

In order to classify nonlinear features with a linear classifier and improve the classification accuracy, a deep learning network named kernel principal component analysis network（ KPCANet） is proposed. First, the data is mapped into a higher-dimensional space with kernel principal component analysis to make the data linearly separable. Then a two-layer KPCANet is built to obtain the principal components of the image. Finally, the principal components are classified with a linear classifier. Experimental results showthat the proposed KPCANet is effective in face recognition, object recognition and handwritten digit recognition. It also outperforms principal component analysis network（ PCANet） generally. Besides, KPCANet is invariant to illumination and stable to occlusion and slight deformation.

Design of fuzzy number recognition based on embedded system platform

A system of number recognition with a graphic user interface （GUI） is implemented on the embedded development platform by using the fuzzy pattern recognition method. An application interface （API） of uC/ OS-Ⅱ is used to implement the features of multi-task concurrency and the communications among tasks. Handwriting function is implemented by the improvement of the interface provided by the platform. Fuzzy pattern recognition technology based on fuzzy theory is used to analyze the input of handwriting. A primary system for testing is implemented. It can receive and analyze user inputs from both keyboard and touch-screen. The experimental results show that the embedded fuzzy recognition system which uses the technology which integrates two ways of fuzzy recognition can retain a high recognition rate and reduce hardware requirements.

Operationalizing physical literacy for learners: Embodying the motivation to move

Physical literacy is a concept that is expected to encompass the mind and body in an integrated way to explain, promote, and help sustain human beings＇ fundamental function： movement. According to Whitehead（2010）, physical literacy is defined by motivation, especially by competence-based and interest-based motivation. This point of view is consistent with vast amount of research evidence on children and adolescents＇ physical activity behavior. In the article I attempt to interpret and operationalize physical literacy from a perspective that children＇s motivation in physical education is both an innate mental disposition and an acquired/learned attribute. Particularly I rely on the conceptual learning theory and motivation regulation mechanisms of the self-determination theory to argue that in physical education, children should experience tasks that inspire them to embody competence and interest along with self-regulation strategies necessary for developing and sustaining the motivation to move.

Teaching for physical literacy: Implications to instructional design and PETE

Physical education teachers play an important role in helping students＇ development of the motor skills needed to be physically literate individuals. Research suggests that teacher made instructional design decisions can lead to enhanced motor skill learning. After presenting a model of evidence-based research this paper presents information that will help teachers plan and execute lessons designed to improve students＇ motor skills. Variables that impact motor skill learning in physical education including time, type of practice, content, presentation and organizational strategies, and student skill level are presented and discussed. A brief section on student attitudes, their relation to motor skill learning and to physical literacy is included. Motor skills are needed for physically literate people to enjoy lifelong physical activity. Physical education teachers and the decisions they make contribute to students＇ learning and whether the goal of physical literacy is met.

AN ADAPTIVELY TRAINED KERNEL-BASED NONLINEAR REPRESENTOR FOR HANDWRITTEN DIGIT CLASSIFICATION

In practice, retraining a trained classifier is necessary when novel data become available. This paper adopts an incremental learning procedure to adaptively train a Kernel-based Nonlinear Representor (KNR), a recently presented nonlinear classifier for optimal pattern representation, so that its generalization ability may be evaluated in time-variant situation and a sparser representation is obtained for computationally intensive tasks. The addressed techniques are applied to handwritten digit classification to illustrate the feasibility for pattern recognition.

Contextualizing physical literacy in the school environment: The challenges

The intent of this paper is to conceptualize physical literacy in the school environment within the United States educational system. Evolution of physical literacy from both a general education and disciplinary focus is overviewed. The challenges of transitioning from a physically educated to a physically literate person as the primary learning outcome of physical education may inhibit progress. Five prioritized recom- mendations are made to assist teachers in overcoming such barriers： （a） whole of school approach, （b） effective, differentiated pedagogy, （c） integration of technology for individualized tracking of progress, （d） supportive school climate, and （e） alignment of local efforts with national initiatives.

Identification and Typing of Respiratory Adenoviruses in Guangzhou, Southern China Using a Rapid and Simple Method

Human adenoviruses (HAdVs), especially HAdV-B3, -E4 and -B7, are associated with Acute Respiratory Disease in Chinese children, and occasionally in adults. In order to establish and document the profiles of the respiratory adenovirus pathogen among children in Guangzhou, Southern China, a rapid, simple and practical method for identification and typing of respiratory adenoviruses was developed and evaluated. One pair of universal PCR primers was designed according to the conserved region of the hexon gene, which can detect not only HAdV-B3, -E4 and -B7, but also HAdV-B14, -F40 and -F41, with a specific 300bp PCR product. Three pairs of type-specific PCR primers were also designed according to the hypervariable regions of the hexon gene to type HAdV-B3, -E4 and -B7 by three independent PCR reactions, making it easy to optimize the PCR conditions. By using this method, one hundred throat swab specimens collected during Oct 2010 to Dec 2011 and suspected of being positive for adenoviral infection were identified and typed for adenoviruses. Of these samples, fifty-five were adenovirus-positive. The most common HAdV type was HAdV-B3, identified in 92.7% of samples, which is not only consistent with the data reported in 2004-2006, but also consistent with the recent report in Hangzhou, eastern China, indicating that HAdV-B3 has been circulating in Guangzhou, and maybe in eastern China, for many years. The method for the respiratory adenovirus identification and typing we developed is rapid, simple and practical, which has a potential in the real-time surveillance of circulating adenovirus strains and also to provide etiological evidence for the adenovirus-relative disease control and prevention in China.

Framework of Digital Machining Process Planning Platform for Cylinder Body Part

Digital factory technology is an advanced manufacturing technology served as to establish a bridge between the process of product development and manufacturing.In terms of application for digital factory technology in machining,especially in machining of a complicated part such as a cylinder body part,a concept of digital process planning and its framework are proposed.Its components including machining domain knowledge model,machining knowledge base,machining resource base and process planning system are studied.A machining knowledge model in tree form and an object-driven knowledge reasoning mechanism are used for machining knowledge base.The process planning system is a user interface that leads a planner to finish the planning process.A case about a cylinder head part is given to demonstrate how the platform works.The framework of digital process planning is the foundation of some intelligent CAPP systems and helps to production line planning.

A sustainable development OCR system in CADAL application

This paper briefly introduces the main ideas of a sustainable development OCR system based on open architecture techniques and then describes the construction of an optical character recognition (OCR) center built on computer clusters, for the purpose of dynamically improving the recognition precision of the digitized texts of a million volumes of books produced by the China-US Million Books Digital Library (CADAL) Project. The practice of this center will provide helpful reference for other digital library projects.

Measuring the Condition of Parking Lot by Image Processing

Aim To study the parking management in the condition of vehicles' increasing. Methods The methods of pattern recognition and image processing were used to analyze the eigenvalues of parking lot images. Results The automatic identification of every parking place in the parking plot was realized. The automatic measuring of parked vehicle count and parking lot utilization was completed. Conclusion It can complete the real time recognition, and has some practicabilities.

Characteristics and Causes of the Preconsolidation Stress of Soils in the Yellow River Delta

Preconsolidation stress （ σP） is the maximum effective stress that a soil has suffered throughout its life. From a geotech- nical point of view, pre-consolidation stress has great importance because it separates elastic and reversible deformations from inelastic and only partially irreversible deformations and marks the starting point of high compressibility. In this study we calculated the preconsolidation stress for 72 undisturbed soil samples from the Yellow River Delta, using the oedometer test and applying the method proposed by Casagrande. The results showed that the over-consolidation ratio （OCR-the ratio of pre-consolidation stress to current natural overburden stress） values of the soil from soil surface to 6m depth varied from 1.72 to 15.34 and the maximum pre- consolidation stress was above 200 kPa. In consequence, the soils of the Yellow River Delta are highly over-consolidated within the upper 6m, the OCR decreasing gradually with depth from 6 to 12m. For samples from deeper than 12m the soils were found to be under-consolidated, which was proved by standard penetration tests （SPTs）. The main causes of this type of consolidation are the mineral composition and the designability of the soil body.

OBLIQUE PROJECTION REALIZATION OF A KERNEL-BASED NONLINEAR DISCRIMINATOR

Previously, a novel classifier called Kernel-based Nonlinear Discriminator (KND) was proposed to discriminate a pattern class from other classes by minimizing mean effect of the latter. To consider the effect of the target class, this paper introduces an oblique projection algorithm to determine the coefficients of a KND so that it is extended to a new version called extended KND (eKND). In eKND construction, the desired output vector of the target class is obliquely projected onto the relevant subspace along the subspace related to other classes. In addition, a simple technique is proposed to calculate the associated oblique projection operator. Experimental results on handwritten digit recognition show that the algorithm performes better than a KND classifier and some other commonly used classifiers.

Increasing Literacy Through Specific Tasks Design

This study focuses on thirty-five Low-level/achieving students on General Education English which meets for two hour.,; per week, eight weeks for two consecutive semesters （totaling thirty-two hours） in the University of Technology in Taiwan. Its chief aims four-fold： First, to promote the students＇ learning motivation; second, to increase the students＇ learning interests; third, to raise their English abilities by reading theme-based/oriented topics; and, fourth, instruct them by giving guidelines to make Power-Point presentations in class. A prior or pilot survey was conducted to provide empirical opportunities to collect and explore the participants＇ views, comments, and opinions in relation to the selected research questions on this topic. The results also indicate that students can speak different/various length of words, utilize appropriate phrase to express their ideas or goals, and to speak in various/different paces, etc. Teachers couldn＇t assess the students only by their test results due to the different learning styles adopted by individual students; however, through this survey, students can be better assisted through the identification of their individual styles or habits, their individual styles or habits of learning. As regards relevant knowledge about their students＇ learning styles, teachers may consider whether and how to adjust their methods of teaching in order to better motivate them to learn English more effectively and efficiently.

Information Moment for Chinese Character Recognition

Moment invariants firstly introduced by M. K Hu in 1962, has some shortcomings. After counting a large number of statistical distribution information of Chinese characters,the authors put forward the concept of information moments and demonstrate its invariance to translation,rotation and scaling.Also they perform the experiment in which information moments compared with moment invaiants for the effects of similar Chinese characters and font recognition.At last they show the recognition rate of 88% by information moments,with 70% by moment inariants.