Geometric hashing (GH) is a general model-based recognition scheme. GH is widely used in the industrial products assembly and inspection tasks. The aim of this study is to speed up the geometric hashing pattern recognition method for the purpose of real-time object detection applications. In our method, a pattern is decomposed into some sub-patterns to reduce the data number in hash table bins. In addition, the sub-patterns are recorded in a plurality of hash tables. Finally we improve the recognition performance by combining with image pyramid and edge direction information. To confirm the validity of our proposed method, we make a complexity analysis, and apply our method to some images. Both complexity analysis and experiment evaluations have demonstrated the efficiency of this technique.

Power consumption limits the application of public key cryptosystem in portable devices. This paper proposes a low power design of 1,024-bit RSA. In algorithm, the Chinese Remainder Theorem (CRT) and an improved Montgomery algorithm are selected to decrease the computation of RSA. In architecture and circuit, the operand isolation technique is applied to avoid unnecessary flip-flops of the combinational logic, and the clock gating technique is used to reduce the power dissipation of the registers. The proposed design is functionally verified on Altera FPGA EP2C8Q208C8N device. With SMIC 0.18m CMOS process, the Synopsys synthesizing result shows that the area and the critical path are 7.1k gates and 5.3ns respectively, while the power is 2.56mW and the throughput can reach 49 kbps. Thus the proposed design requires lower power than previous designs.

Taking the western Qinling Mountain, in the southern Shaanxi Province of china, as an example, based upon comprehensive analysis of geological data for 20 debris flow gullies, the author has put forward a series of indices system and has developed one evaluation system called “dangerous degree evaluation system of mine debris flow based on IGA-BP”. This system adopts Visual Basic 6.0 and Access technology to manage database, adopts immune genetic algorithm to optimize the hidden layer structure and network parameters of BP neural network and adopts sample model of mine debris flow whose dangerous degree has been known to realize the BP neural network evaluation of the debris flow risk which to be determined. The calculating results show that this evaluation method has high reliability and simplicity of operation, and it can make comprehensive evaluation precisely. The evaluation results have important guiding significance in the prevention and reduction mine debris flow.

The study on the quality evaluation and the related technology on distant education can provide evidence for the quality teaching and learning, and ensure the high quality and efficiency for distant education. It is highly significant to construct the teaching resources and learning supporting system by establishing an appropriate system that fits the level of education and guarantees the teaching quality. On the basis of the research results of programs, standards and technology for the quality evaluation of the distant education, this essay puts forward a method of comprehensive quality evaluation by applying the theory of comprehensive evaluation into this area, which is a quantitative research about how to set and calculate the weight indices for the evaluation. This method can process the quality indices by quantity efficiently, give a direct view of the quality by the comparative analysis, and provide the evidence for improving the quality. 

Nowadays college students’ studying-weariness is a common problem needs to be solved in China. Also, college students' studying-interest, studying-weariness psychology and misbehaviors have been the subject of considerable research in the last few years to educators and researchers all over the world. However, most of the existing studies in this field are qualitative theory analysis and short of actual investigation, survey and even less mathematical quantificational study. The investigation and study on studying-interest of college students from four universities in Wuhan demonstrates that college students show generally studying-weary mentality and correlative misbehaviors. With the designed college students' learning-interest questionnaire, college students in four universities of Wuhan were surveyed. And based on this survey, Structural Equation Model (SEM) was used to analyze the date of our investigation of the factors affecting college students’ studying-interest and studying-weariness. Results of our quantitative statistical analysis with mathematical model show the degree of each factor influencing studying-interest and studying-weariness. School-related factor and society-related factor are the main influences on college students’ studying-interest and studying-weariness. The major objective of this paper is to provide an integrative review of the college students’ studying-interest and studying-weariness, in order to contribute to the development of high education. Countermeasures and Suggestions are also put forward to rectify the college students’ studying-weariness. This work will play an important role for education departments and educators to take corresponding measures to provide scientific guidance of high education.

Courses are the link between teachers and students. The matching degree of the curriculum and the students’ future development largely affects the future competitiveness of students and students’ satisfaction with the school specialty. Based on industrial engineering specialty of Nanchang University, this article applies fishbone diagram to analyze the direction of students’ future development, and uses questionnaire to collect students’ preference of the future development, and analyzes the collecting data by AHP (analytical hierarchy process). Combining with the weight of the direction of future development and the importance of courses, we find a new combination of curriculum and a plan of rearrangement. By comparing the results with the existing curriculum program, we ultimately find a more scientific way to rearrange the curriculum.

Instructional technology can make teachers do their jobs easier, better, faster and more effectively. Students can also benefit from its application. However, some college teachers do not adopt instructional technologies in their teaching as we expected. They like to teach the way they were taught as students before. Why and what factors really influence their adoption of instructional technology? This study offered a model suggestiong instructional technology adoption by college teachers depends on: the student, the teacher, the technology and the surroundings. An experiment was designed to verify the model. Samples were selected from teachers at a mid-sized university. Experimental data was collected by interviewing fifteen teachers (samples). Those interviewed represented five high-level users, five medium-level users, and five low-level users of instructional technology. Quantitative methods such as frequency counting were used to analyze and sort the data. Finally, conclusions can be drawn that different components in the model had different influential degree to the different levels of users of instructional technology.

As increasingly large RDF data sets are being published on the Web, effcient RDF data management has become an essential factor in realizing the Semantic Web vision. However, most existing RDF storage schemes, which are built on top of row-store relational databases, are constrained in terms of efficiency and scalability. Still, the growing popularity of the RDF format used in real-world applications arguably calls for an effort to deal with these drawbacks. In this paper, we propose a novel RDF storage and indexing scheme, called CHex, which uses the triple nature of RDF as an asset to implement sextuple indexing for a column-oriented database system. Using binary association tables (BATs) in the column-oriented data model, RDF data is indexed in six possible ways, one for each possible ordering of the three RDF elements. The sextuple indexing scheme in a column-oriented database not only provides efficient single triple pattern lookups, but also allows fast merge-joins for any pair of two triple patterns. To evaluate the performance of our approach, we generate large-scale data sets upto 13 million triples, and devise benchmark queries that cover important RDF join patterns. The experimental results show that our approach outperforms the row-oriented database systems by upto an order of magnitude and is even competitive to the best state-of-the-art native RDF store.