Earticle

EH4 electromagnetic imaging system is relatively advanced electromagnetic exploration instrument at home and abroad with the advantage of great exploration depth, intuitive and portable etc. In this paper, on the basis of the systematical collection of predecessors' research data and combined with the present situation of domestic and foreign researches, the author introduces the working principle of the EH4 electromagnetic imaging system, field-working method, scope, and possibly, and some geological problems that may be solved in gold prospecting. Apart from this, through exploration cases of in Zhangsangou Gold mining in Heilongjiang province, Yuerya gold deposit in Hebei province and in 460 gold mine in region of Beishan of Gansu, this paper illustrates that the effect of EH4 system in gold deposit exploration is remarkable.

Automatic tool changer system with high operability is the critical component of high efficiency automated machine tools. This paper introduces an interactive simulating platform for an automatic tool changer system based on virtual reality technology, with which students can know the structure of chain tool library, the principle of tool changing manipulator and the various cutting tools. In this paper the frame structure of the interactive simulating platform and the working principle of the platform were explained. The motion control mechanism of components of automatic tool changer system was elaborated in the way of taking the process of changing cutting tools as an example. The interactive simulating platform of the automatic tool changer system utilizes browser-based structure, Java3D, virtual, Java Applet and some other technologies to develop a Web3D virtual reality learning environment, with the advantages of easy understandability, good interactivity, strong sense of reality, simple updatability, small investments and so forth, which can satisfy the requirements of online learning for many students at the same time. It is very important in the distance online education or vocational skills remote training of mechanical engineering.

Colloid Cysts, also called neuroepithelial cysts are located in the rostral aspect of the third ventricle in the brain [1]. It appears near the center of the brain and grows along the roof of the third ventricle that holds spinal fluid. Increase in the size of cyst can block the flow of cerebrospinal fluid causing hydrocephalus (water on the brain or a buildup of CSF in the brain). The buildup of CSF in the brain can increase intracranial pressure that compresses surrounding brain tissues in the skull and may cause enlargement of the brain, convulsions, brain damage and even sudden death [2]. Detection of Colloid Cyst at early stages is very important. Analysis and manual interpretation of Magnetic Resonance Images and Computed Tomography Images by radiologists are time consuming and sometimes difficult and error prone. In this paper we propose an algorithm to automate the process of detecting Colloid Cysts in Brain through the use of image processing techniques.

In actual system, it’s a quite attractive character that one can access the channel as he wants. This paper bases on earlier ideal named ISA-MAC(Instantaneous Spectrum Availability MAC) which is promoted and listed in a paper reference [1], and focus on the optimal encode rate and the number of frequency slots of ISA-MAC. Take the probability of no-error channel transmission and the normalized throughput of the system as constrained condition, an analysis come out and be taken as a guide for reality design which is found on the mathematic model and the capability of error detection and correction, and can be adapted to CSMA, ALOHA using FH similar to ISA-MAC which is designed for fulfilling the requirement of accessing at any moment.

The adaptive decision feedback equalizer (ADFE), which makes use of the regenerative effect of the non-linear decision device is an effective means for equalizing the channels that exhibit spectral nulls. A common problem faced by the ADFE is that with increasing data transmission rate, the channel IR length increases and thus the orders of both the FFF and the FBF increase. The resulting increase in complexity makes the real time operation of the ADFE difficult, especially in view of simultaneous shortening of the symbol period, which means that lesser and lesser time will be available to carry out the computations while the volume of computation goes on increasing. Since it has been reported that substantial echo cancellation leads to increased system quality and capacity, this paper proposes different sign LMS based ADFEs to cancel the echo signal. The Signed-Regressor LMS gives better performance in terms of their figure of merits compared to the normal LMS and other signed based ADFEs.

Increasing number of subjective text appears on the internet which contains a lot of information. In this paper, we study how to apply supervised learning techniques to solve sentiment classification problems. Using the Tibetan news as data, we find that standard supervised learning techniques definitively outperform human-produced baselines. Moreover, we find that selecting the words with words with polarity as feature, the special syntactic structure such as exclamation sentence pattern, etc. as feature can improve the performance of sentiment classification. Conclusively, the research of sentiment analysis is a more challenging problem.

The green products in manufacture industry still differ from each other in terms of economics, technology, environmental friendliness, though they all reach the criteria of limitation. This paper expounds the necessity for product choice optimization and provides a model based on information entropy to judge different advantages of product groups. According to Entropy Weight Method and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), the basic theory of green product evaluation model is established. The index system includes selected evaluation indicators of green products, considering about the evaluation index of the critical values to construct a hierarchy criterion, which uses entropy to objectively determine the weight vector of each evaluation index. Then, combined with TOPSIS analysis approach and calculates the pros and cons of green products. It is concluded that the evaluation results based on the Entropy-TOPSIS evaluation model are consistent with the actual results, and the results are consistent with the evaluation results of fuzzy mathematics. The method comprehensively considered many influential factors of the green products, to avoid the limitation of single criterion, and the importance of various factors are analyzed and compared, the prediction result is more scientific, as the theoretical basis of green products, and provide a reliable guidance method for product improvement. This is objective to empower the law, which also fully embodies the idea of variable weights and overcome the past green products that exist in the evaluation process homogeneity empowering. That means fixed weights lead to the limitation of a lack of flexible evaluation.