Key Engineering Materials Vols. 467-469

Abstract: Assembly and disassembly is a new and also a rapid developed trend in manufacturing area. In the future the assembly and disassembly will be one inseparable part of manufacturing process. Especially automated disassembly is a technology, which is trying to satisfy needs and requirements. Many of special requirements are supported by international institutions, research programs and foundations. In our Institute of Manufacturing Systems and Applied Mechanics at Faculty of Materials Science and Technology the project named Intelligent assembly cell is realized. Within the frame of this project designing of structure, following of several assembly steps, organization of material flow and others is processed. Currently disassembly is one part of solving problems as assembly. Automated disassembly technique allows an automated separation of various parts, from which was disassembled product created.

Abstract: This thesis mainly studies Copula model and the application of the model in financial market risk management. On the basis of studying copula, this thesis builds a dynamic Copula model to solve the financial market risk management problems. Using statistics and financial theories and Copula model, the thesis studies applications of Copula model in the financial risk management and resolves the problem that whether the financial contagion exists. The results indicate that the applications of model in the financial market risk management are effective, and should study in deep.

Abstract: All of middlewares of modern wireless sensor networks has this weakness that many of these middlewares have the ability to simultaneous support from limit amounts of quality of service parameters. Our aim is simultaneous and dynamic support from several quality of service measure in middleware layer with obtained weight coefficients. In this paper, we add a layer of Quality of service management to middleware, in which this layer has duty of service of Quality of service management and control. This layer answers demanded Quality of service improvement from application by wireless sensor network.

Abstract: In the present study, the feasibility of the poly(divinyl-benzene vinylpyrrolidone) as solid-phase extraction (SPE) nanoscale adsorbent prior to LC-MS-MS method for the sensitive and selective determination of eight paralytic shellfish poisoning (PSP) (GTX1, GTX2, GTX3, GTX4, GTX5, dcGTX2, dcGTX3 and dcNEO-b) toxins in the shellfish was investigated. Various parameters affecting SPE efficiency including the eluent and its volume, and sample volume were studied. The application of the SPE can remove most of the ematrix interference compared with the conventional SPE procedure. By using slected reaction monitoring (SRM) mode in LC-MS-MS analysis, the acquired calibration curves were strictly linear (r2 > 0.996) for the eight targeted analyses. The feasibility of the proposed method was finally validated by quantifing the eight PSPs in the shellfish samples (scallop, Crassostrea gigas and Ruditapes philippinarum) with the satisfitory recoveries of more than 80% with RSDs less than 10%.

Abstract: Demand for context-aware systems continues to grow due to the diffusion of mobile devices. This trend may represent good market opportunities for mobile service industries. Thus, context-aware or location-based advertising (LBA) has been an interesting marketing tool for many companies. However, some studies reported that the performance of context-aware marketing or advertising has been quite disappointing. In this study, we propose a novel context-aware recommender system for LBA. Our proposed model is designed to apply a modified collaborative filtering (CF) algorithm with regard to the several dimensions for the personalization of mobile devices – location, time and the user’s needs type. In particular, we employ a classification rule to understand user’s needs type using a decision tree algorithm. We empirically validated the effectiveness of the proposed model by using a real-world dataset. Experimental results show that our model makes more accurate and satisfactory advertisements than comparative systems.

Abstract: The fixed-point number arithmetic is always the key and difficult point of the computer organization. It is the basic knowledge of the computer organization. Because there are many operation methods of the fixed-point number and the operation process of it is complicated, the fixed-point number arithmetic is not easy for students to learn. The lack of the software to help the students do simulation computation is the biggest problem in the current teaching of the knowledge. To solve the problem, the simulation software of the fixed-point number arithmetic is developed with C++builder. The software is made up of "the fixed-point integer two's complement addition" module, "the fixed-point decimals two's complement addition" module, "the fixed-point integer two's complement subtraction" module, "the fixed-point decimals two's complement subtraction" module, "the sign-magnitude 1-bit multiplication"module, "the Booth's Algorithm"module, "the sign-magnitude two bits multiplication"module, "the two's complement two bits multiplication"module, "the sign-magnitude recovery remainder division"module, "the sign-magnitude unrecovery remainder division"module, "the two's complement unrecovery remainder division"module, etc. In order to test the simulation software, the test case is designed for the fixed-point arithmetic. According to the designed test case，the detailed test is carried out. The test results show that its simulation effect is good. The simulation software realizes the addition, subtraction, multiplication, and division of the fixed-point number successfully. The CAI (computer-assisted instruction) can be carried out through the software. The software can help the students be familiar with and master the fixed-point number arithmetic rapidly.

Abstract: For the probability neural network (PNN) algorithm is the non-surveillance's pattern taxonomic approach, the work load major problem, moreover the category number's selection will affect the cluster performance. How to optimize PNN enabled it to play a more effective role in the classified question, this paper proposed one use genetic algorithm optimization probability neural network method: introduction the auto-adapted mechanism genetic algorithm, to the probability neural network's parameter carries on the training, formed the supervised learning probability neural network based on the genetic algorithm, overcome the probability neural network existing algorithm flaw. Then introduces this model in the quality control, guaranteed that the production process is at the control state, achieves the quality control goal. Carries on the test through the simulation experiment to this algorithm, and with the probability neural network, the BP neural network carries on the comparative analysis, proved this method accuracy is high.

Abstract: Processing technologies of superfine wood powder is a new field for wood the industry, while a new research direction is added for the wood industry. Grinding equipments for superfine wood powder is one key device for superfine wood powder production, and it plays an important role during processing superfine wood powder. Cutting and grinding methods with both semi-enclosed and two-cycle characteristics are used, there are three kinds of screen with various specifications inside the grinding room, and three kind of wood powder with different granularity requirements. Virtual reality technology is introduced into the wood powder pulverizer with multi-granularity designed, and both three-dimensional model of wood powder pulverizer with multi-granularity and the visual system for enhanced wood pulverizer are built. Virtual design technology can not only reduce product development cost greatly for the wood powder pulverizer but also shorten product development cycle for the wood powder pulverizer greatly, and there has vital significance to save manufacture cost.

Abstract: Wood powder used in fuel is an important part of sustainable energy, whose processing technology is a new research field for the wood industry, while wood powder disintegrator used in fuel is a key equipment of production equipments. Many soft wares such as Pro/E are applied to complete three-dimensional model for the wood powder disintegrator used in fuel while some soft wares such as ADAMS are applied to carry out motion simulation with braking device component of the wood powder disintegrator used in fuel, thus braking results for both braking head and braking bar can be obtained from the curve, which are in line with the anticipated results. Therefore, it can provide a new kind about optimizing structure of the wood powder disintegrator used in fuel further by way of studying grinding equipments for wood powder used in fuel under ADAMS environment, which has not only real economic significance but also broad application prospects.

Abstract: There are a couple of inherent shortcomings which are hard to be overcome in single topology network; thus we propose a novel routing protocol—VCHR, i.e., Virtual Cluster-based Hybrid Routing, which employs hybrid topology, bears the stamp of flat and hierarchical routing protocol. At stage of hierarchical routing, VCHR draws on the idea of the virtual cluster; base station controls clustering process based on network coverage control criteria in centralized model, and ensuring the reliability of virtual clusters by making use of the three-way handshake mechanism. Flat routing employs shortest path routing protocol to get the optimized routing path to base station. In context of low algorithm complexity, the protocol could realize full network coverage control, effectively balance energy load among sensor nodes and quickly respond to network dynamic changes.