Earticle

Intraceability is the most important aspect of RFID security. Mobile RFID readers are used more and more widely, the privacy of mobile reader privacy holders should be considered. In this paper, a BRS-based approach for modeling mutual intraceability of mobile RFID systems is provided. Elements in a RFID protocol can be represented as bigraphs, communications between elements can be represented as reaction rules. RFID intraceability can be represented as behavioral congruence. We take a RFID air interface protocol for mobile RFID systems as a case study and show the usability of this approach.

Uncertain or complicated systems are difficult to control. Modeling the system uncertainties is an especial topics in most of engineering field. On the other hand, since system has uncertainty, design stable and robust controller is crucial importance in control engineering. To solve this challenge nonlinear control technique is the best choice. Sliding mode control is one important type of robust control. Model imprecision may come from actual uncertainty about the plant or from a purposeful simplification of the system's dynamics. Modeling inaccuracies can cause strong adverse effects on the control design of nonlinear systems. For the class of systems to which it applies, sliding mode controller design provides a systematic approach to the problem of maintaining stability and consistent performance in the face of modeling imprecision. However, sliding mode controller is a robust and stable controller but it has an important challenge called, chattering phenomenon. This research focuses on the comparative between three methods to eliminate/reduce the chattering.

Environmental problem is a worldwide focus, so is the effect of environmental regulation on economy. In this paper, we constructed a model including energy consumption and integrated pollutant emissions of "Three wastes" as "bad" output. This studyr used Malmquist –Luenberger based on directional distance function to measure TFP and environmental regulation cost of Chinese 36 industries from 2001 to 2010. The result was that: From the overall analysis, the TFP was lower after considering the environmental regulation. Technological progress was the main driver of productivity growth. Environmental regulation brought about a certain cost; from the industry analysis, Difference of TFP growth and the cost of environmental regulation existed among different industries. The monopoly and heavy industries were the focus in the industry; from the annual analysis, TFP increased during "Eleventh Five-Year Plan" period, mainly drived by technological progress.

As non-formal language, texts containing dirty words are widespread in Web reviews. Due to their bad effects on users of communication, it is essential to perform automatic analysis on Chinese texts containing dirty word. In this paper, we first crawled over millions of evaluating sentences which contain a lot of dirty words from the Web. Second, we manually annotated 40 typical dirty words with weights. And then proposed a machine learning-based approach for collecting dirty word texts corpus. Overall, more than 6000 sentences were collected from the huge amount of Web reviews to form a corpus on Chinese texts containing dirty words. With the corpus, we present SVM (Support Vector Machine) and ME (Maximum Entropy) classifiers to automatic detect Chinese texts containing dirty words. Empirical studies demonstrate that the SVM and ME classifiers are both effective for this task and the recall and precision are both over 97%.

The support vector machine (SVM) is a fast, and reliable machine learning mechanism. In this paper, we evaluated the stock price predictability of SVM, which is a kind of fundamental analysis that predicts the stock price from corporate intrinsic value. Corporate financial statements are used as input into SVM. Based on the results, we predicted the rise or drop of the stock. In addition, we evaluated how long a given financial statement can be used to predict a stock’s price. Compared to the experts forecast, the results of SVM show good predictability. However, as times goes on, the predictability begins to drop. These predictions based on financial statements are excellent, but after a short period, the dissonance between financial statements and stock price can be offset by reasonable investors. These results support the efficient market hypothesis.

In order to solve the group decision making problems with ordinal interval preference information, a new decision method is proposed based on VIKOR method. The VIKOR method of compromise ranking determines a compromise solution, providing a maximum “group utility” for the “majority” and a minimum of an “individual regret” for the “opponent”, which is an effective tool in multi-attribute decision making. By integrating the operational laws of ordinal interval and the concept of VIKOR method, the detail calculation steps are developed for the group decision making with ordinal interval preference information. Because the comprehensive evaluation values are still interval numbers, we induce the possibility degree to compare these interval numbers. Finally, an example is given, the result shows the approach is simple, effective and easy to calculate.

In machining operations, the extents of important effect of the process parameters like speed, feed, and depth of cut are different for different responses. This paper investigates the effect of process parameters in turning of AA6061 T6 on conventional lathe. The problem appeared owing to selection of parameters increases the deficiency of turning process. Modeling can facilitate the acquisition of a better understanding of such complex process, save the machining time and make the process economic. Thus, the present work clearly defines the development of an artificial neural network (ANN) model for predicting the material removal rate. This study presents a new method to prediction the material removal rate (MRR) on a lathe turning Process. Firstly, Process parameters namely, Spindle speed, depth of cut and feed rate are designed using the Box behnken (DOE) was employed as the experimental strategy. The result shows that the ANN model can predict the material removal rate effectively. This approach helps in economic lathe machining.

With the development of the curtain wall industry and expiration of the curtain wall structures which designed and built in the early life, the testing for building curtain walls will be increasingly focused on. In this paper, a Client/Server structure acquisition system of the curtain wall wind pressure resistance characteristics data, which is based on the Advantech data acquisition card PCI-1747U, has been designed and implemented for the GB/T 15227-2007 (Test method of air permeability, watertightness, wind load resistance performance for curtain walls). The hardware of the data acquisition system contain three major components: The sensor part; The signal conditioning circuits part, which consists of sensor supply circuit, I-V conversion circuit and filter circuit; data acquisition part consists of Advantech card PCI-1747U and Advantech industrial computer 610L. The software of the system contain the data acquisition Server and data processing client. They communicate through TCP/IP protocol and complete the sensor calibration, static test and dynamic test of the wind load performance data, query and output historical data and other functions. Microsoft SQL Server 2000 database was used to management the test data. After running and debugging, the system’s sample time and accuracy reached the requirement of wind load resistance performance test.

With appearance of small-world networks and scale-free networks, complex networks have provided natural theories to describe a variety of complex systems in many domains of science. In this paper, from the standpoint of Raman spectrum research aspect in material science, Raman spectrum analysis of graphite and diamond microcrystal retained by gallium phosphide nanoparticles is introduced. We found that molecular configuration of basic fuchsin adsorbed on gallium phosphide nanoparticles through experiments. Based on these, we adopt corresponding method of complex network to research some problems in Raman spectrum analysis and directly use complex network to convert real agglomerations into network model. With the intention of studying the topologies of agglomeration network, synchronizability behavior of agglomeration network are also discussed.

Read stability and write ability, or SNM (static noise margin) in total, of a SRAM cell is the effective tool to determine the practicability of the cell. Leakage current, read speed and read stability are few of the constrained parameters desired for any practical SRAM cell. The aim of this paper is to analyze the read behaviour of the multiple SRAM cell structures using cadence tool at 45nm technology and to compare the cells for read operation while keeping the read and write access time and the supply voltage as low as possible. In particular, the leakage currents, leakage power and read behaviour of each SRAM cells are examined . A 10T SRAM cell implementation is proposed here that results in reduced leakage power and leakage current, at the same time with increased read stability in comparision with the conventional 6T SRAM cell as well as 7T, 8T and 9T SRAM cells. As a result, the 10T SRAM always consumes lowest leakage power and leakage current; improve read stability as compared to the 6T, 7T, 8T and 9T SRAM cells. This paper is aimed to reduce the leakage power, leakage current and improve the read behaviour of the different SRAM cell structures using cadence tool at 45nm technology while keeping the read and write access time and the power as low as possible.

In the paper, we analyze the security vulnerability of the key agreement protocol proposed by Lee et al.'s. We present a forgery attack to their protocol. In this attack, the adversary can modify the signed message and forge a new signature, which can pass the verification. Then, we propose a new group key agreement protocol, which overcomes this security drawback. The new protocol can be proved to be secure under Elliptic Curve Discrete Logarithm Problem, Bilinear Computational Diffie–Hellman Problem and Square-Exponent Problem. On the other hand, in the new protocol, only three pairing operations are used, so it is more efficient. Our protocol is also a contributory group key agreement protocol.

The economy in Suzhou, China is in the late stages of its industrialisation, during which, the completeness of non-profit organizations (NPOs) has been an important indicator for measuring the all-round socio-economic development of Suzhou. Currently, the NPOs of Suzhou make up for deficiencies in the government and the market, and thus make a positive contribution to the political and economic development of Suzhou. However, it is easy to find that NPOs still suffer disadvantages such as slow development, rarity, and low capacity: these inhibit their active benefits. This research investigated the classification and development status of the NPOs in Suzhou; on this basis, it analyzed the main problems facing them. Moreover, aiming at these problems, countermeasures and suggestions were proposed so as to allow them to play a more important in the socio-economic system of Suzhou.

Traditional requirements analysis is focused on capture functions of the system that are being built from scratch. As the size and complexity of process-aware information system continues to grow, the use of COTS (Commercial off-the-shelf) software packages is being viewed as a solution. Use of COTS packages accelerates the implementation process to some extent, however, it puts enterprises into a dilemma: whether to adapt as-is business processes or to customize software packages. In order to help the enterprises get out of the dilemma, a methodology is proposed to automatically elicit software requirement using best practice as domain knowledge. The methodology involves three phases: business modeling, gap detecting and gap bridging. Firstly, VPML is employed to describe as-is business process, Secondly, semantics computing technology is employed to analyze the gap between enterprise needs and COTS software capacity. At last, Goal Reasoning Technology is employed to encourage enterprise users and software vendors take participate in decision making process together.

The key to improve the container terminal efficiency is the integrated optimization of the quay crane (QC) and the yard truck (YT) scheduling, which is normally settled separately and considered in a certain condition in classical literatures. To improve the operation efficiency and simulate the practical operation, a PSO-based integrated QC-YT scheduling optimization model with uncertain factors is established in this research, considering two uncertain factors of YT travel speed and unit time of QC loading/discharging operation that affect the operating efficiency of the terminal greatly. The goal is the minimal operated time of QCs with the coordination of YTs. To solve this difficult combinatorial problem, the PSO algorithm is developed. PSO is evaluated for combinatorial problems with uncertain factors, which represents a new application of PSO. Numerical experiments show that the model of this research gives systemic simulation for the scheduling process with uncertain factors. And the results are better than model without uncertainties in terms of the accuracy and stability.

Vehicular ad hoc network is a type of network and provides the communications between vehicle to road side, vehicle to vehicle and vehicle to infrastructure.VANET has new applications and features for travelers to providing vehicle related information for safety purpose that have never been possible in past. It is an application of MANET. In MANET the node is communicating with the base station. The present paper is mainly intended to compare the routing protocol for the improvement of network services by comparing the routing protocol in terms of throughput, end to end delay by using group mobility model on Qualnet 6.1.The research works evaluate the performance of two protocols namely AODV andDSR. To provide multihop routes from node to the server all mobile nodes were randomly positioned in the network.

In traditional fault diagnosis method, a large number of experiments are needed to get the optimal performance classifier which diagnoses type of fault. Because of classifier algorithm limit, there is no one classifier can be applied to all kinds of fault diagnosis. In order to avoid the disadvantages caused by single classifier approach, decision level fusion method based on multiple classifiers fusion is introduced in the field of fault diagnosis. The fusion method with fuzzy comprehensive evaluation is put forward and the basic evaluation model is set up. The reasonable distribution of classifiers weight that affects diagnosis result directly is vital. Firstly, the evaluation function which measures member classifier’s diagnostic accuracy and correctness is constructed based on the theory of information entropy. Then, weights are distributed to each classifier with entropy coefficient according to the value of evaluation function. Experiments are carried out to demonstrate the effectiveness of the proposed method and results show that fault recognition rate after fusion is higher compared with the single classifier method.

Design based upon CMOS logic are becoming increasingly attractive for many applications under electronic gadgets, but with increasing demand of small and portable devices, new techniques for low power are emerging. This paper focus on the design of subtarction logic for ALU sub-module in microprocessor design. Set of four different 10-T subtraction logic using Gate Diffusion Index(a new technique for low power design) has been designed using 180nm technology using Cadence Virtuoso and simulation are performed . Complete verification for performance of proposed subtraction logic is carried and circuit with least power and delay has been selected for the ALU design of the microprocessor. Layout design for the best optimum ciruit is designed using Layout XL and area of 17.28 X 11.135 μm2 is calculated.

In this paper, we first comparative analysis the existing prediction methods. Based on the GM and ARMA, we propose a new combined forecasting model which integrated the advantage of the GM is suitable for medium and long term forecast, the GM algorithm is simple and the ARMA is suitable for short time forecast. Moreover, we use the rail traffic data to verify this model. The results show that the combined forecasting model we proposed is of high forecast precision, and the combined forecasting model is better than the single forecasting model.

This paper proposes a novel fast direction of arrival (DOA) estimation method for scenarios when uncorrelated and coherent signals exist simultaneously. First, using uniform transformation, we change complex matrix into real matrix, then, just by exploiting real propagator method (RPM), we can attain the uncorrelated signals DOA fastly. Second, based on new spatial difference technique, we can eliminate the effection of uncorrelated signals and make coherent signals become uncorrelated. Finally, utilizing RPM technique, coherent signals DOA can be estimated swiftly. Simulation results validate the performance improvement of the proposed algorithm.

Carbon capture and storage (CCS) facilities coupled to clean coal plants provide a climate change and reducing the Co2 (carbon dioxide) emission .The application of Carbon Capture and Storage (CCS) in the generating electricity is important for reducing the cost electricity and consumer bills. This paper represents new ways to categorize the options for mitigation of cost and consumer bills and Co2 emissions. A detailed description on the ways to Carbon Capture and Storage in the coal fired plant, the power industry, capture, transport and store Co2 has been presented. The power penalties and cost can be big Challenges to apply CCS to the generating electricity while a lot of opportunities exist such as the development of the carbon trade market and industrial utilization of Co2. Carbon Capture and Storage (CCS) connected to clean coal power plants, plays an important role in reducing carbon emission and provide an environmental change. This paper represents a new ways for climate protection, environmental effects, environmental benefits, efficiency benefits, environmental effects and energy analyses in a carbon capture and storage. The power industry, capture, transport and store CO2 has already been presented in the field of carbon capture and storage in coal fired power plant.

With a great deal of digitized textual information now available on the internet, it is almost impossible for people to assimilate all the information timely. Therefore, the technologies of topic detection and tracking are used for constructing news topics from news stories in order to bring convenience to people. However, traditional topic detection methods are not always so effective in detecting emerging hot news topics in a short period of time, and most topic detection methods use single-pass clustering algorithm which is with low accuracy and very sensitive to the input sequence of news documents. In order to improve clustering accuracy, we utilize a temporal distance factor to segment timeline into equal parts and propose a novel two-times single-pass clustering algorithm to deal with news stories in each part of timeline separately. Moreover, the aging theory is combined with our approach to build life-span model of topics from which we can obtain variation trend of hotness value of topics. The results of experiments show that our approach is effective and the life circle model of topics established by our method can conform to reality well.

In the study of mine GIS index optimization of mining decision support system, in order to reduce the overlap between the index nodes, in this paper we propose the intensity of polygon to ensure the index nodes have good geometry. In this paper, we also put forward artificial fish swarm clustering based on Voronoi diagram (AFSCV) and apply the AFSCV to mine GIS index splitting algorithm. In the end, we give the optimization rules of AFSCV. In order to verify the effectiveness of our algorithm we compare our method with traditional methods, the experimental results show that our method can improve the query performance of mine GIS database and greatly reduce the overlap which generates from reinsert after the index node split.

Titaniun di-oxide (TiO2) hasmany excellent physical properties such as high dielectric constant a strong mechanical and chemical stability. Tio2 has high refractive index and good insulating properties, as a result it is widely used as protective layer for very large scale integrated(VLSI)circuits and for manufacture of optical elements.Additionally TiO2 films have potential uses for a number of electroniuc device applications such as dye-sensitized photovoltaic celles as well as anti reflective (AR) coatings, gas sensore, electro chromic displays, and planar waveguides. The nanomaterilas were characterized using x-ray diffraction,UV-visible reflectance spectroscopy.In this paper, we have discussed the groth of the High quality Titanium di oxide (tio2) material and study their optical and lectriacl properties.

Analysis of existing research results of defect testing, software defects during testing should consider the relevance of the defect test software, the design of a Markov chain with the right to test the model, the design of a multi-objective algorithm weights given Markov chain with the right test strategy based on defects associated with the state transition strategy based on multi-objective test weight matrix. The experimental results show that this strategy compared with Controlled Markov Chain testing strategy that can significantly reduce test cases and improve the defect detection rate.

Nowadays, the use of mobile social network has occupied a number of user's daily life. The production of social network makes the user's life richer, and dating is not limited by time and space at all. On the other side, as for the mobile social network, the negative influence result from many respects, including the users' reliance on the mobile social network, their satisfaction about the mobile social network, the users' credibility to the mobile social network, the risk of mobile social network safety and so on. This research investigated the users’ attitude and behavior of Facebook mobile; collected data by questionnaires, literature research and interviews; discussed the negative influence on the mobile social network; finally proposed suggestions for mobile social network. By the research, it focused on the issue of mobile social network’s negative impacts on people’s life and benefit to provide a reliable data and evidence to mobile social network, the conclusions also contribute to mobile social network study and practice in China.

A large number of emerging information networks brings new challenges to the community detection. The meaningful community should be topic-oriented. However, the topology-based methods only reflect the strength of connection, and ignore the consistency of the topics; the content-based methods focus on the contents and completely ignore the links. This paper explores a topic oriented community detection method simLPA based on label propagation for information work. The method utilizes Latent Dirichlet Allocation topic model to represent the node content, and calculate the content similarity by the normalized Kullback–Leibler divergence. simLPA extended by LabelRank fuses the links and the contents naturally to detect the topic community. Extensive experiments on nine real-world datasets with varying sizes and characteristics validate the proposed method outperforms other baseline algorithms in quality. Additionally simLPA integrated into the content is equivalent to LabelRank in efficiency, which is easy to handle large-scale information networks.

The objective of this paper is to improvise a technique for battery optimization of smartphones. The technique is based on reduction in energy consumed by communication over network. This will be achieved by utilizing cooperative device-to-device communication. The proposed system will allow users with higher battery level to carry traffic of users with lower battery level, thereby reducing the chances of user running out of battery early. It can be implemented in form of a proximity service (ProSe) using the device-to-device (D2D) communication architecture underlying Long Term Evolution-Advance (LTE-A) technology in hexagonal cell environment. The paper also includes the goal to develop a technique for efficient positioning of user equipment and implementation of connection handover for this D2D communication ProSe. The technique for handover is based on Observed Time Difference Of Arrival (OTDOA) positioning approach along with the Positioning Reference Signal (PRS), mentioned in Release 9 of LTE technology. It is shown through simulations that the proposed system will reduce the probability of outage i.e. the probability of the UEs running out of battery power before their target usage time. The scheme will also reduce the probability of connection dropping, thereby improving performance of whole system.

Accurate storm tracking and forecasting are essential parts of severe weather warning operations. The main problem of existing tracking and forecasting algorithms is unphysical split and merger of cloud clusters within the life cycle of Mesoscale Convective System (MCS). To address this issue, an automatic algorithm called TFCC (Tracking and Forecasting Convective Cells) is proposed for tracking and forecasting convective cells using infrared (IR) image sequences from geostationary meteorology satellite. In this paper, convective cells are utilized for tracking and forecasting instead of MCS because convective cells are stable portion in MCS. TFCC algorithm utilizes overlapping technique and uses a dynamic constraint technique based combinatorial optimization method. Moreover, displacement of the geometrical centroid is utilized to forecast the movement of convective cells. Case studies show that convective cells are tracked and forecasted efficiently in different phases of MCS lifecycle including genesis, maturity and dissipation using TFCC algorithm. Categorical statistics and contingency tables method applied to various case studies over China show that TFCC algorithm efficiently and accurately.

Multiple Autonomous systems (ASes) of the network are usually consisted of many routers such as inter-router and intra-router connection each other. In order to detect the network routers connection relationship, many researchers at home or abroad use various methods such as active end-to-end links detection or observing SNMP MIBs to understand the links’ connection relationship among the routers in network’ ASes. In this paper, by using the link prediction algorithm based on the similarity, we tried to predict the links’ connection relationship and got the possible network topology structure among the network’ ASes when the actual connection link don’t be completely detected. Through the experiments, the prediction results can be seen that the similarity algorithm index of ACT, SRW, and SimRank based on the random walk can also achieve better prediction accuracy above 0.95, which prove the similarity index especially the random walk algorithm can realize the higher link prediction accuracy to the network’ ASes under the conditions of missing some known connection link, etc.