Earticle

Centripetal Accelerated Particle Swarm Optimization (CAPSO) is a recent and well embraced, interest stimulating topic in swarm intelligence (SI). The original CAPSO method does not have parameters to tune or adjust, so two new parameters are introduced to catapult the efficiency and boost the overall performance. For further enhancement of the algorithm’s efficiency, the principle of quantum-behaved particles is also added. In evaluating the capability of the Improved Centripetal Accelerated Particle Swarm Optimization (ICAPSO) algorithm, we tested it on medical image database, in the aspect of Relevance Feedback of a Content-Based Image Retrieval (CBIR) system, clearly, ICAPSO outperformed others.

To apply efficient rolling conditions in the finishing rolling process, a correct prediction of the behavior of the strip temperature is required. This study is focused on the temperature distribution of the strip temperature from FET to FDT of the actual finishing rolling process. The heat transfer phenomena generated during the finishing rolling process, such as heat generation, cooling and conducting, were modeled in this study using the finite difference method. Using various heat transfer phenomena generated in the finishing rolling process and the correlation formula of spray cooling coefficient, the calculation accuracy was improved and a simulator to predict the temperature distribution of strip was prepared. The calculated result is compared to the online model used in the actual industry.

Triaxial compression tests had been performed to determine the properties of the surrounding rock. The displacement and stress of surrounding rock had been analyzed according to Silin 2 at Yungui railway under three kinds of conditions: the initial state, excavation without supporting , and supporting after excavation. Plane strain FEM was established to analyze the stability of the surrounding rock. Contrasted the monitor measuring data, the results showed that the most unfavorable position in the tunnel was found at the ridge side of the arch, and the implementation of support afforded to ensure the stability of surrounding rock, and the design of the early support approach had the ability to meet the safety requirements. The results had certain significance for understanding the mechanical behavior of shallow tunnel in unsymmetrical strata. tunnel, mechanical behaviour, numerical simulation, deformation, stability.

The repair of catapult is a complicated engineering. In this paper, the method of Condition Based Maintenance is applied into the repair system based on the catapult maintenance of system analysis. In view of the application of Condition Based Maintenance in the modern aviation equipment, the catapult availability is the final goal. The structure of catapult maintenance system is analyzed. The structure model of system dynamic feedback is established by using system dynamics method. Simulation is based on the "Nimitz" actual data of the Surge operation in 1997. The results prove the effectiveness and rationality of the proposed method. Through the analysis of the simulation evaluation results, the method applying Condition Based Maintenance into catapult repair system can improve catapult availability.

The crystallization behavior and microstructural change in glass-ceramics with a cordierite composition were analyzed as a function of concentration and etching time of the HF solution in order to enhance the degree of crystallinity of the glass. Compared to a specimen without etching, the glass frit specimens etched with HF solution showed increased crystalline peak intensities of the μ-cordierite phase in the XRD pattern. The crystal size in the glass matrix also increased with an increasing concentration of the HF solution for the etched glass frit. The crystal peak intensity of the α-cordierite phase in the glass-ceramics made with glass frit etched with 0.5-1.5 wt% HF solution had a slightly higher value than that of pure glass frit regardless of the etching time. The intensity of the specimen with etched glass frit with 3.0 wt% HF solution, however, was lower than that of the specimen of the pure glass frit. Obviously, for the glass-ceramics etched with HF solution of various conditions, the α-cordierite phase is more favorable for crystallization than the α-cordierite phase. This study revealed that the microstructure and ratio of the crystallinity of the α-cordierite phase over the α-cordierite phase in the obtained glass-ceramics could be controlled by changing the HF-etching conditions followed by a heat treatment process.

Semantic Web services have emerged as the solution to the need for automating several aspects related to service-oriented architectures, such as service discovery and composition, and they are realized by combining Semantic Web technologies and Web service standards. The increasing number of available Web services has raised the need for their automated and accurate classification. Services Classification would be useful to enact powerful capabilities such as automatic selection, invocation, composition, location or discovery of web services. In this paper, We proposes a approach of Semantic Web Services classification taking into account the feature of textual description and the semantic annotations of OWL-S advertisements. An experimental test of the proposed techniques is reported, showing positive results, the efficiency and accuracy of the automatic service portfolio has been improved.

Multi-criteria(or) attribute decision making (MCDM/MADM) methods have very high applications inindustriesforsolving real world engineering problems. In the present work, MCDM methods of Weighted summethod (WSM), Weighted ProductMethod (WPM) and TOPSIS, have been employed for the computational analysis of multi-responses. AA7075 has been taken as work piece for the experimentation and the experiments were done on CNC lathe as per the Taguchi’s standard L9 Orthogonal Array. The cutting parameters of speed, feed and depth of cut were taken as experimental inputs and Material Removal Rate (MRR) and Surface Roughness (Ra) were considered as responses. From the Weighted sum method (WSM) and Weighted ProductMethod (WPM) the optimal combination for multi-responses werefound at ninth alternative,i.e. speed: 2000 rpm, feed: 0.4 mm/rev and depth of cut: 0.75 mm. Similarly, from the TOPSIS results, the optimal combination for multi-responses werefound at seventh alternative,i.e. speed: 2000 rpm, feed: 0.2 mm/rev and depth of cut: 1 mm. Analysis of variance (ANOVA) has been done by using MINITAB-16 statistical software to find the influence of cutting parameters on the multi-responses. From the ANOVA results of WSM, WPM and relative closeness coefficient (Ci+), it is found that feed rate has high influence (For WSM, WPM and Ci+the F values are 60.50, 60.30 and 91.42 respectively) in affecting the multi-responses.

Aiming at the existing problems of the DFIG grid side converter, this paper studies its control technology and proposes a composite control strategy which includes a terminal sliding mode variable structure control of the current inner-loop and a PI controller of the voltage outer-loop in grid side converter. The simulation results show that the control strategy proposed in this paper can achieve better control of the inverter output voltage and input current. What's more important, this method can not only reduce the adverse effects on the grid side converter due to parameter variations and other factors, but also increases the robustness of the system. It has important actual significance and practical application value.

C2C-to-B2C transformation, as the inevitable development trend of the Chinese e-commerce, involves many uncertain indexes. The Paper adopts the quantitative and qualitative method to build the index system of the C2C-to-B2C transformation, confirms indexes playing the role in the transformation, and sorts out evaluation factor set and judgement set. And the Paper ensure the weight of evaluation factors by the analytic hierarchy process, confirms the membership degree of indexes to the judgement set baseed on the questionnaire survey, build the single-factor fuzzy judgement to do the comprehensive fuzzy judgement and analysis for each index, and then supply a constructive and instructive way for the transformation-seeking and in-transformation e-commerce.

Wind power energy is receiving attention in recent years. The properties of wind are very hard to predict because of its heavy nonlinear characteristics. This paper predicts the wind speed by ANFIS and FCM clustering. The data were measured in the region of islands in Jeonnam Shinan. One year and 10 minute interval makes 52,560 samples of data but use 48,240 samples instead for stable operation. For prediction of wind speed, the covariance was examined. As a result, the input domain consists of lunar date and wind direction. This input domain has so big range of wind direction and lunar date. Therefore the whole range is partitioned by clusters. For experiments, two type are chosen. one is 4 clusters and the other is 6 clusters. . The error of cluster-6 is 7.5 % lower than cluster-4. This means that the prediction of cluster-6 is more accurate than cluster-4. With four Gaussian bell membership functions, ANFIS is trained over 200 epochs by clustered data. After training, ANFIS could predict the wind speed by lunar date and wind direction. Even if heavy nonlinear system can be predicted by ANFIS and FCM clustering.

Focusing on solving the problems of increasing certificate counterfeiting, a novel certificate management system based on two-dimensional barcode technology was developed in the present work. The system, which was compiled using JAVA programming language, can achieve the two-dimensional barcode encoding and decoding for plain texts, images and information included in a certificate (the combined information of texts and images). To improve the security in practical applications, the scrambling algorithm and watermarking encryption algorithm were added, and accordingly, the security of the information contained in two-dimensional barcodes can be ensured. The whole system consists of three modules-encoding, encryption and decoding. To be specific, before encoding, the scrambling transformations should be performed on the certificate image while the number of scrambling transformations is adopted as the secret key. With respect to the generated two-dimensional barcode, we can embed the existing binary images or the signature messages of the certificate holder on this platform into the space domain, contributing to a significantly enhanced anti-counterfeiting performance of the certificate. The certificate information and watermarking information are extracted during the decoding process, i.e., only when the number of scrambling transformations is accurately input, the watermarking information can be extracted and used for identify whether the certificate is counterfeit. The simulation results indicate that, by combing with digital watermarking technology, the security of the two-dimensional barcodes and the included information can be greatly improved while the anti-counterfeiting of certificates can be indeed achieved. Finally, with the student’s certificates as the example, we performed simulations on the whole system. It can be concluded that the developed system can be promoted in the other application fields only when some appropriate changes are made.

Rewarding the innovative customers in collaborative innovation can increase the initiative of customer involvement and improve the performance of product innovation. Therefore, a method of customer profit distribution based on contribution degree was proposed. Firstly, customer contribution evaluation index system was established from knowledge perspective. Secondly, customer contribution evaluation method based on group linguistic consistency was put forward to determine the contribution degree, and customer profit was distributed according to the contribution degree. Two-tuple linguistic consistency was used to integrate the multi-attribute evaluation information. Finally, the feasibility and effectiveness of the proposed method was verified.

This study is an empirical study for related industries of broadcasting TV Format. Global TV trade market as MIPCOM, MIPTV, ATF, CICAF etc, is growing but TV Format trade is dependent on the exportations of TV Format. This study analyzed that the many person in charge of localization about TV Format trade what they were thinking when they trade on Format business. And carry out a survey targeting the person in charge 500 participants in ATF. For analysis, it used that the trade factors (Format brand reliability, Format confidence, Format genre similarity, Viewers’ Format sympathy and Viewers’ Format reactivity) of the person in charge and localization factors (Format stability and Format possibility of localization). The result of this study found the effects between independent variables (Format brand reliability and Viewers’ Format sympathy) and dependent variables (Format stability and Format possibility of localization). It is necessary to indicate in this result that could find the reason of a trade vitalization about global TV Format distribution because broadcasters and production companies do not know where trade business solutions are. Because of this, this study provides good business chance for the industrial world, and academic meaning has undeniable worth.

To extract the brainstem auditory evoked potentials and remove the spontaneous electroencephalograph and other background noises, the paper proposed a new method of wavelet information entropy theory de-noising based on wavelet de-noising. In the method, the threshold function is improved by introducing the weighting factor and determine the weighting factor according to the wavelet information entropy to obtain a better de-noising effect. The simulation experiment shows, compared to the traditional wavelet de-noising method, the new method can preserve the details of the signal better and make the signal waveform smoother. At the same time, the new method can suppress the pulse signal, which make the system has a better de-noising performance and achieve higher quality extraction brainstem auditory evoked potentials.

In this article, we modelled and simulated Carbon Nanotube Field Effect Transistors (CNTFET); this transistor has a carbon nanotube channel. An Artificial Neural Networks (ANN) model was developed to reproduce accurately the behavior of CNTFET to predict its response for a wide range of temperature and voltage with focusing on the experimental data. The neural model is tested and validated; hence the ANN model is able to predict the CNTFET behavior with good accuracy. Finally, the proposed ANN model is integrated as a component in the library of simulation software of PSPICE electronic components.

Tonal information is important for Chinese Mandarin speech recognition and understanding. Tone information is carried on the shape of fundamental frequencies. When constructing a tone recognition system based on support vector machine, the fundamental frequencies should be normalized by curve fitting method. The fitting coefficients are input data of support vector machine, but it cannot precisely represent the shape of fundamental frequencies. An improved tone model is proposed, which added some other information of fundamental frequencies, such as the maximum and minimum value, the position of maximum and minimum values, the fundamental frequency values of first and last point. The experimental result shows that the proposed model is more accurate with the shape of fundamental frequencies and the accuracy rate of tone recognition is increased by using the improved tone model.

In modern financial issues empirical analysis shows that the volatility of financial market time series showed more variable, volatility clustering, spike and heavy tail. Garch model family in the analysis of financial time series squared error autocorrelation on widely recognized. However Garch model only analysis a single time series, correlation analysis for multiple time series on limitations. This paper introduces Copula function for studying the correlation of multiple time series. Using Garch model as marginal distribution for Copula function. At the same time, analyze correlation of t- Copula and normality Copula in the financial issus.

South Korea’s e-Government is changing its e-Governance to strengthen information transparency and fairness, having passed through the preparation, diffusion, and maturation stages according to the direction and purpose of the government’s policies. Various services are being offered and are evolving towards a system where businesses can bid for public informatization in a way that makes public information open to citizens. This study examined the intentions of procurement business bidding managers that use the e-Procurement system for bidding. The study model combined the UTAUT and TTF models. A positive analysis was performed using the SMART PLS for statistical analysis and hypothesis testing. The results showed that, for procurement business users, performance expectance, social influence, and facilitating conditions but not effort expectance had a significant positive influence, perhaps because systems adopted through government policies are not in a form that can be used voluntarily (e.g., smartphones, tablet PCs, Internet banking) but instead have inherent characteristics that give users no options, regardless of their wishes. This study is significant in identifying the characteristics attributable to obligatory use, instead of voluntary use, for the achievement of organizational (company) goals.

Model-Driven Engineering (MDE) tries to reduce the effort spent on software development by generating codes from models. People concentrate their minds on the transformation between models and models, or between models and codes. People also concentrate on checking consistency between different models such as consistency between a class diagram and a sequence diagram and consistency between a sequence diagram and a state machine diagram. Checking relationship consistency and class redundancy in a class model is still important but ignored in recent years. This paper concentrates on relationship problems between classes in a class diagram and proposes methods of checking various relationship problems. We address the redundancy of a class’s operations and attributes. We identify a large range of the problems for class diagram. Our research is based on the relationship abstraction rules.

Rapid and timely monitoring of traumatic inflammation is conducive to doctors’ diagnosis and treatment. It has been proved that electronic nose (E-nose) is an effective way to predict the bacterial class of wound infection by smelling the odor produced by the metabolites, and the classification accuracy of E-nose is influenced strongly by the classifier. To improve the performance of E-nose in predicting the bacterial class of wound infection, an enhanced SVM with a novel weighted Gaussian RBF kernel is proposed in this paper, and the way of setting parameters of this enhanced SVM is also given. Experimental results prove that the classification accuracy of SVM with the novel weighted Gaussian RBF kernel is 95.24%, which is better than other considered classifiers (PLS-DA, RBFNN, SVM with single Gaussian RBF kernel and SVM with traditional weighted Gaussian RBF kernel). All results make it clear that the enhanced SVM proposed in this paper is an ideal classifier when E-nose is used to detect the bacterial class of wound infection.

This paper uses public opinion propagation structure of Sina microblog as research object, it sets up simulation model of public opinion propagation structures based on complex network theory. Through the analysis of the degree distribution, clustering coefficient and community structure of the model, the validity of the model has been well confirmed. The paper also conducts research and analysis towards propagation quantity of the hot topic within 800 well-known spread microblog from 2013 to 2015, the paper establishes a community structure, through the simulation and demonstration of the community structure, it declares the community structure characteristic under the complex network environment.

In this paper, fuzzy condition rules are studied to improve video format conversion. The propose method consists of three parts: (1) system consideration, (2) image quality assessment, and (3) adjusting parameters. By adopting hedges in membership function, we apply additional effects for fuzzy operations. In addition, by providing condition rules for four fuzzy sets ‘fast’, ‘slow’, ‘homogeneity’, and ‘heterogeneity’, we could improve restored images. The hedges are applied in each fuzzy set depending on the input values, which provides additional effect. Experimental results show that the proposed method outperforms two benchmark methods.

In the present drilling materials supplies management informationization level is low, which lead to low efficiency of management in the Chinese oil enterprises. This paper presents an effective solution combined with RFID and web technology for oil enterprise information service platform system, and studies several key technologies in the design. The system has taken the advantages of RFID and web services in the practical application process, the enterprises can use this RFID solution to enhance the logistics management efficiency in the oil-drilling materials supplies. At the end of the paper we proposed technical barriers is one of the reasons for RFID popularization.

Spamming on microblogging platforms has been a critical issue in microblog-based applications, because spamming has a significant impact on information quality and credibility. In this paper, we characterize two types of spammers on microblogging platforms, namely advertised spammers and following spammers, and then present preliminary approaches to detect these spammers. We first use a real data set to characterize the features of AS and FS in terms of various aspects such as profile, behavior, and social relationship. Specially, we introduce a new feature named duplication for FS detection, which describes the duplicated behavior of users in sharing information on microblogging platforms. We present a content-sharing graph to model the relationship between users and microblogging contents, and propose an effective algorithm to calculate the duplication feature. We run several classification methods on the characterized features to test the effectiveness of the features in AS and FS detection. The results w.r.t. precision, recall, F-measure, and ROC suggest the effectiveness of our proposed features. In particular, the duplication feature is able to improve the effectiveness of FS detection.

Precision of pests, in stored grain insect population density, has been a hot and difficult research in pest detection and control system. The accuracy of prediction of pest density will directly affect to warehouse grain temperature and the food quality etc. In order to improve the accuracy, the paper which using the depth study method, established an insects density prediction mode with the depth of the belief network as the core. The model is applied to the algorithm of deep learning predictive control. According to the temperature and humidity of the grain obtained from the actual measurement and the initial density of the pest, we predicted the pest density. Simulation results show that the root mean square error is small between the predictive value and actual value, high prediction accuracy. The deep learning algorithm is applied to the population density of pests is effective.

The purpose of the study was to investigate the effects of a therapeutic communication simulation scenario development program on critical thinking, self-efficacy for learning, and education satisfaction in nursing students. A total of 61 students were recruited from Kangwon National University, Kangwon, Korea. The program was conducted in a total of six sessions, three times a week for two weeks. A scenario has been developed by a group that consisted of 5~6 persons. They applied an actual situation at the practice field based 1on the learning goals for therapeutic communication and theories of education contents. There were statistical significant increase in critical thinking (t=6.04, p<0.001), self-efficacy for learning (t=2.07, p=0.043), and education satisfaction (t=3.79, p<0.001). These results suggest that an simulation-based training could be used as a practical program for nursing students to improve critical thinking, self-efficacy for learning and education satisfaction.

With the continuous improvement of the economic level, people pay more and more attention to the appreciation of art. Art of flower arranging is an art following certain laws of creation and it has a long history. At present, the flower shape depends mainly on the arrangements’ experience and personal preferences. This paper attempts to use genetic algorithm optimized by the K-medoids algorithm for its research, through the replacement of the genetic algorithm to get more design solutions, so as to broaden the designer's ideas, to achieve the innovation of art design. Experiments show that the beauty of floral works produced by the optimized genetic algorithm is better than that produced by traditional genetic algorithm.

An image encryption method was built based on Lorenz chaotic mapping and finite field theory. First, original image information was divided into two image matrix by using Lorenz chaotic mapping. Second, five step calculations were finished about these two image matrix in the finite field. By combination of chaotic mapping and computing in the finite field, the new encryption method has a good effect and a fast speed. And the new encryption method realize the balance of speed and effect. Experimental results show that the proposed method has good encryption effect, attack resistance, the ideal speed of execution.

As one of the most important parts of aeroengine, blisk has complex structure and its material is titanium alloy hard to machine. It results in some difficulties in modeling and NC programming. In this paper, from the perspective of application, the secondary development technology of UG/Open Grip is used to design and develop the CAD/CAM module of blisk after analyzing structure feature and milling process of blisk. Firstly, it completes parametric modeling of blisk by establishing CAD module through the optimization of the original data points in NUBRS curve fitting and node interpolation technology; secondly, the inner and outer tolerance algorithm are applied to calculate the cutting step, and the row spacing is determined based on constant scallop height. Besides, tool axis vector is defined. All of these things are done to complete the establishment of the CAM module and realize trajectory planning of semi-finish machining of the blisk. It greatly improves the efficiency of programming and machining in blisks; finally, the module of blisk designed is used to model and program in the machining experiments in five axis machining center to verify correctness and reliability of the system. The results show that this module greatly improves manufacturing efficiency of blisk.

This study investigated ecosystem having influence upon psychological wellbeing of alien workers invited by employment permit system who left work not to adapt them to not only life in Korea but also industry, and helped labor workers to realize them and to be good engineer and/or technician in their home countries. The study has problems of small number of samples to investigate at 8 places having educational institutions that could not represent all of foreign labor workers in Korea. Investigation into foreign labor workers at other places having no educational institutions was needed. Various kinds of networks of foreign labor workers were expanded to show their desire of activity in Korea. The foreign labor workers should be supported to work during limited time and to settle in Korea.