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 Cluster Computing   [SJR: 0.605]   [H-I: 24]   [1 followers]  Follow         Hybrid journal (It can contain Open Access articles)    ISSN (Print) 1573-7543 - ISSN (Online) 1386-7857    Published by Springer-Verlag  [2352 journals]
• A zero-watermarking scheme with embedding timestamp in vector maps for Big
Data computing
• Authors: Yizhi Liu; Fan Yang; Kun Gao; Wenjie Dong; Jun Song
Abstract: Abstract Digital watermarking is a frontier technology for information security and also one of the most effective approaches to protect the copyright security of vector maps. Zero-watermarking, a sort of constructed watermarking, is different from the traditional embedded watermarking. Due to the lack of embedding watermark into the vector data, zero watermark exists an obvious difficulty to resist interpretation attack. In this paper, we present an improved zero-watermarking scheme for vector maps by introducing the timestamp method to resist the interpretation attack. The proposed scheme does not need any modifications on the original map data, providing the following feature: adding timestamp to the binary sequence of the scrambled watermarking image, performing the exclusive OR operation on scrambled sequence and extracted feature points, and conducting a reverse extraction detection and a timestamp validation on the zero-watermarking sequence. The experimental results show that the proposed scheme could not only resist interpretation attack in zero-watermarking effectively but also is of robustness and invisibility for the geometric attacks and map updating attacks.
PubDate: 2017-10-12
DOI: 10.1007/s10586-017-1251-3

• Data analysis on safety factors of physical modeling structures based on
the computation of incident impact
• Authors: Wenguang Luo; Guolu Yang; Jing Lu; Senlin Zhu
Abstract: Abstract The seawall slamming has become increasingly important as coastal engineering experiencing larger loads during the seawall impacts against surface wave which can result in structural damage and crew injury. It is necessary to characterize the hydrodynamic loading during wave impacts. This paper aims to study the wave impact on different stepped seawall structures through physical modeling experiments. Five types of stepped seawall structures were designed according to seawall slope and step height. The dynamic pressures exerted by different incident waves acting on the stepped seawall structure were measured and the data was collected. Data analysis was performed to investigate the relation of dynamic pressures with seawall slopes and seawall step heights. Results showed that when the incident wave and the seawall step height remained unchanged, the dynamic pressures acting on horizontal and vertical surface of seawall steps decreased with decreasing seawall slope (within a certain range of seawall slope). Additionally, when the incident wave and the seawall slope remained unchanged, the dynamic wave pressures acting on horizontal and vertical surface of seawall steps increased with increasing seawall step height. These results might provide a theoretical basis for the design of safety stepped seawall structures.
PubDate: 2017-10-12
DOI: 10.1007/s10586-017-1247-z

• Cross-layer based routing protocol and solution to packet reordering for
TCP in MANET
• Authors: Dodda Sunitha; Aitha Nagaraju; Gugulothu Narsimha
Abstract: Abstract In mobile ad hoc networks (MANETs), link failures and route changes occur most frequently, which may result in packet reordering. Transmission control protocol (TCP) performs poorly in such environment, which misinterprets the reordered packets as lost packets due to congestion. This has motivated us on developing a new protocol towards the packet reordering for improving the performance of TCP in MANETs. Optimal path or route selection is the major concern to improve the energy efficiency and network lifetime. In this paper, trust aware routing protocol for selecting optimal route in MANET is proposed. Based on this protocol, trust value for each node is calculated using direct and indirect trust value. Then the routing cost metric value is calculated and the path with minimum cost metric value is chosen as the best path in the network. After selecting the optimal path, data packet is to be transmitted through the optimal path. During the transmission, the data packet may get dropped or reordered due to congestion or mobility. A cross layer approach between network layer and transport layer to identify the dropped and reordered packets in the network is proposed in this paper. Simulation results are reported, which support this proposal.
PubDate: 2017-10-11
DOI: 10.1007/s10586-017-1179-7

• The characteristic coefficient analysis of the pressure curve type based
on the classification method
• Authors: Yameng Wang; Huanfang Liu
Abstract: Abstract Perforated pipes are widely used in applications such as drainage, irrigation and ventilation. The variation in the pressure head, h, in a perforated pipe follows a certain pattern. By analyzing h variation patterns at the tail ends of perforated pipes on flat slope, and the characteristic coefficient of the perforated pipe was proposed. According to the value of characteristic coefficient of the perforated pipe, perforated pipes are classified into three types, namely, short, medium and long pipes. In addition, a method for determining the type of perforated pipe based on its characteristic coefficient and length-to-diameter ratio is provided. Furthermore, on the condition of long perforated pipe, based on the locations of the maximum and minimum h values, the slope at which the perforated pipe is laid and the head loss ratio along the length of the perforated pipe, h curves are classified into five types. The experimental results demonstrate that the experimental data exhibit a variation pattern consistent with that of the calculation results, indicating that the classification of pressure head curves is, to a certain degree, reasonable and applicable.
PubDate: 2017-10-11
DOI: 10.1007/s10586-017-1226-4

• Research on abnormal data detection method of web browser in cloud
computing environment
• Authors: Xindong Duan
Abstract: Abstract The traditional abnormal data detection method uses the simplified gradient method to detect the abnormal data of web browser, which can not accurately remove the web abnormal data with the interference frequency components, and has low detection performance. Therefore, this paper proposed a distributed web browser abnormal data detection method based on the improved genetic algorithm and spatio-temporal correlation. Based on analyzing the principle of the abnormal data detection in the web browser, we select the abnormal data points of web browser through the deviation function and centralized algorithm, and determine the anomaly factor of web browser using the spatio-temporal distribution, and introduce the improved genetic algorithm to realize the detection of abnormal data of web browser. Simulation results show that the proposed method can reduce the energy consumption of the web data, and the signal amplitude is larger than the amplitude of the interference noise data, which has good anti-jamming performance.
PubDate: 2017-10-11
DOI: 10.1007/s10586-017-1221-9

• Optimal evaluation of time step size in numerical simulation for
two-dimensional flow sensing
• Authors: Quanfeng Qiu; Yuanhua Lin; Qiugui Shu; Xiangjun Xie
Abstract: Abstract This paper proposes an optimal evaluation of time step size for numerical computations based on the 180 numerical simulations of the two-dimensional unsteady flow at low Reynolds number around a circular cylinder. A proper time step size is very important to obtain the right magnitude and frequency for the numerical computation to simulating the real flow. The optimal evaluation is found out after analyzing the influences of the time step sizes on the Strouhal numbers, vortex-shedding periods, lift and drag coefficients. The time step size is found out to be a function of the dividend of vortex-shedding period, the velocity, the feature size and the Strouhal number. The optimal dividend point of the vortex-shedding periods for the optimal time step size is in the interval $$\left[ {50,90} \right)$$ , and the average partition counts of the interval is an optimum approximation. So, the proposed optimal evaluation of time step size is calculated by $$D/\left( {14U} \right)$$ , of which D is the feature size and U is the velocity. The calculation to decide time step size is efficient and consequently the numerical simulations are more stable. Numerical results based on the provided time step size also bring on better agreements of the model parameters to reflect the real flow theoretically.
PubDate: 2017-10-11
DOI: 10.1007/s10586-017-1250-4

• Simulation of body extension motion based on dynamics virtualization
• Authors: Yexian Wang
Abstract: Abstract With the further development of virtual human simulation technology and motion modeling, it is an important task to construct and simplify the virtual human geometry model. Aiming at the issues including large computational overhead, unnatural model generation gesture, change of kinematic chain structure and high complexity, this paper takes the body extension motion as the research object, uses the forward dynamics calculation method, conducts analysis of dynamic control structure of arm movement, and uses inverse kinematics algorithm to control leg movement. According to the forward dynamics algorithm to study the collision contact model of the foot and the ground, the virtual human could act more naturally and consistently in extension motion and the computational complexity could be effectively reduced.
PubDate: 2017-10-11
DOI: 10.1007/s10586-017-1208-6

• A framework for secure and privacy protected collaborative contents
sharing using public OSN
• Authors: Shaukat Ali; Azhar Rauf; Naveed Islam; Haleem Farman
Abstract: Abstract A major issue thoroughly raised and potentially vulnerable in online social networks (OSNs) is the user privacy preservation. Generally, the issue of privacy is tackled from the user point of view without considering the service providers and the third-party data collectors, who can manipulate user data for third party advertisement and behavioral analysis. Therefore, the privacy risk exists not only from the unauthorized users but also from the OSN service providers. To secure data from both the unauthorized users and OSN service providers a framework for collaborative contents sharing is proposed. In the proposed framework, contents are secured at the time of data dissemination and provided assurance about the data sharing among the legitimate users based on collaborative contents sharing. The proposed framework assures not only the confidentiality of contents but also the privacy of data owner and co-owners in OSN. An architecture is provided to support the theoretical and practical basis for the proposed framework; which exhibits the objective of preserving user and contents privacy.
PubDate: 2017-10-10
DOI: 10.1007/s10586-017-1236-2

• Finite element model based test and analysis on ACHC short columns and
hoop coefficient
• Authors: Jing Ji; Wenfu Zhang; Chaoqing Yuan; Yingchun Liu; Zhichao Xu; Yang Wang; Xiaokun Chen
Abstract: Abstract In order to promote the application of angle-steel confined high-strength concrete (ACHC) columns in new construction and reinforcement projects of civil engineering, this paper designs 15 groups of ACHC short columns with a shear span ratio of 1.5 under axial compression by taking the hoop coefficient, strength grade of concrete and yield strength of steel as parameters. Based on the constitutive model of steel and confined concrete and considering hoop effect, the simulation analysis on them was carried out by ANSYS software, and the rationality of finite element modelling is verified by comparing it with the experimental data. The author investigated the influence of different hoop coefficients, different concrete strength grades and different yield strength of steel to the mechanic behaviour of ACHC short columns, and the results show that the influence of hoop coefficient to the bearing capacity and ductility is more significantly than other parameters. Considering the hoop effect of batten plate to concrete, the linear relationship between the influence factor of batten plates and the hoop coefficient is inverted by using 1stopt software. At last, the calculation formula of ultimate bearing capacity of ACHC short columns is gotten, and the design method and suggestion of short columns are put forward.
PubDate: 2017-10-10
DOI: 10.1007/s10586-017-1230-8

• Gesture recognition based on an improved local sparse representation
classification algorithm
• Authors: Yang He; Gongfa Li; Yajie Liao; Ying Sun; Jianyi Kong; Guozhang Jiang; Du Jiang; Bo Tao; Shuang Xu; Honghai Liu
Abstract: Abstract The sparse representation classification method has been widely concerned and studied in pattern recognition because of its good recognition effect and classification performance. Using the minimized $$l_{1}$$ norm to solve the sparse coefficient, all the training samples are selected as the redundant dictionary to calculate, but the computational complexity is higher. Aiming at the problem of high computational complexity of the $$l_{1}$$ norm based solving algorithm, $$l_{2}$$ norm local sparse representation classification algorithm is proposed. This algorithm uses the minimum $$l_{2}$$ norm method to select the local dictionary. Then the minimum $$l_{1}$$ norm is used in the dictionary to solve sparse coefficients for classify them, and the algorithm is used to verify the gesture recognition on the constructed gesture database. The experimental results show that the algorithm can effectively reduce the calculation time while ensuring the recognition rate, and the performance of the algorithm is slightly better than KNN-SRC algorithm.
PubDate: 2017-10-10
DOI: 10.1007/s10586-017-1237-1

• Histogram difference with Fuzzy rule base modeling for gradual shot
boundary detection in video cloud applications
• Authors: A. Kethsy Prabavathy; J. Devi Shree
Abstract: Abstract In the field of shot boundary detection the fundamental step is video content analysis towards video indexing, summarization and retrieval as to be carried out for video cloud based applications. However, there are several beneficial in the previous work; reliable detection of video shot is still a challenging issue. In this paper the focus is carried out on the problem of gradual transition detection from video. The proposed approach is fuzzy-rule based system with gradual identification and a set of fuzzy rules are evaluated with dissolve and wipes (fad-in and fad-out) during gradual transition. First, extracting the features from the video frames then applying the fuzzy rules in to the frames for identifying the gradual transitions. The main advantage of the proposed method is its level of accuracy in the gradual detection getting increased. Also, the existing gradual detection algorithms are mainly based on the threshold component, but the proposed method is rule based. The proposed method is evaluated on variety of video sequences from different genres and compared with existing techniques from the literature. Experimental results proved for its effectiveness on calculating performance in terms of the precision and recall rates.
PubDate: 2017-10-07
DOI: 10.1007/s10586-017-1201-0

• Intelligent early warning model of early-stage overflow based on dynamic
clustering
• Authors: Haibo Liang; Guoliang Li; Wenlong Liang
Abstract: Abstract During conventional drilling, the early warning of overflow can be realized by monitoring the total variation of drilling fluid. However, this may pose potential safety risks due to the technical challenges it is faced with such as the serious lag, the low accuracy and the incapability to give an early warning in terms of early-stage overflow. In this paper, a new model for early warning of early-stage overflow has been creatively proposed. The proposed model is characterized by surface detection techniques that are different from existing surface inspection techniques. It is able to give an earlier, faster and more accurate warning. In addition, real-time correction of the instantaneous discharge flow can be achieved. The proposed model is established by employing pattern identification and K-mean dynamic clustering. After clustering and linear fitting, the fitting results are compared with the overflow identification sensitivity so as to determine the occurrence of overflow. The experimental results show that the early warning model proposed has overcome the hysteresis and low accuracy of conventional overflow monitoring methods and is capable of early warning of early-stage overflow.
PubDate: 2017-10-07
DOI: 10.1007/s10586-017-1214-8

• Gesture recognition based on modified adaptive orthogonal matching pursuit
algorithm
• Authors: Bei Li; Ying Sun; Gongfa Li; Jianyi Kong; Guozhang Jiang; Du Jiang; Bo Tao; Shuang Xu; Honghai Liu
Abstract: Abstract Aiming at the disadvantages of greedy algorithms in sparse solution, a modified adaptive orthogonal matching pursuit algorithm (MAOMP) is proposed in this paper. It is obviously improved to introduce sparsity and variable step size for the MAOMP. The algorithm estimates the initial value of sparsity by matching test, and will decrease the number of subsequent iterations. Finally, the step size is adjusted to select atoms and approximate the true sparsity at different stages. The simulation results show that the algorithm which has proposed improves the recognition accuracy and efficiency comparing with other greedy algorithms.
PubDate: 2017-10-07
DOI: 10.1007/s10586-017-1231-7

• Design of integrated steel production scheduling knowledge network system
• Authors: Le Yang; Guozhang Jiang; Xi Chen; Gongfa Li; Tingting Li; Xiaowu Chen
Abstract: Abstract The knowledge network system was developed based on the needs of the modern iron and steel enterprise integrated production management. System was mainly composed of knowledge base, model base and algorithm library .The core part of system was knowledge and the key knowledge represent method was hybrid knowledge expression. Herein, model knowledge representation and intelligent matching mechanism was proposed. The scheduling results were displayed by Gantt chart through calling corresponding intelligent optimization algorithm with automatically selecting the model. The system solved the problem of process, “non-synchronous” at casting and rolling and enhanced the ability of dynamic scheduling. It achieved the iron and steel intelligent production scheduling and guided the real production effectively, reduced the operation of decision maker, also improved the enterprises’ market competitiveness and capacity to face the disturbance. Finally, the system was verified effective by the simulation examples.
PubDate: 2017-10-07
DOI: 10.1007/s10586-017-1215-7

• Scalable top-k keyword search in relational databases
• Authors: Yanwei Xu
Abstract: Abstract Keyword search in relational databases has been widely studied in recent years because it does not require users neither to master a certain structured query language nor to know the complex underlying database schemas. There would be a huge number of valid results for a keyword query in a large database. However, only the top 10 or 20 most relevant matches for the keyword query—according to some definition of “Relevance”—are generally of interest. In this paper, we propose an efficient method which can efficiently compute the top-k results for keyword queries in a pipelined pattern, by incorporating the ranking mechanisms into the query processing method. Four optimization methods based on bounding the relevance scores of potential results, reusing and sharing the intermediate result are presented to improve the efficiency of the proposed algorithms. Compared to the existing top-k keyword search systems, the proposed methods can significantly reduce the number of computed query results with low relevance scores and the times for accessing databases, which result in the high efficiency in computing top-k keyword query results in relational databases. Extensive experiments on two real data sets are conducted to evaluate the effectiveness and efficiency of the proposed approach.
PubDate: 2017-10-06
DOI: 10.1007/s10586-017-1232-6

• Research on health monitoring and sensing technology based on
vulnerability analysis
• Authors: Wang Quan-wei; Xu Ge-ning; Wen Hao
Abstract: Abstract Conventional monitoring technologies have the limitation to monitor because the extensive arrangement of the sensing system has caused many problems such as the increase of costs, difficult in arrangement, inconvenient maintenance, massive amounts of data, etc. To overcome this limitation, it is necessary to obtain new monitoring technology which is able to quickly analyze crane structure and its vulnerable area (or weakest link), and take the reasonable arrangement to sensing system. Therefore in this paper, we proposed the vulnerability analysis method and implementation of crane health monitoring based on vulnerability theory and methodology, such as the importance and redundancy coefficient, determination of failure mode and search of failure path, indeterminacy of static and kinematic, strain energy and flow potential, etc. Also we evaluated the effectiveness of our proposed method through the numerical example.
PubDate: 2017-10-06
DOI: 10.1007/s10586-017-1229-1

• The structural equation analysis of perceived product innovativeness upon
brand loyalty based on the computation of reliability and validity
analysis
• Authors: Baoli Wang; Yubi Gao; Zhenxing Su; Jing Li
Abstract: Abstract Based on the theory of perceived product innovativeness and brand value, this study divides perceived product innovativeness into perceived newness and perceived meaningfulness, while introducing brand image and customer perceived value as mediators and consumer innovativeness as moderator to study the influence mechanism of consumer perceived product innovativeness on brand loyalty. Our research results show that: perceived product innovativeness will not only have a significant positive impact on brand loyalty, but will also have an indirect positive impact on brand loyalty through brand image and customer perceived value; furthermore, consumer innovativeness positively regulates the impact of perceived product innovation on brand image, but has no significant moderating effect on the relationship of perceived product innovativeness and brand loyalty. These findings also provide a theoretical basis for enterprises to improve consumer brand loyalty, excavate potential customers, and focus on brand experience.
PubDate: 2017-10-06
DOI: 10.1007/s10586-017-1218-4

• A FCM cluster: cloud networking model for intelligent transportation in
the city of Macau
• Authors: Zhiming Cai; Lianbing Deng; Daming Li; Xiang Yao; David Cox; Haoxiang Wang
Abstract: Abstract Intelligent transportation systems have seen a very great increase in research contribution especially with the advent of cloud and internet of things for handling big data. With the increasing need to monitor, manage effectively with available set of resources, a majority of concerns have been on a migration pattern towards cloud networks. The proposed research paper has investigated and framed an intelligent cloud based transportation cluster model for effective and efficient delivery of transportation and management data to the server and client. The case study has been taken up for the city of Macau in China which is observed to have a complicated and sophisticated system of transportation with the ever increasing growth of tourism in the country. Vehicular traffic monitoring and management using a fuzzy C means algorithm for effectively reducing the computational overhead in terms of complexity and time has been proposed, implemented and tested with results validated against recent intelligent transportation models found in the literature.
PubDate: 2017-10-05
DOI: 10.1007/s10586-017-1216-6

• A modified multi objective heuristic for effective feature selection in
text classification
• Authors: D. Thiyagarajan; N. Shanthi
Abstract: Abstract Text categorization is the process of sorting text documents into one or more predefined categories or classes of similar documents. Differences in the results of such categorization arise from the feature set chosen to base the association of a given document with a given category. This process is challenging mainly because there can be large number of discriminating words which render many of the current algorithms unable to complete this. For most of these tasks there exist both relevant as well as irrelevant features. The objective here is to bring about a text classification on the basis of the features selected and also pre-processing to bring down the dimensionality and increase the accuracy of classification of the feature vector. Here the most commonly used methods are meta-heuristic algorithms in order to facilitate selection. Artificial fish swarm algorithm (AFSA) takes the underlying intelligence of the behaviour of fish swarming to combat the problems of optimization as well as the combinatorial problems. This method has been greatly successful in diverse applications but does suffer from certain limitations like not having multiplicity. Therefore, a modification has been proposed to AFSA which is MAFSA that has a crossover in its operation in order to bring about an improvement in the text classification selection. SVM or Support Vector Machine, Adaboost classifiers and naïve bayes are all used here. MAFSA has proved itself to be superior to AFSA in terms of precision and also the selected feature numbers.
PubDate: 2017-10-05
DOI: 10.1007/s10586-017-1150-7

• Research on the factors affecting safety behavior based on interpretative
structural modeling
• Authors: Xiaojie Xu; Juan Shi
Abstract: Abstract The study of employee production safety behavior should begin with the key influential factors. This paper aims to find the factors affecting small and medium-sized enterprises’ employees’ safety production behavior and analyze the hierarchical structure relationship among these factors. Then based on the study results, some countermeasures and suggestions are put forward to prevent and control the unsafe behavior of small and medium-sized enterprises (SEMs). This paper first makes an in-depth study on the influential factors of SMEs’ employee safety behavior. Then the paper establishes interpretative structural model by using interpretative structural modeling method to analyze the hierarchical structure relationship among the factors and to find out the direct actors, critical factors and root factors, which is beneficial to study the influential path of employee safety behavior. Based on the root factors, critical factors and direct actors, some countermeasures and suggestions from the prospective of enterprise and the government are put forward to prevent and control the unsafe behavior of SEMs, which have important referential value and referential significance for the SMEs to prevent and control employees’ unsafe production behavior.
PubDate: 2017-10-04
DOI: 10.1007/s10586-017-1228-2

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