bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of the catastrophe theory in ascertainment of vertical bearing capacity of single pile
Authors: Huang Jinlin , Li Zhangming , Tang Guihe 
Published: October 2008

PurposeCatastrophe theory can directly deal with discontinuity without any connection with the special inner mechanism, which makes it suitable for system research, whose inner action is unknown but outer one can be observed. There are many inner factors, which affect the bearing capacity of pile, it is different to ascertain bearing capacity of pile. The purpose of this paper is to present a new calculation method of bearing capacity of pile by the catastrophe theory.Design/methodology/approachThe cusp model of catastrophe theory and its expression are discussed in this paper. By means of mechanical model analysis, bearing capacity of pile is systematically studied coupling catastrophe steady mechanism with equilibrium conditions of single pile. The settlement of top pile is transformed into the normal form of cusp catastrophe. The relationship between the settlement of top pile and vertical bearing capability of pile is built.FindingsVertical bearing capacity of single pile was deduced by means of energy principle and catastrophe theory based on settlement of critical instability of pile.Research limitations/implicationsAccessibility and availability of the constitutive equation of concrete of pile and parameter are the main limitations which model will be applied.Practical implicationsA very useful reference for design processes engineers.Originality/valueThe estimated results of the example correspond to one of practical experience, which provides a basis for design of vertical bearing capacity of single pile.
Theoretical model and application of multilevel modeling in the research of social system
Authors: Jin Yanghua , Nie Biao , Xiao Yuchun 
Published: October 2008

PurposeTo identify the typical multilevel issues in social science, as well as illustrate the theoretical basis, hierarchical models and empirical exemplars of multilevel paradigm.Design/methodology/approachHierarchical and multilevel data are extremely common in social systems, but multilevel analysis is constrained by statistical techniques. With the development of social system theory and empirical methods such as hierarchical structure modeling and latent growth modeling, multilevel paradigm can be used to analyze multilevel data. So it is necessary to identify typical multilevel phenomena in social science and discuss multilevel modeling techniques.FindingsThis paper identifies four typical multilevel phenomena in social system study: hierarchical and clustered sampling, collective construct research, longitudinal repeated measures, and event history analysis. Hierarchical structure modeling and latent growth modeling are effective multilevel analysis techniques in social science because of their advantages in the integration of social system research.Research limitations/implicationsThe quality and availability of multilevel data are the main limitations regarding which model will be applied.Practical implicationsThe paper can aid the provision of effective multilevel models to social workers.Originality/valueThis paper provides information on application of multilevel modeling in social science.
Certain martingale methods of parameter estimation in dynamic system
Authors: Fanliang Kong , Guizhi Wang , Yu Ping 
Published: October 2008

PurposeTo find martingale theory and methods of parameter vector estimation of multidimensional linear control system in dynamic system.Design/methodology/approachIn parameter vector estimation of dynamic system, due to the limitation of conventional methods, the authors study the iterative formula and consistency of parameter vector estimation using the theory and methods of martingale, and extend its application field.FindingsSome conditions of strongly consistent estimation and iterative formula are obtained. And the consistency of parameter vector estimation in multidimensional linear control system is discussed.Practical implicationsSolved some practical problems of parameter vector estimation in dynamic system.Originality/valueThe paper solve the accuracy problem of parameter vector estimation of multidimensional linear control system in dynamic system and extend parameter vector estimation application field.
A new technique of non‐linear statistic prediction and its application in atmospheric systems
Authors: Yushou Kong , Lingling Ji , Changyu Wang , Liguo Li , Liming Zeng 
Published: October 2008

PurposeTo forecast the path of tropic cyclones by using a non‐linear statistical forecasting technique – the method of successive analogy.Design/methodology/approachNon‐linear statistical forecasting models can describe the non‐linear relationship between the factors and the forecasting objects and the real atmospheric movement more accurately, so they usually have stronger forecasting capability. In practice, however, it is shown that the relationships between predictors and predictands sometimes are so complex that it is very difficult or even impossible to establish the kind of non‐linear mathematical model. Therefore, it is an important topic for atmospheric science to solve non‐linear prediction problem of atmospheric systems by using the non‐function model approach.FindingsThe objective and quantitative prediction of tropical cyclone moving path can be given by using the method of successive analogy, a non‐linear forecasting technique, and calculating the similarity parameters between the grayscale field and the height field.Research limitations/implicationsFurther experiments are needed to verify this technique.Practical implicationsA very useful technique for solving non‐linear problem.Originality/valueIllustrates the new technique of solving non‐linear statistic problem and its application.
Human influenza: a virus classification using a probabilistic neural network
Authors: Kou Zheng , Zhou Yanhong , Qiang Xiaoli 
Published: October 2008

PurposeThe traditional method to distinguish the serotype of influenza A virus was based on the antigen reaction of HA and NA with their antibodies. The antibody of specific subtype virus was difficult to get and the reaction was not easy to be done. To be a complementation to the traditional classification methods based on the serological reaction, aims to present a novel method for viral classification.Design/methodology/approachThe similarity values of all subtype HA genes in vector space were considered and classified using a probabilistic neural network (PNN). The PNN model was trained by the 132 viral sequences in the training set and the classification quality was examined using 28 viral sequences in the testing set.FindingsA novel technique for the serotype classification of influenza A virus isolated from human was proposed in the paper. The system achieved 100 per cent accuracy with all serotypes of human influenza A virus.Research limitations/implicationsThe time for the large‐scale calculations of the average similarity based on multisequence alignment is the main limitation.Practical implicationsThis is a supplementation to the traditional virology research.Originality/valueThe novel classification method based on the similarity of viral nucleotide sequences and the PNN model would be useful for the epidemic supervision and prevention.
Multiplicative perturbations of incomplete second order abstract differential equations
Authors: Li Fang 
Published: October 2008

PurposeTo study the multiplicative perturbation of local C‐regularized cosine functions associated with the following incomplete second order abstract differential equations in a Banach space X u″(t)=A(I+B)u(t), u(0)=x, u′(0)=y,(*) where A is a closed linear operator on X and B is a bounded linear operator on X.Design/methodology/approachThe multiplicative perturbation of exponentially bounded regularized C‐cosine functions is generally studied by the Laplace transformation. However, C‐cosine functions might not be exponentially bounded, so that the new method for the multiplicative perturbation of the nonexponentially bounded regularized C‐cosine functions should be applied. In this paper, the property of regularized C‐cosine functions is directly used to obtain the desired results.FindingsThe new results of the multiplicative perturbations of the nonexponentially bounded C‐cosine functions are obtained.Originality/valueThe new techniques differing from those given previously in the literature are employed to deduce the desired conclusions. The results can be applied to deal with incomplete second order abstract differential equations which stem from cybernetics, engineering, physics, etc.
Granularity research based on panweighted field of pansystems
Authors: Li Haixia , Lin He , Li Yongli , Wu Aiping 
Published: October 2008

PurposeIn order to study granularity, this paper aims to discuss how to construct granules from the view of panweighted field of pansystem.Design/methodology/approachBy changing the panweights of panweighted field – subdivision of panweights, increase/decrease of panweights and reallocating panweights, to construct proper granules is the approach taken.FindingsThis paper provides a new method of studying granularity. If the weights of panweighted field are subdivided, then the granularity diminishes; if the panweights of panweighted field are increased, then the corresponding granularity diminished. Contrarily, the decrease of panweights of panweighted field results in the corresponding granularity increased; by reallocating panweights, use different method to construct different granules, such as compatible class, neighbor operator, compatible core, s‐s core and so on.Research limitations/implicationsHow to reallocate panweights is the main limitation.Practical implicationsA very useful advice for studying granularity.Originality/valueThis paper combines the granularity with panweighted field of pansystem, and studies granularity from the view of panweighted field of pansystems.
Discrete variable structure control and its application to ship autopilot
Authors: Li Huaishu , Song Lizhong , Lai Yanhui 
Published: October 2008

PurposeIn order to improve performance robustness of control systems, the discrete variable structure control (VSC) design for uncertain systems and its application to a ship autopilot are to be discussed in this paper.Design/methodology/approachDiscrete‐time variable structure control (DVSC) becomes worth investigating and various DVSC methods have been suggested by many papers. The approach that used the reaching law for controller design can describe how the switching function decreases toward zero and easier to obtain the control law, but this conventional method has some defects not to be ignored. First, due to the influence of the conventional discrete reaching law itself, the system trajectory oscillates in a neighborhood of the origin rather than converges to the origin. Second, this method requires that the uncertainty bound is known as a premise to assure robustness, so creates an over‐conservative controller and enlarges chattering.FindingsIt can be shown that the estimation error dynamics can be decoupled from sliding surface dynamics using the proposed scheme. Robust stability of the closed‐loop system can be ensured in the presence of uncertainties with bounded changing rate. No chattering occurs.Practical implicationsTo supply useful references to controller design.Originality/valueA new approach in the design of discrete VSC based on the reaching law approach is presented, a new discrete reaching law, which is stable at the origin, is proposed, and an algorithm for uncertainty estimation is developed in this paper. The proposed algorithm is applied to the control of a ship autopilot servo system. Simulation results show that the controller designed here can track a desired course well and exhibits very good performance robustness.
Application model of pseudo‐random correlation method in electrical prospecting
Authors: Li Mei , Wei Wen‐Bo , Deng Ming , Yuan Wen‐Ju , Zhang Qi‐Sheng 
Published: October 2008

PurposeThe aim is to apply pseudo‐random correlation method to detect very weak electrical signals because of various natural and artificial electron‐magnetic interferences in electrical prospecting.Design/methodology/approachElectrical prospecting is an important method of geophysical exploration and the electrical prospecting instruments are required to detect very weak electrical signals against strong interferences. Recently, pseudo‐random correlation coding has been widely applied in telecommunications and measurement and test systems to improve the signal noise ratio with great success, but has not been used in electric prospecting. This paper theoretically investigated the application model of pseudo‐random correlation techniques in electrical prospecting.FindingsThe model of pseudo‐random correlation techniques in electrical prospecting, including its principle, detailed protocol and parameter selection, is established.Practical implicationsWith the continuing improvement in the capacity of electrical prospecting transmitters, the pseudo‐random correlation method will be widely used in electrical prospecting.Originality/valueThe pseudo‐random correlation techniques is originally investigated for its application in electrical prospecting. This paper is aimed at researchers and engineers in geophysical exploration.
Spam and JavaScript, future of the web
Authors: Andrew Alex M. 
Published: October 2008

PurposeThe aim is to review developments on the internet, especially those of general cybernetic interest.Design/methodology/approachA means of preventing automated collection of e‐mail addresses from web sites, dating from 2001, is compared to a similar scheme developed independently at a later date. Discussions of the future of the web, particularly its extension as the Semantic Web, are reviewed. The influence of the internet is illustrated by reference to its part in a recent military decision.FindingsThere is choice of the precise method to be used to prevent automated collection of addresses from web sites. The world wide web is set to evolve into the Semantic Web. Despite notoriety in a particular context the Drudge report provides a valuable service.Practical implicationsMarginal advantages are claimed for my anti‐spam scheme over its predecessor, which however has the advantage of simplicity. The choice will be influenced by the view taken of possible developments in address‐gathering web‐crawlers. Development of the Semantic Web offers valuable and exciting prospects but does not displace web activities at less abstract levels. The Drudge report offers comprehensive access to current and recent news and is associated with an archive going back to 2001.Originality/valueIt is hoped this is a valuable periodic review.
Archives, mathematics encyclopaedia, dancing robots, ASC
Authors: Andrew Alex M. 
Published: October 2008

PurposeThe aim is to review developments on the internet, especially those of general cybernetic interest.Design/methodology/approachA massive archive facility is reviewed, as well as an online encyclopaedia devoted to mathematics. Developments in bipedal robot locomotion are discussed, with particular reference to dancing and running. Initiatives of the American Society for Cybernetics, involving Yahoo groups, are introduced and welcomed.FindingsThe archive facility is of astounding magnitude and comprehensiveness. The mathematics encyclopaedia is potentially useful, as are the ASC initiatives. Bipedal locomotion in robots is impressive but not perfect.Practical implicationsThe archive facility must be a valuable tool for many forms of research, as well as for cultural and recreational use. The encyclopaedia and the ASC initiatives are all valuable facilities. Bipedal locomotion has been developed in response to a challenge, and to gain prestige, but may be useful in development of practical robots for rough terrain.Originality/valueIt is hoped this is a valuable periodic review.
Hybrid classification algorithms based on boosting and support vector machines
Authors: Turchetti Maia Thiago , Pádua Braga Antônio , de Carvalho André F. 
Published: October 2008

PurposeTo create new hybrid algorithms that combine boosting and support vector machines to outperform other known algorithms in selected contexts of binary classification problems.Design/methodology/approachSupport vector machines (SVM) are known in the literature to be one of the most efficient learning models for tackling classification problems. Boosting algorithms rely on other classification algorithms to produce different weak hypotheses which are later combined into a single strong hypothesis. In this work the authors combine boosting with support vector machines, namely the AdaBoost.M1 and sequential minimal optimization (SMO) algorithms, to create new hybrid algorithms that outperform standard SVMs in selected contexts. This is achieved by integration with different degrees of coupling, where the four algorithms proposed range from simple black‐box integration to modifications and mergers between AdaBoost.M1 and SMO components.FindingsThe results show that the proposed algorithms exhibited better performance for most problems experimented. It is possible to identify trends of behavior bound to specific properties of the problems solved, where one may hence apply the proposed algorithms in situations where it is known to succeed.Research limitations/implicationsNew strategies for combining boosting and SVMs may be further developed using the principles introduced in this paper, possibly resulting in other algorithms with yet superior performance.Practical implicationsThe hybrid algorithms proposed in this paper may be used in classification problems with properties that they are known to handle well, thus possibly offering better results than other known algorithms in the literature.Originality/valueThis paper introduces the concept of merging boosting and SVM training algorithms to obtain hybrid solutions with better performance than standard SVMs.
Scalability of the genetic hybrid algorithm on a parallel supercomputer
Authors: Östermark Ralf 
Published: October 2008

PurposeTo demonstrate the scalability of the genetic hybrid algorithm (GHA) in monitoring a local neural network algorithm for difficult non‐linear/chaotic time series problems.Design/methodology/approachGHA is a general‐purpose algorithm, spanning several areas of mathematical problem solving. If needed, GHA invokes an accelerator function at key stages of the solution process, providing it with the current population of solution vectors in the argument list of the function. The user has control over the computational stage (generation of a new population, crossover, mutation etc) and can modify the population of solution vectors, e.g. by invoking special purpose algorithms through the accelerator channel. If needed, the steps of GHA can be partly or completely superseded by the special purpose mathematical/artificial intelligence‐based algorithm. The system can be used as a package for classical mathematical programming with the genetic sub‐block deactivated. On the other hand, the algorithm can be turned into a machinery for stochastic analysis (e.g. for Monte Carlo simulation, time series modelling or neural networks), where the mathematical programming and genetic computing facilities are deactivated or appropropriately adjusted. Finally, pure evolutionary computation may be activated for studying genetic phenomena. GHA contains a flexible generic multi‐computer framework based on MPI, allowing implementations of a wide range of parallel models.FindingsThe results indicate that GHA is scalable, yet due to the inherent stochasticity of neural networks and the genetic algorithm, the scalability evidence put forth in this paper is only indicative. The scalability of GHA follows from maximal node intelligence allowing minimal internodal communication in problems with independent computational blocks.Originality/valueThe paper shows that GHA can be effectively run on both sequential and parallel platforms. The multicomputer layout is based on maximizing the intelligence of the nodes – all nodes are provided with the same program and the available computational support libraries – and minimizing internodal communication, hence GHA does not limit the size of the mesh in problems with independent computational tasks.
A requisitely holistic approach to marketing in terms of social well‐being
Authors: Prosenak Damijan , Mulej Matjaž , Snoj Boris 
Published: October 2008

PurposeThe paper aims to answer the following questions. Is marketing requisitely holistic? Marketing serves managers, governors, owners and employees as well as customers, suppliers and other stakeholders with its activities in order to help company increase well‐being of stakeholders. What about the broader society's well‐being and future? What will follow, once the innovative‐society phase of socio‐economic development creates affluence, which diminishes human ambition to work in order to have? Social responsibility might be the next step in achieving success.Design/methodology/approachThere are new forms of marketing (e.g. societal marketing; relationship marketing; cause‐related marketing; and green marketing) that could help humans accomplishing this task, to some extent. Marketing will have to detect, elaborate and disseminate new data, along with using them for its action; the paper does not tackle the latter, but marketing taking into account the social responsibility of the company in order to help companies.FindingsCompanies will namely need more/requisitely holistic bases to develop innovative products, acceptable with social responsibility. Experience says that ethnographers, anthropologists, and other social scientists are becoming necessary in the “open innovation” model and the extremely demanding market of the affluent and nearly affluent society. So is a more systemic/holistic thinking and action of companies, including their marketing.Originality/valueThe paper suggests how marketing must adapt to meet new challenges.
Challenges in the adoption of visualization system: a survey
Authors: Folorunso Olusegun , Shawn Ogunseye Oluwafemi 
Published: October 2008

PurposeThe need for maximum cognition from massive amounts of data is becoming explosive. Different visualization mechanisms are being introduced to achieve this aim. This paper aims to consider the state of organizations as regards being abreast with the recent visualization technologies.Design/methodology/approachIn this paper, the authors look critically at the system adoption life cycle as it applied to visualization system. Also, the two forms of visualization; static and dynamic are looked at, considering the least applied and why. An evaluation of the visualization system was implemented in order to discern if it provides any benefit to organizations.FindingsThe study showed that the RT‐DANGO tool when compared to result from Excel exposed some spikes at some points when visualized dynamically which are not observed using usual static graph as it exposed some unseen events. The mean time taken to finish analysis of 4,000 concurrent‐related data were 168 s using RT‐DANGO and 121 s with the MS‐Excel. The difference was significant to p<0.05 (Z=−2.040). This was considered a reasonable tradeoff for accuracy, clarity and completeness of information.Originality/valueThe paper shows the factors that are responsible for visualization's usage in organizations. The paper will thus serve as an eye opener to critical issues affecting the visualization industry to the benefit of all stakeholders. Some references are made to the challenges faced in Nigeria.