bluuebunny/crossref_metadata_2025 huggingface dataset:
L'impact sur l'innovation des économies d'agglomération
Authors: Greunz Lydia
Published: May 2012

Résumé De nombreuses études s’attachent à évaluer l’impact des économies d’agglomération et des externalités de connaissance qui en découlent sur la croissance industrielle mais court-circuitent le maillon intermédiaire qui est la capacité de création de connaissance. Ce papier tente de pallier ces insuffisances en étudiant l’impact des économies d’urbanisation et de localisation sur l’innovation des régions européennes. L’analyse se base sur un modèle qui intègre des mesures visant à capter des externalités de MARSHALL (1890)-ARROW (1962)-ROMER (1986) (MAR) et de JACOBS (1969) et des variables spécifiques aux régions et secteurs. Les tests effectués sur un échantillon de 153 régions européennes et 16 secteurs manufacturiers suggèrent que les deux types d’externalités influencent positivement l’innovation bien que les externalités de JACOBS jouent un rôle prépondérant dans les régions métropolitaines ainsi que pour les secteurs de haute technologie.
Structure économique et croissance locale : etude Econométrique des arrondissements belges, 1991-1997
Authors: Baudewyns Didier
Published: May 2012

Résumé A partir d’une base de données construites pour les 43 arrondissements formant le territoire de la Belgique, nous montrons que la structure économique locale – en termes de spécialisation, concurrence, diversité, densité urbaine – a un impact significatif sur la croissance locale de la valeur ajoutée entre 1991 et 1997. Les effets jouent essentiellement dans les services tandis que dans l’industrie, probablement en raison de son degré élevé d’ouverture au commerce international et du problème d’agrégation de secteurs fort différents, nous n’avons trouvé aucune preuve empirique d’existence d’économies d’échelle externes de localisation ou d’urbanisation. En ce qui concerne les services, nous obtenons des résultats similaires à ceux de COMBES (2000) pour la France: la diversité locale influencerait bien positivement la croissance, tandis que la spécialisation et la concurrence lui seraient néfastes. La densité urbaine n’a pas d’effet global sur la croissance locale du tertiaire.
Strategic Human Resource Management and Organizational Performance
Authors: Bahuguna P.C. , Kumari P.
Published: May 2012

The discipline of human resource management has progressed significantly over a period of time. Today it is being considered as the most critical source of competitive advantage to the firm. It has progressed to a strategic business partner. Various approaches and models of strategic human resource management have been developed within the framework of strategic human resource management. Like many theories of organization, none are complete. Rather being right or wrong each approach points to different aspect of the process needed to develop effective strategic human resource functions. The issue of fitting HR practices to business strategy has become increasingly relevant over few years. Therefore in the present study we have made efforts to highlight various issues which are relevant to the strategic HRM in the changing scenario of business environment. The present chapter has been divided into five sections. In the first part, the changes occurring in the business environment and its implications for human resource functionaries have been discussed. In the second section we have highlighted the changing role of human resource management. Historical background of strategic human resource management, its role in addressing the challenges of changing business scenario and determinants of strategic fit have also been presented in the second section. In the third section issues regarding the relationship of strategic human resource management with business performance have been discussed. In the fourth section we have made efforts to bring into notice those emerging future trends which might become key issues for high performance in the organization of new era. At last conclusions have been drawn that what needs to be done on the part of the HR functionaries and the organization itself to enhance the strategic fit between the various HR practices and the overall organizational strategic plan.
A Statistical Analysis of Priority Factors for Local e-Government in a Developing Country
Authors: Wijaya St.Wisnu , Dwiatmoko Aris , Surendro Kridanto , Sastramihardja Husni S
Published: May 2012

This chapter presents findings of a study devoted to investigating the factors that influence successful implementation of e-Government at a local level in a developing country context. The study is based on the case study of Yogyakarta Local Government, Indonesia. Using qualitative methods of data gathering, the study developes a conceptual model with 27 items that were used for developing the questionnaire distributed into conducting in-depth interviews with 200 government officials in Yogyakarta, who adopted Information and Communication Technologies (ICTs) as a platform for their daily work activities. The study also conducted desk research that explored many documents on ICT implementation in the public sector. The results reveal that the most significant factors that influence success in e-Government projects are corporate culture and e-Governance competency. The other factors, in order of importance were users’ willingness and competency in using ICTs, Information quality and human resources competency, and system quality, which was moderated by information quality and human resources competency.
Integration of Predated Notifications of Personal Actions for HR-Planning in ERP-Systems
Authors: Cissek Peter , Gomez Jorge Marx
Published: May 2012

This chapter intends to reveal the benefit of predated notifications of personal actions for HR-planning and discusses the interrelated demands on ERP-systems. If e-government is implemented, one has to think of rearranging the government’s HR-structure in order to adapt to the new circumstances, too. This means to take advantage of modern HR-methodology in order to become more efficient in HR-administration. One possible way in improving human resource management (HRM) is using predated notifications of personal actions for HR-planning. Human resource planning (HR-planning) is a component of strategic enterprise planning. It is fully integrated into the enterprise-wide planning process, because HR-planning is not only determined by other planning areas, but it also determines them vice versa. So the more precisely and comprehensively HR-planning is done, the more accurate derived key figures, which are used in other planning areas, can be. Governments usually deal with a huge amount of personnel, so HR is one of the main tasks in administration. Predated notifications of personal actions usually are known in present, but will be started in the future. In contrast to planning a personnel action the predated one will take place with the highest possible probability. An example for making the difference more clear may be an employee’s retirement. It does not stringently depend on the employee’s age, but rather on the person’s individual decision to retire. As a general rule, an employee’s intention to retire is already known about half a year before it takes place. If this information is used in the planning process, the company will have enough time to estimate the loss of knowledge or the cost-savings that will be caused by the employee’s withdrawal. In huge companies, HRM typically is supported by ERP-systems. The functionality offered by the software depends on the company’s needs and may range from a simple keeping of personnel data to a complex module called human capital management, which is used for payroll accounting, talent management, employee self services, and many more. If the decision-making body considers the company’s personnel as business critical, a lot of employee-related data is collected and analyzed, ranging from master data to planning key figures. This chapter will emphasize the importance of efficient HR-planning for governments in order to improve their business processes. It can be seen as one of the goals of e-government. It will be pointed out how HR-planning can be improved by using predated notifications of personal actions, so that HR-divisions in governments can use advanced HR-planning right on from the beginning when preparing themselves for e-government.
Personnel Performance Appraisal Coverage in ITIL, COBIT and CMMi
Authors: Casado-Lumbreras Cristina , Colomo-Palacios Ricardo , Hernández-López Adrián , Soto-Acosta Pedro
Published: May 2012

Human capital is of paramount importance in the ICT industry. This paper analyses one of the elements which underlies effective management of human assets: performance assessment. This analysis uses the development of a common standard based on the tasks and processes outlined in People CMM, the standard in human resource management designed by the Software Engineering Institute. This framework is evaluated in different models related to IT Governance, such as COBIT and ITIL, as well as other related IT practices like CMMI for Development, CMMI for Acquisition, and CMMi-SVC. The results indicate that COBIT is the only framework that presents reliable coverage in relation to personnel performance assessment.
Evaluation of Corporate Structure Based on Social Network Analysis
Authors: Palus Sebastian , Kazienko Przemyslaw , Michalski Radoslaw
Published: May 2012

Social network analysis provides helpful reports and comparisons, which may support the corporate human resources management. Several ideas, measurements, interpretations and evaluation methods are presented and discussed in the chapter, in particular group detection, centrality degree, location analysis, process management support, dynamic analysis, and social concept networks.
Investment in Transaction-Specific Assets and Opportunistic Behavior in a Chinese Supply Chain
Authors: Zhao Xiande , Liu Yi , Qian Liping , Flynn Barbara
Published: May 2012

This chapter addresses the relationship between a supplier and the manufacturers that it serves, from the perspective of transaction cost economics theory (TCE). TCE deals with relationships between organizations, such as customers, manufacturers and suppliers. It states that investment in transaction-specific assets opens the door for opportunistic behavior by an organization’s partners. Interpreted from the perspective of a supplier, the supplier’s investments in transaction-specific assets, such as dedicated plant and equipment, workforce with transaction-specific skills and the development of transaction-specific relationships, will lead to opportunistic behavior on the part of the manufacturers that they serve, providing an environment where behaviors intentionally designed to take advantage of the supplier will flourish. Because the supplier will not be able to redeploy those investments to a different manufacturer if the relationship is discontinued, manufacturers will be motivated to capitalize on this vulnerability by employing behaviors such as seeking unfair price concessions, sharing proprietary information with competitors or other unethical behaviors. This study advances the application of TCE to the context of supply chain management by breaking investments in transaction-specific assets into investments in transaction-specific tangible assets, such as plant and equipment, and transaction-specific intangible assets, such as relationships and the development of human resources, and examining their impact on opportunistic behavior separately. These relationships are examined using a survey of 230 suppliers in the household appliances industry in China. Hierarchical regression analysis revealed that there was a positive relationship between suppliers’ investment in transaction-specific tangible assets and opportunistic behavior by the manufacturers that they serve, but that there was a negative relationship between suppliers’ investments in transaction specific intangible assets and opportunistic behavior by their manufacturers. The moderating role of contracts and relational norms was also examined.
Using Action Research to Assess Student Performance in Traditional vs. E-Learning Formats
Authors: Guy Retta , Wishart Craig
Published: May 2012

While the popularity and acceptance of online education is undeniable, many are concerned about measurable performance of student learning in Web-based courses. The issue of student performance dates back to the start of correspondence courses as the initial challenge to the traditional classroom (McLaren, 2004). Yet, today, it is not a question of whether we pursue this educational medium, but rather, are students in the Web-based courses performing equal to or better than their counterparts in the classroom-based courses? An action research study was conducted to assess student performance in a traditional versus e-learning format at a historically Black land-grant university located in the southern part of the United States. The population sampled included 293 declared business majors who were self enrolled in either organizational behavior or international business undergraduate courses. Both courses in both formats were conducted over a 3-year period. A chi-square test was run to determine if correlation exist between final grades and delivery method. The results revealed that the delivery method did not impact student performance; hence, concluding that there was not sufficient evidence to assert that a relationship exists between final grades and delivery method.
Employees’ Perceptions on Organisational Justice, Job Control and Job Demands
Authors: Tynkkynen Liina-Kaisa , Sinervo Timo , Elovainio Marko , Lehto Juhani , Koivisto Anna-Maija , Noro Anja , Finne-Soveri Harriet
Published: May 2012

The issue to be addressed in this study is whether ownership and HRM practices are associated with employees’ perceptions of organisational justice, job control and job demands. The study focuses on care personnel working in sheltered housing facilities for elderly people. Multi-level linear regression is applied to analyse the data. The results support the argument that an increased similarity between public, not-for-profit and for-profit organisations is emerging in HRM issues. HRM practices were found to associate with positive outcomes in organisational justice and job control. However, to be successful in the implementation of HRM, it is crucial that employees understand the justification for each procedure as well as find it a useful resource in terms of their own job.
Knowledge Worker Faire Compensation
Authors: Costa Gonçalo
Published: May 2012

One of the key characteristics in knowledge management is the importance of human resources. Therefore, main stream literature has been discussing the concept of knowledge worker, its characteristics, and duties versus rights, and human resources policies in its dissimilar perspectives (knowledge workers retention, personal mastery, intellectual property rights, among others). Although, empirical studies seem to disregard if knowledge workers feel that are well compensated, or what dimensions entail faire compensation. Hence, this chapter aims to recognize knowledge workers feeling about faire compensation, and what elements are essential to achieve it through a conceptual framework. For that, the chapter is divided into six sections: the research questions; knowledge worker (key characteristics and responsibilities versus rights); fairness (etymology and the contribution of Rawls); linking the theoretical basis; empirical results (methodological remarks, findings and discussion); future research directions (the surrealist assumption, Dali surrealism and the metaphorical assumption).
Semi-Supervised Clustering for the Identification of Different Cancer Types Using the Gene Expression Profiles
Authors: Martín-Merino Manuel
Published: May 2012

DNA Microarrays allow for monitoring the expression level of thousands of genes simultaneously across a collection of related samples. Supervised learning algorithms such as -NN or SVM (Support Vector Machines) have been applied to the classification of cancer samples with encouraging results. However, the classification algorithms are not able to discover new subtypes of diseases considering the gene expression profiles. In this chapter, the author reviews several supervised clustering algorithms suitable to discover new subtypes of cancer. Next, he introduces a semi-supervised clustering algorithm that learns a linear combination of dissimilarities from the a priory knowledge provided by human experts. A priori knowledge is formulated in the form of equivalence constraints. The minimization of the error function is based on a quadratic optimization algorithm. A norm regularizer is included that penalizes the complexity of the family of distances and avoids overfitting. The method proposed has been applied to several benchmark data sets and to human complex cancer problems using the gene expression profiles. The experimental results suggest that considering a linear combination of heterogeneous dissimilarities helps to improve both classification and clustering algorithms based on a single similarity.
Automated Diagnostics of Coronary Artery Disease
Authors: Kukar Matjaž , Kononenko Igor , Grošelj Ciril
Published: May 2012

The authors present results and the latest advancement in their long-term study on using image processing and data mining methods in medical image analysis in general, and in clinical diagnostics of coronary artery disease in particular. Since the evaluation of modern medical images is often difficult and time-consuming, authors integrate advanced analytical and decision support tools in diagnostic process. Partial diagnostic results, frequently obtained from tests with substantial imperfections, can be thus integrated in ultimate diagnostic conclusion about the probability of disease for a given patient. Authors study various topics, such as improving the predictive power of clinical tests by utilizing pre-test and post-test probabilities, texture representation, multi-resolution feature extraction, feature construction and data mining algorithms that significantly outperform the medical practice. During their long-term study (1995-2011) authors achieved, among other minor results, two really significant milestones. The first was achieved by using machine learning to significantly increase post-test diagnostic probabilities with respect to expert physicians. The second, even more significant result utilizes various advanced data analysis techniques, such as automatic multi-resolution image parameterization combined with feature extraction and machine learning methods to significantly improve on all aspects of diagnostic performance. With the proposed approach clinical results are significantly as well as fully automatically, improved throughout the study. Overall, the most significant result of the work is an improvement in the diagnostic power of the whole diagnostic process. The approach supports, but does not replace, physicians’ diagnostic process, and can assist in decisions on the cost-effectiveness of diagnostic tests.
The Use of Prediction Reliability Estimates on Imbalanced Datasets
Authors: Košir Domen , Bosnic Zoran , Kononenko Igor
Published: May 2012

Data mining techniques are extensively used on medical data, which is typically composed of many normal examples and few interesting ones. When presented with highly imbalanced data, some standard classifiers tend to ignore the minority class which leads to poor performance. Various solutions have been proposed to counter this problem. Random undersampling, random oversampling, and SMOTE (Synthetic Minority Oversampling Technique) are the most well-known approaches. In recent years several approaches to evaluate the reliability of single predictions have been developed. Most recently a simple and efficient approach, based on the classifier’s class probability estimates was shown to outperform the other reliability estimates. The authors propose to use this reliability estimate to improve the SMOTE algorithm. In this study, they demonstrate the positive effects of using the proposed algorithms on artificial datasets. The authors then apply the developed methodology on the problem of predicting the maximal wall shear stress (MWSS) in the human carotid artery bifurcation. The results indicate that it is feasible to improve the classifier’s performance by balancing the data with their versions of the SMOTE algorithm.
Identification of Motor Functions Based on an EEG Analysis
Authors: Belic Aleš , Logar Vito
Published: May 2012

A combination of several techniques is necessary for a reliable identification of activities based on EEG signals. A separation of the overlapping patterns in the EEG signals is often performed first. These separated patterns are then analysed by some artificial intelligence methods in order to identify the activity. As pattern separation and activity identification are often linked, the two processes must be tuned to a specific problem, thus losing some generality of the procedure. The complexity of the patterns in EEG signals is often too great for completely automated pattern recognition. In this case, phase demodulation was introduced as a procedure for the extraction of the phase properties of the EEG signals. These phase shifts are known to correlate with the brain activity; therefore, phase-demodulated EEG signals were used to predict the motor activity. Three studies with off-line identification of the motor activities have been performed so far. In the first study, a continuous gripping force was predicted. In the second study, index- and middle-finger activation was predicted, and in the final study, wrist movements were analysed. The presented procedure can be used for designing a continuous brain-computer interface.
Extraction of Medical Pathways from Electronic Patient Records
Authors: Antonelli Dario , Baralis Elena , Bruno Giulia , Chiusano Silvia , Mahoto Naeem A. , Petrigni Caterina
Published: May 2012

With the introduction of electronic medical records, a large amount of patients’ medical data has been available. An actual problem in this domain is to perform reverse engineering of the medical treatment process to highlight medical pathways typically adopted for specific health conditions. This chapter addresses the ability of sequential data mining techniques to reconstruct the actual medical pathways followed by patients. Detected medical pathways are in the form of sets of exams frequently done together, sequences of exam sets frequently followed by patients and frequent correlations between exam sets. The analysis shows that the majority of the extracted pathways are consistent with the medical guidelines, but also reveals some unexpected results, which can be useful both to enrich existing guidelines and to improve the public sanitary service.
Linguistic Aspects of Informal Learning in Corporate Online Social Networks
Authors: Bielenia-Grajewska Magdalena
Published: May 2012

This chapter discusses the role of corporate online social networks in the process of informal learning. The first part of these studies offers some introduction to the issue of online social networks used in the corporate setting. The second component of the investigation is dedicated to discussing the notion of informal learning in online social networks. To limit the scope of the research, in the subsequent sections the author concentrates on the linguistic aspect of spontaneous and unofficial education acquired online by corporate members. To discuss these issues in greater detail, the concepts of homophilous and heterophilous networks in corporate online learning will be presented and discussed.
Optimisation of Radiation Beam in Linear Nodes Array of Wireless Sensor Network for Improved Performance
Authors: Malik N. N. N. Abd. , Esa M. , Yusof S. K. S. , Hamzah S. A. , Ismail M. K. H.
Published: May 2012

This chapter presents an intelligent method of optimising the radiation beam of wireless sensor nodes in Wireless Sensor Network (WSN). Each node has the feature of a monopole antenna. The optimisation involves selection of nodes to be organised as close as possible to a uniform linear array (ULA) in order to minimise the position errors, which will improve the radiation beam reconfiguring performance. Instead of utilising random beamforming, which needs a large number of sensor nodes to interact with each other and form a narrow radiation beam, the developed optimisation algorithm is emphasized to only a selected number of sensor nodes which can construct a linear array. Thus, the method utilises radiation beam reconfiguration technique to intelligently establish a communication link in a WSN.
Quantum Computing Approach for Alignment-Free Sequence Search and Classification
Authors: Kotamarti Rao M. , Thornton Mitchell A. , Dunham Margaret H.
Published: May 2012

Many classes of algorithms that suffer from large complexities when implemented on conventional computers may be reformulated resulting in greatly reduced complexity when implemented on quantum computers. The dramatic reductions in complexity for certain types of quantum algorithms coupled with the computationally challenging problems in some bioinformatics problems motivates researchers to devise efficient quantum algorithms for sequence (DNA, RNA, protein) analysis. This chapter shows that the important sequence classification problem in bioinformatics is suitable for formulation as a quantum algorithm. This chapter leverages earlier research for sequence classification based on Extensible Markov Model (EMM) and proposes a quantum computing alternative. The authors utilize sequence family profiles built using EMM methodology which is based on using pre-counted word data for each sequence. Then a new method termed quantum seeding is proposed for generating a key based on high frequency words. The key is applied in a quantum search based on Grover algorithm to determine a candidate set of models resulting in a significantly reduced search space. Given Z as a function of M models of size N, the quantum version of the seeding algorithm has a time complexity in the order of as opposed to O(Z) for the standard classic version for large values of Z.
Making a Rod for One’s Own Back
Authors: Russell Christopher
Published: May 2012

This chapter identifies a new pattern of bargaining for technology, based upon nine months’ ethnographic fieldwork amongst the engineers of a Telco’s research and development department. Bargains for smartphones were initiated by the employee and negotiated with the employer by reference to the productivity discourse of the vendor. After a honeymoon phase of exploration, the reality of operation was markedly different, resulting, in several cases, in the disposition of the smartphone or, in one case, the disposition of the employee to leave. Such bargains were driven by conceptions of the personal and organisational use value of the artefact, and this finding reveals shortcomings in the drivers, influences, and stages of adoption found in existing models. A new conceptual framework is presented that facilitates exploration of the contribution of personal and organisational use value to technology adoption.
An Exploratory Study of the Effects of Extended Online Thematic Listening Tasks on the Development of Listening Comprehension
Authors: Sun Yu-Chih , Chang Wen-Li , Yang Fang-Ying
Published: May 2012

This study investigates the effects of employing extended online thematic listening tasks on the development of listening comprehension in an English course focusing on reading and writing skill development. To accomplish this aim, extended online thematic listening tasks were designed and implemented in English as a Foreign-Language (EFL) college level General English course. Pre- and post-tests were conducted to examine students’ gains in overall listening proficiency. Moreover, students’ mid-term and final exams were compared in order to track student progress. Data on student perceptions of online thematic tasks was also collected and analyzed. Findings suggest that extended online thematic listening tasks may constitute a dynamic forum which fosters significant gains in listening comprehension, test performance, and development of learning strategies. In addition, the findings reveal that students’ initial enthusiasm toward extended online listening tasks faded and the efforts that they put into the tasks gradually decreased as the semester progressed. Therefore, time availability and management become an important pedagogical issue in e-learning.
Interactive Learning Between Chinese Students Learning English and English Students Learning Chinese on the Platform of Wiki
Authors: Wang Dongshuo , Zou Bin , Xing Minjie
Published: May 2012

This research investigates the interaction between English students learning Chinese in the UK and Chinese students learning English in China via a wiki platform. Activity theory and legitimate peripheral participation theory were employed as a theoretical framework; wiki was embedded as an interactive learning tool. The findings revealed that Chinese native speakers assisted English students learning Chinese as foreign language (CFL) by means of reorganizing word orders and restructuring sentence patterns. The usages of clarification and elaboration were more frequent than the usages of added and deleted information. Both CFL and English as foreign language (EFL) students interacted with each other in attending to language forms through the essay correction and revision process, and the interaction consequently enhanced their target language learning. The study suggests that wiki provides a dynamic platform, which encourages further integration into the syllabus to support foreign language learning.
Teaching Students to Use Text-Profilers
Authors: Barth Ingrid , Klein-Wohl Esther
Published: May 2012

In this paper the authors suggest that teaching students to use freely available text-profiling software represents an innovative strategy and possible solution to needs of non-native English speakers who leave school without an adequate English vocabulary. First the research basis is described for a new text-profiler designed to help students acquire the high-frequency vocabulary they need in order to become effective readers of academic texts published in English. The authors then illustrate relative advantages of this tool and show how these features address specific issues related to learning English vocabulary at college or university. Finally pedagogic implications of teaching students to use text-profilers are presented and suggestions are offered for future directions.
Competition in Online Comparison Shopping Services
Authors: Saastamoinen Jani
Published: May 2012

Retail markets in online comparison shopping websites are extremely competitive, yet firms voluntarily list in these services. The objective of this paper is to study competition and seller profitability in comparison shopping markets. In the proposed model, two profit-maximizing sellers sell a homogeneous good to Bayesian risk-neutral buyers. Buyers use a reputation system to update their beliefs about the sellers and purchase from the seller that maximizes the buyer’s expected surplus. The model shows that a seller’s profit depends on the distribution of buyer beliefs. A good reputation increases a seller’s profits. Empirical testing is carried out using data from Pricegrabber, a popular comparison shopping website. The evidence indicates that a good reputation may support price premiums as the model suggests.
Social Media Impact on Holiday Travel Planning
Authors: Fotis John , Buhalis Dimitrios , Rossides Nicos
Published: May 2012

The impact of social media on the travel industry is predicted to be tremendous, especially on its holiday travel segment. Although there is a plethora of studies concentrating on the role and impact of social media in travel related decisions, most of them are medium and community specific, or focus on a specific stage of the decision making or the travel planning process. This paper presents a comprehensive view of the role and impact of social media on the travel planning process: before, during and after the trip, providing insights on usage levels, scope of use, level of influence, and trust. The study was conducted through an online structured questionnaire on a sample of 346 members of an online panel of internet users from Russia and the other Former Soviet Union (FSU) Republics who had been on holidays in the previous 12 months. Findings reveal that social media are predominantly used after holidays for experience sharing. It is also shown that there is a strong correlation between level of influence from social media and changes made to holiday plans. Moreover, it is revealed that user-generated content is more trusted than official tourism websites, travel agents, and mass media advertising.
Fuzzy C-Means in High Dimensional Spaces
Authors: Winkler Roland , Klawonn Frank , Kruse Rudolf
Published: May 2012

High dimensions have a devastating effect on the FCM algorithm and similar algorithms. One effect is that the prototypes run into the centre of gravity of the entire data set. The objective function must have a local minimum in the centre of gravity that causes FCM’s behaviour. In this paper, examine this problem. This paper answers the following questions: How many dimensions are necessary to cause an ill behaviour of FCM? How does the number of prototypes influence the behaviour? Why has the objective function a local minimum in the centre of gravity? How must FCM be initialised to avoid the local minima in the centre of gravity? To understand the behaviour of the FCM algorithm and answer the above questions, the authors examine the values of the objective function and develop three test environments that consist of artificially generated data sets to provide a controlled environment. The paper concludes that FCM can only be applied successfully in high dimensions if the prototypes are initialized very close to the cluster centres.
Extension of the TOPSIS for Multi-Attribute Group Decision Making under Atanassov IFS Environments
Authors: Li Deng-Feng , Nan Jiang-Xia
Published: May 2012

This paper extends the technique for order preference by similarity to ideal solution (TOPSIS) for solving multi-attribute group decision making (MAGDM) problems under Atanassov intuitionistic fuzzy set (IFS) environments. In this methodology, weights of attributes and ratings of alternatives on attributes are extracted from fuzziness inherent in decision data and making process and described using Atanassov IFSs. An Euclidean distance measure is developed to calculate the differences between alternatives for each decision maker and an Atanassov IFS positive ideal solution (IFSPIS) as well as an Atanassov IFS negative ideal-solution (IFSNIS). Degrees of relative closeness to the Atanassov IFSPIS for all alternatives with respect to each decision maker in the group are calculated. Then all decision makers in the group may be regarded as “attributes” and a corresponding classical MADM problem is generated and hereby solved by the TOPSIS. The proposed methodology is validated and compared with other similar methods. A numerical example is examined to demonstrate the implementation process of the methodology proposed in this paper.
Proposing a Model to Explain Teachers’ Intention to Use Technology
Authors: Teo Timothy
Published: May 2012

In this paper, the author identifies the constructs that influence teachers’ intention to use technology for instructional purposes. Drawing from widely used and validated theories and models with origins from social psychology, a total of seven constructs were identified to develop a research model. Following, twelve hypotheses were formulated to describe the relationships among the constructs and the teachers’ intention to use. Further studies on the research model for greater validity and expansion are suggested.
Diagnosis of neurofibromatosis type 1 after resection of intercostal nerve neurofibroma
Authors: Aguinagalde Borja , Zabaleta Jon , Fuentes Marta , Bazterargui Nerea , Lobo Carmen , Izquierdo José Miguel
Published: May 2012

We report a case of a 37-year-old man with an asymptomatic extraparenchymal mass in the left hemithorax. Complete surgical removal of the tumour was achieved through a minithoracotomy and histological analysis confirmed the diagnosis of myxoid neurofibroma. Given this histological diagnosis, the patient was re-examined and many café au lait spots (more than 6, larger than 15 mm in diameter) and neurofibromas (elastic tissue) were observed and the patient was diagnosed with neurofibromatosis (NF) type 1 (von Recklinghausen’s disease). We have found only eight case reports of neurogenic tumours originating from an intercostal nerve; only two of these corresponded to neurofibromas. Among these two patients, only one was a case of NF type 1 and, in contrast to our case, the diagnosis was reached prior to surgery. We present a very rare case of intercostal nerve neurofibroma leading to a definitive diagnosis of NF type 1.
An investigation into agricultural cultivation techniques and the impacts thereof on soil microbial biodiversity.
Authors: De Bruyn C. , Vooys R. , Jordaan Anine , Tiedt Louwrens R.
Published: May 2012

The aim of this study is to determine the impacts that various cultivation techniques may have on the biodiversity of the microorganisms as well the microfauna contained within the soil. The presence of nematodes is of particular interest.
Ozone leads to an increase of hydrogen peroxide levels and peroxidase activity in two maize varieties
Authors: Stols E. , Berner Jacques M.
Published: May 2012

The goal of this study was to determine whether ozone induce hydrogen peroxide concentrations and peroxidase activity in two maize cultivars. Hydrogen peroxide levels as well as peroxidase activity was higher in both the ozone treated cultivars.
A Novel Numerical Method of for Three-Dimensional Non-Linear Triharmonic Equations
Authors: Mohanty R. K. , Jain M. K. , Mishra B. N.
Published: May 2012

In this article, we present two new novel finite difference approximations of order two and four, respectively, for the three dimensional non-linear triharmonic partial differential equations on a compact stencil where the values ofu,∂2u/∂n2 and∂4u/∂n4are prescribed on the boundary. We introduce new ideas to handle the boundary conditions and there is no need to discretize the derivative boundary conditions. We require only 7- and 19-grid points on the compact cell for the second and fourth order approximation, respectively. The Laplacian and the biharmonic of the solution are obtained as by-product of the methods. We require only system of three equations to obtain the solution. Numerical results are provided to illustrate the usefulness of the proposed methods.
Asymptotic Stability of an Eikonal Transformation Based ADI Method for the Paraxial Helmholtz Equation at High Wave Numbers
Authors: Sheng Qin , Sun Hai-Wei
Published: May 2012

This paper concerns the numerical stability of an eikonal transformation based splitting method which is highly effective and efficient for the numerical solution of paraxial Helmholtz equation with a large wave number. Rigorous matrix analysis is conducted in investigations and the oscillation-free computational procedure is proven to be stable in an asymptotic sense. Simulated examples are given to illustrate the conclusion.
Computational Aspects of Multiscale Simulation with the Lumped Particle Framework
Authors: al-Khayat Omar , Langtangen Hans Petter
Published: May 2012

First introduced in, the lumped particle framework is a flexible and numerically efficient framework for the modelling of particle transport in fluid flow. In this paper, the framework is expanded to simulate multicomponent particle-laden fluid flow. This is accomplished by introducing simulation protocols to model particles over a wide range of length and time scales. Consequently, we present a time ordering scheme and an approximate approach for accelerating the computation of evolution of different particle constituents with large differences in physical scales. We apply the extended framework on the temporal evolution of three particle constituents in sandladen flow, and horizontal release of spherical particles. Furthermore, we evaluate the numerical error of the lumped particle model. In this context, we discuss the Velocity-Verlet numerical scheme, and show how to apply this to solving Newton’s equations within the framework. We show that the increased accuracy of the Velocity-Verlet scheme is not lost when applied to the lumped particle framework.
Boosted Hybrid Method for Solving Chemical Reaction Systems with Multiple Scales in Time and Population Size
Authors: Hu Yucheng , Abdulle Assyr , Li Tiejun
Published: May 2012

A new algorithm, called boosted hybrid method, is proposed for the simulation of chemical reaction systems with scale-separation in time and disparity in species population. For such stiff systems, the algorithm can automatically identify scale-separation in time and slow down the fast reactions while maintaining a good approximation to the original effective dynamics. This technique is called boosting. As disparity in species population may still exist in the boosted system, we propose a hybrid strategy based on coarse-graining methods, such as the tau-leaping method, to accelerate the reactions among large population species. The combination of the boosting strategy and the hybrid method allow for an efficient and adaptive simulation of complex chemical reactions. The new method does not need a priori knowledge of the system and can also be used for systems with hierarchical multiple time scales. Numerical experiments illustrate the versatility and efficiency of the method.
An All-Speed Asymptotic-Preserving Method for the Isentropic Euler and Navier-Stokes Equations
Authors: Haack Jeffrey , Jin Shi , Liu Jian‐Guo
Published: May 2012

The computation of compressible flows becomes more challenging when the Mach number has different orders of magnitude. When the Mach number is of order one, modern shock capturing methods are able to capture shocks and other complex structures with high numerical resolutions. However, if the Mach number is small, the acoustic waves lead to stiffness in time and excessively large numerical viscosity, thus demanding much smaller time step and mesh size than normally needed for incompressible flow simulation. In this paper, we develop an all-speed asymptotic preserving (AP) numerical scheme for the compressible isentropic Euler and Navier-Stokes equations that is uniformly stable and accurate for all Mach numbers. Our idea is to split the system into two parts: one involves a slow, nonlinear and conservative hyperbolic system adequate for the use of modern shock capturing methods and the other a linear hyperbolic system which contains the stiff acoustic dynamics, to be solved implicitly. This implicit part is reformulated into a standard pressure Poisson projection system and thus possesses sufficient structure for efficient fast Fourier transform solution techniques. In the zero Mach number limit, the scheme automatically becomes a projection method-like incompressible solver. We present numerical results in one and two dimensions in both compressible and incompressible regimes.
A Numerical Comparison Between Quasi-Monte Carlo and Sparse Grid Stochastic Collocation Methods
Authors: dos Santos Azevedo Juarez , Pomponet Oliveira Saulo
Published: May 2012

Quasi-Monte Carlo methods and stochastic collocation methods based on sparse grids have become popular with solving stochastic partial differential equations. These methods use deterministic points for multi-dimensional integration or interpolation without suffering from the curse of dimensionality. It is not evident which method is best, specially on random models of physical phenomena. We numerically study the error of quasi-Monte Carlo and sparse grid methods in the context of ground-water flow in heterogeneous media. In particular, we consider the dependence of the variance error on the stochastic dimension and the number of samples/collocation points for steady flow problems in which the hydraulic conductivity is a lognormal process. The suitability of each technique is identified in terms of computational cost and error tolerance.
Impact of HONO on global atmospheric chemistry calculated with an empirical parameterization in the EMAC model
Authors: Elshorbany Y. F. , Steil B. , Brühl C. , Lelieveld J.
Published: May 2012

Abstract. The photolysis of HONO is important for the atmospheric HOx (OH+HO2) radical budget and ozone formation, especially in polluted air. Nevertheless, owing to the incomplete knowledge of HONO sources, realistic HONO mechanisms have not yet been implemented in global models. We investigated measurement data sets from 15 field measurement campaigns conducted in different countries worldwide. It appears that the HONO/NOx ratio is a good proxy predictor for HONO mixing ratios under different atmospheric conditions. From the robust relationship between HONO and NOx, a representative mean HONO/NOx ratio of 0.02 has been derived. Using a global chemistry-climate model and employing this HONO/NOx ratio, realistic HONO levels are simulated, being about one order of magnitude higher than the reference calculations, which only consider the reaction OH+NO-> HONO. The resulting enhancement of HONO significantly impacts HOx levels and photo-oxidation products (e.g, O3, PAN), mainly in polluted regions. Furthermore, the relative enhancements in OH and secondary products were higher in winter than in summer, thus enhancing the oxidation capacity in polluted regions, especially in winter, when the other photolytic OH sources are of minor importance. Our results underscore the need to improve the understanding of HONO chemistry and its representation in atmospheric models.
Measurement of spatial and temporal fine sediment dynamics in a small river
Authors: Schindler Wildhaber Y. , Michel C. , Burkhardt-Holm P. , Bänninger D. , Alewell C.
Published: May 2012

Abstract. Empirical measurements on fine sediment dynamics and fine sediment infiltration and accumulation have been conducted worldwide, but it is difficult to compare the results because the applied methods differ widely. We compared common methods to capture temporal and spatial dynamics of suspended sediment (SS), fine sediment infiltration and accumulation and tested them for their suitability in a small, canalized river of the Swiss Plateau. Measurement suitability was assessed by data comparison, relation to hydrological data and in the context of previously published data. SS concentration and load were assessed by optical backscatter (OBS) sensors and SS samplers. The former exhibit a better temporal resolution, but were associated with calibration problems. Due to the relatively low cost and easy mounting of SS samplers, they can provide a higher spatial distribution in the river's cross section. The latter resulted in a better correlation between sediment infiltration and SS load assessed by SS samplers than SS concentrations measured with OBS sensors. Sediment infiltration baskets and bedload traps capture the temporal and spatial distribution of fine sediment infiltration. Data obtained by both methods were positively correlated with water level and SS. In contrast, accumulation baskets do not assess the temporal behaviour of fine sediment, but the net accumulation over a certain time period. Less fine sediment accumulated in upwelling zones and within areas of higher mean water level due to scouring of fine sediments. Even though SS and sediment infiltration assessed with the bedload traps increased from up- to downstream, less fine sediment accumulated downstream. This is probably also attributable to more scouring downstream.