Multistage interconnection networks reliability evaluation based on stratified sampling Monte Carlo method
- Authors: Gunawan, Indra
- Date: 2008
- Type: Text , Journal article
- Relation: International Journal of Modelling and Simulation Vol. 28, no. 2 (2008), p. 209-214
- Full Text: false
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- Description: Multistage interconnection networks (MINs) have been widely adopted in communication networks especially in telecommunication and multiprocessor environments. This paper aims to evaluate the reliability performance of shuffle exchange network with an additional stage (SEN+), based on Monte Carlo method using computerized simulation. The evaluation is further improvised by deploying stratified sampling into the Monte Carlo method. SEN+ described in this paper is confined to multiprocessor environment based on identical switching elements used in interconnecting multiple processors. It is shown that Monte Carlo method is capable of providing reliability evaluation for SEN+ system.
Application of artificial intelligence to improve quality of service in computer networks
- Authors: Ahmad, Iftekhar , Kamruzzaman, Joarder , Habibi, Daryoush
- Date: 2012
- Type: Text , Journal article
- Relation: Neural Computing & Applications Vol. 21, no. 1 (2012), p. 81-90
- Full Text: false
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- Description: Resource sharing between book-ahead (BA) and instantaneous request (IR) reservation often results in high preemption rates for ongoing IR calls in computer networks. High IR call preemption rates cause interruptions to service continuity, which is considered detrimental in a QoS-enabled network. A number of call admission control models have been proposed in the literature to reduce preemption rates for ongoing IR calls. Many of these models use a tuning parameter to achieve certain level of preemption rate. This paper presents an artificial neural network (ANN) model to dynamically control the preemption rate of ongoing calls in a QoS-enabled network. The model maps network traffic parameters and desired operating preemption rate by network operator providing the best for the network under consideration into appropriate tuning parameter. Once trained, this model can be used to automatically estimate the tuning parameter value necessary to achieve the desired operating preemption rates. Simulation results show that the preemption rate attained by the model closely matches with the target rate.
Mass estimation
- Authors: Ting, Kaiming , Zhou, Guang , Liu, Fei , Tan, Swee
- Date: 2013
- Type: Text , Journal article
- Relation: Machine Learning Vol. 90, no. 1 (2013), p. 127-160
- Full Text: false
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- Description: This paper introduces mass estimation—a base modelling mechanism that can be employed to solve various tasks in machine learning. We present the theoretical basis of mass and efficient methods to estimate mass. We show that mass estimation solves problems effectively in tasks such as information retrieval, regression and anomaly detection. The models, which use mass in these three tasks, perform at least as well as and often better than eight state-of-the-art methods in terms of task-specific performance measures. In addition, mass estimation has constant time and space complexities.
Performance under pressure
- Authors: Mesagno, Christopher
- Date: 2013
- Type: Text , Journal article
- Relation: International Journal of Sport Psychology Vol. 44, no. 4 (July-August 2013), p. 263-265
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Unique associations of reinforcement sensitivity theory dimensions with social interaction anxiety and social observation anxiety
- Authors: Ly, Corina , Gomez, Rapson
- Date: 2014
- Type: Text , Journal article
- Relation: Personality and Individual Differences Vol. 60, no. (2014), p. 20-24
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- Description: Relationships between Rothbart’s 13 temperament sub-dimensions and the Attention-Deficit/Hyperactivity Disorder (ADHD) factors for the 2-factor model [inattention (IA) and hyperactivity/impulsivity (HI) domains] and the bifactor model (general ADHD, and specific factors for IA and HI) were examined in 267 adults from the general population. Regression analyses revealed that (1) both the IA and HI factors in the 2-factor model and the general ADHD factor in the bifactor model were predicted positively by sad, discomfort and associative sensitivity, and negatively by activation control, (2) the HI domain factor in the 2-factor model was also predicted negatively by inhibitory control, (3) the specific IA factor in the bifactor model was predicted negatively by activation control and attention control, and (4) the HI specific factor in the bifactor model was predicted negatively by inhibitory control and positively by sociability. These theoretical and clinical implications of the findings are discussed. ADHD
Analysis of design structure matrix methods in design process improvement
- Authors: Gunawan, Indra
- Date: 2012
- Type: Text , Journal article
- Relation: International Journal of Modelling and Simulation Vol. 32, no. 2 (2012), p. 95-103
- Full Text: false
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- Description: In this paper, design structure matrix (DSM) methods are presented to manage design iteration or rework which is inherent in the design process. Three DSM methods: path searching, powers of the adjacency matrix, and reachability matrix methods are discussed. Their advantages and disadvantages with respect to the project scope are summarized. As a case study, DSM methods are implemented to reduce the design iteration or rework in a complex engineering project. The main advantage of the DSM methods over traditional project management tools such as CPM or Gantt chart is in compactness and ability to present an organized and efficient mapping among tasks that is clear and easy to read regardless of size.
Recentred local profiles for authorship attribution
- Authors: Layton, Robert , Watters, Paul , Dazeley, Richard
- Date: 2012
- Type: Text , Journal article
- Relation: Natural Language Engineering Vol. 18, no. 3 (2012), p. 293-312
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- Description: Authorship attribution methods aim to determine the author of a document, by using information gathered from a set of documents with known authors. One method of performing this task is to create profiles containing distinctive features known to be used by each author. In this paper, a new method of creating an author or document profile is presented that detects features considered distinctive, compared to normal language usage. This recentreing approach creates more accurate profiles than previous methods, as demonstrated empirically using a known corpus of authorship problems. This method, named recentred local profiles, determines authorship accurately using a simple 'best matching author' approach to classification, compared to other methods in the literature. The proposed method is shown to be more stable than related methods as parameter values change. Using a weighted voting scheme, recentred local profiles is shown to outperform other methods in authorship attribution, with an overall accuracy of 69.9% on the ad-hoc authorship attribution competition corpus, representing a significant improvement over related methods. Copyright © Cambridge University Press 2011.
- Description: 2003010688
Big five personality traits, job satisfaction and subjective wellbeing in China
- Authors: Zhai, Qingguo , Willis, Mike , O'Shea, Bob , Zhai, Yubo , Yang, Yuwen
- Date: 2013
- Type: Text , Journal article
- Relation: International Journal of Psychology Vol. 48, no. 6 (December 2013), p. 1099-1108
- Full Text: false
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- Description: This paper examines the effect of the Big Five personality traits on job satisfaction and subjective wellbeing (SWB). The paper also examines the mediating role of job satisfaction on the Big Five-SWB relationship. Data were collected from a sample of 818 urban employees from five Chinese cities: Harbin, Changchun, Shenyang, Dalian, and Fushun. All the study variables were measured with well-established multi-item scales that have been validated both in English-speaking populations and in China. The study found only extraversion to have an effect on job satisfaction, suggesting that there could be cultural difference in the relationships between the Big Five and job satisfaction in China and in the West. The study found that three factors in the Big Fiveextraversion, conscientiousness, and neuroticismhave an effect on SWB. This finding is similar to findings in the West, suggesting convergence in the relationship between the Big Five and SWB in different cultural contexts. The research found that only the relationship between extraversion and SWB is partially mediated by job satisfaction, implying that the effect of the Big Five on SWB is mainly direct, rather than indirect via job satisfaction. The study also found that extraversion was the strongest predictor of both job satisfaction and SWB. This finding implies that extraversion could be more important than other factors in the Big Five in predicting job satisfaction and SWB in a high collectivism and high power distance country such as China. The research findings are discussed in the Chinese cultural context. The study also offers suggestions on the directions for future research.
- Description: C1
An improved curvature scale-space corner detector and a robust corner matching approach for transformed image identification
- Authors: Awrangjeb, Mohammad , Lu, Guojun
- Date: 2008
- Type: Text , Journal article
- Relation: Image Processing, IEEE Transactions Vol. 17, no. 12 (2008), p. 2425-2441
- Full Text: false
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- Description: There are many applications, such as image copyright protection, where transformed images of a given test image need to be identified. The solution to this identification problem consists of two main stages. In stage one, certain representative features, such as corners, are detected in all images. In stage two, the representative features of the test image and the stored images are compared to identify the transformed images for the test image. Curvature scale-space (CSS) corner detectors look for curvature maxima or inflection points on planar curves. However, the arc-length used to parameterize the planar curves by the existing CSS detectors is not invariant to geometric transformations such as scaling. As a solution to stage one, this paper presents an improved CSS corner detector using the affine-length parameterization which is relatively invariant to affine transformations. We then present an improved corner matching technique as a solution to the stage two. Finally, we apply the proposed corner detection and matching techniques to identify the transformed images for a given image and report the promising results.
Automated unsupervised authorship analysis using evidence accumulation clustering
- Authors: Layton, Robert , Watters, Paul , Dazeley, Richard
- Date: 2013
- Type: Text , Journal article
- Relation: Natural Language Engineering Vol. 19, no. 1 (2013), p. 95-120
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- Reviewed:
- Description: Authorship Analysis aims to extract information about the authorship of documents from features within those documents. Typically, this is performed as a classification task with the aim of identifying the author of a document, given a set of documents of known authorship. Alternatively, unsupervised methods have been developed primarily as visualisation tools to assist the manual discovery of clusters of authorship within a corpus by analysts. However, there is a need in many fields for more sophisticated unsupervised methods to automate the discovery, profiling and organisation of related information through clustering of documents by authorship. An automated and unsupervised methodology for clustering documents by authorship is proposed in this paper. The methodology is named NUANCE, for n-gram Unsupervised Automated Natural Cluster Ensemble. Testing indicates that the derived clusters have a strong correlation to the true authorship of unseen documents. © 2011 Cambridge University Press.
- Description: 2003010584
Performing under pressure in private : Activation of self-focus traits
- Authors: Geukes, Katharina , Mesagno, Christopher , Hanrahan, Stephanie , Kellmann, Michael
- Date: 2013
- Type: Text , Journal article
- Relation: International Journal of Sport and Exercise Psychology Vol. 11, no. 1 (2013), p. 11-23
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- Description: Self-focus and self-presentation traits have been found to predict performance under pressure. The interactionist principle of trait activation indicates that situational demands encourage different traits to be relevant to performance in high-pressure situations. Thus, the purpose of the current study was to investigate the relationship of self-focus and self-presentation traits with performance in a private high-pressure setting. Because the private high-pressure situation offered motivational incentives but only minimal self-presentation cues, only a self-focus trait (private self-consciousness), but not self-presentation traits (public self-consciousness and narcissism), was hypothesized to predict performance under pressure in a private setting. After completing personality questionnaires, future physical education university students (N = 59) with experience in sport competitions performed eight throws at a target in low-pressure and high-pressure conditions. The conditions were identical with the exception that the high-pressure condition involved a monetary incentive and a cover story. Participants' state anxiety increased from low to high pressure. Neither self-focus nor self-presentation traits predicted performance under low pressure. Only the self-focus trait, but not self-presentation traits, negatively contributed to the prediction of high-pressure performance. Hence, findings support the applicability of the trait activation principle and underline that the situational demands of private high-pressure situations activate self-focus personality traits. © 2013 Copyright International Society of Sport Psychology.
- Description: 2003010822
Artificial neural network for prediction of air flow in a single rock joint
- Authors: Ranjith, Pathegama , Khandelwal, Manoj
- Date: 2012
- Type: Text , Journal article
- Relation: Neural Computing and Applications Vol. 21, no. 6 (2012), p. 1413-1422
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- Description: In this paper, an attempt has been made to evaluate and predict the air flow rate in triaxial conditions at various confining pressures incorporating cell pressure, air inlet pressure, and air outlet pressure using artificial neural network (ANN) technique. A three-layer feed forward back propagation neural network having 3-7-1 architecture network was trained using 37 data sets measured from laboratory investigation. Ten new data sets were used for the, validation and comparison of the air flow rate by ANN and multi-variate regression analysis (MVRA) to develop more confidence on the proposed method. Results were compared based on coefficient of determination (CoD) and mean absolute error (MAE) between measured and predicted values of air flow rate. It was found that CoD between measured and predicted air flow rate was 0. 995 and 0. 758 by ANN and MVRA, respectively, whereas MAE was 0. 0413 and 0. 1876. © 2011 Springer-Verlag London Limited.
Spiritual well-being and psychological type: a study among visitors to a medieval cathedral in Wales
- Authors: Francis, Leslie , Fisher, John , Annis, Jennie
- Date: 2015
- Type: Text , Journal article
- Relation: Mental Health, Religion & Culture Vol. 18, no. 8 (2015), p. 675-692
- Full Text: false
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- Description: This study explores the theoretical and empirical connections between spiritual well-being and psychological type by drawing on Fisher's model of spiritual well-being as assessed by the Spiritual Health And Life-Orientation Measure and Francis' classification of psychological type as generated by the Francis Psychological Type Scales. Data provided by 2339 visitors to St David's Cathedral in rural west Wales demonstrated that, when the four components of psychological type were considered independently, higher levels of spiritual well-being were associated with extraversion rather than introversion, with intuition rather than sensing, with feeling rather than thinking and with perceiving rather than judging. Further examination of these data suggested that the judging process (distinguishing between the feeling function and the thinking function) was of greatest importance in shaping individual differences in spiritual health.
Local models - the key to boosting stable learners successfully
- Authors: Ting, Kaiming , Zhu, Lian , Wells, Jonathan
- Date: 2013
- Type: Text , Journal article
- Relation: Computational Intelligence Vol. 29, no. 2 (2013), p. 331-356
- Full Text: false
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- Description: Boosting has been shown to improve the predictive performance of unstable learners such as decision trees, but not of stable learners like Support Vector Machines (SVM), k-nearest neighbours and Naive Bayes classifiers. In addition to the model stability problem, the high time complexity of some stable learners such as SVM prohibits them from generating multiple models to form an ensemble for large data sets. This paper introduces a simple method that not only enables Boosting to improve the predictive performance of stable learners, but also significantly reduces the computational time to generate an ensemble of stable learners such as SVM for large data sets that would otherwise be infeasible. The method proposes to build local models, instead of global models; and it is the first method, to the best of our knowledge, to solve the two problems in Boosting stable learners at the same time. We implement the method by using a decision tree to define local regions and build a local model for each local region. We show that this implementation of the proposed method enables successful Boosting of three types of stable learners: SVM, k-nearest neighbours and Naive Bayes classifiers.
- Description: Boosting has been shown to improve the predictive performance of unstable learners such as decision trees, but not of stable learners like Support Vector Machines (SVM), k-nearest neighbors and Naive Bayes classifiers. In addition to the model stability problem, the high time complexity of some stable learners such as SVM prohibits them from generating multiple models to form an ensemble for large data sets. This paper introduces a simple method that not only enables Boosting to improve the predictive performance of stable learners, but also significantly reduces the computational time to generate an ensemble of stable learners such as SVM for large data sets that would otherwise be infeasible. The method proposes to build local models, instead of global models; and it is the first method, to the best of our knowledge, to solve the two problems in Boosting stable learners at the same time. We implement the method by using a decision tree to define local regions and build a local model for each local region. We show that this implementation of the proposed method enables successful Boosting of three types of stable learners: SVM, k-nearest neighbors and Naive Bayes classifiers.
Microglia activation in the hypothalamic PVN following myocardial infarction
- Authors: Rana, Indrajeetsinh , Stebbing, Martin , Kompa, Andrew , Kelly, Darren , Krum, Henry , Badoer, Emilio
- Date: 2010
- Type: Text , Journal article
- Relation: Brain Research Vol. 1326, no. (April 2010 2010), p. 96-104
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- Description: Following a myocardial infarction (MI), inflammatory cytokines are elevated in the brain, as well as in plasma, indicating that inflammation is occurring in the brain in addition to the periphery. Microglia are the immune cells in the central nervous system and can produce cytokines when they are activated by an insult or injury. In the present study, we investigated whether MI in rats induces activation of microglia in the brain. We used immunohistochemistry to detect CD11b (clone OX-42) and morphological changes to identify activated microglia. Compared to control rats that had undergone sham surgical procedures, there was a significant increase in activated microglia in the hypothalamic paraventricular nucleus (PVN) following myocardial infarction. Activated microglia were not observed in the ventral hypothalamus, adjacent to the PVN, nor in the cortex, indicating the response was not the result of a generalized inflammatory reaction in the brain. Echocardiography and haemodynamic parameters after myocardial infarction indicated that reduced left ventricular function but congestive heart failure had not developed. In conclusion, microglia are activated in the PVN but not in the adjacent hypothalamus following myocardial infarction. The activated microglia may contribute to the increased local production of pro-inflammatory cytokines observed in the PVN after myocardial infarction and resulting in reduced left ventricular function.
- Description: C1
The effect of clustering on statistical tests : an illustration using classroom environment data
- Authors: Dorman, Jeffrey
- Date: 2008
- Type: Text , Journal article
- Relation: An International Journal of Experimental Educational Psychology Vol. 28, no. 5 (2008), p. 583-596
- Full Text: false
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- Description: This paper discusses the effect of clustering on statistical tests and illustrates this effect using classroom environment data. Most classroom environment studies involve the collection of data from students nested within classrooms and the hierarchical nature to these data cannot be ignored. In particular, this paper studies the influence of intraclass correlations on tests of statistical significance conducted with the individual as the unit of analysis. Theory that adjusts t‐test scores for nested data in two‐group comparisons is presented and applied to classroom environment data. This paper demonstrates that Type I error rates inflate greatly as the intraclass correlation increases. Data analysis techniques that recognise the clustering of students in classrooms in classroom environment studies are essential, and it is recommended that either multilevel analysis or adjustments to statistical parameters be undertaken in studies involving nested data.
Preface
- Authors: Pan, Heping , Hayward, Serge
- Date: 2011
- Type: Text , Journal article
- Relation: New Mathematics and Natural Computation Vol. 7, no. 2 (2011), p. 187-196
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Understanding personal use of the Internet at work: An integrated model of neutralization techniques and general deterrence theory
- Authors: Cheng, Lijiao , Li, Wenli , Zhai, Qingguo , Smyth, Russell
- Date: 2014
- Type: Text , Journal article
- Relation: Computers in Human Behavior Vol. 38, no. (September 2014 2014), p. 220-228
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- Description: This paper examines the influence of neutralization techniques, perceived sanction severity, perceived detection certainty and perceived benefits of using the Internet for personal purposes on intention to use the Internet at work for personal use. To do so, we draw on a conceptual framework integrating neutralization theory and general deterrence theory. The study finds that both neutralization techniques and perceived benefits have a positive effect on personal use of the Internet. Perceived detection certainty is found to have a negative effect on personal use of the Internet, while the effect of perceived sanctions severity on personal use of the Internet is not significant. The effect of neutralization and perceived benefits are much stronger than perceived detection certainty. The findings suggest that people may think more about neutralization and perceived benefits than they do about costs, when deciding whether to use the Internet at work for personal purposes.
- Description: C1
Impulsive control for synchronizing delayed discrete complex networks with switching topology
- Authors: Li, Chaojie , Gao, David , Liu, Chao , Chen, Guo
- Date: 2014
- Type: Text , Journal article
- Relation: Neural Computing and Applications Vol. 24, no. 1 (2014), p. 59-68
- Full Text: false
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- Description: In this paper, global exponential synchronization of a class of discrete delayed complex networks with switching topology has been investigated by using Lyapunov-Ruzimiki method. The impulsive scheme is designed to work at the time instant of switching occurrence. A time-varying delay-dependent criterion for impulsive synchronization is given to ensure the delayed discrete complex networks switching topology tending to a synchronous state. Furthermore, a numerical simulation is given to illustrate the effectiveness of main results © 2013 The Author(s).
Benefits of the scientific method to business and how business and science can learn from each other
- Authors: Howgrave-Graham, Alan , Kirstine, Wayne , Larkins, Jo-Ann
- Date: 2009
- Type: Text , Book chapter
- Relation: Small business: Innovation, problem and strategy, method to business and how business and science can learn from each other p. 117-133
- Full Text: false
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- Description: Science can be basic (or pure) and curiosity driven, or applied, in which new products or processes are developed or creative solutions to problems are sought. On the other hand, business primarily focuses on profit generation and growth. However, business itself is represented by both the service and manufacturing sectors. The benefits of science to the latter would be through the development of new products and improvement of their processes, whereas the former could also benefit from logical scientific thinking and investigation. Because small business often focuses on survival and does not have the resources to conduct the investigations required for an early response to new developments and market forces, its competitiveness can suffer. On the other hand, scientists are engrossed in their new discoveries and are usually not as adept at promoting these where they can do the most good. This chapter is a review of some historical, interspersed with current unpublished, examples of how the commercialization gap between science and business can be closed to the benefit of each. Opportunities for small and larger enterprises are described, primarily in the manufacturing sector, but benefits of science to members of the service sector that rely upon natural resources, such as drycleaners and forensic laboratories, will also be discussed. The strategies proposed highlight the importance of networking and facilitation by a ‘champion’ for the communication of innovations in a competitive environment, and the importance of marketing skills in an age of technological transparency, revolutionary advance in science, environmental sensitivity and dwindling resources. Examples range from the utilization or production of high-tech innovations to the implementation of the simplest measures for cutting costs and using resources more efficiently in small business. How the scientific/academic community can derive maximum benefits from collaborating with business is also discussed.