A set of patterns for the web-based interfaces of an employee services system

The provision of Human Resource (HR), especially payroll, is a core function in every organization. Previously, providers of HR/payroll have offered their services to their clients via conventional modes of communication, such as telephones, facsimile, and courier services. In recent years, with the advent of the Internet and the emergence of web-based electronic commerce, there has been a rise in the adoption of web-based technology and information
systems by service providers, thereby enabling them to interact with their clients through this medium. This development necessitates the use of web-based user interfaces as workspaces between the HR/payroll providers and their clients, and thus, raises certain concerns that determine the effectiveness of web-based workflow systems. These concerns, related to the use of web interfaces, form the basis of the patterns discussed in this paper

An email classification model based on rough set theory

The communication via email is one of the most popular services of the Internet. Emails have brought us great convenience in our daily work and life. However, unsolicited messages or spam, flood our email boxes, which results in bandwidth, time and money wasting. To this end, this paper presents a rough set based model to classify emails into three categories - spam, no-spam and suspicious, rather than two classes (spam and non-spam) in most currently used approaches. By comparing with popular classification methods like Naive Bayes classification, the error ratio that a non-spam is discriminated to spam can be reduced using our proposed model.

Internal representation of movement in children with developmental coordination disorder : a mental rotation task

Recent studies show that children with developmental coordination disorder (DCD) have difficulties in generating an accurate visuospatial representation of an intended action, which are shown by deficits in motor imagery. This study sought to test this hypothesis further using a mental rotation paradigm. It was predicted that children with DCD would not conform to the typical pattern of responding when required to imagine movement of their limbs. Participants included 16 children with DCD and 18 control children; mean age for the DCD group was 10 years 4 months, and for controls 10 years. The task required children to judge the handedness of single-hand images that were presented at angles between 0° and 180° at 45° intervals in either direction. Results were broadly consistent with the hypothesis above. Responses of the control children conformed to the typical pattern of mental rotation: a moderate trade-off between response time and angle of rotation. The response pattern for the DCD group was less typical, with a small trade-off function. Response accuracy did not differ between groups. It was suggested that children with DCD, unlike controls, do not automatically enlist motor imagery when performing mental rotation, but rely on an alternative object-based strategy that preserves speed and accuracy. This occurs because these children manifest a reduced ability to make imagined transformations from an egocentric or first-person perspective.

The Permian-Triassic Boundary Stratigraphic Set: characteristics and correlation

Eased on field observations and compilation of data, a new stratigraphic concept, herein named the Permian-Triassic boundary stratigraphic set (PTBST), is proposed. The PTBST consists of, in ascending order, beds of claystone, limestone (or marl) and claystone. This boundary stratigraphic
set has been recognized at many sections in the Yangtze region of South China, with laterally stable lithological characters, the same or comparable biotas, comparable radiometric ages, and identical or similar magnetostratigraphic and chemostratigraphic signals. Therefore, the PTBST marks an isochronous unit and can serve as an important and effective marker set for regional and global correlations.
The important index fossils for the lowermost Triassic, Hindeodus parvus or Claraia, may be diachronous in their first occurrences with respect to the base of the PTBST and, therefore, should not be used as an exclusive indicator for the beginning of the Triassic. Rather more attention should
be paid to events, succession of events and/or event surfaces, which would potentially provide a more precise tool for high-resolution stratigraphic division and correlation.

Some aspects of photosynthetic characteristics in a set of perennial irrigation reservoirs located in five river basins in Sri Lanka

Phytoplankton primary productivity of eleven irrigation reservoirs located in five river basins in Sri Lanka was determined on a single occasion together with light climate and nutrient concentrations. Although area-based gross primary productivity (1.43–11.65 g O2 m−2 d−1) falls within the range already established for tropical water bodies, net daily rate was negative in three water bodies. Light-saturated optimum rates were found in water bodies, with relatively high algal biomass, but photosynthetic efficiency or specific rates were higher in water bodies with low algal biomass, indicating nutrient limitation or physiological adaptation of phytoplankton. Concentrations of micronutrients and algal biomass in the reservoirs are largely altered by high flushing rate resulting from irrigation release. Underwater light climate and nutrient availability control the rate of photosynthesis and subsequent areabased primary production to a great extent. However, morpho-edephic index or euphotic algal biomass in the most productive stratum of the water column is not a good predictor of photosynthetic capacity or daily rate of primary production of these shallow tropical irrigation reservoirs.

On the size of training set and the benefit from ensemble

In this paper, the impact of the size of the training set on the benefit from ensemble, i.e. the gains obtained by employing ensemble learning paradigms, is empirically studied. Experiments on Bagged/ Boosted J4.8 decision trees with/without pruning show that enlarging the training set tends to improve the benefit from Boosting but does not significantly impact the benefit from Bagging. This phenomenon is then explained from the view of bias-variance reduction. Moreover, it is shown that even for Boosting, the benefit does not always increase consistently along with the increase of the training set size since single learners sometimes may learn relatively more from additional training data that are randomly provided than ensembles do. Furthermore, it is observed that the benefit from ensemble of unpruned decision trees is usually bigger than that from ensemble of pruned decision trees. This phenomenon is then explained from the view of error-ambiguity balance.

Institutional and structural forms of HIV-related discrimination in health care : a study set in Beijing

This paper presents key findings of a situational analysis of institutional and structural levels of HIV/AIDS-related discrimination in Beijing, China, with a focus on the area of health care. Initially slow to respond to the presence of HIV, China has altered its approach and enacted strict legislative protection for people living with HIV/AIDS (PLWHA). In order to determine whether this has altered discrimination against PLWHA, this study examined existing legislation and policy, and interviewed key informants working in health care and PLWHA. The overall findings revealed that discrimination in its many forms continued to occur in practice despite China's generally strong legislative protection, and it is the actual practice that is hindering PLWHAs' access to health services. A number of legislative and policy gaps that allow discrimination to occur in practice were also identified and discussed. The paper concludes with a call to rectify specific gaps between legislation, policy and practice. An understanding of the underlying factors that drive discrimination will also be necessary for effective strategic interventions to be developed and implemented.

The application of rough set and Kohonen network to feature selection for object extraction

Selecting a set of features which is optimal for a given task is a problem which plays an important role in a wide variety of contexts including pattern recognition, images understanding and machine learning. The paper describes an application of rough sets method to feature selection and reduction in texture images recognition. The proposed methods include continuous data discretization based on Kohonen neural network and maximum covariance, and rough set algorithms for feature selection and reduction. The experiments on trees extraction from aerial images show that the methods presented in this paper are practical and effective.

Influences of steady and cyclic die rotation on the compression of aluminium

A series of experiments are reported for compression of an aluminum cylinder with monotonic and cyclic die rotation. When the die is monotonically rotated, a higher angular velocity or a lower compression speed of the tool leads to a greater load reduction in comparison of that seen with a stationary die. The test results also show that cyclic die rotation causes a cyclic fluctuation in the load-displacement curve. During the die deceleration phase, the compression load increases until it reaches the level obtained in conventional compression with stationary dies. However, the compression load is observed to reduce to levels lower than those obtained in monotonic rotating compression tests during the die acceleration phase. The frequency of rotating direction change seems to affect the position of load peaks only, not the amplitude of the peaks.

An illustration of variable precision rough set theory : The gender classification of the European barn swallow (Hirundo rustica)

This paper introduces a new technique in the investigation of object classification and illustrates the potential use of this technique for the analysis of a range of biological data, using avian morphometric data as an example. The nascent variable precision rough sets (VPRS) model is introduced and compared with the decision tree method ID3 (through a ‘leave n out’ approach), using the same dataset of morphometric measures of European barn swallows (Hirundo rustica) and assessing the accuracy of gender classification based on these measures. The results demonstrate that the VPRS model, allied with the use of a modern method of discretization of data, is comparable with the more traditional non-parametric ID3 decision tree method. We show that, particularly in small samples, the VPRS model can improve classification and to a lesser extent prediction aspects over ID3. Furthermore, through the ‘leave n out’ approach, some indication can be produced of the relative importance of the different morphometric measures used in this problem. In this case we suggest that VPRS has advantages over ID3, as it intelligently uses more of the morphometric data available for the data classification, whilst placing less emphasis on variables with low reliability. In biological terms, the results suggest that the gender of swallows can be determined with reasonable accuracy from morphometric data and highlight the most important variables in this process. We suggest that both analysis techniques are potentially useful for the analysis of a range of different types of biological datasets, and that VPRS in particular has potential for application to a range of biological circumstances.