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

Design of user interfaces for job shop environment

User-computer interface development has gone through rapid development in recent years. These developments, however, have not yet been fully implemented in management information system (MIS) design for job shop manufacturing situations. Most of the commercially available MISs are operationally inflexible and do not support management in report generation and decision making, particularly in job shops. This paper describes a framework in developing system user interfaces for job shop manufacturing situations to highlight how a generic information system can be made more useful to managerial decision making. Object-oriented programming technology has been used to provide flexible access to information stored by a generic MIS. Twenty interfacing programs have been developed. For illustration, only three of those interface programs relating to generation of strategic level management reports are discussed here.

Management information systems in job shops : design of interfaces

A study of management information system technology suitable for the job shop environment, highlighting deficiencies in generic software with respect to supplying users the information they actually require. To solve this problem a set of flexible interfaces was developed through the use of object-oriented programming. The methods used were simple enough to be adopted by vendors of any generic MIS application.

Human-computer interaction in ubiquitous computing environments

Purpose – The purpose of this paper is to explore characteristics of human-computer interaction when the human body and its movements become input for interaction and interface control in pervasive computing settings.

Design/methodology/approach – The paper quantifies the performance of human movement based on Fitt's Law and discusses some of the human factors and technical considerations that arise in trying to use human body movements as an input medium.

Findings – The paper finds that new interaction technologies utilising human movements may provide more flexible, naturalistic interfaces and support the ubiquitous or pervasive computing paradigm.

Practical implications – In pervasive computing environments the challenge is to create intuitive and user-friendly interfaces. Application domains that may utilize human body movements as input are surveyed here and the paper addresses issues such as culture, privacy, security and ethics raised by movement of a user's body-based interaction styles.

Originality/value – The paper describes the utilization of human body movements as input for interaction and interface control in pervasive computing settings.

Through the looking glass : immersive interfaces for participant engagement in blended e-learning environments

This chapter outlines current research profiling students and educators participating in and constructing immersive interfaces in blended e-learning settings. Multi User Virtual Environments (MUVEs) and real world settings augmented with virtual information can generate problem-solving communities where participants gain greater technical knowledge and skills through meaningful and frequent interaction. MUVEs can also generate technical innovation amongst students from diverse disciplinary backgrounds provided students are encouraged to help each other and learn together. After detailing some false assumptions about computer literacy that can stifle meaningful exploration with new technologies in contemporary education, this chapter documents an exemplar involving extensive collaboration between students from different educational backgrounds with diverse technical competencies. The success of this initiative hinges on the willingness of educators to provide a shared learning experience where technology is used to facilitate increased student communication and offers a site for invention, informed critique, industry participation, and a sense of community.

Computer-aided detection of depression from magnetic resonance images

Magnetic resonance imaging (MRI) of the brain is used to detect depression disorder. However, a large number of MRI scans needs to be analyzed for such detection. Manual segmentation of the biomarkers in MRI scans by clinical experts can become time consuming and sometimes erroneous. This paper presents a study on computer-aided detection of depression from MRI scans. These systems have not yet been identified, categorized and compared in the literature. The paper covers fully automated to semi-automated detection systems. It also presents performance comparison for the considered systems.

Immersive interfaces for art education teaching and learning in mixed reality virtual and real world environments

Selected ubiquitous technologies encourage collaborative participation between higher education students and educators within a virtual socially networked e-learning landscape. Multiple modes of teaching and learning, ranging from real world experiences, to text and digital images accessed within the Deakin Studies Online learning management system and a constructed virtual world in which the user’s creative imagination transports them to the “other side” of their computer screens is discussed in this paper. These constructed environments support interaction between communities of learners and enable multiple simultaneous participants to access graphically built 3D environments, interact with digital artifacts and various functional tools and represent themselves through avatars, to communicate with other participants and engage in collaborative art learning. A narrative interpretative research approach was used to profile the 21st century higher education student learner, to investigate the lived experience and multiple art learning perspectives documented in student visual journal entries and art educator observations to ascertain if an e-technology rich augmented learning environment resulted in the establishment of more effective e-learning communities of practice.

Immersive interfaces for art education teaching and learning in virtual and real world learning environments

Immersive interfaces for art education teaching and learning in virtual and real world learning environments

Selected ubiquitous technologies encourage collaborative participation between higher education students and educators within a virtual socially networked e-learning landscape. Multiple modes of teaching and learning, ranging from real world experiences, to text and digital images accessed within the Deakin Studies Online learning management system and a constructed virtual world in which the user's creative imagination transports them to the “other side” of their computer screens is discussed in this paper. These constructed environments support interaction between communities of learners and enable multiple simultaneous participants to access graphically built 3D environments, interact with digital artifacts and various functional tools and represent themselves through avatars, to communicate with other participants and engage in collaborative art learning. A narrative interpretative research approach was used to profile the 21st century higher education student learner, to investigate the lived experience and multiple art learning perspectives documented in student visual journal entries and art educator observations to ascertain if an e-technology rich augmented learning environment resulted in the establishment of more effective e-learning communities of practice.

An empirical comparison of classification algorithms for diagnosis of depression from brain sMRI scans

To be diagnostically effective, structural magnetic resonance imaging (sMRI) must reliably distinguish a depressed individual from a healthy individual at individual scans level. One of the tasks in the automated diagnosis of depression from brain sMRI is the classification. It determines the class to which a sample belongs (i.e., depressed/not depressed, remitted/not-remitted depression) based on the values of its features. Thus far, very limited works have been reported for identification of a suitable classification algorithm for depression detection. In this paper, different types of classification algorithms are compared for effective diagnosis of depression. Ten independent classification schemas are applied and a comparative study is carried out. The algorithms are: Naïve Bayes, Support Vector Machines (SVM) with Radial Basis Function (RBF), SVM Sigmoid, J48, Random Forest, Random Tree, Voting Feature Intervals (VFI), LogitBoost, Simple KMeans Classification Via Clustering (KMeans) and Classification Via Clustering Expectation Minimization (EM) respectively. The performances of the algorithms are determined through a set of experiments on sMRI brain scans. An experimental procedure is developed to measure the performance of the tested algorithms. A classification accuracy evaluation method was employed for evaluation and comparison of the performance of the examined classifiers.

Closed loop deep brain stimulation: an evolving technology

Deep brain stimulation is an effective and safe medical treatment for a variety of neurological and psychiatric disorders including Parkinson's disease, essential tremor, dystonia, and treatment resistant obsessive compulsive disorder. A closed loop deep brain stimulation (CLDBS) system automatically adjusts stimulation parameters by the brain response in real time. The CLDBS continues to evolve due to the advancement in the brain stimulation technologies. This paper provides a study on the existing systems developed for CLDBS. It highlights the issues associated with CLDBS systems including feedback signal recording and processing, stimulation parameters setting, control algorithm, wireless telemetry, size, and power consumption. The benefits and limitations of the existing CLDBS systems are also presented. Whilst robust clinical proof of the benefits of the technology remains to be achieved, it has the potential to offer several advantages over open loop DBS. The CLDBS can improve efficiency and efficacy of therapy, eliminate lengthy start-up period for programming and adjustment, provide a personalized treatment, and make parameters setting automatic and adaptive.

Improved processing speed: online computer-based cognitive training in older adults

In an increasingly aging population, a number of adults are concerned about declines in their cognitive abilities. Online computer-based cognitive training programs have been proposed as an accessible means by which the elderly may improve their cognitive abilities; yet, more research is needed in order to assess the efficacy of these programs. In the current study, a commercially available 21-day online computer-based cognitive training intervention was administered to 34 individuals aged between 53 and 75 years. The intervention consisted of computerized training in reaction time, inspection time, short-term memory for words, executive function, visual spatial acuity, arithmetic, visual spatial memory, visual scanning/discrimination, and n-back working memory. An active solitaire control group was also included. Participants were tested at baseline, posttraining and at three-weeks follow-up using a battery of neuropsychological outcome measures. These consisted of simple reaction time, complex reaction time, digit forwards and backwards, spatial working memory, digit symbol substitution, RAVLT, and trail making. Significant improvement in simple reaction time and choice reaction time task was found in the cognitive training group both posttraining and at three-weeks follow-up. However, no significant improvements on the other cognitive tasks were found. The training program was found to be successful in achieving transfer of trained cognitive abilities in speed of processing to similar untrained tasks. © 2012 Copyright Taylor and Francis Group, LLC.

Investigation of conformationally switchable biomolecular ligands at aqueous metallic interfaces.

An atomistic understanding was garnered through large scale molecular simulations, for the adsorption and interaction of reconfigurable hybrid biomolecule components at different aqueous metallic interfaces. This would allow for the development of future hybrid biomolecular ligands that could be used to synthesise novel and tuneable materials with unique electromagnetic properties.