A design of benchmarking method for assessing performance of e-Government systems

This paper is an initial work towards developing an e-Government benchmarking model that is user-centric. To achieve the goal then, public service delivery is discussed first including the transition to online public service delivery and the need for providing public services using electronic media. Two major e-Government benchmarking methods are critically discussed and the need to develop a standardized benchmarking model that is user-centric is presented. To properly articulate user requirements in service provision, an organizational semiotic method is suggested.

Multi-modal fingerprinting for multimedia assets: optimisation of media security protection in online distribution environments

Since the advent of the internet in every day life in the 1990s, the barriers to producing, distributing and consuming multimedia data such as videos, music, ebooks, etc. have steadily been lowered for most computer users so that almost everyone with internet access can join the online communities who both produce, consume and of course also share media artefacts. Along with this trend, the violation of personal data privacy and copyright has increased with illegal file sharing being rampant across many online communities particularly for certain music genres and amongst the younger age groups. This has had a devastating effect on the traditional media distribution market; in most cases leaving the distribution companies and the content owner with huge financial losses. To prove that a copyright violation has occurred one can deploy fingerprinting mechanisms to uniquely identify the property. However this is currently based on only uni-modal approaches. In this paper we describe some of the design challenges and architectural approaches to multi-modal fingerprinting currently being examined for evaluation studies within a PhD research programme on optimisation of multi-modal fingerprinting architectures. Accordingly we outline the available modalities that are being integrated through this research programme which aims to establish the optimal architecture for multi-modal media security protection over the internet as the online distribution environment for both legal and illegal distribution of media products.

Calibration of closed loop controllers for setting impedances in force-reflecting systems

This paper discusses a new method of impedance control that has been successfully implemented on the master robot of a teleoperation system. The method involves calibrating the robot to quantify the effect of adjustable controller parameters on the impedances along its different axes. The empirical equations relating end-effector impedance to the controller's feedback gains are obtained by performing system identification tests along individual axes of the robot. With these equations, online control of end-effector stiffness and damping is possible without having to monitor joint torques or solving complex algorithms. Hard contact conditions and compliant interfaces have been effectively demonstrated on a telemanipulation test-bed using appropriate combinations of stiffness and damping settings obtained by this method.

Online modeling with tunable RBF network

In this paper, we propose a novel online modeling algorithm for nonlinear and nonstationary systems using a radial basis function (RBF) neural network with a fixed number of hidden nodes. Each of the RBF basis functions has a tunable center vector and an adjustable diagonal covariance matrix. A multi-innovation recursive least square (MRLS) algorithm is applied to update the weights of RBF online, while the modeling performance is monitored. When the modeling residual of the RBF network becomes large in spite of the weight adaptation, a node identified as insignificant is replaced with a new node, for which the tunable center vector and diagonal covariance matrix are optimized using the quantum particle swarm optimization (QPSO) algorithm. The major contribution is to combine the MRLS weight adaptation and QPSO node structure optimization in an innovative way so that it can track well the local characteristic in the nonstationary system with a very sparse model. Simulation results show that the proposed algorithm has significantly better performance than existing approaches.

Measuring student perception and actual usage of online learning management system

Online learning management systems are in use to facilitate the face to face learning process in many universities. There are many variables that shape and influence a student’s perception of an online learning management system. This study investigates whether there is a relationship between the perception of a student regarding the learning management system and their actual usage of such system. It is believed to help better understand the student usage of online learning management system. An online questionnaire was published on a course management system for a selected subject and the student participation was voluntary. Results indicate that no significant relationship between the perception students had about the learning management system and the actual use of the system. Interestingly, a significant relationship was found between having internet access away from university and the student perception about the system. Students who had internet access away from university had better perception about the learning management system even though there was no significant difference in the level of online learning management system usage between the groups.

Writing in a non-standard Greek variety: Romanized Cypriot Greek in online chat

Cypriot Greek, a variety of Greek spoken in the island of Cyprus, is relatively distinct from Standard Greek in all linguistic domains. The regional variety does not have a standard, official orthography and it is rarely used for everyday written purposes. Following technological development and the emergence of Computer-mediated Communication, a Romanized version of written CG is now widely used in online text-based communication, among teenagers and young adults (Themistocleous, C. (2008), The use of Cypriot-Greek in synchronous computer-mediated communication (PhD thesis), University of Manchester). In this study, I present the innovative ways that Greek-Cypriots use Roman characters in an effort to represent features of their spoken language in their online writings. By analysing data obtained from channel #Cyprus of Internet Relay Chat, I demonstrate how the choice of writing in CG affects the ways that Roman characters are used. I argue that this practice is not just a response to technological constrains but it actually has a wider social significance.

Online persuasion for e-commerce websites

The persuasive design of e-commerce websites has been shown to support people with online purchases. Therefore, it is important to understand how persuasive applications are used and assimilated into e-commerce website designs. This paper demonstrates how the PSD model’s persuasive features could be used to build a bridge supporting the extraction and evaluation of persuasive features in such e-commerce websites; thus practically explaining how feature implementation can enhance website persuasiveness. To support a deeper understanding of persuasive e-commerce website design, this research, using the Persuasive Systems Design (PSD) model, identifies the distinct persuasive features currently assimilated in ten successful e-commerce websites. The results revealed extensive use of persuasive features; particularly features related to dialogue support, credibility support, and primary task support; thus highlighting weaknesses in the implementation of social support features. In conclusion we suggest possible ways for enhancing persuasive feature implementation via appropriate contextual examples and explanation.

FORCe: fully online and automated artifact removal for brain-computer interfacing

A fully automated and online artifact removal method for the electroencephalogram (EEG) is developed for use in brain-computer interfacing. The method (FORCe) is based upon a novel combination of wavelet decomposition, independent component analysis, and thresholding. FORCe is able to operate on a small channel set during online EEG acquisition and does not require additional signals (e.g. electrooculogram signals). Evaluation of FORCe is performed offline on EEG recorded from 13 BCI particpants with cerebral palsy (CP) and online with three healthy participants. The method outperforms the state-of the-art automated artifact removal methods Lagged auto-mutual information clustering (LAMIC) and Fully automated statistical thresholding (FASTER), and is able to remove a wide range of artifact types including blink, electromyogram (EMG), and electrooculogram (EOG) artifacts.

Design of a unified data with business rules storage model for OLTP and OLAP systems

This paper reviews the literature concerning the practice of using Online Analytical Processing (OLAP) systems to recall information stored by Online Transactional Processing (OLTP) systems. Such a review provides a basis for discussion on the need for the information that are recalled through OLAP systems to maintain the contexts of transactions with the data captured by the respective OLTP system. The paper observes an industry trend involving the use of OLTP systems to process information into data, which are then stored in databases without the business rules that were used to process information and data stored in OLTP databases without associated business rules. This includes the necessitation of a practice, whereby, sets of business rules are used to extract, cleanse, transform and load data from disparate OLTP systems into OLAP databases to support the requirements for complex reporting and analytics. These sets of business rules are usually not the same as business rules used to capture data in particular OLTP systems. The paper argues that, differences between the business rules used to interpret these same data sets, risk gaps in semantics between information captured by OLTP systems and information recalled through OLAP systems. Literature concerning the modeling of business transaction information as facts with context as part of the modelling of information systems were reviewed to identify design trends that are contributing to the design quality of OLTP and OLAP systems. The paper then argues that; the quality of OLTP and OLAP systems design has a critical dependency on the capture of facts with associated context, encoding facts with contexts into data with business rules, storage and sourcing of data with business rules, decoding data with business rules into the facts with the context and recall of facts with associated contexts. The paper proposes UBIRQ, a design model to aid the co-design of data with business rules storage for OLTP and OLAP purposes. The proposed design model provides the opportunity for the implementation and use of multi-purpose databases, and business rules stores for OLTP and OLAP systems. Such implementations would enable the use of OLTP systems to record and store data with executions of business rules, which will allow for the use of OLTP and OLAP systems to query data with business rules used to capture the data. Thereby ensuring information recalled via OLAP systems preserves the contexts of transactions as per the data captured by the respective OLTP system.

Online orthographies

The representation in online environments of non-Roman-based script languages has proved problematic. During the initial years of Computer-mediated Communication, the American Standard Code for Information Interchange character set only supported Roman-alphabeted languages. The solution for speakers of languages written in non-Roman scripts was to employ unconventional writing systems, in an effort to represent their native language in online discourse. The first aim of this chapter is to present the different ways that internet users choose to transliterate or even transcribe their native languages online, using Roman characters. With technological development, and consequently the availability of various writing scripts online, internet users now have the option to either use Roman characters or their native script. If the latter is chosen, internet users still seem to deviate from conventional ways of writing, in this case, however, with regards to spelling. The second aim, therefore, is to bring into light recent developments, by looking at the ways that internet users manipulate orthography, to achieve their communicative purposes.

Evaluating e-learning systems: an empirical investigation on students' perception in higher education area

In search of better, traditional learning universities have expanded their ways to deliver knowledge and integrate cost effective e-learning systems. Universities’ use of information and communication technologies has grown tremendously over the last decade. To ensure efficient use of the e-learning system, the Arab Open University (AOU) in Bahrain was the first to use e-learning system there, aimed to evaluate the good and bad practices, detect errors and determine areas for further improvements in usage. This study critically evaluated the students’ perception of the elearning system in Bahrain and recommended changes to improve students’ e-learning usage. Results of the study indicated that, in general, students have favourable perceptions toward using the e-learning system. This study has shown that technology acceptance is the most variable, factor that contributes to students’ perception and satisfaction of the e-learning system.

A new adaptive multiple modelling approach for non-linear and non-stationary systems

This paper proposes a novel adaptive multiple modelling algorithm for non-linear and non-stationary systems. This simple modelling paradigm comprises K candidate sub-models which are all linear. With data available in an online fashion, the performance of all candidate sub-models are monitored based on the most recent data window, and M best sub-models are selected from the K candidates. The weight coefficients of the selected sub-model are adapted via the recursive least square (RLS) algorithm, while the coefficients of the remaining sub-models are unchanged. These M model predictions are then optimally combined to produce the multi-model output. We propose to minimise the mean square error based on a recent data window, and apply the sum to one constraint to the combination parameters, leading to a closed-form solution, so that maximal computational efficiency can be achieved. In addition, at each time step, the model prediction is chosen from either the resultant multiple model or the best sub-model, whichever is the best. Simulation results are given in comparison with some typical alternatives, including the linear RLS algorithm and a number of online non-linear approaches, in terms of modelling performance and time consumption.