Securing RFID systems from SQLIA

While SQL injection attacks have been plaguing web applications for years the threat they pose to RFID systems have only identified recently. Because the architecture of web systems and RFID systems differ considerably the prevention and detection techniques proposed for web applications are not suitable for RFID systems. In this paper we propose a system to secure RFID systems against tag based SQLIA. Our system is optimized for the architecture of RFID systems and consists of a query structure matching technique and tag data cleaning technique. The novelty of the proposed system is that it's specifically aimed at RFID systems and has the ability to detect and prevent second order injections which is a problem most current solutions haven't addressed. The preliminary evaluation of our query matching technique is very promising showing very high detection rate with minimal false positives.

Online context recognition in multisensor systems using Dynamic Time Warping

In this paper, we present our system for online context recognition of multimodal sequences acquired from multiple sensors. The system uses Dynamic Time Warping (DTW) to recognize multimodal sequences of different lengths, embedded in continuous data streams. We evaluate the performance of our system on two real world datasets: 1) accelerometer data acquired from performing two hand gestures and 2) NOKIA's benchmark dataset for context recognition. The results from both datasets demonstrate that the system can perform online context recognition efficiently and achieve high recognition accuracy.

Integrating e-simulations in teaching business information systems

Students’ early exposure to the fundamentals of business and Information and Communications Technologies (ICT), creation of a professional skill base, as well as, the gaining of practical experience in applying such knowledge and skills, are the determinants of success in their study and development as Information Systems (IS) professionals. This chapter argues that e-simulations, or computer-based and online simulations, can be effectively used to engage learners in interactive learning activities and provide them with real world practical experience in the safety of an educational setting. A research project is subsequently described. A suite of e-simulations were developed and deployed across two institutions to support teaching and learning of Information Systems. Using staff discussions and online surveys, quantitative and qualitative data were collected from the staff and students. The collected data were then analysed to evaluate and guide a sequence of curriculum and technology changes with a view to arriving at an optimum support model for students and teachers using the e-simulations. The findings of the study emphasise the usefulness of e-simulations to accommodate the learning styles of generation Y students, to stimulate their interest and creative thinking, and in meeting industry expectations of IS graduates’ ability to fulfil professional roles. Based on these insights, in its concluding remarks, the chapter outlines a conceptual framework for the inclusion of e-simulations in Information Systems curriculum development and teaching delivery.

Student evaluation of teaching : keeping in touch with reality

Student evaluation of teaching is commonplace in many universities and may be the predominant input into the performance evaluation of staff and organisational units. This article used publicly available student evaluation of teaching data to present examples of where institutional responses to evaluation processes appeared to be educationally ineffective and where the pursuit of the ‘right’ student evaluation results appears to have been mistakenly equated with the aim of improved teaching and learning. If the vast resources devoted to student evaluation of teaching are to be effective, then the data produced by student evaluation systems must lead to real and sustainable improvements in teaching quality and student learning, rather than becoming an end in itself.

A critical evaluation and comparison of two formative measures of system quality using criterion variables

Evaluating the validity of formative variables has presented ongoing challenges for researchers. In this paper we use global criterion measures to compare and critically evaluate two alternative formative measures of System Quality. One model is based on the ISO-9126 software quality standard, and the other is based on a leading information systems research model. We find that despite both models having a strong provenance, many of the items appear to be non-significant in our study. We examine the implications of this by evaluating the quality of the criterion variables we used, and the performance of PLS when evaluating formative models with a large number of items. We find that our respondents had difficulty distinguishing between global criterion variables measuring different aspects of overall System Quality. Also, because formative indicators “compete with one another” in PLS, it may be difficult to develop a set of measures which are all significant for a complex formative construct with a broad scope and a large number of items. Overall, we suggest that there is cautious evidence that both sets of measures are valid and largely equivalent, although questions still remain about the measures, the use of criterion variables, and the use of PLS for this type of model evaluation.

Implementing green business processes : the importance of functional affordances of information systems

An environmentally sustainable and thus green business process is one that delivers organizational value whilst also exerting a minimal impact on the natural environment. Recent works from the field of Information Systems (IS) have argued that information systems can contribute to the design and implementation of sustainable business processes. While prior research has investigated how information systems can be used in order to support sustainable business practices, there is still a void as to the actual changes that business processes have to undergo in order to become environmentally sustainable, and the specific role that information systems play in enabling this change. In this paper, we provide a conceptualization of environmentally sustainable business processes, and discuss the role of functional affordances of information systems in enabling both incremental and radical changes in order to make processes environmentally sustainable. Our conceptualization is based on (a) a fundamental definition of the concept of environmental sustainability, grounded in two basic components: the environmental source and sink functions of any project or activity, and (b) the concept of functional affordances, which describe the potential uses originating in the material properties of information systems in relation to their use context. In order to illustrate the application of our framework and provide a first evaluation, we analyse two examples from prior research where information systems impacted on the sustainability of business processes.

The impact of self-efficacy and perceived system efficacy on effectiveness of virtual training systems

This study developed and tested a research model which examined the impact of user perceptions of self-efficacy (SE) and virtual environment (VE) efficacy on the effectiveness of VE training systems. The model distinguishes between the perceptions of one’s own capability to perform trained tasks effectively and the perceptions of system performance, regarding the established parameters from literature. Specifically, the model posits that user perceptions will have positive effects on task performance and memory. Seventy-six adults participated in a VE in a controlled experiment, designed to empirically test the model. Each participant performed a series of object assembly tasks. The task involved selecting, rotating, releasing, inserting and manipulating 3D objects. Initially, the results of factor analysis demonstrated dimensionality of two user perception measures and produced a set of empirical validated factors underlining the VE efficacy. The results of regression analysis revealed that SE had a significant positive effect on perceived VE efficacy. No significant effects were found of perceptions on performance and memory. Furthermore, the study provided insights into the relationships between the perception measures and performance measures for assessing the efficacy of VE training systems. The study also addressed how well users learn, perform, adapt to and perceive the VE training, which provides valuable insight into the system efficacy.
Research and practical implications are presented at the end of the paper.

A generalised data analysis approach for baggage handling systems simulation

Airport baggage handling systems are a critical infrastructure component within major airports, and essential to ensure smooth luggage transfer while preventing dangerous material being loaded onto aircraft. This paper proposes a standard set of measures to assess the expected performance of a baggage handling system through discrete event simulation. These evaluation methods also have application in the study of general network systems. Results from the application of these methods reveal operational characteristics of the studied BHS, in terms of metrics such as peak throughput, in-system time and system recovery time.

Performance evaluation of multi-tier ensemble classifiers for phishing websites

This article is devoted to large multi-tier ensemble classifiers generated as ensembles of ensembles and applied to phishing websites. Our new ensemble construction is a special case of the general and productive multi-tier approach well known in information security. Many efficient multi-tier classifiers have been considered in the literature. Our new contribution is in generating new large systems as ensembles of ensembles by linking a top-tier ensemble to another middletier ensemble instead of a base classifier so that the top~ tier ensemble can generate the whole system. This automatic generation capability includes many large ensemble classifiers in two tiers simultaneously and automatically combines them into one hierarchical unified system so that one ensemble is an integral part of another one. This new construction makes it easy to set up and run such large systems. The present article concentrates on the investigation of performance of these new multi~tier ensembles for the example of detection of phishing websites. We carried out systematic experiments evaluating several essential ensemble techniques as well as more recent approaches and studying their performance as parts of multi~level ensembles with three tiers. The results presented here demonstrate that new three-tier ensemble classifiers performed better than the base classifiers and standard ensembles included in the system. This example of application to the classification of phishing websites shows that the new method of combining diverse ensemble techniques into a unified hierarchical three-tier ensemble can be applied to increase the performance of classifiers in situations where data can be processed on a large computer.

Evaluation of four supervised learning methods for benthic habitat mapping using backscatter from multi-beam sonar

An understanding of the distribution and extent of marine habitats is essential for the implementation of ecosystem-based management strategies. Historically this had been difficult in marine environments until the advancement of acoustic sensors. This study demonstrates the applicability of supervised learning techniques for benthic habitat characterization using angular backscatter response data. With the advancement of multibeam echo-sounder (MBES) technology, full coverage datasets of physical structure over vast regions of the seafloor are now achievable. Supervised learning methods typically applied to terrestrial remote sensing provide a cost-effective approach for habitat characterization in marine systems. However the comparison of the relative performance of different classifiers using acoustic data is limited. Characterization of acoustic backscatter data from MBES using four different supervised learning methods to generate benthic habitat maps is presented. Maximum Likelihood Classifier (MLC), Quick, Unbiased, Efficient Statistical Tree (QUEST), Random Forest (RF) and Support Vector Machine (SVM) were evaluated to classify angular backscatter response into habitat classes using training data acquired from underwater video observations. Results for biota classifications indicated that SVM and RF produced the highest accuracies, followed by QUEST and MLC, respectively. The most important backscatter data were from the moderate incidence angles between 30° and 50°. This study presents initial results for understanding how acoustic backscatter from MBES can be optimized for the characterization of marine benthic biological habitats. © 2012 by the authors.

Synthetic evaluation method for bridge priority ranking

In order to maintain the transportation operation, proper monitoring systems should be established on road structures, especially bridges. Since these systems need enormous investments, only a part of bridges should be equipped. Thus, the priorities of the bridges should be ranked. In this paper, a method based on two-level synthetic evaluation is proposed. First, the importance of each bridge is analyzed through the economic analysis. Six factors are considered for the bridges in a network, including construction cost, service duration, length, location importance coefficient, traffic volume, and reconstruction time. Second, the safety condition of the bridge is evaluated by using improved entropy method (IEM) which combines subjective weight with objective entropy weight. Five indices are incorporated in this step, i.e., design and construction condition, technical condition, level of overloading, hazard of wind and earthquake and environmental factors. Finally, the priorities of all the bridge in one network can be ranked and classified through a judge matrix. To demonstrate the effectiveness of the proposed method, a main highway including 16 bridges is taken as an illustrative example. The results show that the bridges can be ranked and classified quickly by using the proposed method.

Malware detection and prevention in RFID systems

The threat that malware poses to RFID systems was identified only recently. Fortunately, all currently known RFID malware is based on SQLIA. Therefore, in this chapter we propose a dual pronged, tag based SQLIA detection and prevention method optimized for RFID systems. The first technique is a SQL query matching approach that uses simple string comparisons and provides strong security against a majority of the SQLIA types possible on RFID systems. To provide security against second order SQLIA, which is a major gap in the current literature, we also propose a tag data validation and sanitization technique. The preliminary evaluation of our query matching technique is very promising, showing 100% detection rates and 0% false positives for all attacks other than second order injection.

Evaluation and comparison of type reduction algorithms from a forecast accuracy perspective

A variety of type reduction (TR) algorithms have been proposed for interval type-2 fuzzy logic systems (IT2 FLSs). The focus of existing literature is mainly on computational requirements of TR algorithm. Often researchers give more rewards to computationally less expensive TR algorithms. This paper evaluates and compares five frequently used TR algorithms from a forecasting performance perspective. Algorithms are judged based on the generalization power of IT2 FLS models developed using them. Four synthetic and real world case studies with different levels of uncertainty are considered to examine effects of TR algorithms on forecasts accuracies. It is found that Coupland-Jonh TR algorithm leads to models with a better forecasting performance. However, there is no clear relationship between the width of the type reduced set and TR algorithm.

Development and evaluation of a teaching and learning approach in cross-cultural care and antidiscrimination in university nursing students

Background:
Cross-cultural care and antidiscrimination are vital to ethical effective health systems. Nurses require quality educational preparation in cross-cultural care and antidiscrimination. Limited evidence-based research is available to guide teachers.

Objectives:
To develop, implement and evaluate an evidence-based teaching and learning approach in cross-cultural care and antidiscrimination for undergraduate nursing students.

Design:
A quantitative design using pre- and post-survey measures was used to evaluate the teaching and learning approach.

Settings:
The Bachelor of Nursing program in an Australian university.

Participants:
Academics and second year undergraduate nursing students.

Methods:
A literature review and consultation with academics informed the development of the teaching and learning approach. Thirty-three students completed a survey at pre-measures and following participation in the teaching and learning approach at post-measures about their confidence to practice cross-cultural nursing (Transcultural Self-efficacy Tool) and about their discriminatory attitudes (Quick Discrimination Index).

Results:
The literature review found that educational approaches that solely focus on culture might not be sufficient in addressing discrimination and racism. During consultation, academics emphasised the importance of situating cross-cultural nursing and antidiscrimination as social determinants of health. Therefore, cross-cultural nursing was contextualised within primary health care and emphasised care for culturally diverse communities. Survey findings supported the effectiveness of this strategy in promoting students' confidence regarding knowledge about cross-cultural nursing. There was no reported change in discriminatory attitudes. The teaching and learning approach was modified to include stronger experiential learning and role playing.

Conclusions:
Nursing education should emphasise cross-cultural nursing and antidiscrimination. The study describes an evaluated teaching and learning approach and demonstrates how evaluation research can be used to develop cross-cultural nursing education interventions.

Performance evaluation of e-government services using balance scorecard : an empirical study in Jordan

Purpose - the purpose of this paper is to emphasise on a balance between quantitative and qualitative measures, and examine the use of Balanced Scorecard to evaluate and estimate the performance of information and communication technologies (ICT) in delivering valuable e-government services through the internet. Design/methodology/approach - This study tests the hypotheses of e-government effectiveness using Balanced Scorecard technique by incorporating qualitative measures within a quantitative research methodology with data collected by means of a survey questionnaire. The survey sample of 383 stakeholders includes common customers, employees of e-government, and employees from the IT sector. The survey data were analysed to test the hypothesis in measuring e-government effectiveness from Balanced Scorecard's four dimensions: customer perspective, financial perspective, internal business process perspective, and innovation and learning perspective. Findings - The results show that the Balanced Scorecard factors fit very well with monitoring and measuring the performance of e-government in Jordan, and also in evaluating their success in IT project investments. Originality/value - This study attempts to address this gap in the literature and would benefit future studies in applying Balanced Scorecard for performance evaluation of various IT projects that are gaining huge investments from governments and organisations .