Robust Web content extraction

We present an empirical evaluation and comparison of two content extraction methods in HTML: absolute XPath expressions and relative XPath expressions. We argue that the relative XPath expressions, although not widely used, should be used in preference to absolute XPath expressions in extracting content from human-created Web documents. Evaluation of robustness covers four thousand queries executed on several hundred webpages. We show that in referencing parts of real world dynamic HTML documents, relative XPath expressions are on average significantly more robust than absolute XPath ones.

A Web-based system enabling the integration, analysis, and 3D sub-surface visualization of groundwater monitoring data and geological models

The 3D Water Chemistry Atlas is an intuitive, open source, Web-based system that enables the three-dimensional (3D) sub-surface visualization of ground water monitoring data, overlaid on the local geological model (formation and aquifer strata). This paper firstly describes the results of evaluating existing virtual globe technologies, which led to the decision to use the Cesium open source WebGL Virtual Globe and Map Engine as the underlying platform. Next it describes the backend database and search, filtering, browse and analysis tools that were developed to enable users to interactively explore the groundwater monitoring data and interpret it spatially and temporally relative to the local geological formations and aquifers via the Cesium interface. The result is an integrated 3D visualization system that enables environmental managers and regulators to assess groundwater conditions, identify inconsistencies in the data, manage impacts and risks and make more informed decisions about coal seam gas extraction, waste water extraction, and water reuse.

Mining process risks and resource profiles

This research contributes novel techniques for identifying and evaluating business process risks and analysing human resource behaviour. The developed techniques use predefined indicators to identify process risks in individual process instances, evaluate overall process risk, predict process outcomes and analyse human resource behaviour based on the analysis of information about process executions recorded in event logs by information systems. The results of this research can help managers to more accurately evaluate the risk exposure of their business processes, to more objectively evaluate the performance of their employees, and to identify opportunities for improvement of resource and process performance.

Web crippling tests of rivet fastened rectangular hollow flange channel beams under two flange load cases

Recent research on hollow flange beams has led to the development of an innovative rectangular hollow flange channel beam (RHFCB) for use in floor systems. The new RHFCB is a mono-symmetric structural section made by intermittently rivet fastening two torsionally rigid closed rectangular hollow flanges to a web plate element, which allows section optimisation by selecting appropriate combinations of web and flange widths and thicknesses. However, the current design rules for cold-formed steel sections are not directly applicable to rivet fastened RHFCBs. To date, no investigation has been conducted on their web crippling behaviour and strengths. Hence an experimental study was conducted to investigate the web crippling behaviour and capacities of rivet fastened RHFCBs under End Two Flange (ETF) and Interior Two Flange (ITF) load cases. It showed that RHFCBs failed by web crippling, flange crushing and their combinations. Comparison of ultimate web crippling capacities with the predictions from the design equations in AS/NZS 4600 and AISI S100 showed that the current design equations are unconservative for rivet fastened RHFCB sections under ETF and ITF load cases. Hence new equations were proposed to determine the web crippling capacities of rivet fastened RHFCBs. These equations can also be used to predict the capacities of RHFCBs subject to combined web crippling and flange crushing conservatively. However, new capacity equations were proposed in the case of flange crushing failures that occurred in thinner flanges with smaller bearing lengths. This paper presents the details of this web crippling experimental study of RHFCB sections and the results.

Frequent (flier) frustration and the dark side of word‐of‐web: exploring online dysfunctional behavior in online feedback forums

Purpose Following the perspective of frustration theory customer frustration incidents lead to frustration behavior such as protest (negative word‐of‐mouth). On the internet customers can express their emotions verbally and non‐verbally in numerous web‐based review platforms. The purpose of this study is to investigate online dysfunctional customer behavior, in particular negative “word‐of‐web” (WOW) in online feedback forums, among customers who participate in frequent‐flier programs in the airline industry. Design/methodology/approach The study employs a variation of the critical incident technique (CIT) referred to as the critical internet feedback technique (CIFT). Qualitative data of customer reviews of 13 different frequent‐flier programs posted on the internet were collected and analyzed with regard to frustration incidents, verbal and non‐verbal emotional effects and types of dysfunctional word‐of‐web customer behavior. The sample includes 141 negative customer reviews based on non‐recommendations and low program ratings. Findings Problems with loyalty programs evoke negative emotions that are expressed in a spectrum of verbal and non‐verbal negative electronic word‐of‐mouth. Online dysfunctional behavior can vary widely from low ratings and non‐recommendations to voicing switching intentions to even stronger forms such as manipulation of others and revenge intentions. Research limitations/implications Results have to be viewed carefully due to methodological challenges with regard to the measurement of emotions, in particular the accuracy of self‐report techniques and the quality of online data. Generalization of the results is limited because the study utilizes data from only one industry. Further research is needed with regard to the exact differentiation of frustration from related constructs. In addition, large‐scale quantitative studies are necessary to specify and test the relationships between frustration incidents and subsequent dysfunctional customer behavior expressed in negative word‐of‐web. Practical implications The study yields important implications for the monitoring of the perceived quality of loyalty programs. Management can obtain valuable information about program‐related and/or relationship‐related frustration incidents that lead to online dysfunctional customer behavior. A proactive response strategy should be developed to deal with severe cases, such as sabotage plans. Originality/value This study contributes to knowledge regarding the limited research of online dysfunctional customer behavior as well as frustration incidents of loyalty programs. Also, the article presents a theoretical “customer frustration‐defection” framework that describes different levels of online dysfunctional behavior in relation to the level of frustration sensation that customers have experienced. The framework extends the existing perspective of the “customer satisfaction‐loyalty” framework developed by Heskett et al.

Aspect-based opinion mining from product reviews using conditional random fields

Product reviews are the foremost source of information for customers and manufacturers to help them make appropriate purchasing and production decisions. Natural language data is typically very sparse; the most common words are those that do not carry a lot of semantic content, and occurrences of any particular content-bearing word are rare, while co-occurrences of these words are rarer. Mining product aspects, along with corresponding opinions, is essential for Aspect-Based Opinion Mining (ABOM) as a result of the e-commerce revolution. Therefore, the need for automatic mining of reviews has reached a peak. In this work, we deal with ABOM as sequence labelling problem and propose a supervised extraction method to identify product aspects and corresponding opinions. We use Conditional Random Fields (CRFs) to solve the extraction problem and propose a feature function to enhance accuracy. The proposed method is evaluated using two different datasets. We also evaluate the effectiveness of feature function and the optimisation through multiple experiments.

Translating road safety research on night-time visibility to the context of mining

In recent years a significant amount of research has been undertaken in collision avoidance and personnel location technology in order to reduce the number of incidents involving pedestrians and mobile plant equipment which are a high risk in underground coal mines. Improving the visibility of pedestrians to drivers would potentially reduce the likelihood of these incidents. In the road safety context, a variety of approaches have been used to make pedestrians more conspicuous to drivers at night (including vehicle and roadway lighting technologies and night vision enhancement systems). However, emerging research from our group and others has demonstrated that clothing incorporating retroreflective markers on the movable joints as well as the torso can provide highly significant improvements in pedestrian visibility in reduced illumination. Importantly, retroreflective markers are most effective when positioned on the moveable joints creating a sensation of “biological motion”. Based only on the motion of points on the moveable joints of an otherwise invisible body, observers can quickly recognize a walking human form, and even correctly judge characteristics such as gender and weight. An important and as yet unexplored question is whether the benefits of these retroreflective clothing configurations translate to the context of mining where workers are operating under low light conditions. Given that the benefits of biomotion clothing are effective for both young and older drivers, as well as those with various eye conditions common in those >50 years reinforces their potential application in the mining industry which employs many workers in this age bracket. This paper will summarise the visibility benefits of retroreflective markers in a biomotion configuration for the mining industry, highlighting that this form of clothing has the potential to be an affordable and convenient way to provide a sizeable safety benefit. It does not involve modifications to vehicles, drivers, or infrastructure. Instead, adding biomotion markings to standard retroreflective vests can enhance the night-time conspicuity of mining workers by capitalising on perceptual capabilities that have already been well documented.

Experimental studies of lipped channel beams subject to web crippling under ETF and ITF load cases

Lipped channel beams (LCBs) are commonly used as floor joists and bearers in buildings. However, they are subjected to specific failure modes such as web crippling. Despite considerable web crippling research, recent studies [1-6] have shown that the current web crippling design rules are unable to predict the test capacities under ETF and ITF load cases. In many instances, the predictions by the available design standards such as AISI S100, AS/NZS 4600 and Eurocode 3 Part 1-3 [7-9] are inconsistent. Hence thirty-six tests were conducted to assess the web crippling behaviour and strengths of LCBs under two flange load cases. Experimental web crippling capacities were then compared with the predictions from the current design rules. These comparisons showed that AS/NZS 4600 and AISI S100 design equations are very unconservative for LCB sections under ETF load case and are conservative for ITF load case. Hence improved equations were proposed to determine the web crippling capacities of LCBs. Suitable design rules were also developed using the direct strength method. This paper presents the details of this study and the results including improved design rules.

New graph-based algorithms to efficiently solve large scale open pit mining optimisation problems

In the mining optimisation literature, most researchers focused on two strategic-level and tactical-level open-pit mine optimisation problems, which are respectively termed ultimate pit limit (UPIT) or constrained pit limit (CPIT). However, many researchers indicate that the substantial numbers of variables and constraints in real-world instances (e.g., with 50-1000 thousand blocks) make the CPIT’s mixed integer programming (MIP) model intractable for use. Thus, it becomes a considerable challenge to solve the large scale CPIT instances without relying on exact MIP optimiser as well as the complicated MIP relaxation/decomposition methods. To take this challenge, two new graph-based algorithms based on network flow graph and conjunctive graph theory are developed by taking advantage of problem properties. The performance of our proposed algorithms is validated by testing recent large scale benchmark UPIT and CPIT instances’ datasets of MineLib in 2013. In comparison to best known results from MineLib, it is shown that the proposed algorithms outperform other CPIT solution approaches existing in the literature. The proposed graph-based algorithms leads to a more competent mine scheduling optimisation expert system because the third-party MIP optimiser is no longer indispensable and random neighbourhood search is not necessary.

The hidden injuries of mining: Frontier cultural conflict

This chapter addresses a topic of growing significance to green criminology - the harmful effects of mining on local communities and the environment (Ruggiero and South 2013; White 2013a). While mining has long been recognised as an agent of environmental harm (White 2013a), less recognised is that its global expansion also has harmful effects on localised patterns of violence, work and community life in mining towns. Australia provides an excellent case study for exploring some of these mining impacts.

A systematic review of axillary web syndrome (AWS)

Introduction Axillary web syndrome (AWS) can result in early post-operative and long-term difficulties following lymphadenectomy for cancer and should be recognised by clinicians. This systematic review was conducted to synthesise information on AWS clinical presentation and diagnosis, frequency, natural progression, grading, pathoaetiology, risk factors, symptoms, interventions and outcomes. Methods Electronic searches were conducted using Cochrane, Pubmed, MEDLINE, CINAHL, EMBASE, AMED, PEDro and Google Scholar until June 2013. The methodological quality of included studies was determined using the Downs and Black checklist. Narrative synthesis of results was undertaken. Results Thirty-seven studies with methodological quality scores ranging from 11 to 26 on a 28-point scale were included. AWS diagnosis relies on inspection and palpation; grading has not been validated. AWS frequency was reported in up to 85.4 % of patients. Biopsies identified venous and lymphatic pathoaetiology with five studies suggesting lymphatic involvement. Twenty-one studies reported AWS occurrence within eight post-operative weeks, but late occurrence of greater than 3 months is possible. Pain was commonly reported with shoulder abduction more restricted than flexion. AWS symptoms usually resolve within 3 months but may persist. Risk factors may include extensiveness of surgery, younger age, lower body mass index, ethnicity and healing complications. Low-quality studies suggest that conservative approaches including analgesics, non-steroidal anti-inflammatory drugs and/or physiotherapy may be safe and effective for early symptom reduction. Conclusions AWS appears common. Current evidence for the treatment of AWS is insufficient to provide clear guidance for clinical practice. Implications for Cancer Survivors Cancer survivors should be informed about AWS. Further investigation is needed into pathoaetiology, long-term outcomes and to determine effective treatment using standardised outcomes.

Australian patients using a cardiac-diabetes web-based intervention program: Contributions to person-centered clinical practice

Rationale, aims and objectives: Patients with both cardiac disease and diabetes have poorer health outcomes than patients with only one chronic condition. While evidence indicates that internet based interventions may improve health outcomes for patients with a chronic disease, there is no literature on internet programs specific to cardiac patients with comorbid diabetes. Therefore this study aimed to develop a specific web-based program, then to explore patients’ perspectives on the usefulness of a new program. Methods: The interpretive approach using semi-structured interviews on a purposive sample of eligible patients with type 2 diabetes and a cardiac condition in a metropolitan hospital in Brisbane, Australia. Thematic analysis was undertaken to describe the perceived usefulness of a newly developed Heart2heart webpage. Results: Themes identified included confidence in hospital health professionals and reliance on doctors to manage conditions. Patients found the webpage useful for managing their conditions at home. Conclusions: The new Heart2heart webpage provided a positive and useful resource. Further research on to determine the potential influence of this resource on patients’ self-management behaviours is paramount. Implications for practice include using multimedia strategies for providing information to patients’ comorbidities of cardiac disease and type 2 diabetes, and further development on enhancement of such strategies

A process mining-based investigation of adverse events in care processes

This paper proposes the Clinical Pathway Analysis Method (CPAM) approach that enables the extraction of valuable organisational and medical information on past clinical pathway executions from the event logs of healthcare information systems. The method deals with the complexity of real-world clinical pathways by introducing a perspective-based segmentation of the date-stamped event log. CPAM enables the clinical pathway analyst to effectively and efficiently acquire a profound insight into the clinical pathways. By comparing the specific medical conditions of patients with the factors used for characterising the different clinical pathway variants, the medical expert can identify the best therapeutic option. Process mining-based analytics enables the acquisition of valuable insights into clinical pathways, based on the complete audit traces of previous clinical pathway instances. Additionally, the methodology is suited to assess guideline compliance and analyse adverse events. Finally, the methodology provides support for eliciting tacit knowledge and providing treatment selection assistance.

A data mining approach for fault diagnosis: An application of anomaly detection algorithm

Rolling-element bearing failures are the most frequent problems in rotating machinery, which can be catastrophic and cause major downtime. Hence, providing advance failure warning and precise fault detection in such components are pivotal and cost-effective. The vast majority of past research has focused on signal processing and spectral analysis for fault diagnostics in rotating components. In this study, a data mining approach using a machine learning technique called anomaly detection (AD) is presented. This method employs classification techniques to discriminate between defect examples. Two features, kurtosis and Non-Gaussianity Score (NGS), are extracted to develop anomaly detection algorithms. The performance of the developed algorithms was examined through real data from a test to failure bearing. Finally, the application of anomaly detection is compared with one of the popular methods called Support Vector Machine (SVM) to investigate the sensitivity and accuracy of this approach and its ability to detect the anomalies in early stages.

Doing Digital Composition on the Social Web: Knowledge Processes in Literacy Learning

The power to influence others in ever-expanding social networks in the new knowledge economy is tied to capabilities with digital media production. This chapter draws on research in elementary classrooms to examine the repertoires of cross-disciplinary knowledge that literacy learners need to produce innovative digital media via the “social web”. It focuses on the knowledge processes that occurred when elementary students engaged in multimodal text production with new digital media. It draws on Kalantzis and Cope’s (2008) heuristic for theorizing “Knowledge Processes” in the Learning by Design approach to pedagogy. Learners demonstrate eight “Knowledge Processes” across different subject domains, skills areas, and sensibilities. Drawing data from media-based lessons across several classroom and schools, this chapter examines what kinds of knowledge students utilize when they produce digital, multimodal texts in the classroom. The Learning by Design framework is used as an analytic tool to theorize how students learn when they engaged in a specific domain of learning – digital media production.