A short-term production scheduling methodology for open-pit mines

A multi-resource multi-stage scheduling methodology is developed to solve short-term open-pit mine production scheduling problems as a generic multi-resource multi-stage scheduling problem. It is modelled using essential characteristics of short-term mining production operations such as drilling, sampling, blasting and excavating under the capacity constraints of mining equipment at each processing stage. Based on an extended disjunctive graph model, a shifting-bottleneck-procedure algorithm is enhanced and applied to obtain feasible short-term open-pit mine production schedules and near-optimal solutions. The proposed methodology and its solution quality are verified and validated using a real mining case study.

Integration of sentiment analysis into customer relational model : the importance of feature ontology and synonym

Online business or Electronic Commerce (EC) is getting popular among customers today, as a result large number of product reviews have been posted online by the customers. This information is very valuable not only for prospective customers to make decision on buying product but also for companies to gather information of customers’ satisfaction about their products. Opinion mining is used to capture customer reviews and separated this review into subjective expressions (sentiment word) and objective expressions (no sentiment word). This paper proposes a novel, multi-dimensional model for opinion mining, which integrates customers’ characteristics and their opinion about any products. The model captures subjective expression from product reviews and transfers to fact table before representing in multi-dimensions named as customers, products, time and location. Data warehouse techniques such as OLAP and Data Cubes were used to analyze opinionated sentences. A comprehensive way to calculate customers’ orientation on products’ features and attributes are presented in this paper.

Facial expression recognition experiments with data from television broadcasts and the world wide web

Facial expression recognition (FER) systems must ultimately work on real data in uncontrolled environments although most research studies have been conducted on lab-based data with posed or evoked facial expressions obtained in pre-set laboratory environments. It is very difficult to obtain data in real-world situations because privacy laws prevent unauthorized capture and use of video from events such as funerals, birthday parties, marriages etc. It is a challenge to acquire such data on a scale large enough for benchmarking algorithms. Although video obtained from TV or movies or postings on the World Wide Web may also contain ‘acted’ emotions and facial expressions, they may be more ‘realistic’ than lab-based data currently used by most researchers. Or is it? One way of testing this is to compare feature distributions and FER performance. This paper describes a database that has been collected from television broadcasts and the World Wide Web containing a range of environmental and facial variations expected in real conditions and uses it to answer this question. A fully automatic system that uses a fusion based approach for FER on such data is introduced for performance evaluation. Performance improvements arising from the fusion of point-based texture and geometry features, and the robustness to image scale variations are experimentally evaluated on this image and video dataset. Differences in FER performance between lab-based and realistic data, between different feature sets, and between different train-test data splits are investigated.

Analysis of interrelationships between critical waste factors in office building retrofit projects using interpretive structural modelling

The number of office building retrofit projects is increasing. These projects are characterised by processes which have a close relationship with waste generation and therefore demand a high level of waste management. In a preliminary study reported separately, we identified seven critical factors of on-site waste generation in office building retrofit projects. Through semi-structured interviews and Interpretive Structural Modelling, this research further investigated the interrelationships among these critical waste factors, to identify each factor’s level of influence on waste generation and propose effective solutions for waste minimization. “Organizational commitment” was identified as the fundamental issue for waste generation in the ISM system. Factors related to plan, design and construction processes were found to be located in the middle levels of the ISM model but still had significant impacts on the system as a whole. Based on the interview findings and ISM analysis results, some practical solutions were proposed for waste minimization in building retrofit projects: (1) reusable and adaptable fit-out design; (2) a system for as-built drawings and building information; (3) integrated planning for retrofitting work process and waste management; and (4) waste benchmarking development for retrofit projects. This research will provide a better understanding of waste issues associated with building retrofit projects and facilitate enhanced waste minimization.

Constructing a clinical decision-making framework for image-guided radiotherapy using a Bayesian Network

A decision-making framework for image-guided radiotherapy (IGRT) is being developed using a Bayesian Network (BN) to graphically describe, and probabilistically quantify, the many interacting factors that are involved in this complex clinical process. Outputs of the BN will provide decision-support for radiation therapists to assist them to make correct inferences relating to the likelihood of treatment delivery accuracy for a given image-guided set-up correction. The framework is being developed as a dynamic object-oriented BN, allowing for complex modelling with specific sub-regions, as well as representation of the sequential decision-making and belief updating associated with IGRT. A prototype graphic structure for the BN was developed by analysing IGRT practices at a local radiotherapy department and incorporating results obtained from a literature review. Clinical stakeholders reviewed the BN to validate its structure. The BN consists of a sub-network for evaluating the accuracy of IGRT practices and technology. The directed acyclic graph (DAG) contains nodes and directional arcs representing the causal relationship between the many interacting factors such as tumour site and its associated critical organs, technology and technique, and inter-user variability. The BN was extended to support on-line and off-line decision-making with respect to treatment plan compliance. Following conceptualisation of the framework, the BN will be quantified. It is anticipated that the finalised decision-making framework will provide a foundation to develop better decision-support strategies and automated correction algorithms for IGRT.

The Use of Ecological Design to Achieve Sustainable Development in Queensland, Australia

This series of technical papers arose out of the action by a private entrepreneur to initiate a process beyond mere regulatory compliance in order to achieve best environmental practice at proposed large new visitor gateways to Australia’s Great Barrier Reef. Because of the complexity of issues involved at such urbanized downstream sites, the range of topics covered is wide – though still only those considered at this juncture to be of management priority. Included on this platform is one introductory paper reviewing the history of environmental management in the field in Queensland, and three papers which seek to appreciate the main techniques by which government contributes to the solutions viz. through the national park, threatened species list, and environmental impact assessment. The history paper was designed to allow the present series to be considered in broad context as well as performance to date. The work emphasizes that much of the fertile land that must be sustained nowadays lies in the province of the private sector, and that the initiative to create any new cost-effective paradigm in ecologically-sustainable practices lies mostly in their hands. In all instances, this strategic approach to large-scale property planning is through ecological design – using field case studies around the immediate biophysical catchment of the development, with attendant focus on the associated legal catchment (the actual development site) and the social catchment (the effective land managers). The first of these has given rise to a document termed a Regional Landscape Strategy, its implementation planned in concert with an Environmental Impact Assessment of the site and with a Strategic Regional Initiative (still being tested in the field) for community engagement. The first document takes into account the aspirations of government as expressed in its broad-scale regional plans.

Towards training-free appearance-based localization : probabilistic models for whole-image descriptors

Whole image descriptors have recently been shown to be remarkably robust to perceptual change especially compared to local features. However, whole-image-based localization systems typically rely on heuristic methods for determining appropriate matching thresholds in a particular environment. These environment-specific tuning requirements and the lack of a meaningful interpretation of these arbitrary thresholds limits the general applicability of these systems. In this paper we present a Bayesian model of probability for whole-image descriptors that can be seamlessly integrated into localization systems designed for probabilistic visual input. We demonstrate this method using CAT-Graph, an appearance-based visual localization system originally designed for a FAB-MAP-style probabilistic input. We show that using whole-image descriptors as visual input extends CAT-Graph’s functionality to environments that experience a greater amount of perceptual change. We also present a method of estimating whole-image probability models in an online manner, removing the need for a prior training phase. We show that this online, automated training method can perform comparably to pre-trained, manually tuned local descriptor methods.

The Implications of Activity Based Funding for Emergency Departments : A Comprehensive Literature Review

Executive Summary Emergency Departments (EDs) locally, nationally and internationally are becoming increasingly busy. Within this context, it can be challenging to deliver a health service that is safe, of high quality and cost-effective. Whilst various models are described within the literature that aim to measure ED ‘work’ or ‘activity’, they are often not linked to a measure of costs to provide such activity. It is important for hospital and ED managers to understand and apply this link so that optimal staffing and financial resourcing can be justifiably sought. This research is timely given that Australia has moved towards a national Activity Based Funding (ABF) model for ED activity. ABF is believed to increase transparency of care and fairness (i.e. equal work receives equal pay). ABF involves a person-, performance- or activity-based payment system, and thus a move away from historical “block payment” models that do not incentivise efficiency and quality. The aim of the Statewide Workforce and Activity-Based Funding Modelling Project in Queensland Emergency Departments (SWAMPED) is to identify and describe best practice Emergency Department (ED) workforce models within the current context of ED funding that operates under an ABF model. The study is comprised of five distinct phases. This monograph (Phase 1) comprises a systematic review of the literature that was completed in June 2013. The remaining phases include a detailed survey of Queensland hospital EDs’ resource levels, activity and operational models of care, development of new resource models, development of a user-friendly modelling interface for ED mangers, and production of a final report that identifies policy implications. The anticipated deliverable outcome of this research is the development of an ABF based Emergency Workforce Modelling Tool that will enable ED managers to profile both their workforce and operational models of care. Additionally, the tool will assist with the ability to more accurately inform adequate staffing numbers required in the future, inform planning of expected expenditures and be used for standardisation and benchmarking across similar EDs. Summary of the Findings Within the remit of this review of the literature, the main findings include: 1. EDs are becoming busier and more congested Rising demand, barriers to ED throughput and transitions of care all contribute to ED congestion. In addition requests by organisational managers and the community require continued broadening of the scope of services required of the ED and further increases in demand. As the population live longer with more lifestyle diseases their propensity to require ED care continues to grow. 2. Various models of care within EDs exist Models often vary to account for site specific characteritics to suit staffing profile, ED geographical location (e.g. metropolitan or rural site), and patient demographic profile (e.g. paediatrics, older persons, ethnicity). Existing and new models implemented within EDs often depend on the target outcome requiring change. Generally this is focussed on addressing issues at the input, throughput or output areas of the ED. Even with models targeting similar demographic or illness, the structure and process elements underpinning the model can vary, which can impact on outcomes and variance to the patient and carer experience between and within EDs. Major models of care to manage throughput inefficiencies include: A. Workforce Models of Care focus on the appropriate level of staffing for a given workload to provide prompt, timely and clinically effective patient care within an emergency care setting. The studies reviewed suggest that the early involvement of senior medical decision maker and/or specialised nursing roles such as Emergency Nurse Practitioners and Clinical Initiatives Nurse, primary contact or extended scope Allied Health Practitioners can facilitate patient flow and improve key indicators such as length of stay and reducing the number of those who did not wait to be seen amongst others. B. Operational Models of Care within EDs focus on mechanisms for streaming (e.g. fast-tracking) or otherwise grouping patient care based on acuity and complexity to assist with minimising any throughput inefficiencies. While studies support the positive impact of these models in general, it appears that they are most effective when they are adequately resourced. 3. Various methods of measuring ED activity exist Measuring ED activity requires careful consideration of models of care and staffing profile. Measuring activity requires the ability to account for factors including: patient census, acuity, LOS, intensity of intervention, department skill-mix plus an adjustment for non-patient care time. 4. Gaps in the literature Continued ED growth calls for new and innovative care delivery models that are safe, clinically effective and cost effective. New roles and stand-alone service delivery models are often evaluated in isolation without considering the global and economic impact on staffing profiles. Whilst various models of accounting for and measuring health care activity exist, costing studies and cost effectiveness studies are lacking for EDs making accurate and reliable assessments of care models difficult. There is a necessity to further understand, refine and account for measures of ED complexity that define a workload upon which resources and appropriate staffing determinations can be made into the future. There is also a need for continued monitoring and comprehensive evaluation of newly implemented workforce modelling tools. This research acknowledges those gaps and aims to: • Undertake a comprehensive and integrated whole of department workforce profiling exercise relative to resources in the context of ABF. • Inform workforce requirements based on traditional quantitative markers (e.g. volume and acuity) combined with qualitative elements of ED models of care; • Develop a comprehensive and validated workforce calculation tool that can be used to better inform or at least guide workforce requirements in a more transparent manner.

Ozone-induced dissociation of conjugated lipids reveals significant reaction rate enhancements and characteristic odd-electron product ions

Ozone-induced dissociation (OzID) is an alternative ion activation method that relies on the gas phase ion-molecule reaction between a mass-selected target ion and ozone in an ion trap mass spectrometer. Herein, we evaluated the performance of OzID for both the structural elucidation and selective detection of conjugated carbon-carbon double bond motifs within lipids. The relative reactivity trends for \[M + X](+) ions (where X = Li, Na, K) formed via electrospray ionization (ESI) of conjugated versus nonconjugated fatty acid methyl esters (FAMEs) were examined using two different OzID-enabled linear ion-trap mass spectrometers. Compared with nonconjugated analogues, FAMEs derived from conjugated linoleic acids were found to react up to 200 times faster and to yield characteristic radical cations. The significantly enhanced reactivity of conjugated isomers means that OzID product ions can be observed without invoking a reaction delay in the experimental sequence (i.e., trapping of ions in the presence of ozone is not required). This possibility has been exploited to undertake neutral-loss scans on a triple quadrupole mass spectrometer targeting characteristic OzID transitions. Such analyses reveal the presence of conjugated double bonds in lipids extracted from selected foodstuffs. Finally, by benchmarking of the absolute ozone concentration inside the ion trap, second order rate constants for the gas phase reactions between unsaturated organic ions and ozone were obtained. These results demonstrate a significant influence of the adducting metal on reaction rate constants in the fashion Li > Na > K.

A rule-based hybrid method for anomaly detection in online-social-network graphs

Detecting anomalies in the online social network is a significant task as it assists in revealing the useful and interesting information about the user behavior on the network. This paper proposes a rule-based hybrid method using graph theory, Fuzzy clustering and Fuzzy rules for modeling user relationships inherent in online-social-network and for identifying anomalies. Fuzzy C-Means clustering is used to cluster the data and Fuzzy inference engine is used to generate rules based on the cluster behavior. The proposed method is able to achieve improved accuracy for identifying anomalies in comparison to existing methods.

Active security in multiparty computation over black-box groups

Most previous work on unconditionally secure multiparty computation has focused on computing over a finite field (or ring). Multiparty computation over other algebraic structures has not received much attention, but is an interesting topic whose study may provide new and improved tools for certain applications. At CRYPTO 2007, Desmedt et al introduced a construction for a passive-secure multiparty multiplication protocol for black-box groups, reducing it to a certain graph coloring problem, leaving as an open problem to achieve security against active attacks. We present the first n-party protocol for unconditionally secure multiparty computation over a black-box group which is secure under an active attack model, tolerating any adversary structure Δ satisfying the Q 3 property (in which no union of three subsets from Δ covers the whole player set), which is known to be necessary for achieving security in the active setting. Our protocol uses Maurer’s Verifiable Secret Sharing (VSS) but preserves the essential simplicity of the graph-based approach of Desmedt et al, which avoids each shareholder having to rerun the full VSS protocol after each local computation. A corollary of our result is a new active-secure protocol for general multiparty computation of an arbitrary Boolean circuit.

The past, present and future of carbon labelling for construction materials – a review

Global climate change is one of the most significant environmental issues that can harm human development. One central issue for the building and construction industry to address global climate change is the development of a credible and meaningful way to measure greenhouse gas (GHG) emissions. While Publicly Available Specification (PAS) 2050, the first international GHG standard, has been proven to be successful in standardizing the quantification process, its contribution to the management of carbon labels for construction materials is limited. With the recent publication of ISO 14067: Greenhouse gases – carbon footprint of products – requirements and guidelines for quantification and communication in May 2013, it is necessary for the building and construction industry to understand the past, present and future of the carbon labelling practices for construction materials. A systematic review shows that international GHG standards have been evolving in terms of providing additional guidance on communication and comparison, as well as less flexibility on the use of carbon labels. At the same time, carbon labelling schemes have been evolving on standardization and benchmarking. In addition, future actions are needed in the aspect of raising consumer awareness, providing benchmarking, ensuring standardization and developing simulation technologies in order for carbon labelling schemes for construction materials to provide credible, accurate and transparent information on GHG emissions.

Generating natural language texts from business process models

Process Modeling is a widely used concept for understanding, documenting and also redesigning the operations of organizations. The validation and usage of process models is however affected by the fact that only business analysts fully understand them in detail. This is in particular a problem because they are typically not domain experts. In this paper, we investigate in how far the concept of verbalization can be adapted from object-role modeling to process models. To this end, we define an approach which automatically transforms BPMN process models into natural language texts and combines different techniques from linguistics and graph decomposition in a flexible and accurate manner. The evaluation of the technique is based on a prototypical implementation and involves a test set of 53 BPMN process models showing that natural language texts can be generated in a reliable fashion.

On separation of concurrency and conflicts in acyclic process models

Recently, a new approach for structuring acyclic process models has been introduced. The algorithm is based on a transformation between the Refined Process Structure Tree (RPST) of a control flow graph and the Modular Decomposition Tree (MDT) of ordering relations. In this paper, an extension of the algorithm is presented that allows to partially structure process models in the case when a process model cannot be structured completely. We distinguish four different types of unstructuredness of process models and show that only two are possible in practice. For one of these two types of unstructuredness an algorithm is proposed that returns the maximally structured representation of a process model.

On application of structural decomposition for process model abstraction

Real world business process models may consist of hundreds of elements and have sophisticated structure. Although there are tasks where such models are valuable and appreciated, in general complexity has a negative influence on model comprehension and analysis. Thus, means for managing the complexity of process models are needed. One approach is abstraction of business process models-creation of a process model which preserves the main features of the initial elaborate process model, but leaves out insignificant details. In this paper we study the structural aspects of process model abstraction and introduce an abstraction approach based on process structure trees (PST). The developed approach assures that the abstracted process model preserves the ordering constraints of the initial model. It surpasses pattern-based process model abstraction approaches, allowing to handle graph-structured process models of arbitrary structure. We also provide an evaluation of the proposed approach.