Natural disaster risk-informed for a better public infrastructure asset planning in Indonesian Central Government

The natural disasters incident that frequently hit Indonesia are floods, severe droughts, tsunamis, earth-quakes, volcano, eruptions, landslides, windstorm and forest fires. The impact of those natural disasters are significantly severe and affecting the quality of life of the community due to the breakdown of the public as-sets as one source to deliver public services. This paper is aimed to emphasis the importance of natural disaster risk-informed in relation to public asset management in Indonesian Central Government, particularly in asset planning stage where asset decision is made as the gate into the whole public asset management processes. A Case study in the Ministry of Finance Indonesia as the central government public asset manager and in 5 (five) line ministries/governmental agencies as public asset users was used as the approach to achieved the research objective. The case study devoured three data collection techniques i.e. interviews, observations and document archival which will be analysed by a content analysis approach. The result of the study indicates that Indonesian geographical position exposing many of public infra-structure assets as a high vulnerability to natural disasters. Information on natural-disaster trends and predictions to identify and measure the risks are available, however, such information are not utilise and integrated to the process of public infrastructure asset planning as the gate to the whole public asset management processes. Therefore, in order to accommodate and incorporate this natural disaster risk-information into public asset management processes, particularly in public asset planning, a public asset performance measurements framework should be adopted and applied in the process as one sources in making decision for infrastructure asset planning. Findings from this study provide useful input for the Ministry of Finance as public asset manager, scholars and private asset management practitioners in Indonesia to establish natural disaster risks awareness in public infrastructure asset management processes.

Simplifying process model abstraction : techniques for generating model names

The increased adoption of business process management approaches, tools and practices, has led organizations to accumulate large collections of business process models. These collections can easily include hundred to thousand models, especially in the context of multinational corporations or as a result of organizational mergers and acquisitions. A concrete problem is thus how to maintain these large repositories in such a way that their complexity does not hamper their practical usefulness as a means to describe and communicate business operations. This paper proposes a technique to automatically infer suitable names for business process models and fragments thereof. This technique is useful for model abstraction scenarios, as for instance when user-specific views of a repository are required, or as part of a refactoring initiative aimed to simplify the repository’s complexity. The technique is grounded in an adaptation of the theory of meaning to the realm of business process models. We implemented the technique in a prototype tool and conducted an extensive evaluation using three process model collections from practice and a case study involving process modelers with different experience.

The confidence of speech-language pathology students regarding communicating with people with aphasia

Background Aphasia is an acquired language disorder that can present a significant barrier to patient involvement in healthcare decisions. Speech-language pathologists (SLPs) are viewed as experts in the field of communication. However, many SLP students do not receive practical training in techniques to communicate with people with aphasia (PWA) until they encounter PWA during clinical education placements. Methods This study investigated the confidence and knowledge of SLP students in communicating with PWA prior to clinical placements using a customised questionnaire. Confidence in communicating with people with aphasia was assessed using a 100-point visual analogue scale. Linear, and logistic, regressions were used to examine the association between confidence and age, as well as confidence and course type (graduate-entry masters or undergraduate), respectively. Knowledge of strategies to assist communication with PWA was examined by asking respondents to list specific strategies that could assist communication with PWA. Results SLP students were not confident with the prospect of communicating with PWA; reporting a median 29-points (inter-quartile range 17–47) on the visual analogue confidence scale. Only, four (8.2%) of respondents rated their confidence greater than 55 (out of 100). Regression analyses indicated no relationship existed between confidence and students‘ age (p = 0.31, r-squared = 0.02), or confidence and course type (p = 0.22, pseudo r-squared = 0.03). Students displayed limited knowledge about communication strategies. Thematic analysis of strategies revealed four overarching themes; Physical, Verbal Communication, Visual Information and Environmental Changes. While most students identified potential use of resources (such as images and written information), fewer students identified strategies to alter their verbal communication (such as reduced speech rate). Conclusions SLP students who had received aphasia related theoretical coursework, but not commenced clinical placements with PWA, were not confident in their ability to communicate with PWA. Students may benefit from an educational intervention or curriculum modification to incorporate practical training in effective strategies to communicate with PWA, before they encounter PWA in clinical settings. Ensuring students have confidence and knowledge of potential communication strategies to assist communication with PWA may allow them to focus their learning experiences in more specific clinical domains, such as clinical reasoning, rather than building foundation interpersonal communication skills.

Comparison of genomic DNA extraction techniques from whole blood samples : a time, cost and quality evaluation study

Genomic DNA obtained from patient whole blood samples is a key element for genomic research. Advantages and disadvantages, in terms of time-efficiency, cost-effectiveness and laboratory requirements, of procedures available to isolate nucleic acids need to be considered before choosing any particular method. These characteristics have not been fully evaluated for some laboratory techniques, such as the salting out method for DNA extraction, which has been excluded from comparison in different studies published to date. We compared three different protocols (a traditional salting out method, a modified salting out method and a commercially available kit method) to determine the most cost-effective and time-efficient method to extract DNA. We extracted genomic DNA from whole blood samples obtained from breast cancer patient volunteers and compared the results of the product obtained in terms of quantity (concentration of DNA extracted and DNA obtained per ml of blood used) and quality (260/280 ratio and polymerase chain reaction product amplification) of the obtained yield. On average, all three methods showed no statistically significant differences between the final result, but when we accounted for time and cost derived for each method, they showed very significant differences. The modified salting out method resulted in a seven- and twofold reduction in cost compared to the commercial kit and traditional salting out method, respectively and reduced time from 3 days to 1 hour compared to the traditional salting out method. This highlights a modified salting out method as a suitable choice to be used in laboratories and research centres, particularly when dealing with a large number of samples.

Size characterization of airborne SiO2 nanoparticles with on-line and off-line measurement techniques : an interlaboratory comparison study

Results of an interlaboratory comparison on size characterization of SiO2 airborne nanoparticles using on-line and off-line measurement techniques are discussed. This study was performed in the framework of Technical Working Area (TWA) 34—“Properties of Nanoparticle Populations” of the Versailles Project on Advanced Materials and Standards (VAMAS) in the project no. 3 “Techniques for characterizing size distribution of airborne nanoparticles”. Two types of nano-aerosols, consisting of (1) one population of nanoparticles with a mean diameter between 30.3 and 39.0 nm and (2) two populations of non-agglomerated nanoparticles with mean diameters between, respectively, 36.2–46.6 nm and 80.2–89.8 nm, were generated for characterization measurements. Scanning mobility particle size spectrometers (SMPS) were used for on-line measurements of size distributions of the produced nano-aerosols. Transmission electron microscopy, scanning electron microscopy, and atomic force microscopy were used as off-line measurement techniques for nanoparticles characterization. Samples were deposited on appropriate supports such as grids, filters, and mica plates by electrostatic precipitation and a filtration technique using SMPS controlled generation upstream. The results of the main size distribution parameters (mean and mode diameters), obtained from several laboratories, were compared based on metrological approaches including metrological traceability, calibration, and evaluation of the measurement uncertainty. Internationally harmonized measurement procedures for airborne SiO2 nanoparticles characterization are proposed.

Improving short utterance based I-vector speaker recognition using source and utterance-duration normalization techniques

A significant amount of speech is typically required for speaker verification system development and evaluation, especially in the presence of large intersession variability. This paper introduces a source and utterance duration normalized linear discriminant analysis (SUN-LDA) approaches to compensate session variability in short-utterance i-vector speaker verification systems. Two variations of SUN-LDA are proposed where normalization techniques are used to capture source variation from both short and full-length development i-vectors, one based upon pooling (SUN-LDA-pooled) and the other on concatenation (SUN-LDA-concat) across the duration and source-dependent session variation. Both the SUN-LDA-pooled and SUN-LDA-concat techniques are shown to provide improvement over traditional LDA on NIST 08 truncated 10sec-10sec evaluation conditions, with the highest improvement obtained with the SUN-LDA-concat technique achieving a relative improvement of 8% in EER for mis-matched conditions and over 3% for matched conditions over traditional LDA approaches.

Sequential decision fusion of multibiometrics applied to text-dependent speaker verification for controlled errors

Reliability of the performance of biometric identity verification systems remains a significant challenge. Individual biometric samples of the same person (identity class) are not identical at each presentation and performance degradation arises from intra-class variability and inter-class similarity. These limitations lead to false accepts and false rejects that are dependent. It is therefore difficult to reduce the rate of one type of error without increasing the other. The focus of this dissertation is to investigate a method based on classifier fusion techniques to better control the trade-off between the verification errors using text-dependent speaker verification as the test platform. A sequential classifier fusion architecture that integrates multi-instance and multisample fusion schemes is proposed. This fusion method enables a controlled trade-off between false alarms and false rejects. For statistically independent classifier decisions, analytical expressions for each type of verification error are derived using base classifier performances. As this assumption may not be always valid, these expressions are modified to incorporate the correlation between statistically dependent decisions from clients and impostors. The architecture is empirically evaluated by applying the proposed architecture for text dependent speaker verification using the Hidden Markov Model based digit dependent speaker models in each stage with multiple attempts for each digit utterance. The trade-off between the verification errors is controlled using the parameters, number of decision stages (instances) and the number of attempts at each decision stage (samples), fine-tuned on evaluation/tune set. The statistical validation of the derived expressions for error estimates is evaluated on test data. The performance of the sequential method is further demonstrated to depend on the order of the combination of digits (instances) and the nature of repetitive attempts (samples). The false rejection and false acceptance rates for proposed fusion are estimated using the base classifier performances, the variance in correlation between classifier decisions and the sequence of classifiers with favourable dependence selected using the 'Sequential Error Ratio' criteria. The error rates are better estimated by incorporating user-dependent (such as speaker-dependent thresholds and speaker-specific digit combinations) and class-dependent (such as clientimpostor dependent favourable combinations and class-error based threshold estimation) information. The proposed architecture is desirable in most of the speaker verification applications such as remote authentication, telephone and internet shopping applications. The tuning of parameters - the number of instances and samples - serve both the security and user convenience requirements of speaker-specific verification. The architecture investigated here is applicable to verification using other biometric modalities such as handwriting, fingerprints and key strokes.

A people-to-people matching system using graph mining techniques

A people-to-people matching system (or a match-making system) refers to a system in which users join with the objective of meeting other users with the common need. Some real-world examples of these systems are employer-employee (in job search networks), mentor-student (in university social networks), consume-to-consumer (in marketplaces) and male-female (in an online dating network). The network underlying in these systems consists of two groups of users, and the relationships between users need to be captured for developing an efficient match-making system. Most of the existing studies utilize information either about each of the users in isolation or their interaction separately, and develop recommender systems using the one form of information only. It is imperative to understand the linkages among the users in the network and use them in developing a match-making system. This study utilizes several social network analysis methods such as graph theory, small world phenomenon, centrality analysis, density analysis to gain insight into the entities and their relationships present in this network. This paper also proposes a new type of graph called “attributed bipartite graph”. By using these analyses and the proposed type of graph, an efficient hybrid recommender system is developed which generates recommendation for new users as well as shows improvement in accuracy over the baseline methods.

Timed Probabilistic Automaton : a bridge between Raven and Song Scope for automatic species recognition

Raven and Song Scope are two automated sound anal-ysis tools based on machine learning technique for en-vironmental monitoring. Many research works have been conducted upon them, however, no or rare explo-ration mentions about the performance and comparison between them. This paper investigates the comparisons from six aspects: theory, software interface, ease of use, detection targets, detection accuracy, and potential application. Through deep exploration one critical gap is identified that there is a lack of approach to detect both syllables and call structures, since Raven only aims to detect syllables while Song Scope targets call structures. Therefore, a Timed Probabilistic Automata (TPA) system is proposed which separates syllables first and clusters them into complex structures after.

Factors influencing the impact of primary and secondary prevention strategies for cervical cancer among Queensland women

Since the introduction of the National Human Papillomavirus Vaccine Program (NHPVP) in 2007, few studies have assessed women's knowledge, beliefs and attitudes towards cervical screening and human papillomavirus (HPV) vaccination in Australia. It is imperative to ascertain this, as substantial changes are anticipated to the National Cervical Screening Program (NCSP) through a process called 'the Renewal', to ensure any changes that are introduced will be acceptable and well understood by women. The objectives of this study were to describe Queensland women's current knowledge of cervical cancer/screening and HPV, their beliefs and attitudes towards Pap smears and the HPV vaccine and seek their advice on effective methods for communicating changes to the NCSP in their communities. This research was a descriptive-exploratory study that incorporated a combination of qualitative and quantitative methods within the context of the Health Belief Model (HBM). A computer-assisted telephone interview (CATI) survey of 1002 Queensland women was conducted in Phase 1 of the study. During Phase 2 of the study, 23 focus groups were conducted throughout Queensland to gather in-depth information about women's knowledge, awareness and acceptance about cervical cancer prevention strategies. This study found high levels of awareness of HPV (over 60%) and the HPV vaccine (over 86%) amongst Queensland women. However, it also identified considerable uncertainty amongst participants about perceived susceptibility to cervical cancer, especially, the link between cervical cancer, HPV and sexual activity. Women also had limited understanding of the benefit of the Pap smear as a preventative strategy, with many women thinking the main purpose of the Pap smear was for the early detection of cancer. Despite high awareness of HPV, women participating in this study also had significant knowledge deficits about their susceptibility to HPV and the severity of HPV infection. Queensland women had high levels of awareness of the HPV vaccine, which was most commonly via the media. High acceptance of the HPV vaccine was found amongst participants although awareness of the full benefits of vaccination was not evident with little acknowledgement that the quadrivalent vaccine used in the NHPVP would also prevent genital warts. Extensive barriers to having Pap smears, including physical and psychological discomfort, were identified and the most common barriers to vaccination were concerns about side effects and a lack of information upon which to make a decision about consent. Women described enablers for screening participation, such as reminder systems and practitioner characteristics, and expressed positive views towards self collected testing as an enabler, particularly for women who did not attend screening. As this study was conducted with Queensland women it may therefore not be representative of women from other parts of Australia and as participants were more likely to report they were regular screeners than Queensland women overall, these results may not be representative of women least likely to participate in cervical screening. The use of self-reported cervical screening history may also have led to over-reporting of screening status and previous abnormalities by participants. This study reveals significant gaps in Queensland women's knowledge that require effective communication strategies to address. Recommendations from this study highlight the need for increased community education to raise awareness about primary and secondary cervical cancer prevention strategies, training of cervical screening providers in sensitive examination techniques, a reduction in costs associated with screening, the exploration of alternative service models and communication plans that incorporate methods women trust and recommend for disseminating information about changes to the NCSP. This study is the first large study to explore women's perceptions of the Pap smear and barriers to screening, their knowledge about HPV and their attitudes towards the HPV vaccine in Queensland, since the introduction of the NHPVP. It highlights considerable uncertainty about many aspects of cervical cancer and primary and secondary prevention strategies available in Australia and identified many barriers to cervical screening and concerns about HPV vaccination. These knowledge gaps and barriers need to be taken into account and addressed within the context of anticipated changes to the NCSP to ensure benefits are maximised for women in future primary and secondary cervical cancer prevention strategies in the Australian context.

A process-oriented approach to supporting Off-site Manufacture in construction projects

It is well-known that the use of off-site manufacture (OSM) techniques can assist in timely completion of a construction project though the utilisation of such techniques may have other disadvantages. Currently, OSM uptake within the Australian construction industry is limited. To successfully incorporate OSM practices within a construction project, it is crucial to understand the impact of OSM adoption on the processes used during a construction project. This paper presents how a systematic process-oriented approach may be able to support OSM utilisation within a construction project. Process modelling, analysis and automation techniques which are well-known within the Business Process Management (BPM) discipline have been applied to develop a collection of construction process models that represent the end-to-end generic construction value chain. The construction value chain enables researchers to identify key activities, resources, data, and stakeholders involved in construction processes in each defined construction phase. The collection of construction process models is then used as a basis for identification of potential OSM intervention points in collaboration with domain experts from the Australian construction industry. This ensures that the resulting changes reflect the needs of various stakeholders within the construction industry and have relevance in practice. Based on the input from the domain experts, these process models are further refined and operational requirements are taken into account to develop a prototype process automation (workflow) system that can support and coordinate OSM-related process activities. The resulting workflow system also has the potential to integrate with other IT solutions used within the construction industry (e.g., BIM, Acconex). As such, the paper illustrates the role that process-oriented thinking can play in assisting OSM adoption within the industry.

Scaffolding techniques : a teacher training for cooperative learning in Thailand primary education

Using cooperative learning in classrooms promotes academic achievement, communication skills, problem-solving, social skills and student motivation. Yet it is reported that cooperative learning as a Western educational concept may be ineffective in Asian cultural contexts. The study aims to investigate the utilisation of scaffolding techniques for cooperative learning in Thailand primary mathematics classes. A teacher training program was designed to foster Thai primary school teachers’ cooperative learning implementation. Two teachers participated in this experimental program for one and a half weeks and then implemented cooperative learning strategies in their mathematics classes for six weeks. The data collected from teacher interviews and classroom observations indicates that the difficulty or failure of implementing cooperative learning in Thailand education may not be directly derived from cultural differences. Instead, it does indicate that Thai culture can be constructively merged with cooperative learning through a teacher training program and practices of scaffolding techniques.

Frontier Techniques for Measuring and Estimating Airport Efficiency : An Empirical Review with Practical Guidelines for Analysis and Future Research

Airport efficiency is important because it has a direct impact on customer safety and satisfaction and therefore the financial performance and sustainability of airports, airlines, and affiliated service providers. This is especially so in a world characterized by an increasing volume of both domestic and international air travel, price and other forms of competition between rival airports, airport hubs and airlines, and rapid and sometimes unexpected changes in airline routes and carriers. It also reflects expansion in the number of airports handling regional, national, and international traffic and the growth of complementary airport facilities including industrial, commercial, and retail premises. This has fostered a steadily increasing volume of research aimed at modeling and providing best-practice measures and estimates of airport efficiency using mathematical and econometric frontiers. The purpose of this chapter is to review these various methods as they apply to airports throughout the world. Apart from discussing the strengths and weaknesses of the different approaches and their key findings, the paper also examines the steps faced by researchers as they move through the modeling process in defining airport inputs and outputs and the purported efficiency drivers. Accordingly, the chapter provides guidance to those conducting empirical research on airport efficiency and serves as an aid for aviation regulators and airport operators among others interpreting airport efficiency research outcomes.

Training-free probability models for whole-image based place recognition

Whole-image descriptors such as GIST have been used successfully for persistent place recognition when combined with temporal filtering or sequential filtering techniques. However, whole-image descriptor localization systems often apply a heuristic rather than a probabilistic approach to place recognition, requiring substantial environmental-specific tuning prior to deployment. In this paper we present a novel online solution that uses statistical approaches to calculate place recognition likelihoods for whole-image descriptors, without requiring either environmental tuning or pre-training. Using a real world benchmark dataset, we show that this method creates distributions appropriate to a specific environment in an online manner. Our method performs comparably to FAB-MAP in raw place recognition performance, and integrates into a state of the art probabilistic mapping system to provide superior performance to whole-image methods that are not based on true probability distributions. The method provides a principled means for combining the powerful change-invariant properties of whole-image descriptors with probabilistic back-end mapping systems without the need for prior training or system tuning.

Response of a buried tunnel to surface blast using different numerical techniques

This paper presents a comparative study on the response of a buried tunnel to surface blast using the arbitrary Lagrangian-Eulerian (ALE) and smooth particle hydrodynamics (SPH) techniques. Since explosive tests with real physical models are extremely risky and expensive, the results of a centrifuge test were used to validate the numerical techniques. The numerical study shows that the ALE predictions were faster and closer to the experimental results than those from the SPH simulations which over predicted the strains. The findings of this research demonstrate the superiority of the ALE modelling techniques for the present study. They also provide a comprehensive understanding of the preferred ALE modelling techniques which can be used to investigate the surface blast response of underground tunnels.