Rough set based approach to text classification

Textual document set has become an important and rapidly growing information source in the web. Text classification is one of the crucial technologies for information organisation and management. Text classification has become more and more important and attracted wide attention of researchers from different research fields. In this paper, many feature selection methods, the implement algorithms and applications of text classification are introduced firstly. However, because there are much noise in the knowledge extracted by current data-mining techniques for text classification, it leads to much uncertainty in the process of text classification which is produced from both the knowledge extraction and knowledge usage, therefore, more innovative techniques and methods are needed to improve the performance of text classification. It has been a critical step with great challenge to further improve the process of knowledge extraction and effectively utilization of the extracted knowledge. Rough Set decision making approach is proposed to use Rough Set decision techniques to more precisely classify the textual documents which are difficult to separate by the classic text classification methods. The purpose of this paper is to give an overview of existing text classification technologies, to demonstrate the Rough Set concepts and the decision making approach based on Rough Set theory for building more reliable and effective text classification framework with higher precision, to set up an innovative evaluation metric named CEI which is very effective for the performance assessment of the similar research, and to propose a promising research direction for addressing the challenging problems in text classification, text mining and other relative fields.

A web-based approach to data imputation

In this paper, we present WebPut, a prototype system that adopts a novel web-based approach to the data imputation problem. Towards this, Webput utilizes the available information in an incomplete database in conjunction with the data consistency principle. Moreover, WebPut extends effective Information Extraction (IE) methods for the purpose of formulating web search queries that are capable of effectively retrieving missing values with high accuracy. WebPut employs a confidence-based scheme that efficiently leverages our suite of data imputation queries to automatically select the most effective imputation query for each missing value. A greedy iterative algorithm is proposed to schedule the imputation order of the different missing values in a database, and in turn the issuing of their corresponding imputation queries, for improving the accuracy and efficiency of WebPut. Moreover, several optimization techniques are also proposed to reduce the cost of estimating the confidence of imputation queries at both the tuple-level and the database-level. Experiments based on several real-world data collections demonstrate not only the effectiveness of WebPut compared to existing approaches, but also the efficiency of our proposed algorithms and optimization techniques.

Exploring a biomimicry based approach and key barriers to evolving water infrastructure systems

Access to clean water is essential for human life and a critical issue facing much of modern society, especially as a result of the 21st Century triad of challenges – population growth, resource scarcity and pollution – which contribute to the rising complexity of providing adequate access to this essential resource for large parts of society. As such, there is now an increasing need for innovative solutions to source, treat and distribute water to cities across the globe. This position paper explores biomimicry – emulating natural form, function, process and systems – as an alternative and sustainable design approach to traditional water infrastructure systems. The key barriers to innovations such as biomimicry are summarised, indicating that regulatory and economic grounds are some of the major hindrances to integrating alternative design approaches in the water sector in developed countries. This paper examines some of the benefits of moving past these barriers to develop sustainable, efficient and resilient solutions that provide adequate access to water in the face of contemporary challenges.

Dry tropics water smart : a community based approach to residential outdoor water consumption

This paper discusses the Townsville City Council Dry Tropics Water Smart (DTWS) initiative, developed by TCC Integrated Sustainability Services (ISS) and Townsville Water, and informed by The University of Adelaide. The program draws on many years of experience by the TCC team to blend key community-based research approaches in order to develop this residential outdoor water conservation program. Several community pilots have been conducted to test different behaviour change strategies and messages. This paper outlines recent steps taken to develop the community trials, as guided by a combination of behaviour change theories including community-based social marketing and thematic communications methods. Some preliminary results are outlined focused on community uptake of different strategies, community perceptions of communication materials, and some insights into the effectiveness of outdoor water hardware.

A criteria based approach for evaluating innovation commercialisation

This study attempts to provide a criteria-based approach that can be used to evaluate the potential for technology transfer and commercialisation of a new technology from university research. More specifically, this study offers the critical factors for assessing marketability and feasibility of an innovation for the commercialisation and technology transfer process. The Delphi technique has been used to refine and categorise assessment criteria identified from various models and frameworks that emerged from literature. Proposed categories of criteria that are found to be important in the evaluation and assessment of a new technology for the commercialisation purpose include: Technological Readiness; Legal and Regulatory; Social Benefits and Impact; Economic and Market Factors.

Perturbing event logs to identify cost reduction opportunities: a genetic algorithm-based approach

Organisations are constantly seeking new ways to improve operational efficiencies. This research study investigates a novel way to identify potential efficiency gains in business operations by observing how they are carried out in the past and then exploring better ways of executing them by taking into account trade-offs between time, cost and resource utilisation. This paper demonstrates how they can be incorporated in the assessment of alternative process execution scenarios by making use of a cost environment. A genetic algorithm-based approach is proposed to explore and assess alternative process execution scenarios, where the objective function is represented by a comprehensive cost structure that captures different process dimensions. Experiments conducted with different variants of the genetic algorithm evaluate the approach's feasibility. The findings demonstrate that a genetic algorithm-based approach is able to make use of cost reduction as a way to identify improved execution scenarios in terms of reduced case durations and increased resource utilisation. The ultimate aim is to utilise cost-related insights gained from such improved scenarios to put forward recommendations for reducing process-related cost within organisations.

The use of a Riesz fractional differential-based approach for texture enhancement in image processing

Texture enhancement is an important component of image processing that finds extensive application in science and engineering. The quality of medical images, quantified using the imaging texture, plays a significant role in the routine diagnosis performed by medical practitioners. Most image texture enhancement is performed using classical integral order differential mask operators. Recently, first order fractional differential operators were used to enhance images. Experimentation with these methods led to the conclusion that fractional differential operators not only maintain the low frequency contour features in the smooth areas of the image, but they also nonlinearly enhance edges and textures corresponding to high frequency image components. However, whilst these methods perform well in particular cases, they are not routinely useful across all applications. To this end, we apply the second order Riesz fractional differential operator to improve upon existing approaches of texture enhancement. Compared with the classical integral order differential mask operators and other first order fractional differential operators, we find that our new algorithms provide higher signal to noise values and superior image quality.

Development of health risk-based metrics for defining a heatwave : a time series study in Brisbane, Australia

Background: This study attempted to develop health risk-based metrics for defining a heatwave in Brisbane, Australia. Methods: Poisson generalised additive model was performed to assess the impact of heatwaves on mortality and emergency hospital admissions (EHAs) in Brisbane. Results: In general, the higher the intensity and the longer the duration of a heatwave, the greater the health impacts. There was no apparent difference in EHAs risk during different periods of a warm season. However, there was a greater risk of mortality in the second half of a warm season than that in the first half. While elderly (>75 years)were particularly vulnerable to both the EHA and mortality effects of a heatwave, the risk for EHAs also significantly increased for two other age groups (0-64 years and 65-74 years) during severe heatwaves. Different patterns between cardiorespiratory mortality and EHAs were observed. Based on these findings, we propose the use of a teiered heat warning system based on the health risk of heatwave. Conclusions: Health risk-based metrics are a useful tool for the development of local heatwave definitions. thsi tool may have significant implications for the assessment of heatwave-related health consequences and development of heatwave response plans and implementation strategies.

An agent-based approach to immune modelling

This study focuses on trying to understand why the range of experience with respect to HIV infection is so diverse, especially as regards to the latency period. The challenge is to determine what assumptions can be made about the nature of the experience of antigenic invasion and diversity that can be modelled, tested and argued plausibly. To investigate this, an agent-based approach is used to extract high-level behaviour which cannot be described analytically from the set of interaction rules at the cellular level. A prototype model encompasses local variation in baseline properties contributing to the individual disease experience and is included in a network which mimics the chain of lymphatic nodes. Dealing with massively multi-agent systems requires major computational efforts. However, parallelisation methods are a natural consequence and advantage of the multi-agent approach. These are implemented using the MPI library.

A human rights-based approach to disaster displacement in the Asia-Pacific

This paper analyzes the application of rights-based approaches to disaster displacement in the Asia-Pacific region in order to assess whether the current framework is sufficient to protect the rights of internally displaced persons. It identifies that disaster-induced displacement is increasingly prevalent in the region and that economic and social conditions in many countries mean that the impact of displacement is often prolonged and more severe. The paper identifies the relevant human rights principles which apply in the context of disaster-induced displacement and examines their implementation in a number of soft-law instruments. While it identifies shortcomings in impementation and enforcement, the paper concludes that a rights-based approach could be enhanced by greater engagement with existing human rights treaties and greater implementation of soft-law principles, and that no new instrument is required.

Modality as portrayed in upper secondary school textbooks : A corpus-based approach

Tämän pro gradu -lopputyön aiheena on englannin kielen modaalisten apuverbien ns. ydinjoukko: will, would, can, could, shall, should, may, might ja must. Semantiikan kannalta nämä apuverbit ovat erityisen kompleksisia: niiden tulkinnassa on usein huomattavaa monivivahteisuutta, vaikka perinteiset kieliopit antavat ymmärtää niillä olevan kaksi tai kolme toisistaan selkeästi erillään olevaa merkitystä. Ne asettavatkin vieraan kielen oppimisympäristössä erityisiä haasteita. Viimeaikainen kehitys korpuslingvistiikan metodeissa on tuottanut entistä tarkempia kuvauksia siitä, miten modaalisia apuverbejä nykyenglannissa käytetään ja mihin suuntaan niiden kehitys on lyhyenkin ajan sisällä kulkenut. Tämän tutkielman tavoitteena on ollut verrata näiden uusien tutkimusten tuloksia siihen todellisuuteen, jonka englannin kielen lukiotasoinen oppimateriaali Suomessa opiskelijalle tarjoaa. Lähdin siitä, että opetussuunnitelman vaatima autenttisuus ja kommunikaativisuus kieltenopetuksessa tulisi näkyä tasapuolisena modaalisten apuverbien kohteluna. Alkuperäinen hypoteesini kuitenkin oli, että siinä miten modaalisuus ilmenee autenttisessa ympäristössä ja siinä miten se esitetään oppikirjoissa, on poikkeavuuksia. Lähestymistapani tähän tutkielmaan oli korpuslähtöinen. Valitsin kahdesta lukion kirjasarjasta ne kirjat, joissa modaaliset apuverbit mainittiin eksplisiittisesti. Skannasin jokaisen neljästä eri kirjasta löytyvän (kokonaisen) tekstin ja rakensin näistä aineksista pienen korpuksen. Tästä korpuksesta hain korpusanalyyseihin tarkoitetulla ohjelmalla kaikki lauseet, joissa esiintyi modaalisia apuverbejä. Tämän jälkeen analysoin jokaisen modaalisen apuverbin semanttisesti lauseyhteydessään. Tämän analyysin tuloksena pystyin rakentamaan taulukoita ja vertailemaan tuloksia uusimpien tutkimusten tuloksiin. Tämän tutkielman perusteella poikkeavuuksia on olemassa. Yleisesti ottaen modaalisten apuverbien keskinäinen frekvenssi oli oikean suuntainen: mitään apuverbiä ei ollut käytetty merkittävästi enemmän tai vähemmän kuin mitä viimeaikaisen tutkimuksen valossa olisi suotavaa. Sen sijaan apuverbien semanttisessa jakaumassa oli paikoin suuriakin eroja siinä, mitkä merkitykset oppikirjoissa painottuivat ja mitkä taas nykyenglannissa vaikuttaisivat olevan frekvensseiltään suurempia. Erityisesti can ja must erottuivat joukosta siinä, että oppikirjojen tarjoama kuva niiden käytöstä on päinvastainen kuin mitä voisi odottaa: can-verbin käyttö painottui selvästi tarkoittamaan ’kykyä’ eikä ’mahdollisuutta’, joka nykytutkimuksen valossa on sen pääasiallinen käyttötapa. Toisaalta must tarkoitti aineistossa ylikorostuneesti ’pakkoa’, kun se useimmiten nykyään tarkoittaa yhtä usein ’johtopäätöstä’ kuin ’pakkoa’. Lisäksi ’lupaa’ pyydettiin aineistossa merkillisen harvoin. Tulosten perusteella esitän, että oppikirjojen tekijät yleisellä tasolla luopuisivat kielioppikirjojen luutuneista käsityksistä ja uskaltaisivat altistaa opiskelijat koko modaalisten apuverbien merkityskirjolle.

Risk-based surveillance for avian influenza control along poultry market chains in South China: The value of social network analysis.

Over the past two decades, the poultry sector in China went through a phase of tremendous growth as well as rapid intensification and concentration. Highly pathogenic avian influenza virus (HPAIV) subtype H5N1 was first detected in 1996 in Guangdong province, South China and started spreading throughout Asia in early 2004. Since then, control of the disease in China has relied heavily on wide-scale preventive vaccination combined with movement control, quarantine and stamping out. This strategy has been successful in drastically reducing the number of outbreaks during the past 5 years. However, HPAIV H5N1 is still circulating and is regularly isolated in traditional live bird markets (LBMs) where viral infection can persist, which represent a public health hazard for people visiting them. The use of social network analysis in combination with epidemiological surveillance in South China has identified areas where the success of current strategies for HPAI control in the poultry production sector may benefit from better knowledge of poultry trading patterns and the LBM network configuration as well as their capacity for maintaining HPAIV H5N1 infection. We produced a set of LBM network maps and estimated the associated risk of HPAIV H5N1 within LBMs and along poultry market chains, providing new insights into how live poultry trade and infection are intertwined. More specifically, our study provides evidence that several biosecurity factors such as daily cage cleaning, daily cage disinfection or manure processing contribute to a reduction in HPAIV H5N1 presence in LBMs. Of significant importance is that the results of our study also show the association between social network indicators and the presence of HPAIV H5N1 in specific network configurations such as the one represented by the counties of origin of the birds traded in LBMs. This new information could be used to develop more targeted and effective control interventions.