The Trans-Pacific partnership: Brunei, trade, and human rights

The Prime Minister of Australia, Tony Abbott, has said that ‘Australia is Open for Business’. His trade and investment minister, Andrew Robb, has vigorously pursued bilateral trade agreements with neighbours, South Korea, Japan, China, and India — as well as the regional trade agreement, the Trans-Pacific Partnership. Such trade activity raises questions about the relationship between trade policy and human rights. If we are open for business, should we be open for business for countries engaged in human rights abuses? Should enter into trade agreements, which could have an adverse upon human rights? The Trans-Pacific Partnership highlights a range of problems with Australia’s treaty-making process. One important issue is the question of the relationship between trade and human rights.

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.

Quality of information for quality of life: Healthcare big data analytics

Big data analysis in healthcare sector is still in its early stages when comparing with that of other business sectors due to numerous reasons. Accommodating the volume, velocity and variety of healthcare data Identifying platforms that examine data from multiple sources, such as clinical records, genomic data, financial systems, and administrative systems Electronic Health Record (EHR) is a key information resource for big data analysis and is also composed of varied co-created values. Successful integration and crossing of different subfields of healthcare data such as biomedical informatics and health informatics could lead to huge improvement for the end users of the health care system, i.e. the patients.

Information Accountability of Healthcare Big Data

Huge amount of data are generated from a variety of information sources in healthcare while the data sources originate from a veracity of clinical information systems and corporate data warehouses. The data derived from the above data sources are used for analysis and trending purposes thus playing an influential role as a real time decision-making tool. The unstructured, narrative data provided by these data sources qualify as healthcare big-data and researchers argue that the application of big-data in healthcare might enable the accountability and efficiency.

The Trans-Pacific Partnership: Copyright Law, the Creative Industries, and Internet Freedom

The Trans-Pacific Partnership (TPP) is a highly secretive trade agreement being negotiated between the US and eleven Pacific Rim countries, including Australia. Having obtained a fast-track authority from the United States Congress, US President Barack Obama is keen to finalise the deal. However, he was unable to achieve a resolution of the deal at recent talks in Hawaii on the TPP. A number of chapters of the TPP will affect the creative artists, cultural industries and internet freedom — including the intellectual property chapter, the investment chapter, and the electronic commerce chapter. Legacy copyright industries have pushed for longer and stronger copyright protection throughout the Pacific Rim. In the wake of the Hawaii talks, Knowledge Ecology International leaked the latest version of the intellectual property chapter of the TPP. Jamie Love of Knowledge Ecology International commented upon the leaked text about copyright law: ‘In many sections of the text, the TPP would change global norms, restrict access to knowledge, create significant financial risks for persons using and sharing information, and, in some cases, impose new costs on persons producing new knowledge goods.’ The recent leaked text reveals a philosophical debate about the nature of intellectual property law. There are mixed messages in respect of the treatment of the public domain under copyright law. In one part of the agreement on internet service providers, there is text that says that the parties recognise the need for ‘promoting innovation and creativity,’ ‘facilitating the diffusion of information, knowledge, technology, culture, and the arts’, and ‘foster competition and open and efficient markets.’ A number of countries suggested ‘acknowledging the importance of the public domain.’ The United States and Japan opposed the recognition of the public domain in this text.

Adopting healthcare big data in Sri Lankan healthcare sector

The concept of big data has already outperformed traditional data management efforts in almost all industries. Other instances it has succeeded in obtaining promising results that provide value from large-scale integration and analysis of heterogeneous data sources for example Genomic and proteomic information. Big data analytics have become increasingly important in describing the data sets and analytical techniques in software applications that are so large and complex due to its significant advantages including better business decisions, cost reduction and delivery of new product and services [1]. In a similar context, the health community has experienced not only more complex and large data content, but also information systems that contain a large number of data sources with interrelated and interconnected data attributes. That have resulted in challenging, and highly dynamic environments leading to creation of big data with its enumerate complexities, for instant sharing of information with the expected security requirements of stakeholders. When comparing big data analysis with other sectors, the health sector is still in its early stages. Key challenges include accommodating the volume, velocity and variety of healthcare data with the current deluge of exponential growth. Given the complexity of big data, it is understood that while data storage and accessibility are technically manageable, the implementation of Information Accountability measures to healthcare big data might be a practical solution in support of information security, privacy and traceability measures. Transparency is one important measure that can demonstrate integrity which is a vital factor in the healthcare service. Clarity about performance expectations is considered to be another Information Accountability measure which is necessary to avoid data ambiguity and controversy about interpretation and finally, liability [2]. According to current studies [3] Electronic Health Records (EHR) are key information resources for big data analysis and is also composed of varied co-created values [3]. Common healthcare information originates from and is used by different actors and groups that facilitate understanding of the relationship for other data sources. Consequently, healthcare services often serve as an integrated service bundle. Although a critical requirement in healthcare services and analytics, it is difficult to find a comprehensive set of guidelines to adopt EHR to fulfil the big data analysis requirements. Therefore as a remedy, this research work focus on a systematic approach containing comprehensive guidelines with the accurate data that must be provided to apply and evaluate big data analysis until the necessary decision making requirements are fulfilled to improve quality of healthcare services. Hence, we believe that this approach would subsequently improve quality of life.

Information accountability and health big data analytics: A consent-based model

With the ever increasing amount of eHealth data available from various eHealth systems and sources, Health Big Data Analytics promises enticing benefits such as enabling the discovery of new treatment options and improved decision making. However, concerns over the privacy of information have hindered the aggregation of this information. To address these concerns, we propose the use of Information Accountability protocols to provide patients with the ability to decide how and when their data can be shared and aggregated for use in big data research. In this paper, we discuss the issues surrounding Health Big Data Analytics and propose a consent-based model to address privacy concerns to aid in achieving the promised benefits of Big Data in eHealth.

A principled experimental design approach to Big Data analysis

Big Datasets are endemic, but they are often notoriously difficult to analyse because of their size, heterogeneity, history and quality. The purpose of this paper is to open a discourse on the use of modern experimental design methods to analyse Big Data in order to answer particular questions of interest. By appealing to a range of examples, it is suggested that this perspective on Big Data modelling and analysis has wide generality and advantageous inferential and computational properties. In particular, the principled experimental design approach is shown to provide a flexible framework for analysis that, for certain classes of objectives and utility functions, delivers near equivalent answers compared with analyses of the full dataset under a controlled error rate. It can also provide a formalised method for iterative parameter estimation, model checking, identification of data gaps and evaluation of data quality. Finally, it has the potential to add value to other Big Data sampling algorithms, in particular divide-and-conquer strategies, by determining efficient sub-samples.

FlexAnalytics: A flexible data analytics framework for big data applications with I/O performance improvement

Increasingly larger scale applications are generating an unprecedented amount of data. However, the increasing gap between computation and I/O capacity on High End Computing machines makes a severe bottleneck for data analysis. Instead of moving data from its source to the output storage, in-situ analytics processes output data while simulations are running. However, in-situ data analysis incurs much more computing resource contentions with simulations. Such contentions severely damage the performance of simulation on HPE. Since different data processing strategies have different impact on performance and cost, there is a consequent need for flexibility in the location of data analytics. In this paper, we explore and analyze several potential data-analytics placement strategies along the I/O path. To find out the best strategy to reduce data movement in given situation, we propose a flexible data analytics (FlexAnalytics) framework in this paper. Based on this framework, a FlexAnalytics prototype system is developed for analytics placement. FlexAnalytics system enhances the scalability and flexibility of current I/O stack on HEC platforms and is useful for data pre-processing, runtime data analysis and visualization, as well as for large-scale data transfer. Two use cases – scientific data compression and remote visualization – have been applied in the study to verify the performance of FlexAnalytics. Experimental results demonstrate that FlexAnalytics framework increases data transition bandwidth and improves the application end-to-end transfer performance.

Incidence and mortality of female breast cancer in the Asia-Pacific region

Objective: To provide an overview of the incidence and mortality of female breast cancer for countries in the Asia-Pacific region. Methods: Statistical information about breast cancer was obtained from publicly available cancer registry and mortality databases (such as GLOBOCAN), and supplemented with data requested from individual cancer registries. Rates were directly age-standardised to the Segi World Standard population and trends were analysed using joinpoint models. Results: Breast cancer was the most common type of cancer among females in the region, accounting for 18% of all cases in 2012, and was the fourth most common cause of cancer-related deaths (9%). Although incidence rates remain much higher in New Zealand and Australia, rapid rises in recent years were observed in several Asian countries. Large increases in breast cancer mortality rates also occurred in many areas, particularly Malaysia and Thailand, in contrast to stabilising trends in Hong Kong and Singapore, while decreases have been recorded in Australia and New Zealand. Mortality trends tended to be more favourable for women aged under 50 compared to those who were 50 years or older. Conclusion: It is anticipated that incidence rates of breast cancer in developing countries throughout the Asia-Pacific region will continue to increase. Early detection and access to optimal treatment are the keys to reducing breast cancer-related mortality, but cultural and economic obstacles persist. Consequently, the challenge is to customise breast cancer control initiatives to the particular needs of each country to ensure the best possible outcomes.

Violence against children in the Asia Pacific region: the situation is becoming clearer [Editorial]

Up to the year 2000, there was very little scientific evidence in this region about the scale of child maltreatment, its effects on children, families, and society, and the resultant economic burden. Since then, many agencies large and small, government and nongovernment, and universitybased researchers have worked independently with diverse groups of people to measure violence, neglect and other childhood adversities and to understand the harmful consequences...

The burden of child maltreatment in the East Asia and Pacific region

This study estimated the health and economic burden of child maltreatment in the East Asia and Pacific region, addressing a significant gap in the current evidence base. Systematic reviews and meta-analyses were conducted to estimate the prevalence of child physical abuse, sexual abuse, emotional abuse, neglect, and witnessing parental violence. Population Attributable Fractions were calculated and Disability-Adjusted Life Years (DALYs) lost from physical and mental health outcomes and health risk behaviors attributable to child maltreatment were estimated using the most recent comparable Global Burden of Disease data. DALY losses were converted into monetary value by assuming that one DALY is equal to the sub-region’s per capita GDP. The estimated economic value of DALYs lost to violence against children as a percentage of GDP ranged from 1.24% to 3.46% across sub-regions defined by the World Health Organization. The estimated economic value of DALYs (in constant 2000 US$) lost to child maltreatment in the EAP region totaled US $151 billion, accounting for 1.88% of the region’s GDP. Updated to 2012 dollars, the estimated economic burden totaled US $194 billion. In sensitivity analysis, the aggregate costs as a percentage of GDP range from 1.36% to 2.52%. The economic burden of child maltreatment in the East Asia and Pacific region is substantial, indicating the importance of preventing and responding to child maltreatment in this region. More comprehensive research into the impact of multiple types of childhood adversity on a wider range of putative health outcomes is needed to guide policy and programs for child protection in the region, and globally.

The case for “n«all”: Why the Big Data revolution will probably happen differently in the mining sector

Big Data and predictive analytics have received significant attention from the media and academic literature throughout the past few years, and it is likely that these emerging technologies will materially impact the mining sector. This short communication argues, however, that these technological forces will probably unfold differently in the mining industry than they have in many other sectors because of significant differences in the marginal cost of data capture and storage. To this end, we offer a brief overview of what Big Data and predictive analytics are, and explain how they are bringing about changes in a broad range of sectors. We discuss the “N=all” approach to data collection being promoted by many consultants and technology vendors in the marketplace but, by considering the economic and technical realities of data acquisition and storage, we then explain why a “n « all” data collection strategy probably makes more sense for the mining sector. Finally, towards shaping the industry’s policies with regards to technology-related investments in this area, we conclude by putting forward a conceptual model for leveraging Big Data tools and analytical techniques that is a more appropriate fit for the mining sector.

Pacific Journalism Review : Twenty years on the front line of regional identity and freedom

Pacific Journalism Review has consistently, at a good standard, honoured its 1994 founding goal: to be a credible peer-reviewed journal in the Asia-Pacific region, probing developments in journalism and media, and supporting journalism education. Global, it considers new media and social movements; ‘regional’, it promotes vernacular media, human freedoms and sustainable development. Asking how it developed, the method for this article was to research the archive, noting authors, subject matter, themes. The article concludes that one answer is the journal’s collegiate approach; hundreds of academics, journalists and others, have been invited to contribute. Second has been the dedication of its one principal editor, Professor David Robie, always somehow providing resources—at Port Moresby, Suva, and now Auckland—with a consistent editorial stance. Eclectic, not partisan, it has nevertheless been vigilant over rights, such as monitoring the Fiji coups d’etat. Watching through a media lens, it follows a ‘Pacific way’, handling hard information through understanding and consensus. It has 237 subscriptions indexed to seven databases. Open source, it receives more than 1000 site visits weekly. With ‘clientele’ mostly in Australia, New Zealand and ‘Oceania’, it extends much further afield. From 1994 to 2014, 701 articles and reviews were published, now more than 24 scholarly articles each year.