Creating E-Learning Material to Teach Essential Vocabulary for Young EFL Learners

Increasingly, larger numbers of young learners in Japanese primary schools are learning English. This expansion of Teaching English to Young Learners (TEYL) marks a major change that will affect secondary level teaching. To both address the gap in missing daily vocabulary currently observed in Japanese school textbooks and to provide primary school English teachers with an important core vocabulary, the authors created a list of the 600 everyday words most relevant to students’ daily lives. The vocabulary selection procedure is outlined in this paper, as well as the initial stages in the development of an effective and enjoyable elearning program for teaching this vocabulary to Japanese primary school children

Pulsar Search Using Supervised Machine Learning

Pulsars are rapidly rotating neutron stars which emit a strong beam of energy through mechanisms that are not entirely clear to physicists. These very dense stars are used by astrophysicists to study many basic physical phenomena, such as the behavior of plasmas in extremely dense environments, behavior of pulsar-black hole pairs, and tests of general relativity. Many of these tasks require information to answer the scientific questions posed by physicists. In order to provide more pulsars to study, there are several large-scale pulsar surveys underway, which are generating a huge backlog of unprocessed data. Searching for pulsars is a very labor-intensive process, currently requiring skilled people to examine and interpret plots of data output by analysis programs. An automated system for screening the plots will speed up the search for pulsars by a very large factor. Research to date on using machine learning and pattern recognition has not yielded a completely satisfactory system, as systems with the desired near 100% recall have false positive rates that are higher than desired, causing more manual labor in the classification of pulsars. This work proposed to research, identify, propose and develop methods to overcome the barriers to building an improved classification system with a false positive rate of less than 1% and a recall of near 100% that will be useful for the current and next generation of large pulsar surveys. The results show that it is possible to generate classifiers that perform as needed from the available training data. While a false positive rate of 1% was not reached, recall of over 99% was achieved with a false positive rate of less than 2%. Methods of mitigating the imbalanced training and test data were explored and found to be highly effective in enhancing classification accuracy

Case Collection on Philippines (2012)

This is the second working paper in the series on Social Entrepreneurship in Asia published by the Asia Centre for Social Entrepreneurship and Philanthropy (ACSEP). ACSEP’s mission is to advance the understanding and impactful practice of social entrepreneurship and philanthropy in Asia through research and education. While Asia is rich with the practice of social entrepreneurship given the plethora of social issues and challenges facing the region, there is still catch-up to be done in the documentation of these challenges and the responses from the private, public and people sectors. Case studies provide the platform for story-telling, analysis and theory building. Each of these applications serves a function in capacity building in the social entrepreneurship space in Asia. Story-telling inspires, engenders passion, informs of possibilities, sparks action, builds communities and facilitates information exchange for change. Iterations of analysis (and synthesis) done in the classroom among practitioners, professionals and students develop critical skills of assessment and evaluation. Academics interact with the models of social entrepreneurship which surface from data drawn from practice to build theory which again informs on practice. This collection of cases on social entrepreneurship was borne out of a three-year partnership between the National University of Singapore Business School, the Ateneo de Manila University and Gawad Kalinga in a collaboration on curriculum development in entrepreneurship for sustainable development. On behalf of the partners, I want to thank Temasek Foundation for its generous support for this collaboration. It provides capability and capacity training in entrepreneurial skills for both for-profit and not-for-profit enterprises. This case collection stands as a testimony of the collaboration which started in 2010. The collaboration has two dimensions. First, it is a curriculum development programme for curriculum writers to design a cornerstone undergraduate module on entrepreneurship for sustainable development. The programme introduces a method in curriculum development which integrates multiple disciplines throughout the module. In June 2012, this module was offered in the School of Social Sciences and the John Gokongwei School of Management for the first time. This case collection was commissioned to accompany this cornerstone module on entrepreneurship for sustainable development and can be used for discussion in many of its lesson plans. Second, it is a train-the-trainer programme for Gawad Kalinga leaders to train entrepreneurs in some 2,300 communities throughout the Philippines. The programme provides process learning for Gawad Kalinga community leaders to train entrepreneurs in their own communities. 24 Gawad Kalinga trainers and leaders were trained in May 2011. As planned, this Gawad Kalinga training program has been cascaded to their communities to build capacity, targeting to train at least 100 leaders and entrepreneurs by April 2013. The theoretical framework for the curriculum development process has been documented in a video clip and can be viewed in YouTube [https://www.youtube.com/watch?v=L5S8vm_enu0]. Apart from its use in formal curriculum on entrepreneurship for sustainable development, we hope that this case collection can be inspiring reading to challenge the vision of and provoke passion in some of our aspiring entrepreneurs and social entrepreneurs. We in Asia contribute 60 percent of the world’s poor. Entrepreneurship and social entrepreneurship, besides education, are some of the keys to restore dignity, alleviate poverty and create employment. Therefore, social entrepreneurs in Asia are faced with one of the widest spectrums of unmet people needs and the correspondingly open range of entrepreneurial possibilities. I believe that one of the better ways of internalising the skill to recognise opportunities and create that value proposition is to keep looking at paradigms after paradigms, models after models. Some of these ought to be failure stories. Regrettably, there is a survivorship bias even in storytelling. Notwithstanding, the constant practice of reading such cases or stories, consciously or subconsciously, sharpens our senses of differentiating a success potential from a failure potential. It is with this hope that ACSEP publishes its Case Collection on Philippines. I also recognise that each Asian economy has its own trajectory in socio-economic development. Therefore, the corresponding solutions to its social issues are distinct to its context. This case collection is drawn from the Philippines. Over time, I hope that a beautiful mosaic will emerge from the myriad of entrepreneurial solutions in this collection and elsewhere for sustainable development

Molecular Signatures of Severe Acute Infections in Hospitalised African Children

Despite the improvement in global health over the last three decades, infectious diseases are still a major cause of morbidity and mortality globally, with the highest burden in developing countries and in children under 5 years. The heterogeneity in the clinical presentation of severely ill patients and the lack of rapid diagnostic and prognostic tools for the aetiological distinction of infecting pathogens complicates care decisions, leading to the indiscriminate use of antibiotics and consequently, increased antimicrobial resistance and mortality. Reducing childhood mortality and morbidity due to infectious diseases requires better diagnostics and prognostics, particularly in low-resource settings. Understanding the molecular processes that underlie different aetiologies and survival outcomes would enable the initiation of appropriate and timely treatment. This thesis aimed to characterise protein and transcriptomic signatures associated with (i) different microbial aetiologies of severe acute infection and (ii) an elevated risk of death in African children hospitalised with severe acute infections. An untargeted high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) approach was used to characterise the plasma proteome of children admitted to hospital with different infectious aetiologies. The resulting data was analysed using a collection of machine learning algorithms. The data was used to identify a protein signature with the highest power to discriminate between children with bacterial or viral infections. A novel protein microarray chip was then developed to validate the discovered signature in an independent cohort of hospitalised children with severe acute infections. Lastly, an RNA seq-based transcriptomics approach was used to characterise gene expression changes associated with post-admission outcomes. Using gene set enrichment and modular analysis, the correlation between gene expression and impending inpatient mortality was characterised. Key findings from this work include a validated protein signature that could classify children according to bacterial or viral aetiology and a description of the immune response to severe disease that could be correlated with an increased likelihood of death in children admitted to hospital with severe acute infection. In the proteomics analysis, a random forest-derived protein signature made up of CRP, LBP, AGT, SERPINA1, SERPINA3, PON1 and HRG was identified that could correctly classify bacterial infection from viral infection in a held-out test set with AUC of 0.84 (95%CI 0.72 – 0.95). The performance of individual proteins in the signature was assessed in an independent cohort of children using a novel protein microarray chip and AGT had the best discriminatory power of 0.7 (95%CI 0.64 – 0.75) relative to a clinically-approved CRP test whose AUC was 0.76 (95%CI 0.68 - 0.84). In addition, there was an association between the expression levels of AGT, SERPINA1, PON1 and HRG with mortality. AGT was also associated with severe acute malnutrition in children. Functional analysis of the proteomics data showed that children with bacterial infections had an enrichment of acute phase responses and neutrophil degranulation pathways while platelet degranulation was negatively associated with bacterial infections. Analysis of the transcriptomics data showed that imminent inpatient death was marked by a down regulation of CD8 T cell activation, type I interferon signalling and an over expression of the unfolded protein response and heme metabolism pathways

STATIC AND DYNAMIC ANALYSES FOR PROTECTING THE JAVA SOFTWARE EXECUTION ENVIRONMENT

In my thesis, I present three projects on which I have worked during my Ph.D. studies. All of them focus on software protection in the Java environment with static and dynamic techniques for control-flow and data-dependency analysis. More specifically, the first two works are dedicated to the problem of deserialization of untrusted data in Java. In the first, I present a defense system that was designed for protecting the Java Virtual Machine, along with the results that were obtained. In the second, I present a recent research project that aims at automatic generation of deserialization attacks, to help identifying them and increasing protection. The last discussed work concerns another branch of software protection: the authentication on short-distance channels (or the lack thereof) in Android APKs. In said work, I present a tool that was built for automatically identifying the presence of high-level authentication in Android apps. I thoroughly discuss experiments, limitations and future work for all three projects, concluding with general principles that bring these works together, and can be applied when facing related security issues in high-level software protection

The European Lake Microbiome: A Study in Complexity

While it is known that microbes play many indispensable roles in ecosystems, the relationship between microbiomes and their environment is far from being well-understood. In part, this is the case because the methods necessary for studying environmental microbiomes, such as Next- Generation Sequencing and high-dimensional Machine Learning, have been developed relatively recently. However, the complex nature of ecosystems and environmental microbiomes acts as a further barrier to progress in this field of research. This thesis develops methods and concepts used to gain insight into the ecology of micro- biomes in lakes. It is based around two metabarcoding datasets sampled from lakes in Austria and the whole of Europe, respectively, and attempts to elucidate the microbiome’s relationship to environmental parameters. To this end, a tool for GPS-based dataset enhancement and a ma- chine learning framework for measuring microbiome covariation is developed. Building on this, the latent structure of the microbiome is estimated. In the discussion, a novel theory of informa- tion transmission in complex environments is described. Taken together, the work included herein presents a thorough analysis of the European lake microbiome that takes the complexity of the study object into account. The results point to- wards parameters that act as drivers of lake microbiome structure as well as microorganisms that might act as keystone species for ecosystem functioning. Furthermore, this work might provide the basis for considerable future progress in the study of environmental microbiomes

Challenges and prospects of spatial machine learning

The main objective of this thesis is to improve the usefulness of spatial machine learning for the spatial sciences and to allow its unused potential to be exploited. To achieve this objective, this thesis addresses several important but distinct challenges which spatial machine learning is facing. These are the modeling of spatial autocorrelation and spatial heterogeneity, the selection of an appropriate model for a given spatial problem, and the understanding of complex spatial machine learning models.Das wesentliche Ziel dieser Arbeit ist es, die Nützlichkeit des räumlichen maschinellen Lernens für die Raumwissenschaften zu verbessern und es zu ermöglichen, ungenutztes Potenzial auszuschöpfen. Um dieses Ziel zu erreichen, befasst sich diese Arbeit mit mehreren wichtigen Herausforderungen, denen das räumliche maschinelle Lernen gegenübersteht. Diese sind die Modellierung von räumlicher Autokorrelation und räumlicher Heterogenität, die Auswahl eines geeigneten Modells für ein gegebenes räumliches Problem und das Verständnis komplexer räumlicher maschineller Lernmodelle

Pulmonary Large Cell Neuroendocrine Carcinoma:a unique type of lung cancer? Identification of molecular and clinical subtypes & consequences for treatment

About 1-3% of all new cases of lung cancer are large cell neuroendocrine carcinoma (LCNEC). This is an aggressive form of lung cancer; patients with metastatic disease have an average of 4-9 months to live after diagnosis. The treatment for them currently consists of chemotherapy as we also use for other forms of lung cancer. This dissertation studied similarities and differences between LCNEC and other forms of (lung) cancer. Through more clarity about these similarities and differences, it can be better predicted to which type of treatment LCNEC patients will respond well. Also, different subgroups of LCNEC are distinguished. Patients in these subgroups may also benefit from a slightly different treatment. LCNEC appears to be a form of lung cancer with unique characteristics, but also with a clear overlap with other forms of lung cancer

Human-building interaction towards a sustainable built environment: A review

Human Building Interaction (HBI), a recently introduced emerging area, can be used for various purposes, including the development of better designs, constructions, and operations, as well as the support of building managers and occupants in meeting their goals. The expanding community of HBI researchers seeks to investigate the future of HBI research and design for an interactive built environment. Building managers and owners strive for energy-efficient, sustainable, and more livable buildings to improve and become 'smart.' Diverse buildings and urban spaces are individually designed and outfitted with various systems, components, and accessories. With the advent of the Internet of Things (IoT), these devices form a network of internet-connected 'things' that generate massive amounts of data. We can collect vast volumes of data in unprecedented numbers, providing critical insights that allow buildings to care for us by learning from acquired data and adjusting to our requirements. This paper contributes to HBI by surveying various efforts to interact with buildings using IoT sensors and interconnected things to gain useful insights. Buildings, in our perspective, have distinct personalities and obligations to achieve their objectives. So, we are trying to incorporate them into reality. Considering a building to be a bio-inspired living architecture, we compare human anatomy to building anatomy to understand better the functions and operations that buildings can perform in their built environment. Thinking from this outlook allows us to investigate how sensors can help us achieve such building sustainability standards and what operations they perform to create an interactive built environment. This review paper aims to investigate the role of sensors in particular and to what extent they can provide various useful insights to building occupants and users to meet sustainability standards. We examine the most recent work on how people engage with and interact with buildings via various interfaces to achieve sustainability goals. Finally, some domain-specific challenges that limit human engagement and interactions with the built environment are discussed