137 research outputs found
Integrating new assessment strategies into mathematics classrooms: an exploratory study in Singapore primary and secondary schools
No full textEducational researchers and practitioners have in recent years paid mounting attention to the importance of new assessment (or the so-called alternative assessment) strategies in Mathematics instruction to better reflect the new desired educational goals and shifted values in education. However, research is wanting in this area, particularly in Singapore's educational setting. This project seeks to investigate the influence of using new assessment strategies in Mathematics teaching and learning on students' achievements, in both the cognitive and affective domains, in our local school settings. A quasi-experimental study with about 15-20 teachers at primary and lower secondary levels will be carried out to assess the impact of using a variety of strategies (e.g., projects, journal writing, oral presentation, performance tasks, student self-assessment, classroom observation and interview, etc.) for three school semesters on students' learning. The project will also look into issues concerning how to use new assessment strategies effectively in classrooms in local schools. For this purpose, data will be collected from classroom observation, interviews with teachers and students, and questionnaire surveys. It is hoped that the project will provide research-based evidence and practical suggestions for promoting the effective use of alternative assessment in Singapore Mathematics classrooms. <br/
High prevalence of relapse in children with Philadelphia-like acute lymphoblastic leukemia despite risk-adapted treatment
No full textSusan L Heatley, Teresa Sadras, Eva Nievergall, Chung Hoow Kok, Phuong Dang, Kelly Quek, Nicola C Venn, Sarah Moore, Tamara Law, Anthea Ng, Murray D Norris, Tamas Revesz, Michael P Osborn, Chris Fraser, Frank Alvaro, Glenn M Marshall, Luciano Dalla Pozza, Timothy P. Hughes, Charles G. Mullighan, Rosemary Sutton and Deborah L Whit
Human trafficking involving marriage and partner migration to Australia
No full textAbstract: In this report, what is known about human trafficking involving marriage and partner migration to Australia is described, drawing on primary information obtained from victim/survivor testimonies, stakeholder knowledge and expertise, and reported cases that progressed through the Australian justice system. It confirms what some stakeholders in the human trafficking area have long suspected—that marriage and partner migration have been used to facilitate the trafficking of people into Australia
Co-fuse: a new class discovery analysis tool to identify and prioritize recurrent fusion genes from RNA-sequencing data
No full textRecurrent oncogenic fusion genes play a critical role in the development of various cancers and diseases and provide, in some cases, excellent therapeutic targets. To date, analysis tools that can identify and compare recurrent fusion genes across multiple samples have not been available to researchers. To address this deficiency, we developed Co-occurrence Fusion (Co-fuse), a new and easy to use software tool that enables biologists to merge RNA-seq information, allowing them to identify recurrent fusion genes, without the need for exhaustive data processing. Notably, Co-fuse is based on pattern mining and statistical analysis which enables the identification of hidden patterns of recurrent fusion genes. In this report, we show that Co-fuse can be used to identify 2 distinct groups within a set of 49 leukemic cell lines based on their recurrent fusion genes: a multiple myeloma (MM) samples-enriched cluster and an acute myeloid leukemia (AML) samples-enriched cluster. Our experimental results further demonstrate that Co-fuse can identify known driver fusion genes (e.g., IGH-MYC, IGH-WHSC1) in MM, when compared to AML samples, indicating the potential of Co-fuse to aid the discovery of yet unknown driver fusion genes through cohort comparisons. Additionally, using a 272 primary glioma sample RNA-seq dataset, Co-fuse was able to validate recurrent fusion genes, further demonstrating the power of this analysis tool to identify recurrent fusion genes. Taken together, Co-fuse is a powerful new analysis tool that can be readily applied to large RNA-seq datasets, and may lead to the discovery of new disease subgroups and potentially new driver genes, for which, targeted therapies could be developed. The Co-fuse R source code is publicly available at https://github.com/sakrapee/co-fuse .Sakrapee Paisitkriangkrai, Kelly Quek, Eva Nievergall, Anissa Jabbour, Andrew Zannettino, Chung Hoow Ko
Structural variation in cancer genomes & the identification of personalized DNA-based cancer biomarkers
No full textStock prediction, trading simulation and options volatility prediction using FASCOM++ (fuzzy associative cortical maps architecture)
No full textFuzzy Associative Cortical Maps Architecture (FASCOM) is inspired from the cortical maps found in many biological and artificial neural systems. The cortical maps organise and represent information obtained from sensory inputs and play important roles in learning and memory processes. FASCOM uses features inspired by the structure and functions of cortical maps and is integrated a linguistic fuzzy model to perform associative learning of input-output pairs. The project undertakes to improve the architecture of FASCOM to incorporate a learning mechanism, so that the network is capable of modifying its properties on the basis of the incoming data leading to better prediction and higher accuracy.
The author aims to validate the modified architecture of FASCOM by conducting benchmarking experiments and observing the improvement in the performance of the system over other systems. For this purpose, various classical datasets for classification and regression problems were used.
The author worked on many real-life application to observe FASCOM++’s performance on real-life data. One of the applications is stock data prediction where the author used Hong Kong stock data and predicted prices using FASCOM++ and compared the results with the actual prices. The analysis of FASCOM++’s performance helps in gauging its practical use in real-life applications such as stock trading. The author simulated a simple stock trading algorithm to compare and evaluate FASCOM++’s performance against other architectures.
The author explored other areas of applications and worked on options volatility prediction which is one of the core areas of research in the financial industry. By exploiting on the online learning capabilities FASCOM++ was able to perform better than the other architectures and demonstrated its capability to be a potential architecture for real-life purpose.Bachelor of Engineering (Computer Science
Of predictive policing and punishment
No full textThis paper will start off by looking at the current predictive policing tools in the United States and China, two of the most populous and technologically advanced countries in the world. Given the reduction of legal resources and heightened security climate globally, there is a need for the police to work smarter, with the help with mathematical algorithms based on scientific studies and historical crime records. And if they predictive policing tools are able to predict crime, what is stopping us from prepunishing the would-be offenders? Perhaps the only obstacle is that predictive policing tools are at best estimates for potential crime but never the giver of full knowledge of would-be crime.Bachelor of Art
BBIPS : a blackboard based intergrated process supervision
No full textThe research effort undertaken by the author attempts to investigate the use of the blackboard architecture to realize the Integrated Process Supervision paradigm in a heterogeneous control environment that supports dynamic switching of control regimes and their corresponding techniques.Master of Engineering (SCE
Recurrent correlation associative memories
No full textThe online technique of neuro-fuzzy system has been increasing in popularity in the recent years. In actuality external factors play an important role in the time-variant dataset, changing its pattern. This change in pattern is known as drift and shift. To tackle these changes, Hebbian learning was introduced. However this learning is characterised by uni-directional learning, resulting in the instability of the model.
Hence, the BCM theory was developed to overcome the problem of Hebbian learning through the provision of Hebbian and Anti-Hebbian learning.
However, time variant data possesses both dynamic and temporal problems. The purpose of the author is to address this issue through the modification of the current recurrent fuzzy neural network. The underlying principle is to store past information to be recalled later for application in the current context.
The existing recurrent neuro-fuzzy system shows promising results that motivates the author to further the efficacy of the recurrent neuro-fuzzy system.
This report proposes a recurrent neuro-fuzzy system that uses the BCM theory of online learning with self-organizing effectiveness. In addition, rules are represented using the Takagi Sugeno Kang model to achieve a better accuracy compared to the Mamdani model which focuses on interpretability.
The performance of Recurrent SeroTSK is evaluated and compared against neuro-fuzzy systems through various time-series benchmark experiments and prediction for cancer diagnosis which is a classification data. The results show that Recurrent SeroTSK is better for time-series prediction and it works for classification data as well.Bachelor of Engineering (Computer Science
Values as resources in career counselling methods: case studies with integrative approach for clients with disabilities in Malaysia
No full textThis article responds to the Government\u27s call for counsellors to extend career guidance, which includes counselling Malaysians for enhancing human capital development with inclusiveness for attaining Vision 2020. This research paper does not study the types and degrees of severity of clients\u27 disabilities or explain the methodology for the integrative approach. It aims at creating awareness among career counsellors in: (1) understanding the integration of values for facilitating clients with disabilities in the counselling processand (2) using this insight for enabling clients to integrate into their society as productive and valued individuals. Hence, three cases of career counselling which were conducted by the author were selected to highlight the uses of values: (1) in Case I to develop objectivity, (2) in Case 2 to build therapeutic goals and (3) in Case 3 to cope with contextual barriers at work and at home. Using case studies, the relevance of the integrative approach is discussed within the context of the clients\u27 own values in the counselling process, facilitating them in integrating into society as productive contributors. However, it is cautioned that career counsellors refrain from imposing their values on clients in using the integrative approach. More dialogue from the counselling fraternity is invited to address the use of the integrative approach in improving inclusiveness at the cross-cultural level
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