title: Using swarm optimization to enhance autoencoder’s images

authors: Doaud, Maisa

subjects: computer science

abstract: Autoencoders learn data representations through reconstruction. Robust training is the key factor affecting the quality of the learned representations and, consequently, the accuracy of the application that use them. Previous works suggested methods for deciding the optimal autoencoder configuration which allows for robust training. Nevertheless, improving the accuracy of a trained autoencoder has got limited, if no, attention. We propose a new approach that improves the accuracy of a trained autoencoder’s results and answers the following question, Given a trained autoencoder, a test image, and using a real-parameter optimizer, can we generate better quality reconstructed image version than the one generated by the autoencoder?. Our proposed approach combines both the decoder part of a trained Resitricted Boltman Machine-based autoencoder with the Competitive Swarm Optimization algorithm. Experiments show that it is possible to reconstruct images using trained decoder from randomly initialized representations. Results also show that our approach reconstructed better quality images than the autoencoder in most of the test cases. Indicating that, we can use the approach for improving the performance of a pre-trained autoencoder if it does not give satisfactory results.

text: Using swarm optimization to enhance autoencoder’s images Autoencoders learn data representations through reconstruction. Robust training is the key factor affecting the quality of the learned representations and, consequently, the accuracy of the application that use them. Previous works suggested methods for deciding the optimal autoencoder configuration which allows for robust training. Nevertheless, improving the accuracy of a trained autoencoder has got limited, if no, attention. We propose a new approach that improves the accuracy of a trained autoencoder’s results and answers the following question, Given a trained autoencoder, a test image, and using a real-parameter optimizer, can we generate better quality reconstructed image version than the one generated by the autoencoder?. Our proposed approach combines both the decoder part of a trained Resitricted Boltman Machine-based autoencoder with the Competitive Swarm Optimization algorithm. Experiments show that it is possible to reconstruct images using trained decoder from randomly initialized representations. Results also show that our approach reconstructed better quality images than the autoencoder in most of the test cases. Indicating that, we can use the approach for improving the performance of a pre-trained autoencoder if it does not give satisfactory results.

year: 2017

title: New Zealand teachers' experiences in implementing the technology curriculum

authors: Jones, Alister

abstract: This paper describes the results of a national study to investigate teachers' experiences in the implementation of the technology curriculum in New Zealand schools from years 1–13. This investigation of the implementation of the technology curriculum is part of a larger study being undertaken nationally in all curriculum areas (National Schools Sampling Study) to explore how effective the curriculum is in practice and how the results can inform future developments. National focus groups, questionnaires and case studies are used to explore how the curriculum is being implemented. The questionnaires were distributed to over 10% of New Zealand schools. The key findings indicate that most primary school teachers are aiming for curriculum coverage, have moderate levels of confidence but are concerned about curriculum overcrowding. Years 7 and 8 teachers are mainly concerned about assessment, whereas secondary school teachers are constrained by existing structures in schools.

text: New Zealand teachers' experiences in implementing the technology curriculum This paper describes the results of a national study to investigate teachers' experiences in the implementation of the technology curriculum in New Zealand schools from years 1–13. This investigation of the implementation of the technology curriculum is part of a larger study being undertaken nationally in all curriculum areas (National Schools Sampling Study) to explore how effective the curriculum is in practice and how the results can inform future developments. National focus groups, questionnaires and case studies are used to explore how the curriculum is being implemented. The questionnaires were distributed to over 10% of New Zealand schools. The key findings indicate that most primary school teachers are aiming for curriculum coverage, have moderate levels of confidence but are concerned about curriculum overcrowding. Years 7 and 8 teachers are mainly concerned about assessment, whereas secondary school teachers are constrained by existing structures in schools.

year: 2004

title: Planning and governance under the LGA: Lessons from the RMA experience.

authors: Borrie, Nancy

subjects: New Zealand

abstract: The purpose of this report is to identify ways in which experiences gained from the
RMA as a devolved and co-operative planning mandate can enable local and central
government and other stakeholders to more effectively implement the LGA. The
report is based on findings from the FRST-funded research programme on Planning
under Co-operative Mandates (PUCM). We argue in this report that the experiences gained from the RMA can inform
effective implementation of the LGA in three important respects: Preparation and implementation of LTCCPs; The community consultation process for formulating community outcomes;
and Māori participation in planning and governance.

text: Planning and governance under the LGA: Lessons from the RMA experience. The purpose of this report is to identify ways in which experiences gained from the
RMA as a devolved and co-operative planning mandate can enable local and central
government and other stakeholders to more effectively implement the LGA. The
report is based on findings from the FRST-funded research programme on Planning
under Co-operative Mandates (PUCM). We argue in this report that the experiences gained from the RMA can inform
effective implementation of the LGA in three important respects: Preparation and implementation of LTCCPs; The community consultation process for formulating community outcomes;
and Māori participation in planning and governance.

year: 2004-06-01