title: Microstructure and mechanical behaviour of ultrafine grained Al-4wt%Cu-(2.5-10) Vol.% SiC metal matrix composites produced by powder compact forging

authors: Gazawi, Amro Abdul-Karim

subjects: Al composite

abstract: Ultrafine grained Al-4wt%Cu-(2.5-10) vol.% SiC metal matrix composite powders were produced from a mixture of Al, Cu and SiC powders using high energy mechanical milling (HEMM). The composite powders produced were first hot pressed at 300°C with a pressure of 240 MPa to produce cylindrical powder compacts with a relative density in the range of 80-94% which decreased with increasing the SiC volume fraction. Powder compact forging was utilized to consolidate the powder compacts into nearly fully dense forged disks. With increasing the volume fraction of SiC from 2.5% to 10%, the average microhardness of the forged disks increased from 73HV to 162HV. The fracture strength of the forged disks increased from 225 to 412 MPa with increasing the volume fraction of SiC particles from 2.5 to 10%. The Al-4wt%Cu-2.5vol.%SiC forged disk did not show any macroscopic plastic yielding, while the Al-4wt%Cu-(7.5 and 10)vol.% SiC forged disk showed macroscopic plastic yielding with a small plastic strain to fracture (~1%).

text: Microstructure and mechanical behaviour of ultrafine grained Al-4wt%Cu-(2.5-10) Vol.% SiC metal matrix composites produced by powder compact forging Ultrafine grained Al-4wt%Cu-(2.5-10) vol.% SiC metal matrix composite powders were produced from a mixture of Al, Cu and SiC powders using high energy mechanical milling (HEMM). The composite powders produced were first hot pressed at 300°C with a pressure of 240 MPa to produce cylindrical powder compacts with a relative density in the range of 80-94% which decreased with increasing the SiC volume fraction. Powder compact forging was utilized to consolidate the powder compacts into nearly fully dense forged disks. With increasing the volume fraction of SiC from 2.5% to 10%, the average microhardness of the forged disks increased from 73HV to 162HV. The fracture strength of the forged disks increased from 225 to 412 MPa with increasing the volume fraction of SiC particles from 2.5 to 10%. The Al-4wt%Cu-2.5vol.%SiC forged disk did not show any macroscopic plastic yielding, while the Al-4wt%Cu-(7.5 and 10)vol.% SiC forged disk showed macroscopic plastic yielding with a small plastic strain to fracture (~1%).

year: 2011

title: Improving the Evaluation of Network Anomaly Detection Using a Data
Fusion Approach

authors: Löf, Andreas

subjects: network anomaly detection

abstract: Currently, the evaluation of network anomaly detection methods is often not repeatable. It is difficult to ascertain if different implementations of the same methods have the same performance or the relative performance of different methods. This is in part due to a lack of open implementations, the absence of recent datasets and no common format to express results.

A common approach to evaluating a method is to use the Defense Advanced Research Projects Agency (DARPA) 1999 datasets, or a derivative of them, in combination with a different dataset or network capture. The DARPA datasets are relatively old and bear little resemblance to modern day traffic and the other datasets are unlabelled and typically publicly unavailable making it difficult to ascertain the validity of the research evaluated in such a way.

This thesis primarily contributes a new evaluation methodology that uses a data fusion based approach that allows for reproducible evaluations with modern datasets.

The new methodology incorporates three other contributions: A new way to capture network traces that are fully anonymised yet retains more information than any current network traces and a new trace annotation format and a method for verifying the correctness of the annotations.

The DARPA 1999 dataset was used to demonstrate the validity of the approach and an evaluation was performed on a new dataset that has been captured using the methods introduced. In the evaluation we find that methodology is a viable approach forward, but that it comes with a different set of drawbacks than the current state of the art.

text: Improving the Evaluation of Network Anomaly Detection Using a Data
Fusion Approach Currently, the evaluation of network anomaly detection methods is often not repeatable. It is difficult to ascertain if different implementations of the same methods have the same performance or the relative performance of different methods. This is in part due to a lack of open implementations, the absence of recent datasets and no common format to express results.

A common approach to evaluating a method is to use the Defense Advanced Research Projects Agency (DARPA) 1999 datasets, or a derivative of them, in combination with a different dataset or network capture. The DARPA datasets are relatively old and bear little resemblance to modern day traffic and the other datasets are unlabelled and typically publicly unavailable making it difficult to ascertain the validity of the research evaluated in such a way.

This thesis primarily contributes a new evaluation methodology that uses a data fusion based approach that allows for reproducible evaluations with modern datasets.

The new methodology incorporates three other contributions: A new way to capture network traces that are fully anonymised yet retains more information than any current network traces and a new trace annotation format and a method for verifying the correctness of the annotations.

The DARPA 1999 dataset was used to demonstrate the validity of the approach and an evaluation was performed on a new dataset that has been captured using the methods introduced. In the evaluation we find that methodology is a viable approach forward, but that it comes with a different set of drawbacks than the current state of the art.

year: 2013

title: Improving prediction of potential for treatment completion at Tai Aroha

authors: Astridge Clarke,  Abigail Darcy

subjects: Treatment

abstract: Participant non-completion can be a major problem for treatment programmes. Staff may try to minimise non-completion by deciding who to select for treatment using professional intuition and referral information. It can be difficult for treatment staff to make these decisions regarding the potential for programme completion due to a lack of clear guidelines about what information to consider. This lack of clear guidelines can increase susceptibility to biases, and lead to unreliable and potentially inaccurate decisions. Research has identified ‘simple rules’ that are tools to aid decision-making quickly, effectively, and consistently. Therefore, using past treatment data, we1 aimed to identify predictors of programme completion vs. non-completion at Tai Aroha—a residential treatment programme based in Hamilton—to explore whether a “simple rule” can be developed from information readily available at the time of referral, to support staff decision-making when selecting offenders to attend treatment, with the potential to increase programme completion. We were successful in the development of a simple rule to aid Tai Aroha staff selection decisions. The implications, and limitations of our rule and our study are discussed, and future research relating to simple rules are identified.

text: Improving prediction of potential for treatment completion at Tai Aroha Participant non-completion can be a major problem for treatment programmes. Staff may try to minimise non-completion by deciding who to select for treatment using professional intuition and referral information. It can be difficult for treatment staff to make these decisions regarding the potential for programme completion due to a lack of clear guidelines about what information to consider. This lack of clear guidelines can increase susceptibility to biases, and lead to unreliable and potentially inaccurate decisions. Research has identified ‘simple rules’ that are tools to aid decision-making quickly, effectively, and consistently. Therefore, using past treatment data, we1 aimed to identify predictors of programme completion vs. non-completion at Tai Aroha—a residential treatment programme based in Hamilton—to explore whether a “simple rule” can be developed from information readily available at the time of referral, to support staff decision-making when selecting offenders to attend treatment, with the potential to increase programme completion. We were successful in the development of a simple rule to aid Tai Aroha staff selection decisions. The implications, and limitations of our rule and our study are discussed, and future research relating to simple rules are identified.

year: 2023