Combining and choosing case base maintenance algorithms

Case-Based Reasoning (CBR) uses past experiences to solve new problems. The quality of the past experiences, which are stored as cases in a case base, is a big factor in the performance of a CBR system. The system's competence may be improved by adding problems to the case base after they have been solved and their solutions verified to be correct. However, from time to time, the case base may have to be refined to reduce redundancy and to get rid of any noisy cases that may have been introduced. Many case base maintenance algorithms have been developed to delete noisy and redundant cases. However, different algorithms work well in different situations and it may be difficult for a knowledge engineer to know which one is the best to use for a particular case base. In this thesis, we investigate ways to combine algorithms to produce better deletion decisions than the decisions made by individual algorithms, and ways to choose which algorithm is best for a given case base at a given time. We analyse five of the most commonly-used maintenance algorithms in detail and show how the different algorithms perform better on different datasets. This motivates us to develop a new approach: maintenance by a committee of experts (MACE). MACE allows us to combine maintenance algorithms to produce a composite algorithm which exploits the merits of each of the algorithms that it contains. By combining different algorithms in different ways we can also define algorithms that have different trade-offs between accuracy and deletion. While MACE allows us to define an infinite number of new composite algorithms, we still face the problem of choosing which algorithm to use. To make this choice, we need to be able to identify properties of a case base that are predictive of which maintenance algorithm is best. We examine a number of measures of dataset complexity for this purpose. These provide a numerical way to describe a case base at a given time. We use the numerical description to develop a meta-case-based classification system. This system uses previous experience about which maintenance algorithm was best to use for other case bases to predict which algorithm to use for a new case base. Finally, we give the knowledge engineer more control over the deletion process by creating incremental versions of the maintenance algorithms. These incremental algorithms suggest one case at a time for deletion rather than a group of cases, which allows the knowledge engineer to decide whether or not each case in turn should be deleted or kept. We also develop incremental versions of the complexity measures, allowing us to create an incremental version of our meta-case-based classification system. Since the case base changes after each deletion, the best algorithm to use may also change. The incremental system allows us to choose which algorithm is the best to use at each point in the deletion process.

Development of germanium/silicon integration for near infrared detection

Silicon (Si) is the base material for electronic technologies and is emerging as a very attractive platform for photonic integrated circuits (PICs). PICs allow optical systems to be made more compact with higher performance than discrete optical components. Applications for PICs are in the area of fibre-optic communication, biomedical devices, photovoltaics and imaging. Germanium (Ge), due to its suitable bandgap for telecommunications and its compatibility with Si technology is preferred over III-V compounds as an integrated on-chip detector at near infrared wavelengths. There are two main approaches for Ge/Si integration: through epitaxial growth and through direct wafer bonding. The lattice mismatch of ~4.2% between Ge and Si is the main problem of the former technique which leads to a high density of dislocations while the bond strength and conductivity of the interface are the main challenges of the latter. Both result in trap states which are expected to play a critical role. Understanding the physics of the interface is a key contribution of this thesis. This thesis investigates Ge/Si diodes using these two methods. The effects of interface traps on the static and dynamic performance of Ge/Si avalanche photodetectors have been modelled for the first time. The thesis outlines the original process development and characterization of mesa diodes which were fabricated by transferring a ~700 nm thick layer of p-type Ge onto n-type Si using direct wafer bonding and layer exfoliation. The effects of low temperature annealing on the device performance and on the conductivity of the interface have been investigated. It is shown that the diode ideality factor and the series resistance of the device are reduced after annealing. The carrier transport mechanism is shown to be dominated by generation–recombination before annealing and by direct tunnelling in forward bias and band-to-band tunnelling in reverse bias after annealing. The thesis presents a novel technique to realise photodetectors where one of the substrates is thinned by chemical mechanical polishing (CMP) after bonding the Si-Ge wafers. Based on this technique, Ge/Si detectors with remarkably high responsivities, in excess of 3.5 A/W at 1.55 μm at −2 V, under surface normal illumination have been measured. By performing electrical and optical measurements at various temperatures, the carrier transport through the hetero-interface is analysed by monitoring the Ge band bending from which a detailed band structure of the Ge/Si interface is proposed for the first time. The above unity responsivity of the detectors was explained by light induced potential barrier lowering at the interface. To our knowledge this is the first report of light-gated responsivity for vertically illuminated Ge/Si photodiodes. The wafer bonding approach followed by layer exfoliation or by CMP is a low temperature wafer scale process. In principle, the technique could be extended to other materials such as Ge on GaAs, or Ge on SOI. The unique results reported here are compatible with surface normal illumination and are capable of being integrated with CMOS electronics and readout units in the form of 2D arrays of detectors. One potential future application is a low-cost Si process-compatible near infrared camera.