Fuzzy-Granular Based Data Mining for Effective Decision Support in Biomedical Applications

Due to complexity of biomedical problems, adaptive and intelligent knowledge discovery and data mining systems are highly needed to help humans to understand the inherent mechanism of diseases. For biomedical classification problems, typically it is impossible to build a perfect classifier with 100% prediction accuracy. Hence a more realistic target is to build an effective Decision Support System (DSS). In this dissertation, a novel adaptive Fuzzy Association Rules (FARs) mining algorithm, named FARM-DS, is proposed to build such a DSS for binary classification problems in the biomedical domain. Empirical studies show that FARM-DS is competitive to state-of-the-art classifiers in terms of prediction accuracy. More importantly, FARs can provide strong decision support on disease diagnoses due to their easy interpretability. This dissertation also proposes a fuzzy-granular method to select informative and discriminative genes from huge microarray gene expression data. With fuzzy granulation, information loss in the process of gene selection is decreased. As a result, more informative genes for cancer classification are selected and more accurate classifiers can be modeled. Empirical studies show that the proposed method is more accurate than traditional algorithms for cancer classification. And hence we expect that genes being selected can be more helpful for further biological studies

Non-equilibrium Green's function predictions of band tails and band gap narrowing in III-V semiconductors and nanodevices

High-doping induced Urbach tails and band gap narrowing play a significant role in determining the performance of tunneling devices and optoelectronic devices such as tunnel field-effect transistors (TFETs), Esaki diodes and light-emitting diodes. In this work, Urbach tails and band gap narrowing values are calculated explicitly for GaAs, InAs, GaSb and GaN as well as ultra-thin bodies and nanowires of the same. Electrons are solved in the non-equilibrium Green's function method in multi-band atomistic tight binding. Scattering on polar optical phonons and charged impurities is solved in the self-consistent Born approximation. The corresponding nonlocal scattering self-energies as well as their numerically efficient formulations are introduced for ultra-thin bodies and nanowires. Predicted Urbach band tails and conduction band gap narrowing agree well with experimental literature for a range of temperatures and doping concentrations. Polynomial fits of the Urbach tail and band gap narrowing as a function of doping are tabulated for quick reference

Space-Time Phononic Crystals with Anomalous Topological Edge States

It is well known that an interface created by two topologically distinct structures could host nontrivial edge states that are immune to defects. In this letter, we introduce a one-dimensional space-time phononic crystal and study the associated anomalous topological edge states. A space-decoupled time modulation is assumed. While preserving the key topological feature of the system, such a modulation also duplicates the edge state mode across the spectrum, both inside and outside the band gap. It is shown that, in contrast to conventional topological edge states which are excited by frequencies in the Bragg regime, the time-modulation-induced frequency conversion can be leveraged to access topological edge states at a deep subwavelength scale where the entire phononic crystal size is merely 1/5.1 of the wavelength. This remarkable feature could open a new route for designing miniature devices that are based on topological physics

Perceptual Experiences Cannot Be an Inference’s Conclusion

Susanna Siegel holds a view that experiences can be the conclusion of an inference. In this paper, I shall refute this claim. Siegel has to endorse a specific account of inference that allows her to make this claim. Thus, my line of reasoning is to first provide argument against Siegel’s account of inference; then I propose and defend an account of inference that does not allow experiences to be the conclusion of an inference

An Intelligent Decision Support System for Business IT Security Strategy

Cyber threat intelligence (CTI) is an emerging approach to improve cyber security of business IT environment. It has information of an a ected business IT context. CTI sharing tools are available for subscribers, and CTI feeds are increasingly available. If another business IT context is similar to a CTI feed context, the threat described in the CTI feed might also take place in the business IT context. Businesses can take proactive defensive actions if relevant CTI is identi ed. However, a challenge is how to develop an e ective connection strategy for CTI onto business IT contexts. Businesses are still insu ciently using CTI because not all of them have su cient knowledge from domain experts. Moreover, business IT contexts vary over time. When the business IT contextual states have changed, the relevant CTI might be no longer appropriate and applicable. Another challenge is how a connection strategy has the ability to adapt to the business IT contextual changes. To ll the gap, in this Ph.D project, a dynamic connection strategy for CTI onto business IT contexts is proposed and the strategy is instantiated to be a dynamic connection rule assembly system. The system can identify relevant CTI for a business IT context and can modify its internal con gurations and structures to adapt to the business IT contextual changes. This thesis introduces the system development phases from design to delivery, and the contributions to knowledge are explained as follows. A hybrid representation of the dynamic connection strategy is proposed to generalise and interpret the problem domain and the system development. The representation uses selected computational intelligence models and software development models. In terms of the computational intelligence models, a CTI feed context and a business IT context are generalised to be the same type, i.e., context object. Grey number model is selected to represent the attribute values of context objects. Fuzzy sets are used to represent the context objects, and linguistic densities of the attribute values of context objects are reasoned. To assemble applicable connection knowledge, the system constructs a set of connection objects based on the context objects and uses rough set operations to extract applicable connection objects that contain the connection knowledge. Furthermore, to adapt to contextual changes, a rough set based incremental updating approach with multiple operations is developed to incrementally update the approximations. A set of propositions are proposed to describe how the system changes based on the previous states and internal structures of the system, and their complexities and e ciencies are analysed. In terms of the software development models, some uni ed modelling language (UML) models are selected to represent the system in design phase. Activity diagram is used to represent the business process of the system. Use case diagram is used to represent the human interactions with the system. Class diagram is used to represent the internal components and relationships between them. Using the representation, developers can develop a prototype of the system rapidly. Using the representation, an application of the system is developed using mainstream software development techniques. RESTful software architecture is used for the communication of the business IT contextual information and the analysis results using CTI between the server and the clients. A script based method is deployed in the clients to collect the contextual information. Observer pattern and a timer are used for the design and development of the monitor-trigger mechanism. In summary, the representation generalises real-world cases in the problem domain and interprets the system data. A speci c business can initialise an instance of the representation to be a speci c system based on its IT context and CTI feeds, and the knowledge assembled by the system can be used to identify relevant CTI feeds. From the relevant CTI data, the system locates and retrieves the useful information that can inform security decisions and then sends it to the client users. When the system needs to modify itself to adapt to the business IT contextual changes, the system can invoke the corresponding incremental updating functions and avoid a time-consuming re-computation. With this updating strategy, the application can provide its users in the client side with timely support and useful information that can inform security decisions using CTI

The Acquisition of Mandarin Chinese by American Heritage Speakers and Second Language Learners of Chinese

Heritage language acquisition has always been controversial and has been widely discussed by scholars in recent years. Some people think that heritage language acquisition is the same as L2 language acquisition, while other people think that heritage language acquisition is different from either L1 or L2 language acquisition. The current study aims to investigate the phonological acquisition of Mandarin Chinese by American heritage speakers and intermediate L2 learners. 5 heritage speakers, 8 intermediate adult L2 Chinese learners (including 5 lower intermediate and 3 upper intermediate learners), and 5 native speakers participated in the perception and production experiment. The logistic regression model on the results of error rates in the perception of half-T3 sandhi proves that both heritage listeners and intermediate L2 listeners are more sensitive to high tones or the tone starting with a high pitch point compared to low tones. Both groups rely on the starting point of the tonal pitch to perceive Mandarin tones rather than tonal contours. The results of the production experimentreveal that heritage speakers produce different Mandarin aspirated voiceless alveolo-palatal affricate [tɕʰ] from either native speakers or intermediate L2 speakers. The finding implies that heritage speakers may establish a new L2 sound category for L1 sounds and differ from low intermediate L2 speakers who assimilate the target phoneme to English voiceless post-aveloar affricate [tʃ]. The current study offers an aspect of heritage phonological acquisition in terms of the learning of Mandarin segmental and suprasegmental features by learners who acquire Chinese as an additional language.Master of Art