Finding optimal alternatives based on efficient comparative preference inference

Choosing the right or the best option is often a demanding and challenging task for the user (e.g., a customer in an online retailer) when there are many available alternatives. In fact, the user rarely knows which offering will provide the highest value. To reduce the complexity of the choice process, automated recommender systems generate personalized recommendations. These recommendations take into account the preferences collected from the user in an explicit (e.g., letting users express their opinion about items) or implicit (e.g., studying some behavioral features) way. Such systems are widespread; research indicates that they increase the customers' satisfaction and lead to higher sales. Preference handling is one of the core issues in the design of every recommender system. This kind of system often aims at guiding users in a personalized way to interesting or useful options in a large space of possible options. Therefore, it is important for them to catch and model the user's preferences as accurately as possible. In this thesis, we develop a comparative preference-based user model to represent the user's preferences in conversational recommender systems. This type of user model allows the recommender system to capture several preference nuances from the user's feedback. We show that, when applied to conversational recommender systems, the comparative preference-based model is able to guide the user towards the best option while the system is interacting with her. We empirically test and validate the suitability and the practical computational aspects of the comparative preference-based user model and the related preference relations by comparing them to a sum of weights-based user model and the related preference relations. Product configuration, scheduling a meeting and the construction of autonomous agents are among several artificial intelligence tasks that involve a process of constrained optimization, that is, optimization of behavior or options subject to given constraints with regards to a set of preferences. When solving a constrained optimization problem, pruning techniques, such as the branch and bound technique, point at directing the search towards the best assignments, thus allowing the bounding functions to prune more branches in the search tree. Several constrained optimization problems may exhibit dominance relations. These dominance relations can be particularly useful in constrained optimization problems as they can instigate new ways (rules) of pruning non optimal solutions. Such pruning methods can achieve dramatic reductions in the search space while looking for optimal solutions. A number of constrained optimization problems can model the user's preferences using the comparative preferences. In this thesis, we develop a set of pruning rules used in the branch and bound technique to efficiently solve this kind of optimization problem. More specifically, we show how to generate newly defined pruning rules from a dominance algorithm that refers to a set of comparative preferences. These rules include pruning approaches (and combinations of them) which can drastically prune the search space. They mainly reduce the number of (expensive) pairwise comparisons performed during the search while guiding constrained optimization algorithms to find optimal solutions. Our experimental results show that the pruning rules that we have developed and their different combinations have varying impact on the performance of the branch and bound technique.

Beginning primary teachers’ perspectives on becoming a teacher in the workplace: Contextual, emotional, and temporo-spatial dimensions of identity shaping

The issue, with international and national overtones, of direct relevance to the present study, relates to the shaping of beginning teachers’ identities in the workplace. As the shift from an initial teacher education programme into initial practice in schools is a period of identity change worthy of investigation, this study focuses on the transformative search by nine beginning primary teachers for their teaching identities, throughout the course of their initial year of occupational experience, post-graduation. The nine beginning teacher participants work in a variety of primary school settings, thus strengthening the representativeness of the research cohort. Privileging ‘insider’ perspectives, the research goal is to understand the complexities of lived experience from the viewpoints of the participating informants. The shaping of identity is conceived of in dimensional terms. Accordingly, a framework composed of three dimensions of beginning teacher experience is devised, namely: contextual; emotional; temporo-spatial. Data collection and analysis is informed by principles derived from sociocultural theories; activity theory; figured worlds theory; and, dialogical self theory. Individual, face-to-face semi-structured interviews, and the maintenance of solicited digital diaries, are the principal methods of data collection employed. The use of a dimensional model fragments the integrated learning experiences of beginning teachers into constituent parts for the purpose of analysis. While acknowledging that the actual journey articulated by each participant is a more complex whole than the sum of its parts, key empirically-based claims are presented as per the dimensional framework employed: contextuality; emotionality; temporo-spatiality. As a result of applying the foci of an international literature to an under-researched aspect of Irish education, this study is offered as a context-specific contribution to the knowledge base on beginning teaching. As the developmental needs of beginning teachers constitute an emerging area of intense policy focus in Ireland, this research undertaking is both relevant and timely.

Physico-chemical properties and component interactions in high solids food systems

The present study aimed to investigate interactions of components in the high solids systems during storage. The systems included (i) lactose–maltodextrin (MD) with various dextrose equivalents at different mixing ratios, (ii) whey protein isolate (WPI)–oil [olive oil (OO) or sunflower oil (SO)] at 75:25 ratio, and (iii) WPI–oil– {glucose (G)–fructose (F) 1:1 syrup [70% (w/w) total solids]} at a component ratio of 45:15:40. Crystallization of lactose was delayed and increasingly inhibited with increasing MD contents and higher DE values (small molecular size or low molecular weight), although all systems showed similar glass transition temperatures at each aw. The water sorption isotherms of non-crystalline lactose and lactose–MD (0.11 to 0.76 aw) could be derived from the sum of sorbed water contents of individual amorphous components. The GAB equation was fitted to data of all non-crystalline systems. The protein–oil and protein–oil–sugar materials showed maximum protein oxidation and disulfide bonding at 2 weeks of storage at 20 and 40°C. The WPI–OO showed denaturation and preaggregation of proteins during storage at both temperatures. The presence of G–F in WPI–oil increased Tonset and Tpeak of protein aggregation, and oxidative damage of the protein during storage, especially in systems with a higher level of unsaturated fatty acids. Lipid oxidation and glycation products in the systems containing sugar promoted oxidation of proteins, increased changes in protein conformation and aggregation of proteins, and resulted in insolubility of solids or increased hydrophobicity concomitantly with hardening of structure, covalent crosslinking of proteins, and formation of stable polymerized solids, especially after storage at 40°C. We found protein hydration transitions preceding denaturation transitions in all high protein systems and also the glass transition of confined water in protein systems using dynamic mechanical analysis.

Application of signal detection methods to fisheries management

The abundance of many commercially important fish stocks are declining and this has led to widespread concern on the performance of traditional approach in fisheries management. Quantitative models are used for obtaining estimates of population abundance and the management advice is based on annual harvest levels (TAC), where only a certain amount of catch is allowed from specific fish stocks. However, these models are data intensive and less useful when stocks have limited historical information. This study examined whether empirical stock indicators can be used to manage fisheries. The relationship between indicators and the underlying stock abundance is not direct and hence can be affected by disturbances that may account for both transient and persistent effects. Methods from Statistical Process Control (SPC) theory such as the Cumulative Sum (CUSUM) control charts are useful in classifying these effects and hence they can be used to trigger management response only when a significant impact occurs to the stock biomass. This thesis explores how empirical indicators along with CUSUM can be used for monitoring, assessment and management of fish stocks. I begin my thesis by exploring various age based catch indicators, to identify those which are potentially useful in tracking the state of fish stocks. The sensitivity and response of these indicators towards changes in Spawning Stock Biomass (SSB) showed that indicators based on age groups that are fully selected to the fishing gear or Large Fish Indicators (LFIs) are most useful and robust across the range of scenarios considered. The Decision-Interval (DI-CUSUM) and Self-Starting (SS-CUSUM) forms are the two types of control charts used in this study. In contrast to the DI-CUSUM, the SS-CUSUM can be initiated without specifying a target reference point (‘control mean’) to detect out-of-control (significant impact) situations. The sensitivity and specificity of SS-CUSUM showed that the performances are robust when LFIs are used. Once an out-of-control situation is detected, the next step is to determine how much shift has occurred in the underlying stock biomass. If an estimate of this shift is available, they can be used to update TAC by incorporation into Harvest Control Rules (HCRs). Various methods from Engineering Process Control (EPC) theory were tested to determine which method can measure the shift size in stock biomass with the highest accuracy. Results showed that methods based on Grubb’s harmonic rule gave reliable shift size estimates. The accuracy of these estimates can be improved by monitoring a combined indicator metric of stock-recruitment and LFI because this may account for impacts independent of fishing. The procedure of integrating both SPC and EPC is known as Statistical Process Adjustment (SPA). A HCR based on SPA was designed for DI-CUSUM and the scheme was successful in bringing out-of-control fish stocks back to its in-control state. The HCR was also tested using SS-CUSUM in the context of data poor fish stocks. Results showed that the scheme will be useful for sustaining the initial in-control state of the fish stock until more observations become available for quantitative assessments.

Assessment of dietary background exposure of the Irish adult population to dioxins and PCBs particularly taking into account additional exposure due to the 2008 Irish dioxin food contamination incident

Irish monitoring data on PCDD/Fs, DL-PCBs and Marker PCBs were collated and combined with Irish Adult Food Consumption Data, to estimate dietary background exposure of Irish adults to dioxins and PCBs. Furthermore, all available information on the 2008 Irish pork dioxin food contamination incident was collated and analysed with a view to evaluate any potential impact the incident may have had on general dioxin and PCB background exposure levels estimated for the adult population in Ireland. The average upperbound daily intake of Irish adults to dioxins Total WHO TEQ (2005) (PCDD/Fs & DLPCBs) from environmental background contamination, was estimated at 0.3 pg/kg bw/d and at the 95th percentile at 1 pg/kg bw/d. The average upperbound daily intake of Irish adults to the sum of 6 Marker PCBs from environmental background contamination ubiquitous in the environment was estimated at 1.6 ng/kg bw/d and at the 95th percentile at 6.8 ng/kg bw/d. Dietary background exposure estimates for both dioxins and PCBs indicate that the Irish adult population has exposures below the European average, a finding which is also supported by the levels detected in breast milk of Irish mothers. Exposure levels are below health based guidance values and/or Body Burdens associated with the TWI (for dioxins) or associated with a NOAEL (for PCBs). Given the current toxicological knowledge, based on biomarker data and estimated dietary exposure, general background exposure of the Irish adult population to dioxins and PCBs is of no human health concern. In 2008, a porcine fat sample taken as part of the national residues monitoring programme led to the detection of a major feed contamination incidence in the Republic of Ireland. The source of the contamination was traced back to the use of contaminated oil in a direct-drying feed operation system. Congener profiles in animal fat and feed samples showed a high level of consistency and pinpointed the likely source of fuel contamination to be a highly chlorinated commercial PCB mixture. To estimate additional exposure to dioxins and PCBs due to the contamination of pig and cattle herds, collection and a systematic review of all data associated with the contamination incident was conducted. A model was devised that took into account the proportion of contaminated product reaching the final consumer during the 90 day contamination incident window. For a 90 day period, the total additional exposure to Total TEQ (PCDD/F &DL-PCB) WHO (2005) amounted to 407 pg/kg bw/90d at the 95th percentile and 1911 pg/kg bw/90d at the 99th percentile. Exposure estimates derived for both dioxins and PCBs showed that the Body Burden of the general population remained largely unaffected by the contamination incident and approximately 10 % of the adult population in Ireland was exposed to elevated levels of dioxins and PCBs. Whilst people in this 10 % cohort experienced quite a significant additional load to the existing body burden, the estimated exposure values do not indicate approximation of body burdens associated with adverse health effects, based on current knowledge. The exposure period was also limited in time to approximately 3 months, following the FSAI recall of contaminated meat immediately on detection of the contamination. A follow up breast milk study on Irish first time mothers conducted in 2009/2010 did not show any increase in concentrations compared to the study conducted in 2002. The latter supports the conclusion that the majority of the Irish adult population was not affected by the contamination incident.

Design of digital differentiators

A digital differentiator simply involves the derivation of an input signal. This work includes the presentation of first-degree and second-degree differentiators, which are designed as both infinite-impulse-response (IIR) filters and finite-impulse-response (FIR) filters. The proposed differentiators have low-pass magnitude response characteristics, thereby rejecting noise frequencies higher than the cut-off frequency. Both steady-state frequency-domain characteristics and Time-domain analyses are given for the proposed differentiators. It is shown that the proposed differentiators perform well when compared to previously proposed filters. When considering the time-domain characteristics of the differentiators, the processing of quantized signals proved especially enlightening, in terms of the filtering effects of the proposed differentiators. The coefficients of the proposed differentiators are obtained using an optimization algorithm, while the optimization objectives include magnitude and phase response. The low-pass characteristic of the proposed differentiators is achieved by minimizing the filter variance. The low-pass differentiators designed show the steep roll-off, as well as having highly accurate magnitude response in the pass-band. While having a history of over three hundred years, the design of fractional differentiator has become a ‘hot topic’ in recent decades. One challenging problem in this area is that there are many different definitions to describe the fractional model, such as the Riemann-Liouville and Caputo definitions. Through use of a feedback structure, based on the Riemann-Liouville definition. It is shown that the performance of the fractional differentiator can be improved in both the frequency-domain and time-domain. Two applications based on the proposed differentiators are described in the thesis. Specifically, the first of these involves the application of second degree differentiators in the estimation of the frequency components of a power system. The second example concerns for an image processing, edge detection application.