3 resultados para Chunk-based information diffusion

em CORA - Cork Open Research Archive - University College Cork - Ireland


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In order to widely use Ge and III-V materials instead of Si in advanced CMOS technology, the process and integration of these materials has to be well established so that their high mobility benefit is not swamped by imperfect manufacturing procedures. In this dissertation number of key bottlenecks in realization of Ge devices are investigated; We address the challenge of the formation of low resistivity contacts on n-type Ge, comparing conventional and advanced rapid thermal annealing (RTA) and laser thermal annealing (LTA) techniques respectively. LTA appears to be a feasible approach for realization of low resistivity contacts with an incredibly sharp germanide-substrate interface and contact resistivity in the order of 10 -7 Ω.cm2. Furthermore the influence of RTA and LTA on dopant activation and leakage current suppression in n+/p Ge junction were compared. Providing very high active carrier concentration > 1020 cm-3, LTA resulted in higher leakage current compared to RTA which provided lower carrier concentration ~1019 cm-3. This is an indication of a trade-off between high activation level and junction leakage current. High ION/IOFF ratio ~ 107 was obtained, which to the best of our knowledge is the best reported value for n-type Ge so far. Simulations were carried out to investigate how target sputtering, dose retention, and damage formation is generated in thin-body semiconductors by means of energetic ion impacts and how they are dependent on the target physical material properties. Solid phase epitaxy studies in wide and thin Ge fins confirmed the formation of twin boundary defects and random nucleation growth, like in Si, but here 600 °C annealing temperature was found to be effective to reduce these defects. Finally, a non-destructive doping technique was successfully implemented to dope Ge nanowires, where nanowire resistivity was reduced by 5 orders of magnitude using PH3 based in-diffusion process.

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The aim of this research, which focused on the Irish adult population, was to generate information for policymakers by applying statistical analyses and current technologies to oral health administrative and survey databases. Objectives included identifying socio-demographic influences on oral health and utilisation of dental services, comparing epidemiologically-estimated dental treatment need with treatment provided, and investigating the potential of a dental administrative database to provide information on utilisation of services and the volume and types of treatment provided over time. Information was extracted from the claims databases for the Dental Treatment Benefit Scheme (DTBS) for employed adults and the Dental Treatment Services Scheme (DTSS) for less-well-off adults, the National Surveys of Adult Oral Health, and the 2007 Survey of Lifestyle Attitudes and Nutrition in Ireland. Factors associated with utilisation and retention of natural teeth were analysed using count data models and logistic regression. The chi-square test and the student’s t-test were used to compare epidemiologically-estimated need in a representative sample of adults with treatment provided. Differences were found in dental care utilisation and tooth retention by Socio-Economic Status. An analysis of the five-year utilisation behaviour of a 2003 cohort of DTBS dental attendees revealed that age and being female were positively associated with visiting annually and number of treatments. Number of adults using the DTBS increased, and mean number of treatments per patient decreased, between 1997 and 2008. As a percentage of overall treatments, restorations, dentures, and extractions decreased, while prophylaxis increased. Differences were found between epidemiologically-estimated treatment need and treatment provided for those using the DTBS and DTSS. This research confirms the utility of survey and administrative data to generate knowledge for policymakers. Public administrative databases have not been designed for research purposes, but they have the potential to provide a wealth of knowledge on treatments provided and utilisation patterns.

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Users seeking information may not find relevant information pertaining to their information need in a specific language. But information may be available in a language different from their own, but users may not know that language. Thus users may experience difficulty in accessing the information present in different languages. Since the retrieval process depends on the translation of the user query, there are many issues in getting the right translation of the user query. For a pair of languages chosen by a user, resources, like incomplete dictionary, inaccurate machine translation system may exist. These resources may be insufficient to map the query terms in one language to its equivalent terms in another language. Also for a given query, there might exist multiple correct translations. The underlying corpus evidence may suggest a clue to select a probable set of translations that could eventually perform a better information retrieval. In this paper, we present a cross language information retrieval approach to effectively retrieve information present in a language other than the language of the user query using the corpus driven query suggestion approach. The idea is to utilize the corpus based evidence of one language to improve the retrieval and re-ranking of news documents in the other language. We use FIRE corpora - Tamil and English news collections in our experiments and illustrate the effectiveness of the proposed cross language information retrieval approach.