41 resultados para Analytic Reproducing Kernel


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Intergenerational transmission of trauma describes the impact that traumatic events experienced by one generation have for the subsequent generation. In Northern Ireland, violent conflict raged between 1969 and 1998, when a peace process begun. This study explored to what extent (if any) parents’ experiences of the conflict influenced how children perceived life in this society. Parents completed a questionnaire, and their children drew 2 pictures, depicting Northern Ireland now and before they were born. Children’s behaviors and awareness of the conflict were influenced by their parents’ experiences and narratives, their age, gender, and school. Parental narrative about the violence was influenced by individual learning history, the child’s age and gender, and present circumstances. A behavior analytic approach is offered.

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In this paper, a novel and effective lip-based biometric identification approach with the Discrete Hidden Markov Model Kernel (DHMMK) is developed. Lips are described by shape features (both geometrical and sequential) on two different grid layouts: rectangular and polar. These features are then specifically modeled by a DHMMK, and learnt by a support vector machine classifier. Our experiments are carried out in a ten-fold cross validation fashion on three different datasets, GPDS-ULPGC Face Dataset, PIE Face Dataset and RaFD Face Dataset. Results show that our approach has achieved an average classification accuracy of 99.8%, 97.13%, and 98.10%, using only two training images per class, on these three datasets, respectively. Our comparative studies further show that the DHMMK achieved a 53% improvement against the baseline HMM approach. The comparative ROC curves also confirm the efficacy of the proposed lip contour based biometrics learned by DHMMK. We also show that the performance of linear and RBF SVM is comparable under the frame work of DHMMK.

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Management control in public university hospitals is a challenging task because of continuous changes due to external pressures (e.g. economic pressures, stakeholder focuses and scientific progress) and internal complexities (top management turnover, shared leadership, technological evolution, and researcher oriented mission). Interactive budgeting contributed to improving vertical and horizontal communication between hospital and stakeholders and between different organizational levels. This paper describes an application of Analytic Hierarchy Process (AHP) to enhance interactive budgeting in one of the biggest public university hospital in Italy. AHP improved budget allocation facilitating elicitation and formalization of units' needs. Furthermore, AHP facilitated vertical communication among manager and stakeholders, as it allowed multilevel hierarchical representation of hospital needs, and horizontal communication among staff of the same hospital, as it allowed units' need prioritization and standardization, with a scientific multi-criteria approach, without using complex mathematics. Finally, AHP allowed traceability of a complex decision making processes (as budget allocation), this aspect being of paramount importance in public sectors, where managers are called to respond to many different stakeholders about their choices.

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In-Memory Databases (IMDBs), such as SAP HANA, enable new levels of database performance by removing the disk bottleneck and by compressing data in memory. The consequence of this improved performance means that reports and analytic queries can now be processed on demand. Therefore, the goal is now to provide near real-time responses to compute and data intensive analytic queries. To facilitate this, much work has investigated the use of acceleration technologies within the database context. While current research into the application of these technologies has yielded positive results, they have tended to focus on single database tasks or on isolated single user requests. This paper uses SHEPARD, a framework for managing accelerated tasks across shared heterogeneous resources, to introduce acceleration into an IMDB. Results show how, using SHEPARD, multiple simultaneous user queries all receive speed-up by using a shared pool of accelerators. Results also show that offloading analytic tasks onto accelerators can have indirect benefits for other database workloads by reducing contention for CPU resources.

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There has been a recent identification of a need for a New Business History. This discussion connects with the analytic narrative approach. By following this approach, the study of business history provides important implications for the conduct and institutional design of contemporary industrial policy. The approach also allows us to solve historical puzzles. The failure of the De Lorean Motor Company Limited (DMCL) is one specific puzzle. Journalistic accounts that focus on John De Lorean's alleged personality defects as an explanation for this failure miss the crucial institutional component. Moreover, distortions in the rewards associated with industrial policy, and the fact that the objectives of the institutions implementing the policy were not solely efficiency-based, led to increased opportunities for rent-seeking. Political economy solves the specific puzzle; by considering institutional dimensions, we can also solve the more general puzzle of why activist industrial policy was relatively unsuccessful in Northern Ireland.