700 research outputs found

    The zero effect: voxel-based lesion symptom mapping of number transcoding errors following stroke

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    Zero represents a special case in our numerical system because it is not represented on a semantic level. Former research has shown that this can lead to specific impairments when transcoding numerals from dictation to written digits. Even though, number processing is considered to be dominated by the left hemisphere, studies have indicated that both left as well as right hemispheric stroke patients commit errors when transcoding numerals including zeros. Here, for the first time, a large sample of subacute stroke patients (N = 667) was assessed without being preselected based on the location of their lesion, or a specific impairment in transcoding zero. The results show that specific errors in transcoding zeros were common (prevalence = 14.2%) and a voxel-based lesion symptom mapping analysis (n = 153) revealed these to be related to lesions in and around the right putamen. In line with former research, the present study argues that the widespread brain network for number processing also includes subcortical regions, like the putamen with connections to the insular cortex. These play a crucial role in auditory perception as well as attention. If these areas are lesioned, number processing tasks with higher attentional and working memory loads, like transcoding zeros, can be impaired

    Study of a Framework For Video Streaming In Mobile Devices (AMoV and ESoV)

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    AMoV (adaptive mobile video streaming) and ESoV(efficient social video sharing) are the terms which are currently gaining the attention of variety of computer users and researchers. While enjoying the multimedia services like videos and images, the basic quandary faced by any individual is the progressive downloading or the buffering of the videos. As the researches are focusing on various technologies in said issue, very least focus is given on to the security issues present in these technologies. The basic idea behind this paper is to study and to survey the literature and to propose the security aspects in related field

    Quantile Function-based Models for Resource Utilization and Power Consumption of Applications

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    Server consolidation is currently widely employed in order to improve the energy efficiency of data centers. While being a promising technique, server consolidation may lead to resource interference between applications and thus, reduced performance of applications. Current approaches to account for possible resource interference are not well suited to respect the variation in the workloads for the applications. As a consequence, these approaches cannot prevent resource interference if workload for applications vary. It is assumed that having models for the resource utilization and power consumption of applications as functions of the workload to the applications can improve decision making and help to prevent resource interference in scenarios with varying workload. This thesis aims to develop such models for selected applications. To produce varying workload that resembles statistical properties of real-world workload a workload generator is developed in a first step. Usually, the measurement data for such models origins from different sensors and equipment, all producing data at different frequencies. In order to account for these different frequencies, in a second step this thesis particularly investigates the feasibility to employ quantile functions as model inputs. Complementary, since conventional goodness-of-fit tests are not appropriate for this approach, an alternative to assess the estimation error is presented.:1 Introduction 2 Thesis Overview 2.1 Testbed 2.2 Contributions and Thesis Structure 2.3 Scope, Assumptions, and Limitations 3 Generation of Realistic Workload 3.1 Statistical Properties of Internet Traffic 3.2 Statistical Properties of Video Server Traffic 3.3 Implementation of Workload Generation 3.4 Summary 4 Models for Resource Utilization and for Power Consumption 4.1 Introduction 4.2 Prior Work 4.3 Test Cases 4.4 Applying Regression To Samples Of Different Length 4.5 Models for Resource Utilization as Function of Request Size 4.6 Models for Power Consumption as Function of Resource Utilization 4.7 Summary 5 Conclusion & Future Work 5.1 Summary 5.2 Future Work AppendicesServerkonsolidierung wird derzeit weithin zur Verbesserung der Energieeffizienz von Rechenzentren eingesetzt. Während diese Technik vielversprechende Ergebnisse zeitigt, kann sie zu Ressourceninterferenz und somit zu verringerter Performanz von Anwendungen führen. Derzeitige Ansätze, um dieses Problem zu adressieren, sind nicht gut für Szenarien geeignet, in denen die Workload für die Anwendungen variiert. Als Konsequenz daraus folgt, dass diese Ansätze Ressourceninterferenz in solchen Szenarien nicht verhindern können. Es wird angenommen, dass Modelle für Anwendungen, die deren Ressourenauslastung und die Leistungsaufnahme als Funktion der Workload beschreiben, die Entscheidungsfindung bei der Konsolidierung verbessern und Ressourceninterferenz verhindern können. Diese Arbeit zielt darauf ab, solche Modelle für ausgewählte Anwendungen zu entwickeln. Um variierende Workload zu erzeugen, welche den statistischen Eigenschaften realer Workload folgt, wird zunächst ein Workload-Generator entwickelt. Gewöhnlicherweise stammen Messdaten für die Modelle aus verschienenen Sensoren und Messgeräten, welche jeweils mit unterschiedlichen Frequenzen Daten erzeugen. Um diesen verschiedenen Frequenzen Rechnung zu tragen, untersucht diese Arbeit insbesondere die Möglichkeit, Quantilfunktionen als Eingabeparameter für die Modelle zu verwenden. Da konventionelle Anpassungsgütetests bei diesem Ansatz ungeeignet sind, wird ergänzend eine Alternative vorgestellt, um den durch die Modellierung entstehenden Schätzfehler zu bemessen.:1 Introduction 2 Thesis Overview 2.1 Testbed 2.2 Contributions and Thesis Structure 2.3 Scope, Assumptions, and Limitations 3 Generation of Realistic Workload 3.1 Statistical Properties of Internet Traffic 3.2 Statistical Properties of Video Server Traffic 3.3 Implementation of Workload Generation 3.4 Summary 4 Models for Resource Utilization and for Power Consumption 4.1 Introduction 4.2 Prior Work 4.3 Test Cases 4.4 Applying Regression To Samples Of Different Length 4.5 Models for Resource Utilization as Function of Request Size 4.6 Models for Power Consumption as Function of Resource Utilization 4.7 Summary 5 Conclusion & Future Work 5.1 Summary 5.2 Future Work Appendice

    Analysis of Various Decentralized Load Balancing Techniques with Node Duplication

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    Experience in parallel computing is an increasingly necessary skill for today’s upcoming computer scientists as processors are hitting a serial execution performance barrier and turning to parallel execution for continued gains. The uniprocessor system has now reached its maximum speed limit and, there is very less scope to improve the speed of such type of system. To solve this problem multiprocessor system is used, which have more than one processor. Multiprocessor system improves the speed of the system but it again faces some problems like data dependency, control dependency, resource dependency and improper load balancing. So this paper presents a detailed analysis of various decentralized load balancing techniques with node duplication to reduce the proper execution time
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