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This paper assesses the potential of one approach to predicting student performance in an introductory computer science class using information about students' preparation, attitudes and study habits. An expert system has been utilized for this purpose. The expert system accepts data related to seven different categories of preparation, belief and attitude and, through the partial activation of multiple...
Blur is certainly one of the most encountered and the most annoying degradation types in image. It is due to several causes such as compression, motion, filtering and so on. In order to estimate the quality of this kind of degraded images, several metrics have been proposed in the literature. In this paper, we focus our attention on stereoscopic images and we propose a fusion-based blind stereoscopic...
The Domain Name Service (DNS) is a vital service in the Internet. Much more than a simple translation mechanism, it also allows higher profile functionalities such as load balancing and enhanced content distribution. In the scope of cloud computing, DNS is foreseen as an elastic and robust service, supporting failover mechanisms, decentralised configuration and multi-tenant isolation.
Top-k reports are compound metrics that provide useful information when diagnosing problems in a system, e.g., to identify persistent CPU usage by a process. In large systems, these reports are collected at regular intervals and need to be resampled to a coarser granularity to answer user queries for different sampling periods, or to save space and make it possible to keep historical data for long...
In this paper, we propose a novel no reference (NR) quality assessment metric for stereoscopic images by statistical features. First, we calculate the luminance map through the local normalization, which is further used to extract the statistic luminance features. Second, we predict the disparity map of the stereoscopic image, which is further combined with the corresponding left and right views to...
We would like to present the idea of our Continuous Defect Prediction (CDP) research and a related dataset that we created and share. Our dataset is currently a set of more than 11 million data rows, representing files involved in Continuous Integration (CI) builds, that synthesize the results of CI builds with data we mine from software repositories. Our dataset embraces 1265 software projects, 30,022...
AMNESiA is an affinity measurement platform for NFV-enabled networks, designed to consolidate and interpret existing monitoring data into an affinity metric, aiding operators to identify affinity and anti-affinity relations in the network. AMNESiA uses the latest snapshot of usage data, collected through a generic monitoring solution, from the database to measure affinity between VNFs.
The paper gives an insight into the development of informetrics from its beginnings. Informetrics is a part of information sciences dedicated to measuring of information phenomenon. Informetrics can be defined as the discipline which studies quantitative aspects of information in any form not only within scientific community but also within any other social community. The term informetrics is an umbrella...
Defect Inspection as a part of yield learning and Improvement has been a critical part for the enormous progress of semiconductor manufacturing to ensure quality and high yield. For a Multi Product Foundry, challenges arise when quality and high yield will be set in all products. This paper describes the successful implementation of a cost effective Defect Inspection System for a multiproduct foundry...
In this paper a no-reference image quality assessment (IQA) metric for DIBR-synthesized images is proposed. Sparsity based features of morphologically decomposed image subbands are used to estimate distortion level in images. A General regression neural network is utilized to calculate quality score. The performance is evaluated using publicly available IRCCyN/IVC DIBR image database. Experimental...
Subjective video quality assessment (VQA) strongly depends on semantics, context, and the types of visual distortions. Currently, all existing VQA databases include only a small number of video sequences with artificial distortions. The development and evaluation of objective quality assessment methods would benefit from having larger datasets of real-world video sequences with corresponding subjective...
Early design space evaluation of computer systems is usually performed using performance models (e.g., detailed simulators, RTL-based models, etc.). However, it is very challenging (often impossible) to run many emerging applications on detailed performance models owing to their complex software-stacks and long run times. To overcome such challenges in benchmarking these complex applications, we propose...
Code smells are sub-optimal coding circumstances such as blob classes or spaghetti code - they have received much attention and tooling in recent software engineering research. Higher-up in the abstraction level, architectural smells are problems or sub-optimal architectural patterns or other design-level characteristics. These have received significantly less attention even though they are usually...
Search engine is one of the mostly-used big data applications. However, search system varies in different platforms and fields, and there are few approaches to evaluate its quality. Search engine for online shopping systems combines text search and classification-based retrieval. It is more difficult to validate and evaluate quality since there are no definite quality standards or testing methods...
Data management applications deployed on IaaS cloud environments must simultaneously strive to minimize cost and provide good performance. Balancing these two goals requires complex decision-making across a number of axes: resource provisioning, query placement, and query scheduling. While previous works have addressed each axis in isolation for specific types of performance goals, this demonstration...
Having an effective security level for Embedded System (ES), helps a reliable and stable operation of this system. In order to identify, if the current security level for a given ES is effective or not, we need a proactive evaluation for this security level. The evaluation of the security level for ESs is not straightforward process, things like the heterogeneity among the components of ES complicate...
Over-booking cloud resources is an effective way to increase the cost efficiency of a cluster, and is being studied within Microsoft for the Azure SQL Database service. A key challenge is to strike the right balance between the potentially conflicting goals of optimizing for resource allocation efficiency and positive user experience. Understanding when cloud database customers use their database...
A goal of performance testing is to find situations when applications unexpectedly exhibit worsened characteristics for certain combinations of input values. A fundamental question of performance testing is how to select a manageable subset of the input data faster to find performance problems in applications automatically. We present a novel tool, FOREPOST, for finding performance problems in applications...
Modern applications are increasingly being composed from multiple components that require and consume services at dierent layers of the cloud stack. The diverse, dynamic and unpredictable nature of both cloud services and application workloads makes quality-assured provision of such cloud service-based applications (CSBAs) a major challenge. While elasticity and autoscaling gives CSBA providers the...
Reduced-reference Image Quality Metric for Contrast-changed images (RIQMC) and No-Reference Quality metric for Contrast-Distorted Images (NR-IQACDI) are the state-of-the-art IQA for Contrast-Distorted Images (CDI). Nevertheless, there is room for improvement especially for the assessment results using image database called TID2013 and CSIQ. Most of the existing No-Reference Image Quality Assessment...
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