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Spectral correction factors are often used to characterize the impact of spectral variations on PV module output. We compare three different methods to predict a spectral correction factor and validate these against outdoor spectroradiometer measurements. It is found that commonly used models lead to a constant error due to assumptions made when determining coefficients describing geometric air mass...
We propose an efficient linear similarity metric learning method for face verification called Triangular Similarity Metric Learning (TSML). Compared with relevant state-of-the-art work, this method improves the efficiency of learning the cosine similarity while keeping effectiveness. Concretely, we present a geometrical interpretation based on the triangle inequality for developing a cost function...
This paper presents a novel visual analysis based framework for automated planogram compliance check in retail stores. Our framework provides an efficient and convenient solution for ensuring planogram compliance by real-time analysis of the shelf image acquired in freehand manner. We present a novel application of Hausdorff metric for occupancy computation in product shelf images. Subsequently, we...
This paper investigates the problem of fine-grained face verification under unconstrained conditions. For the conventional face verification task, the verification model is trained with some positive and negative face pairs, where each positive sample pair contains two face images of the same person while each negative sample pair usually consists of two face images from different subjects. However,...
AS-level end-to-end paths are of great value for ISPs and a variety of network applications. Although tools like traceroute may reveal AS paths, they require the permission to access source hosts and introduce additional probing traffic, which is not feasible in many applications. In contrast, AS path inference based on BGP control plane data and AS relationship information is a more practical and...
Stack Overflow (SO) is a question and answers (Q&A) web platform on software development that is gaining in popularity. With increasing popularity often comes a very unwelcome side effect: A decrease in the average quality of a post. To keep Q&A websites like SO useful it is vital that this side effect is countered. Previous research proved to be reasonably successful in using properties...
In order to measure the harmonic current emission of equipment in accordance with IEC standards, a measurement setup (voltage source, measurement equipment) with a specified accuracy and reproducibility is required. One possibility to verify its accuracy is the measurement of a set of reference loads with known harmonic emission and a comparison of measured and calculated values. However, laboratory...
In this paper, the authors propose a methodology to guide verification of single phase reactive power meters under non sinusoidal conditions. At first, it is presented a brief review about different definitions of reactive power proposed in literature. Then a test signal for the detection of the implemented approach without a priori knowledge provided by the manufacturer was designed and numerically...
In order to develop provably safe human-in-the-loop systems, accurate and precise models of human behavior must be developed. Driving is a good example of such a system because the driver has full control of the vehicle, and her likely actions are highly dependent on her mental state and the context of the current situation. This paper presents a testbed for collecting driver data that allows us to...
This paper investigates the accuracy of predictive auto-scaling systems in the Infrastructure as a Service (IaaS) layer of cloud computing. The hypothesis in this research is that prediction accuracy of auto-scaling systems can be increased by choosing an appropriate time-series prediction algorithm based on the performance pattern over time. To prove this hypothesis, an experiment has been conducted...
From its very inception, the study of software architecture has recognized architectural decay as a regularly occurring phenomenon in long-lived systems. Architectural decay is caused by repeated changes to a system during its lifespan. Despite decay's prevalence, there is a relative dearth of empirical data regarding the nature of architectural changes that may lead to decay, and of developers' understanding...
This paper investigates several techniques that increase the accuracy of motion boundaries in estimated motion fields of a local dense estimation scheme. In particular, we examine two matching metrics, one is MSE in the image domain and the other one is a recently proposed multiresolution metric that has been shown to produce more accurate motion boundaries. We also examine several different edge-preserving...
Today's infrastructure clouds provide resource elasticity (i.e. Auto-scaling) mechanisms enabling self-adaptive resource provisioning to reflect variations in the load intensity over time. These mechanisms impact on the application performance, however, their effect in specific situations is hard to quantify and compare. To evaluate the quality of elasticity mechanisms provided by different platforms...
In imbalanced learning, most standard classification algorithms usually fail to properly represent data distribution and provide unfavorable classification performance. More specifically, the decision rule of minority class is usually weaker than majority class, leading to many misclassification of expensive minority class data. Motivated by our previous work ADASYN [1], this paper presents a novel...
Alternate Test has demonstrated in the last decade that advanced machine-learning tools can leverage the accuracy gap between functional test and indirect, or model-based, test. If a regression approach is taken, a model should be trained for each specification. The advantage is that the results are interpreted just like performance measurements but the drawback is that accuracy is required over the...
It is well known that geometry is of significance to the performance of multistatic radars. In multistatic passive radars the receiver placement is especially critical since the transmitters of opportunity are beyond control of radar designer. Instead of considering a single objective, we suggest to implement the receiver placement by using multiobjective optimization in this paper. Specifically,...
We present an accurate, real-time approach to robotic grasp detection based on convolutional neural networks. Our network performs single-stage regression to graspable bounding boxes without using standard sliding window or region proposal techniques. The model outperforms state-of-the-art approaches by 14 percentage points and runs at 13 frames per second on a GPU. Our network can simultaneously...
In the surveillance field, it is very common to have camera networks covering large crowded areas. Not rarely, cameras in these networks do not share the same field of view and they are not always calibrated. In these cases, common problems such as tracking cannot be directly applied as the information from one camera must be also consistent with the others. This is the most common scenario for the...
Feature Selection plays an important role in Intrusion Detection, where a large number of features extracted from whole data needs to be analyzed. Feature relevance is the basic measurement in feature selection techniques. In this paper, different feature selection techniques are analyzed. By using pre-processed data set, various feature selection techniques are compared. The NSL - KDD dataset is...
There exist a wide variety of time sensitive contexts (e.g. image-guided neurosurgery (IGNS)), whereby image registration is required to be both fast and accurate if it is to be adopted clinically. Many sampling techniques have been proposed to speed up the registration process but these often come at the expense of accuracy (e.g. random). In this paper, we describe a fast and accurate multi-modal...
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