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Software Quality model is a well-accepted way for assessing high-level quality characteristics (e.g., maintainability) by aggregation from low-level metrics. Aggregation method in a software quality model denotes how to aggregate low-level metrics to high-level quality characteristics. Most of the existing quality models adopt the weighted linear aggregation method. The main drawback of weighted linear...
Heterogeneous defect prediction (HDP) aims to predict defect-prone software modules in one project using heterogeneous data collected from other projects. Recently, several HDP methods have been proposed. However, these methods do not sufficiently incorporate the two characteristics of the defect prediction data: (1) data could be linearly inseparable, and (2) data could be highly imbalanced. These...
In the current transfer machine for the flexible band, the equipment sometimes stops due to fluctuations in the tension of the flexible band, the readjustment is required at this time and the productivity is reduced. Therefore, in this study, we clarified factors influencing the positioning accuracy of the flexible band, proposed a monitoring method of operating condition, and aimed at the improvement...
In this paper groups of coherent generators are identified based on a correlation metric. The main contribution is related to the rapid, simple, and reliable identification of coherent generators, which may be aggregated in order to constitute equivalent generators, thus reducing the dimensionality of the original model. Different levels of aggregation may be attained and results demonstrate the proposal's...
One of the first steps towards the effective Technical Debt (TD) management is the quantification and continuous monitoring of the TD principal. In the current state-ofresearch and practice the most common ways to assess TD principal are the use of: (a) structural proxies—i.e., most commonly through quality metrics; and (b) monetized proxies—i.e., most commonly through the use of the SQALE (Software...
Clustering techniques have gained great popularity in neuroscience data analysis especially in analysing data from complex experiment paradigm where it is hard to apply traditional model-based method. However, when employing clustering analysis, many clustering algorithms are available nowadays and even with an individual clustering algorithm, choices like parameter settings and distance metrics are...
On a PCB, the high-speed link layout design with high component density has to satisfy strict mechanical and electrical specifications. Not only does the design and manufacturing process become difficult, but also the correlation between measurements and simulations is extremely challenging. In this paper, we focus on the above-mentioned challenge encountered in the measurement correlation process...
Brain functional connectivity measured by functional magnetic resonance imaging was shown to be influenced by preprocessing procedures. We aim to describe this influence separately for different preprocessing factors and in 20 different most used preprocessing pipelines. We evaluate the effects of slice-timing correction and physiological noise filtering by RETROICOR, diverse levels of motion correction,...
The Vehicular Ad Hoc Networks (VANETs), as an important part of intelligent transportation systems (ITS), has been becoming a promising research area. Due to the high mobility of vehicles and intermittent connected topology resulting in the dramatically changing network topology, it is difficult to design a protocol including congestion control mechanism, which is helpful for a well network performance...
In this work we study the task of image annotation, of which the goal is to describe an image using a few tags. Instead of predicting the full list of tags, here we target for providing a short list of tags under a limited number (e.g., 3), to cover as much information as possible of the image. The tags in such a short list should be representative and diverse. It means they are required to be not...
We present a novel, purely affinity-based natural image matting algorithm. Our method relies on carefully defined pixel-to-pixel connections that enable effective use of information available in the image and the trimap. We control the information flow from the known-opacity regions into the unknown region, as well as within the unknown region itself, by utilizing multiple definitions of pixel affinities...
The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences...
Customers need to know how reliable a new release is, and whether or not the new release has substantially different, either better or worse, reliability than the one currently in production. Customers are demanding quantitative evidence, based on pre-release metrics, to help them decide whether or not to upgrade (and thereby offer new features and capabilities to their customers). Finding ways to...
the task of full-focused digital images construction relates to computational photography and is a process of increasing the information capacity of images obtained via photo- and video-fixation devices with limited optical depth of field. Additional to this task is the question of automatic evaluation of the quality of the images. The most popular non-reference metrics for comparing the quality of...
Many wireless networks provide a large number of available channels for data transmissions. Due to the multi-path environment, channels have different channel qualities. There- fore, selecting a good channel from the multiple channels can improve the communication effectiveness. The Packet Reception Rate (PRR) has been utilized to represent the channel quality. In order to know which channel has good...
The design of intelligent powered wheelchairs has traditionally focused heavily on providing effective and efficient navigation assistance. Significantly less attention has been given to the end-user's preference between different assistance paradigms. It is possible to include these subjective evaluations in the design process, for example by soliciting feedback in post-experiment questionnaires...
Reliable management of modern cloud computing infrastructures is unrealizable without monitoring and analysis of a huge number of system indicators (metrics) as time series data stored in big databases. Efficient storage and processing of collected historical data from all "objects" of those infrastructures are technology challenges for this Big Data application. We propose a data compression...
DNN-based cross-modal retrieval has become a research hotspot, by which users can search results across various modalities like image and text. However, existing methods mainly focus on the pairwise correlation and reconstruction error of labeled data. They ignore the semantically similar and dissimilar constraints between different modalities, and cannot take advantage of unlabeled data. This paper...
Automated affective computing in the wild is a challenging task in the field of computer vision. This paper presents three neural network-based methods proposed for the task of facial affect estimation submitted to the First Affect-in-the-Wild challenge. These methods are based on Inception-ResNet modules redesigned specifically for the task of facial affect estimation. These methods are: Shallow...
We present a comprehensive overview of the stereoscopic Intel RealSense RGBD imaging systems. We discuss these systems' mode-of-operation, functional behavior and include models of their expected performance, shortcomings, and limitations. We provide information about the systems' optical characteristics, their correlation algorithms, and how these properties can affect different applications, including...
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