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In recent times, there has been significant interest in the machine recognition of human emotions, due to the suite of applications to which this knowledge can be applied. A number of different modalities, such as speech or facial expression, individually and with eye gaze, have been investigated by the affective computing research community to either classify the emotion (e.g. sad, happy, angry)...
Automatic Target Recognition (ATR) aims at detecting the presence and at recognizing the typology and the orientation of targets within a scenario, by using an unsupervised approach. In Syntethic Aperture Radar imaging this turns to be a difficult task due to the specific characteristics of clutter and background noise. Within this manuscript a new two-steps ATR algorithm based on Kolmogorov-Smirnov...
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...
This paper provides an analysis of tweets and of their vocabulary in a specific emergency situation — earthquakes, moreover, the correlations between several words from messages and on the linear regressions between word usages and the intensity of the earthquakes. We analyzed the vocabulary used on tweets about Romanian earthquakes with the vocabulary of tweets used for other European earthquakes.
In this paper, we made the emotion recognition for Romanian language using EMO-IIT database with seven emotions (joy, sadness, fury, neutral tone, anxiety, disgust and boredom). Compared to our previous studies we introduced two new emotions: disgust and boredom and a new set of sentences in order to express better the emotional states. The best recognition rate of emotions is around 75% and was obtained...
In order to find a set of optimal discriminant vectors which can maximize the inter-class scatter while simultaneously minimizing the intra-class scatter after the projection, a new algorithm of orthogonal optimal discriminant vectors and a new algorithm of statistically uncorrelated optimal discriminant vectors for feature extraction were proposed. Compared with the original MMC feature extraction...
Here we describe an approach for the dynamic selection of test cases in continuous integration test environments. By correlating historical test case results with product source code changes, we are able to construct a simple model that enables us to dynamically and automatically create test suites that are customized for each individual product software delivery. Using this technique, we are able...
Multiple view data with different feature representations have widely arisen in various practical applications. Due to the information diversity, fusing multiview features is very valuable for classification purpose. In this paper, we propose a new multifeature fusion method called fractional-order discriminative multiview correlation projection (FDMCP), which is based on fractional-order scatter...
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...
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...
Free view point video (FVV), which offers immersive experience to users with multiple views, is one of the new trends in advanced visual media. These new viewpoints are traditionally synthesized via depth image-based rendering(DIBR) and geometric distortions are therefore observed. Mid-level contours descriptors are capable of evaluating such edges incoherence among the synthesized images which common...
Facial analysis plays very important role in many vision applications, such as authentication and entertainments. The very early works in the 1990s mostly focus on estimating geometric deformations of facial landmarks to address this task. While in the past several years, more and more efforts have been made to directly learn an appearance regression for facial analysis. Though training regressions...
Although organizations have widely adopted Business Process Management Systems (BPMS) as an automation and integration middleware, these systems remain limited in their orchestration capabilities. BPMS can only react to event information that enterprise applications emit and only integrate against the service interfaces these applications provide. At the same time, organizations increasingly leverage...
When performing a separation of test results, coping with enormous high-dimensional data sets is necessary but problematic. The input of high-dimensional data, in which not a few elements are irrelevant or less relevant than others, usually lead to inadequate results. It is therefore useful to consult methods, which classify the individual dimensions of the data volumes according to their relevance...
This work considers the problem of fault localization in transparent optical networks. The aim is to localize single-link failures by utilizing statistical machine learning techniques trained on data that describe the network state upon current and past failure incidents. In particular, a Gaussian Process (GP) classifier is trained on historical data extracted from the examined network, with the goal...
In database-driven spectrum sharing, despite the spectrum sharing policy given by a database, harmful interference can occur between a primary user (PU) and a secondary user (SU) due to the unexpected propagation paths. In a previous study, a primary exclusive region (PER) centered at a PU, wherein the SUs are forbidden to use the spectrum, has been proposed. However, the PER figure that efficiently...
Geochemical analyses can provide multiple analytical variables. Accordingly, the generation of large geochemical databases enables imputation studies or analytical estimates of missing values or complex measuring. The processing of bauxite is a key step in the production of aluminum, in which the determination of Reactive Silica (RxSiO2) and Available Alumina (AvAl2O3) are very relevant. The traditional...
This paper proposes a statistical analysis of photovoltaic output power and solar radiation for a photovoltaic system located in Iasi, Romania. The photovoltaic system performance can be analyzed using the correlation coefficients between the photovoltaic output energy and amount of global irradiance during different reference periods.
This study continues some previous research done on the hand physiological tremor (PT) signal - a motor phenomenon that we treated as a potential window to better understand the dynamical structures underlying the human visuomotor circuits. In order to understand how visual inputs processing interacts with limb motor system, two intermittent light stimulation (ILS) paradigms were implemented and the...
The main objective of this quantitative — relational work is to analyze the variation of the profitability according to the sources of financing of the Medium — sized Enterprises of Ecuador (MESE). In order to carry out this study, financial information of 168 companies of the province of Loja, obtained from the database of the Superintendence of Companies of Ecuador, is taken into account. As a period...
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