Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
This paper mainly studies the relief extraction and data processing in image fusion design. To depend on plane interception and geometric detail extraction in detail shift of point model, intercepting plane is built and the segmentation between relief and base plane of relief product is realized through plane interception. Then, the extracted intermediate relief is performed the isolated sampling...
Nowadays, mining approximate frequent itemsets from noisy data has attracted much attention in real applications. However, there is not widely accepted algorithm at present to solve the problem under noisy databases, which dues to two key issues. Firstly, the anti-monotonicity property does not hold which is used to prune candidate itemsets efficiently. And secondly, the computation of support counting...
Security of published data cannot be less important as compared to unpublished data or the data which is not made public. Therefore, PII (Personally Identifiable Information) is removed and data sanitized when organizations recording large volumes of data publish that data. However, this approach of ensuring data privacy and security can result in loss of utility of that published data for knowledge...
Data Streams are instances that arrive at a very rapid rate with changes in underlying conceptual distributions. Many ensemble learning approaches were developed to handle these changes in the dataset, which proved to be better than a single classifier system. In our work, we will discuss the framework of our new approach, Double Weighted Methodology and empirically prove it to be better than the...
Many democratic countries choose their representatives through electronic elections. Even being a modern tool, its results can be explored maliciously. Because that, many instruments and protocols are using to protect electronic elections from attacks. This work propose a new system to improve the security in electronic elections. It is based on analyses of behavior voter to detect urns with dissonant...
Feature selection is based on the notion that redundant and/or irrelevant variables bring no additional information about the data classes and can be considered noise for the predictor. As a result, the total feature set of a dataset could be minimized to only few features containing maximum discrimination information about the class. Classification accuracy is used as the evaluation measure in guiding...
Noises are inevitable when mining software archives for software fault prediction. Although some researchers have investigated the noise tolerance of existing feature selection methods, few studies focus on proposing new feature selection methods with a certain noise tolerance. To solve this issue, we propose a novel method FECS (FEature Clustering with Selection strategies). This method includes...
This paper presents a density based clustering (DBSCAN) technique to visualize and analyze the smart-grid data. The technique will aid in detecting bad-data, various fault types, deviation on frequency, voltage or current values for better situational awareness. Synchrophasors (or a PMU) is a sensor placed on a transmission line that tracks voltage, current, phase and frequency of the line. To improve...
Improvement of classification accuracy is importance in data analysis problems. Enhancement of techniques have been proposed previously to address the problems as regard to classification performance, however, the issues of misclassification and noise elimination in the early stage of processing have been ignored by many researchers. If these problems were addressed, the performance of the classification...
The article analyses effects of price signals on the consumption behavior of household electricity customers. It proposes a systematic analysis process consisting of data preprocessing, aggregation steps and clustering methods. This analysis process was applied to two smart meter datasets (Olympic Peninsula Project, RESIDENS). Large fluctuations in customers' response to the same price signal were...
Synchrophasors are the state-of-the-art measuring sensors that sense voltage, current, or frequency with high data rate. This paper presents an approach to analyze the streaming smart-grid data generated by synchrophasors. A novel unit-circle representation is used to visualize the real-time phasor data. A Density based clustering (DBSCAN) method is proposed to cluster the phasor data to detect bad-data...
We present a transformation procedure for large scale individual level data that produces output data in which no linear combinations of the resulting attributes can yield the original sensitive attributes from the transformed data. In doing this, our procedure eliminates all linear information regarding a sensitive attribute from the input data. The algorithm combines principal components analysis...
With the technological evolution in telecommunication networks, performance requirements such as better coverage, higher bandwidth, and lower latency have been pushed to new horizons. However, as a direct result network complexity has increased dramatically over the recent years, and with this complexity manageability has suffered. This paper presents the architecture of the E-Stream project which...
Distortions in electrocardiogram (ECG) signals affect the image quality and increase scan time of Cardiac Magnetic Resonance Imaging (CMRI) exams. This study proposes an alternative method of acquiring CMRI cine images in mouse heart using a self-gated Ultra-short Echo Time (UTE) protocol. In our method, a bandpass filter and a lowpass filter are adopted to extract the self-gated signals from the...
Currently the volume of telecom network management data is expanding exponentially, mainly due to the explosive growth in the number of communicating devices along with the increase in heterogeneity of the networks. Such scale of data obsoletes the traditional approach of extracting offline analytics from the network traces governed by some pre-defined schemes. In order to increase the efficiency...
The reliability of a prediction model depends on the quality of the data from which it was trained. Therefore, defect prediction models may be unreliable if they are trained using noisy data. Recent research suggests that randomly-injected noise that changes the classification (label) of software modules from defective to clean (and vice versa) can impact the performance of defect models. Yet, in...
Understanding the severity of reported bugs is important in both research and practice. In particular, a number of recently proposed mining-based software engineering techniques predict bug severity, bug report quality, and bug-fix time, according to this information. Many bug tracking systems provide a field "severity" offering options such as "severe", "normal", and...
Clustering is a technique in which a given data set is divided into groups called clusters in such a manner that the data points that are similar lie together in one cluster. Clustering plays an important role in the field of data mining due to the large amount of data sets. This paper reviews the various clustering algorithms available for data mining and provides a comparative analysis of the various...
The task of determining informative sensors and clustering the sensor measurements according to their information content is considered. To this end, the standard canonical correlation analysis (CCA) framework is equipped with norm-one and norm-two regularization terms to estimate the unknown number of field sources and identify informative groups of sensors. Coordinate descent techniques are combined...
Visualization of sound field using Schlieren technique provides many advantages. It enables us to investigate the change of the sound field in real-time from every point of the observing region. However, since the density gradient of air caused by the disturbance of acoustic field is very small, it is difficult to observe the audible sound field from the raw Schlieren video. In this paper, to enhance...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.