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.
Mild cognitive impairment (MCI) is a transition stage between normal aging and dementia. Brain network has been proven to occupy an important role in the study of differences in Alzheimer's disease (AD) and MCI. However, there is little knowledge about individual metabolic network abnormities which might be sensitive features in the prediction of MCI progression. In this paper, we constructed the...
With the rapid growth of the web services technologies, users often leverage various web services to perform their daily activities, such as on-line shopping. Due to the massive amount of web services available, a user faces numerous choices to meet their personal preferences when selecting the desired services from the web services with the similar functionality. Therefore, it becomes tedious and...
In order to recognize faults of the high voltage circuit breaker (HVCB) in the whole fault state space precisely and minimize the impact of the lack of fault data on the accuracy of fault recognition, a method of fault recognition was proposed based on the incremental learning algorithm for SVM. Firstly, the incremental learning algorithm for SVM was analyzed theoretically, and the state monitoring...
In this paper, an approach using the spatio-temporal feature and nonnegative locality-constrained linear coding (NLLC) is proposed to detect abnormal events in videos. This approach utilizes position-based spatio-temporal descriptors as the low-level representations of a video clip. Each descriptor consists of the position information of a space-time interest point and an appearance feature vector...
In traditional Chinese medicine (TCM), it is frequently found that more than one syndrome of a patient are recognized in clinical practice, which has its own symptoms and signs. While, most algorithms are used to solve issues of syndrome diagnosis that only focus on one syndrome. Therefore, we proposed a hybrid intelligent syndrome diagnosis (HISD) model. Methods. The HTSD model combined feature selection...
In order to track degradation trend of bearing performance using shock feature hidden in vibration signal, a best Morlet wavelet transform-based extraction method of full information energy entropy was proposed through integrating Morlet wavelet transform technology and full information technology. The optimization of Morlet wave shape factor was controlled by the minimum Shannon entropy. The information...
Pathological image retrieval contributes to computer-aided diagnosis for breast cancer due to the fact that the retrieval results generally contain detailed diagnostic information (e.g. abnormal regions and diagnostic opinion from other doctors) which can offer some reference and assistance to the doctor during diagnosis process. In this paper, we present a novel pathological image retrieval approach...
This paper presents a method to determine music-motion correspondence.For specific type of dance and music,system extract low-level features,calculate correspondence ,then select muisc-motion correspondence using genetic algorithms,and get a correspondence satisfing match accuracy and operation speed in the end.The experimental results indicate that system fully express the changes between music and...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.