The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
For better resolving the safety risk early warning of the apron effectively, the attribute reduction algorithm based on Rough Set is used to simplify the set as the warning index set of the apron is too large. The improved Particle Swarm Optimization (PSO) algorithm is used to optimize the parameters of Support Vector Machine. Combined with the Rough Set and SVM which is optimized by the improved...
Individualized blood transfusion management would benefit from the ability to prospectively identify patients at risk of complications of blood transfusion, and target them for closer monitoring or intervention. This study presents a simple and efficient multi-task learning method for predicting multiple surgical outcomes based on the weighted least squares support vector machine. To accelerate the...
Tuberculosis is one of the top ten causes of death worldwide. Although this disease is curable and preventable, yet many new tuberculosis cases still occur especially in developing countries. Many low-income families cannot afford the medical diagnosis for tuberculosis. Therefore, this paper proposes an initial screening for tuberculosis infection using a data mining approach. In this paper, the initial...
Gas Insulted Switchgear (GIS) plays an important role in switch, control and protection and its safe and reliable operation is vital to the power system. However, its partial discharge failure usually cause serious consequences. It is necessary to monitor SF6 insulated power equipment operation state by detecting and analyzing the gas decomposition components with the aid of pattern recognition algorithm...
Compared with H.264, High Efficient Video Coding (HEVC) improves the coding efficiency by 50% at the price of significant increase in encoding time, due to Rate Distortion Optimization (RDO) on large variations of block sizes and prediction modes. In this paper, a fast intra coding algorithm is proposed to alleviate the high computational complexity of HEVC intra-frame coding. The proposed algorithm...
Software components, which are vulnerable to being exploited, need to be identified and patched. Employing any prevention techniques designed for the purpose of detecting vulnerable software components in early stages can reduce the expenses associated with the software testing process significantly and thus help building a more reliable and robust software system. Although previous studies have demonstrated...
This study is carried out on application of different machine learning techniques for prediction of features using bioinformatics data such as that of cancer. The prediction process is undertaken based on feature extraction and then on feature selection process. After selecting the relevant features, machine learning techniques like Support vector machine (SVM), Extreme learning machine (ELM) are...
Accurate modeling of Electroencephalography (EEG) signals is an important problem in clinical diagnosis of brain diseases. The method using support vectors machine (SVM) based on the structure risk minimization provides us an effective way of learning machine. But solving the quadratic programming problem for training SVM becomes a bottle-neck of using SVM because of the long time of SVM training...
The attorney's office in Brazil, receive daily a lot of notifications. These notifications must be manually analyzed by procurators to determine what kind of document should they prepare to respond. This situation causes in many cases notifications are not answered in time causing these prescribed. All this has motivated the development of this work whose main objective is the development of a computational...
Diabetes is a disease caused due of the expanded level of sugar fixation in the blood. Various computerized information systems were outlined utilizing diverse classifiers for anticipating and diagnosing diabetes. Selecting legitimate classifiers clearly expands the exactness and proficiency of the system. Here a decision support system is proposed that uses AdaBoost algorithm with Decision Stump...
This paper introduces a novel approach to predict human motion for the Non-binding Lower Extremity Exoskeleton (NBLEX). Most of the exoskeletons must be attached to the pilot, which exists potential security problems. In order to solve these problems, the NBLEX is studied and designed to free pilots from the exoskeletons. Rather than applying Electromyography (EMG) and Ground Reaction Force (GFR)...
Cost-performance trade off is one of the critical challenges in cloud computing environments. Predictive auto-scaling systems mitigate this issue by scaling in/out system automatically based on performance prediction results. The goal of this research is to investigate the impact of different prediction results on the scaling actions generated by predictive auto-scaling systems. In this study, predictive...
Support vector machine (SVM) can ensure the promotion capability of machine model, so it is widely used in various fields. The selection of SVM's parameters has a great effect on its performance, if genetic algorithm (GA) is introduced to optimize support vector machine's parameters, the effect will be better. Traditional GA-SVM algorithm can optimize SVM parameters including penalty factor C and...
Aiming at increasing the precision of tunnel settlement prediction, a modified support vector machine (SVM) based on the dynamic on-line sliding window (Dolsw) technique is proposed. In the prediction model, the historically observational settlement data act as the learning samples. The nonlinear relationship between settlement data and influencing variables is established on the basis of on-line...
As a new model of distributed computing, all kinds of distributed resources are virtualized to establish a shared resource pool through cloud computing. The target of cloud computing is to provide convenient and configurable resource for users with pay-per-usage charging model. Therefore, the reasonable and efficient mechanism for resource allocating is becoming a hot spot in research. According to...
Support Vector Machines are the state-of-the-art tools in data mining. However, their strength are also their main weakness, as the generated nonlinear models are typically regarded as incomprehensible black-box models. Therefore, opening the black-boxor making SVMs explainable became more important and necessary in areas such as medical diagnosis and credit evaluation. Rule extraction from SVMs,...
Finding the location of binding sites in DNA is a difficult problem. Although the location of some binding sites have been experimentally identified, other parts of the genome may or may not contain binding sites. This poses problems with negative data in a trainable classifier. Here we show that using randomized negative data gives a large boost in classifier performance when compared to the original...
The identification of disease-related microRNAs is vital for understanding the pathogenesis of disease at the molecular level and may lead to the design of specific molecular tools for diagnosis, treatment and prevention. Experimental identification of disease-related microRNAs poses difficulties. Computational prediction of microRNA-disease associations is one of the complementary means. However,...
MicroRNAs (miRNAs) are small Ribonucleic Acid (RNA) molecules ~18-22 nucleotides (nt) in length that regulates gene expression in animals, plants and viruses. Due to its small size and occurrence in different development stages of organisms, the experimental identification of miRNAs becomes difficult, and computational approaches are being developed in order to precede and guide biological experiments...
SVM is powerful for the problem with small samples, non linear and high dimension. But such important parameters as the kernel function parameters, the insensitive parameters and the penalty coefficient are determined based on experience and cross-validation in the SVM, so it has certain blindness. In the paper, support vector machine optimized particle algorithm is used to predict the intensity of...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.