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.
This contribution aims at studying the input impedance of household appliances in the frequency range from 9 kHz to 500 kHz (FCC band). The method using the network analyzer is chosen as it provides a very good trade-off between required accuracy and ease of use. Some of the most common household appliances present in customer installations are characterized in terms of impedance in their respective...
Modern methods of a three-dimensional digital model of the surface of objects with high accuracy were presented. The method of solving this problem by modulating the light intensity, which scans the object, was proposed. This allows increasing both the speed and the resolution of the scanner due to reducing degradation of the scanning line and capabilities to accurate reference subject position profile...
In this article the results of testing of numerical methods of solution of differential equations describing the systems with chaotic dynamics in MATLAB are discussed. The results of evaluation of the actual error, the global error and root-mean-square error of the numerical solution of the test differential equation system are discussed. The results of evaluation of the main radio technical parameters...
We propose a new pretreatment for pedestrian detection with convolutional networks. It is widely known that the phenomenon of overlapping feature distribution is common, which leads to overfitting problem. We present a method that divide one category that have overlapping distributed features into multi-subcategories. By this means smooth boundaries can be easily found to separate different subcategories,...
In the daily audit work, informationization brings huge amounts of business data. Auditors face huge amounts of data, and personnel allocation has no planned way. In order to solve these practical problems, we introduce the data mining technology. Isolated point algorithm based on unit is applied to computer network audit. Boundary cell value of the isolated point algorithm is adjusted. By means of...
Need of effective and efficient Intrusion Detection System, used the concept of hybrid approach in Iintrusion Detection System where many combination of different techniques has been used so far. In this paper, proposed hybrid approach which is the combination of Fuzzy C-Mean (FCM), a clustering technique and Support Vector Machines (SVM) will be compared with K-Means and SVM, K-Means and Naïve bayes,...
Now days to prevent malicious use of original companies logos or identity, the automated image processing based frameworks are presented. The process of logo detection and recognition hence becoming the vital task for various applications. In this project we are presenting automated framework for logo detection using the real world logos images and its test image. Basically the working is that input...
Machine learning based classifiers used quite often for predicting forest cover types, are the Naïve Bayes classifier, the k-Nearest Neighbors classifier, and the Random forest classifier. This paper is directed towards examining all of these classifiers coupled with feature selection and attribute derivation in order to evaluate which one is best suited for forest cover type classification. Numerous...
In this paper, the various technologies of data mining (DM) models for forecast of heart disease are discussed. Data mining plays an important role in building an intelligent model for medical systems to detect heart disease (HD) using data sets of the patients, which involves risk factor associated with heart disease. Medical practitioners can help the patients by predicting the heart disease before...
Privacy-preserving data publishing is an important problem which exists in research and has become increasingly vital in recent years. We come across situations where a data owner wishes to publish data without revealing private information. A known solution to this problem is differential privacy which is a research topic that implements noise injection using the Laplace distribution and building...
Textile inspection system, which carries a lot of importance in the production process of textile goods, has been part of a great deal of research for automating the process. Manual textile inspection is a lengthy, slow as well as erroneous job; therefore, automation of textile inspection is a demand of time. Machine vision based i.e. automated fabric inspection deals with two primary challenges,...
EEG based controls are extensively used in applications such as autonomous navigation of remote vehicles and wheelchairs, as prosthetic control for limb movements in health care, in robotics and in gaming. The work aimed at implementing and classifying the intended controls for autonomous navigation, by analyzing the recorded EEG signals. Here, eye closures extracted from the EEG signals were pulse...
This paper describes an algorithm that parallelizes support vector machines. The data is split into subsets and optimized separately with multiple SVMs, instead of analyzing the whole training set in one optimization step. The partial results are combined and filtered in a cascade of SVMs. The process terminates when the global optimum is reached. The Cascade SVM is spread over multiple processors...
Predicting stock market accurately has always fascinated the market analysts. During the previous few decades assorted machine learning techniques (Regression, RBFN, SOM, BN and SVM) have been applied to examine the highly debatable nature of stock market by capturing and using repetitive patterns. Our main aim is to accurately predict value for the future and maximum amount of profit for a holder...
On an average 9 out of 10 startups fail(industry standard). Several reasons are responsible for the failure of a startup including bad management, lack of funds, etc. This work aims to create a predictive model for startups based on many key things involved at various stages in the life of a startup. It is highly desirable to increase the success rate of startups and not much work have been done to...
Quality assurance (QA) is a crucial process to ensure the maximize accuracy of the data delivered to client. Equipped with many moving parts whose relative positions can change over time depending on use, handling frequency and care, the QA is essential for TLS. Furthermore, with rapid and dense three-dimensional (3D) data collection ability, TLS has gain interest for many accurate 3D applications...
In this paper we apply particle swarm optimization (PSO) feature selection to enhance Hidden Markov Model (HMM) states and parameters for face recognition systems. Ideal Feature selection for face images based on the idea of collaborative behavior of bird flocking to reduce the feature size and hence recognition time complicity. The framework has been inspected on 400 face pictures of the Olivetti...
The accuracy of the eye tracking systems is a key indicator of data validity. Currently developed eye tracking systems can be configured to be used as remote wireless autonomous systems. In order to meet the required constraints of system's responsiveness and effectively use the available hardware, image compression techniques can be employed in order to reduce the amount of data needed to be sent...
The musculoskeletal disorder is still one of the significant concerns among all work-related injuries. A great deal of research efforts had been made in developing tools that can be used in practical working environments for real time assessment of manual workloads. To perform those evaluations, the working posture analysis is required. Recently, the RGB-D camera has been considered by researchers...
New technology advances provide more sophisticated features which increasingly require complex software. The growing complexity of software presents a significant challenge to software quality and reliability. The prediction of defects in software is aimed at maintaining software quality without allocating a lot of resources in the quality assurance activities. The distribution of defects in modules...
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.