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.
Digital elevation model (DEM) is primarily a way of visualising 2D maps, photographs and images in 3D. Common uses of DEMs are creation of relief maps, rendering of 3D visualizations, rectification of satellites images and aerial photographs, creation of different physical models, etc. DEMs can be produced by different methods. In this study, DEMs are produced by 1:25000 digital topographic maps,...
A performance metric like Linearity, Sensitivity as well as Accuracy will determine the successful behavior and performance of Metal Oxide Semiconductor Field Effect Transistor. In analytical modeling of any length or of any structure MOSFET, it is essential to be well-informed about its characteristics as compared to simulator. And this can be achieved by developing effective metrics. In this paper,...
This article offers a general approach to developing methods of determining operation tolerances for the parameters' values of memristor-based artificial neural networks (ANNM), as a system that constitutes an united physical and informational object implemented by the hardware and software learning facilities. While looking for a solution to the issues of analysis and synthesis of this system's tolerances,...
This paper examines the quality of feature set obtained from Wavelet based Energy-entropy with variation of scale and wavelet type. Here motor imagery of left-right hand movement classification problem has been studied. Elliptic bandpass filters are used to discard unwanted signals and also to extract alpha & beta rhythms. We have implemented wavelet-based energy-entropy with three level of decomposition...
The Weighted Center Localization (WCL), which is a classical localization scheme for the Wireless Sensor Network (WSN), can't decrease the average localization errors and the maximum errors simultaneously due to the fixed weight argument. Improving the localization accuracy of WCL is to decrease the distance measurement errors or to set a proper dynamic weight argument. We have already improved the...
Due to the increasing interest of the emerging millimeter wave (mmWave) frequency band for application to cellular networks, new flexible and scalable approaches for their modeling, analysis and optimization are needed. Recently, a new approach has been proposed: it is based on the theory of point processes and it leverages tools from stochastic geometry for tractable system-level modeling, performance...
Radiation-induced soft errors are major reliability concerns in advanced technology nodes. The de facto approach for evaluation of the soft error vulnerability is to perform a costly fault injection campaign. Due to the long residency of some errors in system states, the error has to be traced for even millions of cycles. However, only a very small portion of injected errors leads to the failure....
A relevant aspect in design analysis and verification is monitoring how logic relations among different variables change at run time. Current static approaches suffer from scalability problems that prevent their adoption on large designs. On the contrary, dynamic techniques scale better from the memory-consumption point of view. However, to achieve a high accuracy, they require to analyse a huge number...
A first error analysis for finite element solutions of time-harmonic boundary value problems involving cylinders moving in the axial direction is carried out. It is shown that the solutions are affected by errors which behave in a very regular way, as it happens with traditional problems and finite element simulators in the presence of motionless objects. The effects of the motion on the errors considered...
In this paper, we develop the max-margin similarity preserving factor analysis (MMSPFA) model. MMSPFA utilizes the latent variable support vector machine (LVSVM) as the classification criterion in the latent space to learn a discriminative subspace with max-margin constraint. It jointly learns factor analysis (FA) model, similarity preserving (SP) term and max-margin classifier in a united Bayesian...
In this paper, a novel analytical method based on CADET (covariance analysis description equation technique) is proposed to solve the computing problem of the precision of the three-dimensional shooting engine when evaluating the effectiveness of the three-dimensional virtual shooting system. This method statistical linearizes the nonlinear factors that will affect shooting accuracy, and then get...
Software code review is a process of developers inspecting new code changes made by others, to evaluate their quality and identify and fix defects, before integrating them to the main branch of a version control system. Modern Code Review (MCR), a lightweight and tool-based variant of conventional code review, is widely adopted in both open source and proprietary software projects. One challenge that...
An efficient way to deal with the time series prediction problem in grey perturbed systems is by constructing effective grey operators. Due to the fixed structures of existing strengthening operators, the action intensity of these operators cannot be effectively controlled. This study aims to propose some nonlinear strengthening operators with flexible structures to effectively control the action...
A multivariate discrete grey forecasting model is proposed to solve the problem that the qualitative relative factors can't be employed in traditional models. Firstly, a new model is constructed though introducing dummy drivers. Then, the parameters estimation method and recursive function of the model are discussed. Furthermore, dummy driver setting, pre and posttest methods of dummy drivers are...
Confirmation bias is the human tendency to search for, collect, interpret, analyse, or recall information in a way that confirms one's prior beliefs or preferences. In this paper, we review previous research and demonstrate confirmation bias and its effect in two software engineering contexts. The first study documents that managers bias their interpretation of randomly generated project data towards...
In machine learning, ensemble model is combining two or more models for obtaining the better prediction, accuracy and robustness as compared to individual model separately. Before getting ensemble model first we have to assign our training dataset into different models, after that we have to select the best model suited for our data sets. In this work we explored six machine learning parameter for...
The opinion conveyed by the user towards a movie can be understood by doing Sentiment Analysis on the movie review. In the current work we focus on Genre Specific Aspect Based Sentiment Analysis of Movie Reviews. Using the aforementioned dataset and considering movie genres like action, comedy, crime, drama and horror, we develop a fine grained unsupervised analysis model using lexicons that are context...
Enterprise in financial trouble is a comprehensive event and the enterprise financial situation can be reflected through the liquidity ratio, earnings per share and net assets per share and cash content per share. Artificial neural network method is used to establish the financial early warning model to find the potential financial crisis at an early age. The experiment results show that BP neural...
Analytical methods for estimating on-chip network performance can be very useful to accelerate and simplify the design process of Networks on Chip. However, in order to increase the confidence in these approaches it is fundamental to perform systematic studies that assess their potential. We present a methodical investigation on the tightness between analytical end-to-end delay bounds and worst-case...
In this paper we introduce an object-based change detection model using correlation analysis and classification. First we use eCognition to obtain an over-segmentation map. Then linear regression is used to gain three unique types of parameters — regression coefficient, offset, and correlation coefficient which can provide valuable information about the location and numeric change value derived within...
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.