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.
Surrogate-Assisted Evolutionary Computation (SAEC) has widely applied to approximate an objective function. However, SAEC may potentially also reduce the processing time of inexpensive optimization problems wherein solutions are evaluated within a few seconds or minutes. To achieve this, the approximation model of a fitness function should be iterated as few times as possible during optimization....
Motivated by the question of whether the recently introduced Reduced Cutset Coding (RCC) [1], [2] offers rate-complexity performance benefits over conventional context-based conditional lossless coding for sources with two-dimensional Markov structure, this paper compares several row-centric coding strategies that vary in the amount of conditioning as well as whether a model or an empirical table...
It was first observed by John Bell that quantum theory predicts correlations between measurement outcomes that lie beyond the explanatory power of local hidden variable theories. These correlations have traditionally been studied extensively in the probabilistic framework. A drawback of this perspective is that one is then forced to use in a single argument the outcomes of mutually-exclusive measurements...
This research proposes a comparative analysis of the performance of various random utility models (RUM) — namely Multinomial Logit, Nested Logit, Cross Nested Logit, FinMix and CoNL-estimated on a synthetic dataset with variable sample size and correlation patterns. This experimental framework allows comparing model estimates in a fair, controlled environment wherein all relevant characteristics (coefficients,...
This work deals with the application of the Kriging technique for the accurate modeling of analog circuits, namely, a CMOS second generation current conveyor, and a CMOS voltage follower. Three types of correlation functions are used for this purpose: the Spline, the Gaussian and the Exponential Correlation functions. A comparative study is given. Two metrics are used; Root Mean Square Error and the...
Typical neuroimaging studies analyze associations between physiological or behavioral traits and brain structure or function. Some rely on predicting these scores from neuroimaging data. To explain association between brain features and multiple traits, reduced-rank regression (RRR) models are often used, such as canonical correlation analysis (CCA) and partial least squares (PLS). These methods estimate...
Statistical craniofacial reconstruction methods have become an important research aspect in computer-aided craniofacial reconstruction. The existing joint statistical craniofacial reconstruction method based on PCA modeling is not scientific in terms of forensic anthropology, and its description ability for the shape correlation of skull and face is inadequate. So, partial least squares regression...
According to the influence of the stand spatial structure on the crown shape of Chinese fir, a new method of diversified 3D Chinese fir modeling based on spatial structure was proposed. In this study, spatial structure units that were divided by a reasonable method were selected in Chinese fir stands. And the data of spatial structure and crown shape in different units was surveyed. Two parameters...
Saliency detection is an important problem in many computer vision applications. As a kind of popular method, graph based manifold ranking (GMR) has been successfully used in saliency detection problem. In traditional GMR saliency detection, it involves two main stages, i.e., ranking with background queries and ranking with foreground queries. However, in GMR method, these two stages are conducted...
The inference of the network traffic matrix from partial measurement data becomes increasingly critical for various network engineering tasks, such as capacity planning, load balancing, path setup, network provisioning, anomaly detection, and failure recovery. The recent study shows it is promising to more accurately interpolate the missing data with a three-dimensional tensor as compared to interpolation...
Analog computational circuits have been demonstrated to provide substantial improvements in power and speed relative to digital circuits, especially for applications requiring extreme parallelism but only modest precision. Deep machine learning is one such area and stands to benefit greatly from analog and mixed-signal implementations. However, even at modest precisions, offsets and non-linearity...
Post silicon trimming is extensively used to counter the effects of manufacturing process variation on certain critical electrical parameters of an integrated circuit (IC). Usually, trimming is performed iteratively by adjusting the resistance value of a trim circuit to specific discrete values. Test programs represent those values by codes and apply common search algorithms in order to find a code...
Evaluating and scoring essay questions is an exhausting, time consuming process and require a lot of effort. So, applying automated tools is essentially required to tackle these drawbacks. In this study, we propose an automated scoring approach for short answers to Arabic essay questions. The scoring process is based on the similarity between the student's answer and model answer, cosine similarity...
The paper proposes the use of just mostly voiced speech (MVS) for speaker verification (SV). The speech is partitioned into an MVS part and a non-MVS part by a simple machine classification. SV experiments were held with a standard Gaussian mixture model (GMM) with universal background model (UBM) system and a GMM with computationally improved individual background model (IBM) system. They demonstrate...
The amount of video traffic on the Internet has seen a tremendous increase over the past few years. In 2020, it is predicted to account for 85% of the total Internet consumer traffic. Due to this dominant role, streaming traffic has to be considered by workload models used to evaluate the performance of networking systems. A de facto standard technology for Internet-based Video on Demand (VoD) services...
Automotive Machine Type Communication (MTC) features three groups of applications: safety, road traffic efficiency and infotainment. The concrete set of automotive applications is yet uncertain. This application uncertainty and, thus communication traffic uncertainty, directly translates into the need for a highly flexible traffic model. Traffic model is required in order to chose appropriate communication...
Large data analysis problems often involve a large number of variables, and the corresponding analysis algorithms may examine all variable combinations to find the optimal solution. For example, to model the time required to complete a scientific workflow, we need to consider the impact of dozens of parameters. To reduce the model building time and reduce the likelihood of overfitting, we look to...
This paper introduces an approach that handleswith the trustworthy cloud service selection issue in Cloudcomputing environments. Despite the fact that most of theexisting trust systems consider several QoS attributes for trustcomputing, none of them did consider the correlation that mayexist among these attributes. However, we demonstrate in thispaper that the integration of correlation between QoS...
Soft sensors are used to infer the quality variable from easy-to-measure process variables. The conventional static soft sensor is incapable of handling the dynamic of processes. For data-based soft sensor development, with abundance of the raw sensor data, the problem of variable correlations and large number of sample are encountered. This work presents a latent variable model (LVM) based active...
diverse cloud applications deployed on-demand make for workload burstiness. Burstiness is quantified statistically through different variance measures. This paper focuses on the statistical measures used to quantify cloud workload burstiness. Using diverse workloads, it identifies different statistical models that uniquely capture workload specific burstiness. Subsequently, it employs recent econometric...
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.