Search results for "Data type"

An Interactive Simple Indicator-Based Evolutionary Algorithm (I-SIBEA) for Multiobjective Optimization Problems

2015

This paper presents a new preference based interactive evolutionary algorithm (I-SIBEA) for solving multiobjective optimization problems using weighted hypervolume. Here the decision maker iteratively provides her/his preference information in the form of identifying preferred and/or non-preferred solutions from a set of nondominated solutions. This preference information provided by the decision maker is used to assign weights of the weighted hypervolume calculation to solutions in subsequent generations. In any generation, the weighted hypervolume is calculated and solutions are selected to the next generation based on their contribution to the weighted hypervolume. The algorithm is compa…

An EKF Based Method for Path Following in Turbulent Air

2017

An innovative use of the Extended Kalman Filter (EKF) is proposed to perform both accurate path following and adequate disturbance rejection in turbulent air. The tuned up procedure employs simultaneously two different EKF: the first one estimates gust disturbances, the second one estimates modified aircraft parameters. The first filter, by using measurements gathered in turbulent air, estimates both aircraft states and wind components. The second one, by using the estimated disturbances, obtains command laws that are able to reject disturbances. The predictor of the second EKF uses the estimated wind components to solve motion equations in turbulent air. Besides a set of unknown stability …

Survey: Intrusion Detection Systems in Encrypted Traffic

2016

Intrusion detection system, IDS, traditionally inspects the payload information of packets. This approach is not valid in encrypted traffic as the payload information is not available. There are two approaches, with different detection capabilities, to overcome the challenges of encryption: traffic decryption or traffic analysis. This paper presents a comprehensive survey of the research related to the IDSs in encrypted traffic. The focus is on traffic analysis, which does not need traffic decryption. One of the major limitations of the surveyed researches is that most of them are concentrating in detecting the same limited type of attacks, such as brute force or scanning attacks. Both the …

The Role of Log Entries in the Quality Control of Video Distribution

2012

Diversification of university teaching with the help of video lectures has become much more common during the past few years. Once videos have become an essential part of teaching arrangements, whoever organizes the teaching must also pay attention to factors related to videos in quality system work for teaching. In the video production process it is the factors related to video transmission that exert influence on the usability of videos and set limitations for their production. A lot of information about those factors can be obtained from the media server log files. The particular focus of this paper is on the functionality of the connection between a server and a client and its effect on…

Prediction of defects using machine learning techniques in order to improve quality management system – A case study

2021

According to ISO 9000, a quality management system is part of a set of related or interacting elements of an organization that sets policies and objectives, as well as the processes necessary to achieve the quality objectives. Quality is the extent to which a set of intrinsic characteristics of an object meets the requirements. Based on these definitions, the factory, considered in this paper, S.C. APULUM S.A.,decided to implement a quality management system since 1998. Subsequently, the organization’s attention is focus on the continuous improvement of the implemented quality management system. The purpose of this paper is to study the percent of specified defects specific to ceramic produ…

Paradigm of tunable clustering using Binarization of Consensus Partition Matrices (Bi-CoPaM) for gene discovery

2013

Copyright @ 2013 Abu-Jamous et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Clustering analysis has a growing role in the study of co-expressed genes for gene discovery. Conventional binary and fuzzy clustering do not embrace the biological reality that some genes may be irrelevant for a problem and not be assigned to a cluster, while other genes may participate in several biological functions and should simultaneously belong to multiple clusters. Also, these algorithms cannot generate tight cluster…

Quantitative lower bounds to the Euclidean and the Gaussian Cheeger constants

2020

We provide a quantitative lower bound to the Cheeger constant of a set $\Omega$ in both the Euclidean and the Gaussian settings in terms of suitable asymmetry indexes. We provide examples which show that these quantitative estimates are sharp.

THE GOLDMAN CONSTANT FIELD ASSUMPTION - SIGNIFICANCE AND APPLICABILITY CONDITIONS

1986

Ionic transport phenomena in simple, porous membranes can be approximately represented by the Nernst-Planck flux equations and Poisson's equation. In order to solve this set of equations for each particular case, the Goldman constant field assumption is one of the most widely used. In the present paper the significance and the applicability conditions of the above hypothesis is critically examined. and the particular situations where it is exact are shown. These conditions are later verified by solving numerically the electrodiffusion equations. The analysis carried out shows that some of the earlier studies based on asymptotic expansions and numerical solutions should be partially revised.

2D motif basis applied to the classification of digital images

2016

The classification of raw data often involves the problem of selecting the appropriate set of features to represent the input data. Different types of features can be extracted from the input dataset, but only some of them are actually relevant for the classification process. Since relevant features are often unknown in real-world problems, many candidate features are usually introduced. This degrades both the speed and the predictive accuracy of the classifier due to the presence of redundancy in the set of candidate features. Recently, a special class of bidimensional motifs, i.e. 2D motif basis has been introduced in the literature. 2D motif basis showed to be powerful in capturing the r…

2021

This paper proposes a new method for blind mesh visual quality assessment (MVQA) based on a graph convolutional network. For that, we address the node classification problem to predict the perceived visual quality. First, two matrices representing the 3D mesh are considered: a graph adjacency matrix and a feature matrix. Both matrices are used as input to a shallow graph convolutional network. The network consists of two convolutional layers followed by a max-pooling layer to provide the final feature representation. With this structure, the Softmax classifier predicts the quality score category without the reference mesh’s availability. Experiments are conducted on four publicly available …