127,576 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Further criterion for stochastic stability analysis of semi‐Markovian jump linear systems
No full textThis article is devoted to provide further criterion for stochastic stability analysis of semi-Markovian jump linear systems (S-MJLSs), in which more generic transition rates (TRs) will be studied. As is known, the time-varying TR is one of the key issues to be considered in the analysis of S-MJLS. Therefore, this article is to investigate general cases for the TRs that covered almost all types, especially for the type that the jumping information from one mode to another is fully unknown, which is merely investigated before. By virtue of stochastic functional theory, sufficient conditions are developed to check stochastic stability of the underlying systems via linear matrix inequalities formulation combined with a maximum optimization algorithm. Finally, a numerical example is given to verify the validity and effectiveness of the obtained results
Analysis of damage mechanisms in drilling of composite materials by acoustic emission
No full textComposite Structures
Volume 131, November 01, 2015, Pages 107-114
Analysis of damage mechanisms in drilling of composite materials by acoustic emission (Article)
Zarif Karimi, N.a ,
Minak, G.a ,
Kianfar, P.b
a Alma Mater Studiorum-Università di Bologna, Department of Industrial Engineering DIN, via Fontanelle 40, Forlì, Italy
b Amirkabir University of Technology, Department of Bioengineering, 424 Hafez Ave., Tehran, Iran
View references (49)
Abstract
Conventional methods for analysis of drilling of composite materials usually study the amount of damaged area and effective parameters. However, these methods do not provide investigators with sufficient information regarding drilling-induced damage. In this paper, a procedure for discrimination and identification of different damage mechanisms based on the analysis of acoustical signals emitted during the process is presented. Using principle component analysis for data reduction and unsupervised pattern recognition analysis, the drilling process was divided into three main stages, i.e. entry stage, cutting stage and exit stage. Different methods of signal processing were then used to identify and discriminate the most active damage mechanisms in each stage. As a result, matrix cracking, delamination, fiber pull out and friction were discriminated and the frequency distribution of each one was identifie
Non-rigid image registration to reduce beam-induced blurring of cryo-electron microscopy images
No full textMicroscopic imaging and technolog
Passive and active flow control effects in the platoon and overtaking maneuvers
No full textThe current numerical study is dedicated to investigating the effect of passive, active, and combined flow control techniques on the performance of the vehicles in different maneuvers including, platoon and overtaking on critical highway velocity (70 miles per hour) for a reference bluff body vehicle called Ahmed body. The target passive flow control method is an innovative technique called Rear Linking Tunnels (RLTs), introduced previously by the group of authors. Studying the effect of the Single Dielectric Barrier Discharge Actuator (SDBD) as an active flow control method and its combined effect with RLTs on the drag and lift of controlled vehicles and surrounding vehicles in various maneuvers is one of the main aims of this research study
A logarithmic descent direction algorithm for the quadratic knapsack problem
No full textThe quadratic knapsack problem is an NP-hard optimization problem with many diverse applications in industrial and management engineering. However, computational complexities still remain in the quadratic knapsack problem. In this study, a logarithmic descent direction algorithm is proposed to approximate a solution to the quadratic knapsack problem. The proposed algorithm is based on the Karush–Kuhn–Tucker necessary optimality condition and the damped Newton method. The convergence of the algorithm is proven, and the numerical results indicate its effectiveness
A traverse algorithm approach to stochastic stability analysis of Markovian jump systems with unknown and uncertain transition rates
No full textThis paper intents to investigate the problem of mean-square stability analysis of Markovian jump systems with generally unknown and uncertain transition rates. Different from pervious works that the transition rates from one mode to others may be partially unknown or uncertain, in this note, the case that the transition rates from one mode to others are totally unknown will be investigated. By means of transition rate estimation, two ways are provided to tackle with the totally unknown case. In general, five cases in the transition rates matrix are studied for the mean-square stability analysis, which almost have covered all types of generally unknown and uncertain transition rates. Simultaneously, corresponding conditions for checking the mean-square stability of the considered Markovian jump systems are developed for the five studied cases. Finally, numerical examples are provided to verify the effectiveness of the proposed results
Deep learning-based automated tile defect detection system for Portuguese cultural heritage buildings
No full textA prominent feature in Portuguese historic architecture is Portugal's azulejos or tiles that cover cultural heritage buildings with colorful patterns. However, tiles are prone to deterioration due to the quality of masonry materials, exposure over time, and natural and human factors. A careful approach is necessary to detect and assess tile damage in time to conserve cultural heritage. Deep learning (DL) methods are applied to detect deterioration and damage by automating vision-based monitoring. This study uses the You Only Look Once (YOLO), method to detect deterioration in tiles automatically. To obtain the initial dataset, over 5000 images of damage were collected, including cracks, craters, glaze detachment, and tile lacunae, as well as images with no defects. Additionally, a MobileNet model was used for binary classification of damaged and intact tiles to compare classification and detection approaches. Through the fine-tuning of hyperparameters and updating the dataset, an overall accuracy of over 72% for YOLO (multiple classification) and 97% accuracy for binary classification was achieved, demonstrating the adequacy of the tool for real-world applications
Performance enhancement of single dielectric barrier discharge flow control actuators by means of rear linking tunnels on a reference bluff body using CFD
No full textThis paper studies drag reduction on a reference bluff body (Ahmed body) with single dielectric barrier discharge (SDBD) actuators, also called plasma actuators, located at different positions on the model’s rear part with a spanwise arrangement. This active actuator modifies the laminar-to-turbulent transition leading to reattachments of separated flows on the body. A reduction of actuator efficiency when increasing velocity is the main limitation of this method. The main aim of this work is to find a solution for this problem by employing passive flow control to improve the SDBD actuators’ efficiency. For this purpose, rear linking tunnels are added to the model as a novel passive flow control. Numerical simulations were performed to determine the best position of the active actuators on the model. The next step is to study the effect of the passive and active flow control on drag reduction and investigating the combination of these methods for improving the active flow control performance at four different freestream velocities (Re 1⁄4 0.289 106–0.722 106). The positive effect of this combination is noticeable (a 59% increase in the SDBD actuator’s efficiency for Re 1⁄4 0.722 106), and the non-linear behaviour of this combination leads to high drag reduction of between 13.29% and 17.96% for different Reynolds numbers
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