Automatic feedrate control systems have recently been introduced to lighten the job of combine harvester operators by adjusting the driving speed according to the amount of biomass entering the straw elevator. However...
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Automatic feedrate control systems have recently been introduced to lighten the job of combine harvester operators by adjusting the driving speed according to the amount of biomass entering the straw elevator. However, knowledge of the crop in front of the machine could considerably improve their performance. Therefore, the feasibility of using two types of Light Detection And Ranging (LiDAR) sensor, and different methods of onlinedata-processing for estimating crop density in front of a combine harvester, has been investigated. Using either of both sensor types to measure the variation in laser penetration depth, good crop density estimations were obtained for different driving speeds and machine vibrations with coefficients of determination (R(2)) in the range 0.80-0.96. The high-frequency laser scanner gave very good results based on the histogram peak ratio and on a 3-dimensional field reconstruction. Since the amount of incoming biomass is function of both crop stand density and crop volume, a new method for the estimation of crop volume has been proposed which calculates the volume between the ground profile and the crop profile using thin plate spline fitting through the ground level and ear level points. This method was shown to have potential to improve estimates of crop volume. (c) 2008 IAgrE. Elsevier Ltd. All rights reserved.
An intelligent frog call identifier is developed in this work to provide the public with easy online consultation. The raw frog call samples are first filtered by noise removal, high frequency compensation, and discre...
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An intelligent frog call identifier is developed in this work to provide the public with easy online consultation. The raw frog call samples are first filtered by noise removal, high frequency compensation, and discrete wavelet transform techniques in that order. An adaptive end-point detection segmentation algorithm is proposed to effectively separate the individual syllables from the noise. Eight features, including spectral centroid, signal bandwidth, spectral roll-off, threshold-crossing rate, delta spectrum magnitude, spectral flatness, average energy, and mel-frequency cepstral coefficients are extracted and serve as the input parameters of the classifier. Three well-known classifiers, the kth nearest neighboring, a backpropagation neural network, and a naive Bayes classifier, are employed in this work for comparison. A series of experiments were conducted to measure the outcome performance of the proposed work. Experimental results show that the recognition rate of the k-nearest neighbor classifier with the parameters of mel-frequency cepstral coefficients can achieve up to 93.81%. The effectiveness of the proposed frog call identifier is thus verified.
The article discusses the use of an enterprise data warehouse (EDW) as a means to access medical records during disasters. EDW is considered a source of informational data to aid strategic decision making, the authors...
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The article discusses the use of an enterprise data warehouse (EDW) as a means to access medical records during disasters. EDW is considered a source of informational data to aid strategic decision making, the authors state, rather than operational data for supporting on-going business operations. Other topics include an architectural extension for EDW, uninterrupted medical services during and after large-scale disasters such as Hurricane Katrina in 2005, and the information technology (IT) systems of the U.S. Veteran Health Administration (VHA).
The article discusses the security efforts of colleges and universities to protect the private information of employees and students. The authors examines the online privacy practices utilized in higher education, add...
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The article discusses the security efforts of colleges and universities to protect the private information of employees and students. The authors examines the online privacy practices utilized in higher education, addressing the issue of how well such institutions manage online privacy. An audit of Web site privacy notices of leading U.S. colleges and universities is presented in order to determine whether fair information practices (FIP) are being observed at such schools. Also discussed are the organizational obligations for data protection at educational institutions.
onlinedata collection within social and behavioral research is burgeoning. For surveying individuals online, researchers are increasingly relying on online panels and similar subject pools. phpPanelAdmin is a Web-bas...
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onlinedata collection within social and behavioral research is burgeoning. For surveying individuals online, researchers are increasingly relying on online panels and similar subject pools. phpPanelAdmin is a Web-based platform that is intended to assist researchers in quickly setting up and managing an online panel. phpPanelAdmin solves many problems that can arise when one is collecting data in online panels. As an open-source program placed under GNU General Public License, phpPanelAdmin (***/panelware) is not only free of charge but free of restrictions on its use, modification, and distribution. Building a new online panel-which before required weeks and special skills-is now possible within minutes and at no cost. Furthermore, phpPanelAdmin can be connected to an existing online panel or even be used for managing oftline subject pools. Functions include creating a panel sign-up form;automatically unfolding the panel database;searching for panelists;viewing, modifying, and deleting panelists' data;deleting and cloning variables;drawing samples;sending e-mail to panelists;exporting data;displaying panel statistics at a glance;identifying duplicates;creating and managing e-mail templates;executing user-defined SQL statements;and obtaining help.
We consider preemptive offline and online scheduling on identical machines and uniformly related machines in the hierarchical model, with the goal of minimizing the makespan. In this model, each job can be assigned to...
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We consider preemptive offline and online scheduling on identical machines and uniformly related machines in the hierarchical model, with the goal of minimizing the makespan. In this model, each job can be assigned to a subset of the machines which is a prefix of the machine set. We design optimal offline and online algorithms for two uniformly related machines, both when the machine of higher hierarchy is faster and when it is slower, as well as for the case of three identical machines. Specifically, for each one of the three variants, we give a simple formula to compute the makespan of an optimal schedule, provide a linear time offline algorithm which computes an optimal schedule and design an online algorithm of the best possible competitive ratio. (c) 2008 Published by Elsevier Inc.
In this article, a method that models user navigation on the web, as opposed to a single website, is presented, aiming to assist the user by recommending pages. User modeling is done through data mining of web usage l...
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In this article, a method that models user navigation on the web, as opposed to a single website, is presented, aiming to assist the user by recommending pages. User modeling is done through data mining of web usage logs, resulting in aggregate, rather than personal models. The proposed approach extends grammatical inference methods by introducing an extra merging criterion, which examines the semantic similarity of automaton states. The experimental results showed that the method does indeed facilitate the modeling of web navigation, which was not possible with the existing web usage mining methods. However, a content-based recommendation model is shown to still outperform the proposed method, which suggests that the knowledge of the navigation sequence does not contribute to the recommendation process. This is due to the thematic cohesion of navigation sessions, in comparison to the large thematic diversity of web usage data. Among three variants of the proposed method, the one based on Blue Fringe, that examines a larger space of possible merges, performs better.
Scalable data mining algorithms have become crucial to efficiently support KDD processes on large databases. In this paper, we address the task of scaling up k-medoid-based algorithms through the utilization of metric...
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Scalable data mining algorithms have become crucial to efficiently support KDD processes on large databases. In this paper, we address the task of scaling up k-medoid-based algorithms through the utilization of metric access methods, allowing clustering algorithms to be executed by database management systems in a fraction of the time usually required by the traditional approaches. We also present an optimization strategy that can be applied as an additional step of the proposed algorithm in order to achieve better clustering solutions. Experimental results based on several datasets, including synthetic and real ones, show that the proposed algorithm can reduce the number of distance calculations by a factor of more than three thousand times when compared to existing algorithms, while producing clusters of equivalent quality. (C) 2007 Elsevier Inc. All rights reserved.
The article discusses the use of a service-oriented approach by teachers who conduct web-based instruction. Details about the web-based learning management programs on the market are provided and a different solution ...
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The article discusses the use of a service-oriented approach by teachers who conduct web-based instruction. Details about the web-based learning management programs on the market are provided and a different solution for web-based learning management is presented. According to the author, though the monolithic approach to material organization is intuitive, a service-oriented approach offers a more flexible structure and other benefits. A table comparing the differences between a monolithic approach and a service-oriented approach to instructional processes is also included.
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