1,720,962 research outputs found
PEMROSESAN AWAL DATA RUNTUN WAKTU HASIL PENGUKURAN UNTUK IDENTIFIKASI SISTEM TUNGKU SINTER DEGUSSA
Full text linkABSTRAK─Pemrosesan awal data merupakan langkah penting dan kritis serta memiliki dampak besar pada keberhasilan analisis atau penggunaan selanjutnya dari data. Data hasil pengukuran yang terbebas dari noise tidak pernah dapat diperoleh dalam pengukuran menggunakan sensor dilaboratorium proses kimia atau fisika karena adanya noise yang timbul dari efek termodinamika dan kuantum. Selain itu noise juga terjadi karena kesalahan transmisi, lokasi memori yang rusak, dan kesalahan timing pada konversi analog ke digital. Pada makalah ini dilakukan penelitian dan eksperimen untuk mencari parameter optimal penapisan noise spike (outlier) menggunakan median filter pada data runtun waktu input-output hasil akuisisi proses sintering. Dari hasil eksperimen diperoleh parameter optimal median filter untuk data runtun waktu input–output proses sintering adalah dengan lebar jendela pergeseran N=25. Parameter tersebut menghasilkan rasio sinyal terhadap noise (SNR) yang cukup tinggi dengan rerata 3,6685 dan rerata kesalahan kuadrat (MSE) rendah dengan rerata 0,0352 dengan tetap mempertahankan bentuk asli puncak sinyal. Dengan demikian data hasil pemrosesan awal data dapat digunakan pada proses selanjutnya yaitu identifikasi sistem menggunakan teknik cerdas dengan efisien dan akurat. Kata Kunci – Pemrosesan awal data, runtun waktu, median filter, sintering ABSTRACT─Data preprocessing is an important and critical step and have a huge impact on the success of the analysis or the subsequent use of the data. Measurement data with free of noise can never be obtained from the sensor measurement in chemical or physical process laboratory due to the noise arising from thermodynamics and quantum effects. In addition, noise also occurs because of a transmission error, faulty memory location, and timing errors at the analog to digital conversion. In this paper carried out research and experiments to find the optimal parameters for filtering spikes noise (outliers) using a median filter on input-output time series data that obtained from the data acquisition of the sintering process. From the experimental results obtained that median filter optimal parameter is using moving windows size N=25. These parameters produce sufficiently high Signal to Noise Ratio (SNR) with the average of 3.6685 and a low Mean Square Error (MSE) with the average of 0.0352 while maintaining the shape of the original signal peaks on the data. Thus the results of data preprocessing can be used in the next step of the data usage i.e. for system identification using intelligent technique efficiently and accurately. Keywords – Data preprocessing, time series, median filtering, sinterin
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Virtual sensor for time series prediction of hydrogen safety parameter in DEGUSSA sintering furnace
No full textIdentification of Industrial Furnace Temperature for Sintering Process in Nuclear Fuel Fabrication Using NARX Neural Networks
No full textNonlinear system identification is becoming an important tool which can be used to improve control performance and achieve robust fault-tolerant behavior. Among the different nonlinear identification techniques, methods based on neural network model are gradually becoming established not only in the academia, but also in industrial application. An identification scheme of nonlinear systems for sintering furnace temperature in nuclear fuel fabrication using neural network autoregressive with exogenous inputs (NNARX) model investigated in this paper. The main contribution of this paper is to identify the appropriate model and structure to be applied in control temperature in the sintering process in nuclear fuel fabrication, that is, a nonlinear dynamical system. Satisfactory agreement between identified and experimental data is found with normalized sum square error 1.9 − 03 for heating step and 6.3859 − 08 for soaking step. That result shows the model successfully predict the evolution of the temperature in the furnace
Identification of Industrial Furnace Temperature for Sintering Process in Nuclear Fuel Fabrication Using NARX Neural Networks
Full text linkNonlinear system identification is becoming an important tool which can be used to improve control performance and achieve robust fault-tolerant behavior. Among the different nonlinear identification techniques, methods based on neural network model are gradually becoming established not only in the academia, but also in industrial application. An identification scheme of nonlinear systems for sintering furnace temperature in nuclear fuel fabrication using neural network autoregressive with exogenous inputs (NNARX) model investigated in this paper. The main contribution of this paper is to identify the appropriate model and structure to be applied in control temperature in the sintering process in nuclear fuel fabrication, that is, a nonlinear dynamical system. Satisfactory agreement between identified and experimental data is found with normalized sum square error 1.9e-03 for heating step and 6.3859e-08 for soaking step. That result shows the model successfully predict the evolution of the temperature in the furnace
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe 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
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